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Sample records for interactome predicts spatiotemporal

  1. PTIR: Predicted Tomato Interactome Resource.

    PubMed

    Yue, Junyang; Xu, Wei; Ban, Rongjun; Huang, Shengxiong; Miao, Min; Tang, Xiaofeng; Liu, Guoqing; Liu, Yongsheng

    2016-01-01

    Protein-protein interactions (PPIs) are involved in almost all biological processes and form the basis of the entire interactomics systems of living organisms. Identification and characterization of these interactions are fundamental to elucidating the molecular mechanisms of signal transduction and metabolic pathways at both the cellular and systemic levels. Although a number of experimental and computational studies have been performed on model organisms, the studies exploring and investigating PPIs in tomatoes remain lacking. Here, we developed a Predicted Tomato Interactome Resource (PTIR), based on experimentally determined orthologous interactions in six model organisms. The reliability of individual PPIs was also evaluated by shared gene ontology (GO) terms, co-evolution, co-expression, co-localization and available domain-domain interactions (DDIs). Currently, the PTIR covers 357,946 non-redundant PPIs among 10,626 proteins, including 12,291 high-confidence, 226,553 medium-confidence, and 119,102 low-confidence interactions. These interactions are expected to cover 30.6% of the entire tomato proteome and possess a reasonable distribution. In addition, ten randomly selected PPIs were verified using yeast two-hybrid (Y2H) screening or a bimolecular fluorescence complementation (BiFC) assay. The PTIR was constructed and implemented as a dedicated database and is available at http://bdg.hfut.edu.cn/ptir/index.html without registration. PMID:27121261

  2. PTIR: Predicted Tomato Interactome Resource

    PubMed Central

    Yue, Junyang; Xu, Wei; Ban, Rongjun; Huang, Shengxiong; Miao, Min; Tang, Xiaofeng; Liu, Guoqing; Liu, Yongsheng

    2016-01-01

    Protein-protein interactions (PPIs) are involved in almost all biological processes and form the basis of the entire interactomics systems of living organisms. Identification and characterization of these interactions are fundamental to elucidating the molecular mechanisms of signal transduction and metabolic pathways at both the cellular and systemic levels. Although a number of experimental and computational studies have been performed on model organisms, the studies exploring and investigating PPIs in tomatoes remain lacking. Here, we developed a Predicted Tomato Interactome Resource (PTIR), based on experimentally determined orthologous interactions in six model organisms. The reliability of individual PPIs was also evaluated by shared gene ontology (GO) terms, co-evolution, co-expression, co-localization and available domain-domain interactions (DDIs). Currently, the PTIR covers 357,946 non-redundant PPIs among 10,626 proteins, including 12,291 high-confidence, 226,553 medium-confidence, and 119,102 low-confidence interactions. These interactions are expected to cover 30.6% of the entire tomato proteome and possess a reasonable distribution. In addition, ten randomly selected PPIs were verified using yeast two-hybrid (Y2H) screening or a bimolecular fluorescence complementation (BiFC) assay. The PTIR was constructed and implemented as a dedicated database and is available at http://bdg.hfut.edu.cn/ptir/index.html without registration. PMID:27121261

  3. Computational prediction of the human-microbial oral interactome

    PubMed Central

    2014-01-01

    Background The oral cavity is a complex ecosystem where human chemical compounds coexist with a particular microbiota. However, shifts in the normal composition of this microbiota may result in the onset of oral ailments, such as periodontitis and dental caries. In addition, it is known that the microbial colonization of the oral cavity is mediated by protein-protein interactions (PPIs) between the host and microorganisms. Nevertheless, this kind of PPIs is still largely undisclosed. To elucidate these interactions, we have created a computational prediction method that allows us to obtain a first model of the Human-Microbial oral interactome. Results We collected high-quality experimental PPIs from five major human databases. The obtained PPIs were used to create our positive dataset and, indirectly, our negative dataset. The positive and negative datasets were merged and used for training and validation of a naïve Bayes classifier. For the final prediction model, we used an ensemble methodology combining five distinct PPI prediction techniques, namely: literature mining, primary protein sequences, orthologous profiles, biological process similarity, and domain interactions. Performance evaluation of our method revealed an area under the ROC-curve (AUC) value greater than 0.926, supporting our primary hypothesis, as no single set of features reached an AUC greater than 0.877. After subjecting our dataset to the prediction model, the classified result was filtered for very high confidence PPIs (probability ≥ 1-10−7), leading to a set of 46,579 PPIs to be further explored. Conclusions We believe this dataset holds not only important pathways involved in the onset of infectious oral diseases, but also potential drug-targets and biomarkers. The dataset used for training and validation, the predictions obtained and the network final network are available at http://bioinformatics.ua.pt/software/oralint. PMID:24576332

  4. A predicted protein interactome identifies conserved global networks and disease resistance subnetworks in maize

    PubMed Central

    Musungu, Bryan; Bhatnagar, Deepak; Brown, Robert L.; Fakhoury, Ahmad M.; Geisler, Matt

    2015-01-01

    Interactomes are genome-wide roadmaps of protein-protein interactions. They have been produced for humans, yeast, the fruit fly, and Arabidopsis thaliana and have become invaluable tools for generating and testing hypotheses. A predicted interactome for Zea mays (PiZeaM) is presented here as an aid to the research community for this valuable crop species. PiZeaM was built using a proven method of interologs (interacting orthologs) that were identified using both one-to-one and many-to-many orthology between genomes of maize and reference species. Where both maize orthologs occurred for an experimentally determined interaction in the reference species, we predicted a likely interaction in maize. A total of 49,026 unique interactions for 6004 maize proteins were predicted. These interactions are enriched for processes that are evolutionarily conserved, but include many otherwise poorly annotated proteins in maize. The predicted maize interactions were further analyzed by comparing annotation of interacting proteins, including different layers of ontology. A map of pairwise gene co-expression was also generated and compared to predicted interactions. Two global subnetworks were constructed for highly conserved interactions. These subnetworks showed clear clustering of proteins by function. Another subnetwork was created for disease response using a bait and prey strategy to capture interacting partners for proteins that respond to other organisms. Closer examination of this subnetwork revealed the connectivity between biotic and abiotic hormone stress pathways. We believe PiZeaM will provide a useful tool for the prediction of protein function and analysis of pathways for Z. mays researchers and is presented in this paper as a reference tool for the exploration of protein interactions in maize. PMID:26089837

  5. Mapping Plant Interactomes Using Literature Curated and Predicted Protein–Protein Interaction Data Sets[W

    PubMed Central

    Lee, KiYoung; Thorneycroft, David; Achuthan, Premanand; Hermjakob, Henning; Ideker, Trey

    2010-01-01

    Most cellular processes are enabled by cohorts of interacting proteins that form dynamic networks within the plant proteome. The study of these networks can provide insight into protein function and provide new avenues for research. This article informs the plant science community of the currently available sources of protein interaction data and discusses how they can be useful to researchers. Using our recently curated IntAct Arabidopsis thaliana protein–protein interaction data set as an example, we discuss potentials and limitations of the plant interactomes generated to date. In addition, we present our efforts to add value to the interaction data by using them to seed a proteome-wide map of predicted protein subcellular locations. PMID:20371643

  6. A predicted protein interactome identifies conserved global networks and disease resistance subnetworks in maize

    Technology Transfer Automated Retrieval System (TEKTRAN)

    An interactome is the genome-wide roadmap of protein-protein interactions that occur within an organism. Interactomes for humans, the fruit fly, and now plants such as Arabidopsis thaliana and Oryza sativa have been generated using high throughput experimental methods. It is possible to use these ...

  7. Spatiotemporal patterns and predictability of cyberattacks.

    PubMed

    Chen, Yu-Zhong; Huang, Zi-Gang; Xu, Shouhuai; Lai, Ying-Cheng

    2015-01-01

    A relatively unexplored issue in cybersecurity science and engineering is whether there exist intrinsic patterns of cyberattacks. Conventional wisdom favors absence of such patterns due to the overwhelming complexity of the modern cyberspace. Surprisingly, through a detailed analysis of an extensive data set that records the time-dependent frequencies of attacks over a relatively wide range of consecutive IP addresses, we successfully uncover intrinsic spatiotemporal patterns underlying cyberattacks, where the term "spatio" refers to the IP address space. In particular, we focus on analyzing macroscopic properties of the attack traffic flows and identify two main patterns with distinct spatiotemporal characteristics: deterministic and stochastic. Strikingly, there are very few sets of major attackers committing almost all the attacks, since their attack "fingerprints" and target selection scheme can be unequivocally identified according to the very limited number of unique spatiotemporal characteristics, each of which only exists on a consecutive IP region and differs significantly from the others. We utilize a number of quantitative measures, including the flux-fluctuation law, the Markov state transition probability matrix, and predictability measures, to characterize the attack patterns in a comprehensive manner. A general finding is that the attack patterns possess high degrees of predictability, potentially paving the way to anticipating and, consequently, mitigating or even preventing large-scale cyberattacks using macroscopic approaches. PMID:25992837

  8. Spatiotemporal patterns and predictability of cyberattacks.

    PubMed

    Chen, Yu-Zhong; Huang, Zi-Gang; Xu, Shouhuai; Lai, Ying-Cheng

    2015-01-01

    A relatively unexplored issue in cybersecurity science and engineering is whether there exist intrinsic patterns of cyberattacks. Conventional wisdom favors absence of such patterns due to the overwhelming complexity of the modern cyberspace. Surprisingly, through a detailed analysis of an extensive data set that records the time-dependent frequencies of attacks over a relatively wide range of consecutive IP addresses, we successfully uncover intrinsic spatiotemporal patterns underlying cyberattacks, where the term "spatio" refers to the IP address space. In particular, we focus on analyzing macroscopic properties of the attack traffic flows and identify two main patterns with distinct spatiotemporal characteristics: deterministic and stochastic. Strikingly, there are very few sets of major attackers committing almost all the attacks, since their attack "fingerprints" and target selection scheme can be unequivocally identified according to the very limited number of unique spatiotemporal characteristics, each of which only exists on a consecutive IP region and differs significantly from the others. We utilize a number of quantitative measures, including the flux-fluctuation law, the Markov state transition probability matrix, and predictability measures, to characterize the attack patterns in a comprehensive manner. A general finding is that the attack patterns possess high degrees of predictability, potentially paving the way to anticipating and, consequently, mitigating or even preventing large-scale cyberattacks using macroscopic approaches.

  9. Spatiotemporal Patterns and Predictability of Cyberattacks

    PubMed Central

    Chen, Yu-Zhong; Huang, Zi-Gang; Xu, Shouhuai; Lai, Ying-Cheng

    2015-01-01

    A relatively unexplored issue in cybersecurity science and engineering is whether there exist intrinsic patterns of cyberattacks. Conventional wisdom favors absence of such patterns due to the overwhelming complexity of the modern cyberspace. Surprisingly, through a detailed analysis of an extensive data set that records the time-dependent frequencies of attacks over a relatively wide range of consecutive IP addresses, we successfully uncover intrinsic spatiotemporal patterns underlying cyberattacks, where the term “spatio” refers to the IP address space. In particular, we focus on analyzing macroscopic properties of the attack traffic flows and identify two main patterns with distinct spatiotemporal characteristics: deterministic and stochastic. Strikingly, there are very few sets of major attackers committing almost all the attacks, since their attack “fingerprints” and target selection scheme can be unequivocally identified according to the very limited number of unique spatiotemporal characteristics, each of which only exists on a consecutive IP region and differs significantly from the others. We utilize a number of quantitative measures, including the flux-fluctuation law, the Markov state transition probability matrix, and predictability measures, to characterize the attack patterns in a comprehensive manner. A general finding is that the attack patterns possess high degrees of predictability, potentially paving the way to anticipating and, consequently, mitigating or even preventing large-scale cyberattacks using macroscopic approaches. PMID:25992837

  10. Rapid, Optimized Interactomic Screening

    PubMed Central

    Hakhverdyan, Zhanna; Domanski, Michal; Hough, Loren; Oroskar, Asha A.; Oroskar, Anil R.; Keegan, Sarah; Dilworth, David J.; Molloy, Kelly R.; Sherman, Vadim; Aitchison, John D.; Fenyö, David; Chait, Brian T.; Jensen, Torben Heick; Rout, Michael P.; LaCava, John

    2015-01-01

    We must reliably map the interactomes of cellular macromolecular complexes in order to fully explore and understand biological systems. However, there are no methods to accurately predict how to capture a given macromolecular complex with its physiological binding partners. Here, we present a screen that comprehensively explores the parameters affecting the stability of interactions in affinity-captured complexes, enabling the discovery of physiological binding partners and the elucidation of their functional interactions in unparalleled detail. We have implemented this screen on several macromolecular complexes from a variety of organisms, revealing novel profiles even for well-studied proteins. Our approach is robust, economical and automatable, providing an inroad to the rigorous, systematic dissection of cellular interactomes. PMID:25938370

  11. DDI-CPI, a server that predicts drug–drug interactions through implementing the chemical–protein interactome

    PubMed Central

    Luo, Heng; Zhang, Ping; Huang, Hui; Huang, Jialiang; Kao, Emily; Shi, Leming; He, Lin; Yang, Lun

    2014-01-01

    Drug–drug interactions (DDIs) may cause serious side-effects that draw great attention from both academia and industry. Since some DDIs are mediated by unexpected drug–human protein interactions, it is reasonable to analyze the chemical–protein interactome (CPI) profiles of the drugs to predict their DDIs. Here we introduce the DDI-CPI server, which can make real-time DDI predictions based only on molecular structure. When the user submits a molecule, the server will dock user's molecule across 611 human proteins, generating a CPI profile that can be used as a feature vector for the pre-constructed prediction model. It can suggest potential DDIs between the user's molecule and our library of 2515 drug molecules. In cross-validation and independent validation, the server achieved an AUC greater than 0.85. Additionally, by investigating the CPI profiles of predicted DDI, users can explore the PK/PD proteins that might be involved in a particular DDI. A 3D visualization of the drug-protein interaction will be provided as well. The DDI-CPI is freely accessible at http://cpi.bio-x.cn/ddi/. PMID:24875476

  12. DDI-CPI, a server that predicts drug-drug interactions through implementing the chemical-protein interactome.

    PubMed

    Luo, Heng; Zhang, Ping; Huang, Hui; Huang, Jialiang; Kao, Emily; Shi, Leming; He, Lin; Yang, Lun

    2014-07-01

    Drug-drug interactions (DDIs) may cause serious side-effects that draw great attention from both academia and industry. Since some DDIs are mediated by unexpected drug-human protein interactions, it is reasonable to analyze the chemical-protein interactome (CPI) profiles of the drugs to predict their DDIs. Here we introduce the DDI-CPI server, which can make real-time DDI predictions based only on molecular structure. When the user submits a molecule, the server will dock user's molecule across 611 human proteins, generating a CPI profile that can be used as a feature vector for the pre-constructed prediction model. It can suggest potential DDIs between the user's molecule and our library of 2515 drug molecules. In cross-validation and independent validation, the server achieved an AUC greater than 0.85. Additionally, by investigating the CPI profiles of predicted DDI, users can explore the PK/PD proteins that might be involved in a particular DDI. A 3D visualization of the drug-protein interaction will be provided as well. The DDI-CPI is freely accessible at http://cpi.bio-x.cn/ddi/. PMID:24875476

  13. Sensitivity to Spatiotemporal Percepts Predicts the Perception of Emotion

    PubMed Central

    Castro, Vanessa L.; Boone, R. Thomas

    2015-01-01

    The present studies examined how sensitivity to spatiotemporal percepts such as rhythm, angularity, configuration, and force predicts accuracy in perceiving emotion. In Study 1, participants (N = 99) completed a nonverbal test battery consisting of three nonverbal emotion perception tests and two perceptual sensitivity tasks assessing rhythm sensitivity and angularity sensitivity. Study 2 (N = 101) extended the findings of Study 1 with the addition of a fourth nonverbal test, a third configural sensitivity task, and a fourth force sensitivity task. Regression analyses across both studies revealed partial support for the association between perceptual sensitivity to spatiotemporal percepts and greater emotion perception accuracy. Results indicate that accuracy in perceiving emotions may be predicted by sensitivity to specific percepts embedded within channel- and emotion-specific displays. The significance of such research lies in the understanding of how individuals acquire emotion perception skill and the processes by which distinct features of percepts are related to the perception of emotion. PMID:26339111

  14. Predicting genome-scale Arabidopsis-Pseudomonas syringae interactome using domain and interolog-based approaches

    PubMed Central

    2014-01-01

    Background Every year pathogenic organisms cause billions of dollars' worth damage to crops and livestock. In agriculture, study of plant-microbe interactions is demanding a special attention to develop management strategies for the destructive pathogen induced diseases that cause huge crop losses every year worldwide. Pseudomonas syringae is a major bacterial leaf pathogen that causes diseases in a wide range of plant species. Among its various strains, pathovar tomato strain DC3000 (PstDC3000) is asserted to infect the plant host Arabidopsis thaliana and thus, has been accepted as a model system for experimental characterization of the molecular dynamics of plant-pathogen interactions. Protein-protein interactions (PPIs) play a critical role in initiating pathogenesis and maintaining infection. Understanding the PPI network between a host and pathogen is a critical step for studying the molecular basis of pathogenesis. The experimental study of PPIs at a large scale is very scarce and also the high throughput experimental results show high false positive rate. Hence, there is a need for developing efficient computational models to predict the interaction between host and pathogen in a genome scale, and find novel candidate effectors and/or their targets. Results In this study, we used two computational approaches, the interolog and the domain-based to predict the interactions between Arabidopsis and PstDC3000 in genome scale. The interolog method relies on protein sequence similarity to conduct the PPI prediction. A Pseudomonas protein and an Arabidopsis protein are predicted to interact with each other if an experimentally verified interaction exists between their respective homologous proteins in another organism. The domain-based method uses domain interaction information, which is derived from known protein 3D structures, to infer the potential PPIs. If a Pseudomonas and an Arabidopsis protein contain an interacting domain pair, one can expect the two

  15. Network-based function prediction and interactomics: the case for metabolic enzymes.

    PubMed

    Janga, S C; Díaz-Mejía, J Javier; Moreno-Hagelsieb, G

    2011-01-01

    As sequencing technologies increase in power, determining the functions of unknown proteins encoded by the DNA sequences so produced becomes a major challenge. Functional annotation is commonly done on the basis of amino-acid sequence similarity alone. Long after sequence similarity becomes undetectable by pair-wise comparison, profile-based identification of homologs can often succeed due to the conservation of position-specific patterns, important for a protein's three dimensional folding and function. Nevertheless, prediction of protein function from homology-driven approaches is not without problems. Homologous proteins might evolve different functions and the power of homology detection has already started to reach its maximum. Computational methods for inferring protein function, which exploit the context of a protein in cellular networks, have come to be built on top of homology-based approaches. These network-based functional inference techniques provide both a first hand hint into a proteins' functional role and offer complementary insights to traditional methods for understanding the function of uncharacterized proteins. Most recent network-based approaches aim to integrate diverse kinds of functional interactions to boost both coverage and confidence level. These techniques not only promise to solve the moonlighting aspect of proteins by annotating proteins with multiple functions, but also increase our understanding on the interplay between different functional classes in a cell. In this article we review the state of the art in network-based function prediction and describe some of the underlying difficulties and successes. Given the volume of high-throughput data that is being reported the time is ripe to employ these network-based approaches, which can be used to unravel the functions of the uncharacterized proteins accumulating in the genomic databases.

  16. Computational methodology for predicting the landscape of the human-microbial interactome region level influence.

    PubMed

    Coelho, Edgar D; Santiago, André M; Arrais, Joel P; Oliveira, José Luís

    2015-10-01

    Microbial communities thrive in close association among themselves and with the host, establishing protein-protein interactions (PPIs) with the latter, and thus being able to benefit (positively impact) or disturb (negatively impact) biological events in the host. Despite major collaborative efforts to sequence the Human microbiome, there is still a great lack of understanding their impact. We propose a computational methodology to predict the impact of microbial proteins in human biological events, taking into account the abundance of each microbial protein and its relation to all other microbial and human proteins. This alternative methodology is centered on an improved impact estimation algorithm that integrates PPIs between human and microbial proteins with Reactome pathway data. This methodology was applied to study the impact of 24 microbial phyla over different cellular events, within 10 different human microbiomes. The results obtained confirm findings already described in the literature and explore new ones. We believe the Human microbiome can no longer be ignored as not only is there enough evidence correlating microbiome alterations and disease states, but also the return to healthy states once these alterations are reversed.

  17. Prediction of Spatiotemporal Patterns of Neural Activity from Pairwise Correlations

    NASA Astrophysics Data System (ADS)

    Marre, O.; El Boustani, S.; Frégnac, Y.; Destexhe, A.

    2009-04-01

    We designed a model-based analysis to predict the occurrence of population patterns in distributed spiking activity. Using a maximum entropy principle with a Markovian assumption, we obtain a model that accounts for both spatial and temporal pairwise correlations among neurons. This model is tested on data generated with a Glauber spin-glass system and is shown to correctly predict the occurrence probabilities of spatiotemporal patterns significantly better than Ising models only based on spatial correlations. This increase of predictability was also observed on experimental data recorded in parietal cortex during slow-wave sleep. This approach can also be used to generate surrogates that reproduce the spatial and temporal correlations of a given data set.

  18. Prediction of Spatiotemporal Patterns of Neural Activity from Pairwise Correlations

    SciTech Connect

    Marre, O.; El Boustani, S.; Fregnac, Y.; Destexhe, A.

    2009-04-03

    We designed a model-based analysis to predict the occurrence of population patterns in distributed spiking activity. Using a maximum entropy principle with a Markovian assumption, we obtain a model that accounts for both spatial and temporal pairwise correlations among neurons. This model is tested on data generated with a Glauber spin-glass system and is shown to correctly predict the occurrence probabilities of spatiotemporal patterns significantly better than Ising models only based on spatial correlations. This increase of predictability was also observed on experimental data recorded in parietal cortex during slow-wave sleep. This approach can also be used to generate surrogates that reproduce the spatial and temporal correlations of a given data set.

  19. MitoInteractome: Mitochondrial protein interactome database, and its application in 'aging network' analysis

    PubMed Central

    2009-01-01

    Background Mitochondria play a vital role in the energy production and apoptotic process of eukaryotic cells. Proteins in the mitochondria are encoded by nuclear and mitochondrial genes. Owing to a large increase in the number of identified mitochondrial protein sequences and completed mitochondrial genomes, it has become necessary to provide a web-based database of mitochondrial protein information. Results We present 'MitoInteractome', a consolidated web-based portal containing a wealth of information on predicted protein-protein interactions, physico-chemical properties, polymorphism, and diseases related to the mitochondrial proteome. MitoInteractome contains 6,549 protein sequences which were extracted from the following databases: SwissProt, MitoP, MitoProteome, HPRD and Gene Ontology database. The first general mitochondrial interactome has been constructed based on the concept of 'homologous interaction' using PSIMAP (Protein Structural Interactome MAP) and PEIMAP (Protein Experimental Interactome MAP). Using the above mentioned methods, protein-protein interactions were predicted for 74 species. The mitochondrial protein interaction data of humans was used to construct a network for the aging process. Analysis of the 'aging network' gave us vital insights into the interactions among proteins that influence the aging process. Conclusion MitoInteractome is a comprehensive database that would (1) aid in increasing our understanding of the molecular functions and interaction networks of mitochondrial proteins, (2) help in identifying new target proteins for experimental research using predicted protein-protein interaction information, and (3) help in identifying biomarkers for diagnosis and new molecular targets for drug development related to mitochondria. MitoInteractome is available at http://mitointeractome.kobic.kr/. PMID:19958484

  20. Predicting BCI subject performance using probabilistic spatio-temporal filters.

    PubMed

    Suk, Heung-Il; Fazli, Siamac; Mehnert, Jan; Müller, Klaus-Robert; Lee, Seong-Whan

    2014-01-01

    Recently, spatio-temporal filtering to enhance decoding for Brain-Computer-Interfacing (BCI) has become increasingly popular. In this work, we discuss a novel, fully Bayesian-and thereby probabilistic-framework, called Bayesian Spatio-Spectral Filter Optimization (BSSFO) and apply it to a large data set of 80 non-invasive EEG-based BCI experiments. Across the full frequency range, the BSSFO framework allows to analyze which spatio-spectral parameters are common and which ones differ across the subject population. As expected, large variability of brain rhythms is observed between subjects. We have clustered subjects according to similarities in their corresponding spectral characteristics from the BSSFO model, which is found to reflect their BCI performances well. In BCI, a considerable percentage of subjects is unable to use a BCI for communication, due to their missing ability to modulate their brain rhythms-a phenomenon sometimes denoted as BCI-illiteracy or inability. Predicting individual subjects' performance preceding the actual, time-consuming BCI-experiment enhances the usage of BCIs, e.g., by detecting users with BCI inability. This work additionally contributes by using the novel BSSFO method to predict the BCI-performance using only 2 minutes and 3 channels of resting-state EEG data recorded before the actual BCI-experiment. Specifically, by grouping the individual frequency characteristics we have nicely classified them into the subject 'prototypes' (like μ - or β -rhythm type subjects) or users without ability to communicate with a BCI, and then by further building a linear regression model based on the grouping we could predict subjects' performance with the maximum correlation coefficient of 0.581 with the performance later seen in the actual BCI session.

  1. Spatiotemporal properties of microsaccades: Model predictions and experimental tests

    NASA Astrophysics Data System (ADS)

    Zhou, Jian-Fang; Yuan, Wu-Jie; Zhou, Zhao

    2016-10-01

    Microsaccades are involuntary and very small eye movements during fixation. Recently, the microsaccade-related neural dynamics have been extensively investigated both in experiments and by constructing neural network models. Experimentally, microsaccades also exhibit many behavioral properties. It’s well known that the behavior properties imply the underlying neural dynamical mechanisms, and so are determined by neural dynamics. The behavioral properties resulted from neural responses to microsaccades, however, are not yet understood and are rarely studied theoretically. Linking neural dynamics to behavior is one of the central goals of neuroscience. In this paper, we provide behavior predictions on spatiotemporal properties of microsaccades according to microsaccade-induced neural dynamics in a cascading network model, which includes both retinal adaptation and short-term depression (STD) at thalamocortical synapses. We also successfully give experimental tests in the statistical sense. Our results provide the first behavior description of microsaccades based on neural dynamics induced by behaving activity, and so firstly link neural dynamics to behavior of microsaccades. These results indicate strongly that the cascading adaptations play an important role in the study of microsaccades. Our work may be useful for further investigations of the microsaccadic behavioral properties and of the underlying neural dynamical mechanisms responsible for the behavioral properties.

  2. Spatiotemporal properties of microsaccades: Model predictions and experimental tests

    PubMed Central

    Zhou, Jian-Fang; Yuan, Wu-Jie; Zhou, Zhao

    2016-01-01

    Microsaccades are involuntary and very small eye movements during fixation. Recently, the microsaccade-related neural dynamics have been extensively investigated both in experiments and by constructing neural network models. Experimentally, microsaccades also exhibit many behavioral properties. It’s well known that the behavior properties imply the underlying neural dynamical mechanisms, and so are determined by neural dynamics. The behavioral properties resulted from neural responses to microsaccades, however, are not yet understood and are rarely studied theoretically. Linking neural dynamics to behavior is one of the central goals of neuroscience. In this paper, we provide behavior predictions on spatiotemporal properties of microsaccades according to microsaccade-induced neural dynamics in a cascading network model, which includes both retinal adaptation and short-term depression (STD) at thalamocortical synapses. We also successfully give experimental tests in the statistical sense. Our results provide the first behavior description of microsaccades based on neural dynamics induced by behaving activity, and so firstly link neural dynamics to behavior of microsaccades. These results indicate strongly that the cascading adaptations play an important role in the study of microsaccades. Our work may be useful for further investigations of the microsaccadic behavioral properties and of the underlying neural dynamical mechanisms responsible for the behavioral properties. PMID:27739541

  3. Predicting and tracking spatiotemporal moments in electrical resistivity tomography

    NASA Astrophysics Data System (ADS)

    Ward, W. O. C.; Wilkinson, P. B.; Chambers, J.; Bai, L.

    2015-12-01

    Visualisation is an invaluable tool in the study of near sub-surface processes, whether by mathematical modelling or by geophysical imaging. Quantitative analysis can further assist interpretation of the ongoing physical processes, and it is clear that any reliable model should take direct observations into account. Using electrical resistivity tomography (ERT), localised areas can be surveyed to produce 2-D and 3-D time-lapse images. This study investigates combining quantitative results obtained via ERT with spatio-temporal motion models in tracer experiments to interpret and predict fluid flow. As with any indirect imaging technique, ERT suffers specific issues with resolution and smoothness as a result of its inversion process. In addition, artefacts are typical in the resulting volumes. Mathematical models are also a source of uncertainty - and in combining these with ERT images, a trade-off must be made between the theoretical and the observed. Using computational imaging, distinct regions of stable resistivity can be directly extracted from a time-slice of an ERT volume. The automated nature, as well the potential for more than one region-of-interest, means that multiple regions can be detected. Using Kalman filters, it is possible to convert the detections into a process state, taking into account pre-defined models and predicting progression. In consecutive time-steps, newly detected features are assigned, where possible, to existing predictions to create tracks that match the tracer model. Preliminary studies looked at a simple motion model, tracking the centre of mass of a tracer plume with assumed constant velocity and mean resistivity. Extending the model to factor in spatial distribution of the plume, an oriented semi-axis is used to represent the centralised second-order moment, with an increasing factor of magnitude to represent the plume dispersion. Initial results demonstrate the efficacy of the approach, significantly improving reliability as the

  4. Ozone Concentration Prediction via Spatiotemporal Autoregressive Model With Exogenous Variables

    NASA Astrophysics Data System (ADS)

    Kamoun, W.; Senoussi, R.

    2009-04-01

    Forecast of environmental variables are nowadays of main concern for public health or agricultural management. In this context a large literature is devoted to spatio-temporal modelling of these variables using different statistical approaches. However, most of studies ignored the potential contribution of local (e.g. meteorological and/or geographical) covariables as well as the dynamical characteristics of observations. In this study, we present a spatiotemporal short term forecasting model for ozone concentration based on regularly observed covariables in predefined geographical sites. Our driving system simply combines a multidimensional second order autoregressive structured process with a linear regression model over influent exogenous factors and reads as follows: ‘2 ‘q j Z (t) = A (Î&,cedil;D )Ã- [ αiZ(t- i)]+ B (Î&,cedil;D )Ã- [ βjX (t)]+ ɛ(t) i=1 j=1 Z(t)=(Z1(t),…,Zn(t)) represents the vector of ozone concentration at time t of the n geographical sites, whereas Xj(t)=(X1j(t),…,Xnj(t)) denotes the jth exogenous variable observed over these sites. The nxn matrix functions A and B account for the spatial relationships between sites through the inter site distance matrix D and a vector parameter Î&.cedil; Multidimensional white noise ɛ is assumed to be Gaussian and spatially correlated but temporally independent. A covariance structure of Z that takes account of noise spatial dependences is deduced under a stationary hypothesis and then included in the likelihood function. Statistical model and estimation procedure: Contrarily to the widely used choice of a {0,1}-valued neighbour matrix A, we put forward two more natural choices of exponential or power decay. Moreover, the model revealed enough stable to readily accommodate the crude observations without the usual tedious and somewhat arbitrarily variable transformations. Data set and preliminary analysis: In our case, ozone variable represents here the daily maximum ozone

  5. Impaired Spatio-Temporal Predictive Motor Timing Associated with Spinocerebellar Ataxia Type 6

    PubMed Central

    Onuki, Yoshiyuki; Abdelgabar, Abdel R.; Owens, Cullen B.; Picard, Samuel; Willems, Jessica; Boele, Henk-Jan; Gazzola, Valeria; Van der Werf, Ysbrand D.; De Zeeuw, Chris I.

    2016-01-01

    Many daily life activities demand precise integration of spatial and temporal information of sensory inputs followed by appropriate motor actions. This type of integration is carried out in part by the cerebellum, which has been postulated to play a central role in learning and timing of movements. Cerebellar damage due to atrophy or lesions may compromise forward-model processing, in which both spatial and temporal cues are used to achieve prediction for future motor states. In the present study we sought to further investigate the cerebellar contribution to predictive and reactive motor timing, as well as to learning of sequential order and temporal intervals in these tasks. We tested patients with spinocerebellar ataxia type 6 (SCA6) and healthy controls for two related motor tasks; one requiring spatio-temporal prediction of dynamic visual stimuli and another one requiring reactive timing only. We found that healthy controls established spatio-temporal prediction in their responses with high temporal precision, which was absent in the cerebellar patients. SCA6 patients showed lower predictive motor timing, coinciding with a reduced number of correct responses during the ‘anticipatory’ period on the task. Moreover, on the task utilizing reactive motor timing functions, control participants showed both sequence order and temporal interval learning, whereas patients only showed sequence order learning. These results suggest that SCA6 affects predictive motor timing and temporal interval learning. Our results support and highlight cerebellar contribution to timing and argue for cerebellar engagement during spatio-temporal prediction of upcoming events. PMID:27571363

  6. Impaired Spatio-Temporal Predictive Motor Timing Associated with Spinocerebellar Ataxia Type 6.

    PubMed

    Broersen, Robin; Onuki, Yoshiyuki; Abdelgabar, Abdel R; Owens, Cullen B; Picard, Samuel; Willems, Jessica; Boele, Henk-Jan; Gazzola, Valeria; Van der Werf, Ysbrand D; De Zeeuw, Chris I

    2016-01-01

    Many daily life activities demand precise integration of spatial and temporal information of sensory inputs followed by appropriate motor actions. This type of integration is carried out in part by the cerebellum, which has been postulated to play a central role in learning and timing of movements. Cerebellar damage due to atrophy or lesions may compromise forward-model processing, in which both spatial and temporal cues are used to achieve prediction for future motor states. In the present study we sought to further investigate the cerebellar contribution to predictive and reactive motor timing, as well as to learning of sequential order and temporal intervals in these tasks. We tested patients with spinocerebellar ataxia type 6 (SCA6) and healthy controls for two related motor tasks; one requiring spatio-temporal prediction of dynamic visual stimuli and another one requiring reactive timing only. We found that healthy controls established spatio-temporal prediction in their responses with high temporal precision, which was absent in the cerebellar patients. SCA6 patients showed lower predictive motor timing, coinciding with a reduced number of correct responses during the 'anticipatory' period on the task. Moreover, on the task utilizing reactive motor timing functions, control participants showed both sequence order and temporal interval learning, whereas patients only showed sequence order learning. These results suggest that SCA6 affects predictive motor timing and temporal interval learning. Our results support and highlight cerebellar contribution to timing and argue for cerebellar engagement during spatio-temporal prediction of upcoming events. PMID:27571363

  7. Next Place Prediction Based on Spatiotemporal Pattern Mining of Mobile Device Logs

    PubMed Central

    Lee, Sungjun; Lim, Junseok; Park, Jonghun; Kim, Kwanho

    2016-01-01

    Due to the recent explosive growth of location-aware services based on mobile devices, predicting the next places of a user is of increasing importance to enable proactive information services. In this paper, we introduce a data-driven framework that aims to predict the user’s next places using his/her past visiting patterns analyzed from mobile device logs. Specifically, the notion of the spatiotemporal-periodic (STP) pattern is proposed to capture the visits with spatiotemporal periodicity by focusing on a detail level of location for each individual. Subsequently, we present algorithms that extract the STP patterns from a user’s past visiting behaviors and predict the next places based on the patterns. The experiment results obtained by using a real-world dataset show that the proposed methods are more effective in predicting the user’s next places than the previous approaches considered in most cases. PMID:26805850

  8. Retrospective prediction of intraurban spatiotemporal distribution of PM2.5 in Taipei

    NASA Astrophysics Data System (ADS)

    Hwa-Lung, Yu; Chih-Hsin, Wang

    2010-08-01

    Numerous studies have shown that fine airborne particulate matter particles (PM2.5) are more dangerous to human health than coarse particles, e.g. PM10. The assessment of the impacts to human health or ecological effects by long-term PM2.5 exposure is often limited by lack of PM2.5 measurements. In Taipei, PM2.5 was not systematically observed until August, 2005. Taipei is the largest metropolitan area in Taiwan, where a variety of industrial and traffic emissions are continuously generated and distributed across space and time. PM-related data, i.e., PM10 and Total Suspended Particles (TSP) are independently systematically collected by different central and local government institutes. In this study, the retrospective prediction of spatiotemporal distribution of monthly PM2.5 over Taipei will be performed by using Bayesian Maximum Entropy method (BME) to integrate (a) the spatiotemporal dependence among PM measurements (i.e. PM10, TSP, and PM2.5), (b) the site-specific information of PM measurements which can be certain or uncertain information, and (c) empirical evidence about the PM2.5/PM10 and PM10/TSP ratios. The performance assessment of the retrospective prediction for the spatiotemporal distribution of PM2.5 was performed over space and time during 2003-2004 by comparing the posterior pdf of PM2.5 with the observations. Results show that the incorporation of PM10 and TSP observations by BME method can effectively improve the spatiotemporal PM2.5 estimation in the sense of lower mean and standard deviation of estimation errors. Moreover, the spatiotemporal retrospective prediction with PM2.5/PM10 and PM2.5/TSP ratios can provide good estimations of the range of PM2.5 levels over space and time during 2003-2004 in Taipei.

  9. Spatiotemporal prediction of fine particulate matter during the 2008 northern California wildfires using machine learning.

    PubMed

    Reid, Colleen E; Jerrett, Michael; Petersen, Maya L; Pfister, Gabriele G; Morefield, Philip E; Tager, Ira B; Raffuse, Sean M; Balmes, John R

    2015-03-17

    Estimating population exposure to particulate matter during wildfires can be difficult because of insufficient monitoring data to capture the spatiotemporal variability of smoke plumes. Chemical transport models (CTMs) and satellite retrievals provide spatiotemporal data that may be useful in predicting PM2.5 during wildfires. We estimated PM2.5 concentrations during the 2008 northern California wildfires using 10-fold cross-validation (CV) to select an optimal prediction model from a set of 11 statistical algorithms and 29 predictor variables. The variables included CTM output, three measures of satellite aerosol optical depth, distance to the nearest fires, meteorological data, and land use, traffic, spatial location, and temporal characteristics. The generalized boosting model (GBM) with 29 predictor variables had the lowest CV root mean squared error and a CV-R2 of 0.803. The most important predictor variable was the Geostationary Operational Environmental Satellite Aerosol/Smoke Product (GASP) Aerosol Optical Depth (AOD), followed by the CTM output and distance to the nearest fire cluster. Parsimonious models with various combinations of fewer variables also predicted PM2.5 well. Using machine learning algorithms to combine spatiotemporal data from satellites and CTMs can reliably predict PM2.5 concentrations during a major wildfire event. PMID:25648639

  10. Spatiotemporal prediction of fine particulate matter during the 2008 northern California wildfires using machine learning.

    PubMed

    Reid, Colleen E; Jerrett, Michael; Petersen, Maya L; Pfister, Gabriele G; Morefield, Philip E; Tager, Ira B; Raffuse, Sean M; Balmes, John R

    2015-03-17

    Estimating population exposure to particulate matter during wildfires can be difficult because of insufficient monitoring data to capture the spatiotemporal variability of smoke plumes. Chemical transport models (CTMs) and satellite retrievals provide spatiotemporal data that may be useful in predicting PM2.5 during wildfires. We estimated PM2.5 concentrations during the 2008 northern California wildfires using 10-fold cross-validation (CV) to select an optimal prediction model from a set of 11 statistical algorithms and 29 predictor variables. The variables included CTM output, three measures of satellite aerosol optical depth, distance to the nearest fires, meteorological data, and land use, traffic, spatial location, and temporal characteristics. The generalized boosting model (GBM) with 29 predictor variables had the lowest CV root mean squared error and a CV-R2 of 0.803. The most important predictor variable was the Geostationary Operational Environmental Satellite Aerosol/Smoke Product (GASP) Aerosol Optical Depth (AOD), followed by the CTM output and distance to the nearest fire cluster. Parsimonious models with various combinations of fewer variables also predicted PM2.5 well. Using machine learning algorithms to combine spatiotemporal data from satellites and CTMs can reliably predict PM2.5 concentrations during a major wildfire event.

  11. A data mining based approach to predict spatiotemporal changes in satellite images

    NASA Astrophysics Data System (ADS)

    Boulila, W.; Farah, I. R.; Ettabaa, K. Saheb; Solaiman, B.; Ghézala, H. Ben

    2011-06-01

    The interpretation of remotely sensed images in a spatiotemporal context is becoming a valuable research topic. However, the constant growth of data volume in remote sensing imaging makes reaching conclusions based on collected data a challenging task. Recently, data mining appears to be a promising research field leading to several interesting discoveries in various areas such as marketing, surveillance, fraud detection and scientific discovery. By integrating data mining and image interpretation techniques, accurate and relevant information (i.e. functional relation between observed parcels and a set of informational contents) can be automatically elicited. This study presents a new approach to predict spatiotemporal changes in satellite image databases. The proposed method exploits fuzzy sets and data mining concepts to build predictions and decisions for several remote sensing fields. It takes into account imperfections related to the spatiotemporal mining process in order to provide more accurate and reliable information about land cover changes in satellite images. The proposed approach is validated using SPOT images representing the Saint-Denis region, capital of Reunion Island. Results show good performances of the proposed framework in predicting change for the urban zone.

  12. Predictive Spatiotemporal Manipulation of Signaling Perturbations Using Optogenetics.

    PubMed

    Valon, Leo; Etoc, Fred; Remorino, Amanda; di Pietro, Florencia; Morin, Xavier; Dahan, Maxime; Coppey, Mathieu

    2015-11-01

    Recently developed optogenetic methods promise to revolutionize cell biology by allowing signaling perturbations to be controlled in space and time with light. However, a quantitative analysis of the relationship between a custom-defined illumination pattern and the resulting signaling perturbation is lacking. Here, we characterize the biophysical processes governing the localized recruitment of the Cryptochrome CRY2 to its membrane-anchored CIBN partner. We develop a quantitative framework and present simple procedures that enable predictive manipulation of protein distributions on the plasma membrane with a spatial resolution of 5 μm. We show that protein gradients of desired levels can be established in a few tens of seconds and then steadily maintained. These protein gradients can be entirely relocalized in a few minutes. We apply our approach to the control of the Cdc42 Rho GTPase activity. By inducing strong localized signaling perturbation, we are able to monitor the initiation of cell polarity and migration with a remarkable reproducibility despite cell-to-cell variability.

  13. Viruses and interactomes in translation.

    PubMed

    Meyniel-Schicklin, Laurène; de Chassey, Benoît; André, Patrice; Lotteau, Vincent

    2012-07-01

    A decade of high-throughput screenings for intraviral and virus-host protein-protein interactions led to the accumulation of data and to the development of theories on laws governing interactome organization for many viruses. We present here a computational analysis of intraviral protein networks (EBV, FLUAV, HCV, HSV-1, KSHV, SARS-CoV, VACV, and VZV) and virus-host protein networks (DENV, EBV, FLUAV, HCV, and VACV) from up-to-date interaction data, using various mathematical approaches. If intraviral networks seem to behave similarly, they are clearly different from the human interactome. Viral proteins target highly central human proteins, which are precisely the Achilles' heel of the human interactome. The intrinsic structural disorder is a distinctive feature of viral hubs in virus-host interactomes. Overlaps between virus-host data sets identify a core of human proteins involved in the cellular response to viral infection and in the viral capacity to hijack the cell machinery for viral replication. Host proteins that are strongly targeted by a virus seem to be particularly attractive for other viruses. Such protein-protein interaction networks and their analysis represent a powerful resource from a therapeutic perspective.

  14. Proactive Spatiotemporal Resource Allocation and Predictive Visual Analytics for Community Policing and Law Enforcement.

    PubMed

    Malik, Abish; Maciejewski, Ross; Towers, Sherry; McCullough, Sean; Ebert, David S

    2014-12-01

    In this paper, we present a visual analytics approach that provides decision makers with a proactive and predictive environment in order to assist them in making effective resource allocation and deployment decisions. The challenges involved with such predictive analytics processes include end-users' understanding, and the application of the underlying statistical algorithms at the right spatiotemporal granularity levels so that good prediction estimates can be established. In our approach, we provide analysts with a suite of natural scale templates and methods that enable them to focus and drill down to appropriate geospatial and temporal resolution levels. Our forecasting technique is based on the Seasonal Trend decomposition based on Loess (STL) method, which we apply in a spatiotemporal visual analytics context to provide analysts with predicted levels of future activity. We also present a novel kernel density estimation technique we have developed, in which the prediction process is influenced by the spatial correlation of recent incidents at nearby locations. We demonstrate our techniques by applying our methodology to Criminal, Traffic and Civil (CTC) incident datasets.

  15. Proactive Spatiotemporal Resource Allocation and Predictive Visual Analytics for Community Policing and Law Enforcement.

    PubMed

    Malik, Abish; Maciejewski, Ross; Towers, Sherry; McCullough, Sean; Ebert, David S

    2014-12-01

    In this paper, we present a visual analytics approach that provides decision makers with a proactive and predictive environment in order to assist them in making effective resource allocation and deployment decisions. The challenges involved with such predictive analytics processes include end-users' understanding, and the application of the underlying statistical algorithms at the right spatiotemporal granularity levels so that good prediction estimates can be established. In our approach, we provide analysts with a suite of natural scale templates and methods that enable them to focus and drill down to appropriate geospatial and temporal resolution levels. Our forecasting technique is based on the Seasonal Trend decomposition based on Loess (STL) method, which we apply in a spatiotemporal visual analytics context to provide analysts with predicted levels of future activity. We also present a novel kernel density estimation technique we have developed, in which the prediction process is influenced by the spatial correlation of recent incidents at nearby locations. We demonstrate our techniques by applying our methodology to Criminal, Traffic and Civil (CTC) incident datasets. PMID:26356900

  16. Spatio-Temporal Variation and Prediction of Ischemic Heart Disease Hospitalizations in Shenzhen, China

    PubMed Central

    Wang, Yanxia; Du, Qingyun; Ren, Fu; Liang, Shi; Lin, De-nan; Tian, Qin; Chen, Yan; Li, Jia-jia

    2014-01-01

    Ischemic heart disease (IHD) is a leading cause of death worldwide. Urban public health and medical management in Shenzhen, an international city in the developing country of China, is challenged by an increasing burden of IHD. This study analyzed the spatio-temporal variation of IHD hospital admissions from 2003 to 2012 utilizing spatial statistics, spatial analysis, and space-time scan statistics. The spatial statistics and spatial analysis measured the incidence rate (hospital admissions per 1,000 residents) and the standardized rate (the observed cases standardized by the expected cases) of IHD at the district level to determine the spatio-temporal distribution and identify patterns of change. The space-time scan statistics was used to identify spatio-temporal clusters of IHD hospital admissions at the district level. The other objective of this study was to forecast the IHD hospital admissions over the next three years (2013–2015) to predict the IHD incidence rates and the varying burdens of IHD-related medical services among the districts in Shenzhen. The results show that the highest hospital admissions, incidence rates, and standardized rates of IHD are in Futian. From 2003 to 2012, the IHD hospital admissions exhibited similar mean centers and directional distributions, with a slight increase in admissions toward the north in accordance with the movement of the total population. The incidence rates of IHD exhibited a gradual increase from 2003 to 2012 for all districts in Shenzhen, which may be the result of the rapid development of the economy and the increasing traffic pollution. In addition, some neighboring areas exhibited similar temporal change patterns, which were also detected by the spatio-temporal cluster analysis. Futian and Dapeng would have the highest and the lowest hospital admissions, respectively, although these districts have the highest incidence rates among all of the districts from 2013 to 2015 based on the prediction using the GM (1

  17. A climate-based spatiotemporal prediction for dengue fever epidemics: a case study in southern Taiwan

    NASA Astrophysics Data System (ADS)

    Yu, H.-L.; Yang, S.-J.; Lin, Y.-C.

    2012-04-01

    Dengue Fever (DF) has been identified by the World Health organization (WHO) as one of the most serious vector-borne infectious diseases in tropical and sub-tropical areas. DF has been one of the most important epidemics in Taiwan which occur annually especially in southern Taiwan during summer and autumn. Most DF studies have focused mainly on temporal DF patterns and its close association with climatic covariates, whereas few studies have investigated the spatial DF patterns (spatial dependence and clustering) and composite space-time effects of the DF epidemics. The present study proposes a spatio-temporal DF prediction approach based on stochastic Bayesian Maximum Entropy (BME) analysis. Core and site-specific knowledge bases are considered, including climate and health datasets under conditions of uncertainty, space-time dependence functions, and a Poisson regression model of climatic variables contributing to DF occurrences in southern Taiwan during 2007, when the highest number of DF cases was recorded in the history of Taiwan epidemics (over 2000). The obtained results show that the DF outbreaks in the study area are highly influenced by climatic conditions. Furthermore, the analysis can provide the required "one-week-ahead" outbreak warnings based on spatio-temporal predictions of DF distributions. Therefore, the proposed analysis can provide the Taiwan Disease Control Agency with a valuable tool to timely identify, control, and even efficiently prevent DF spreading across space-time.

  18. Microclimate Data Improve Predictions of Insect Abundance Models Based on Calibrated Spatiotemporal Temperatures

    PubMed Central

    Rebaudo, François; Faye, Emile; Dangles, Olivier

    2016-01-01

    A large body of literature has recently recognized the role of microclimates in controlling the physiology and ecology of species, yet the relevance of fine-scale climatic data for modeling species performance and distribution remains a matter of debate. Using a 6-year monitoring of three potato moth species, major crop pests in the tropical Andes, we asked whether the spatiotemporal resolution of temperature data affect the predictions of models of moth performance and distribution. For this, we used three different climatic data sets: (i) the WorldClim dataset (global dataset), (ii) air temperature recorded using data loggers (weather station dataset), and (iii) air crop canopy temperature (microclimate dataset). We developed a statistical procedure to calibrate all datasets to monthly and yearly variation in temperatures, while keeping both spatial and temporal variances (air monthly temperature at 1 km² for the WorldClim dataset, air hourly temperature for the weather station, and air minute temperature over 250 m radius disks for the microclimate dataset). Then, we computed pest performances based on these three datasets. Results for temperature ranging from 9 to 11°C revealed discrepancies in the simulation outputs in both survival and development rates depending on the spatiotemporal resolution of the temperature dataset. Temperature and simulated pest performances were then combined into multiple linear regression models to compare predicted vs. field data. We used an additional set of study sites to test the ability of the results of our model to be extrapolated over larger scales. Results showed that the model implemented with microclimatic data best predicted observed pest abundances for our study sites, but was less accurate than the global dataset model when performed at larger scales. Our simulations therefore stress the importance to consider different temperature datasets depending on the issue to be solved in order to accurately predict species

  19. Microclimate Data Improve Predictions of Insect Abundance Models Based on Calibrated Spatiotemporal Temperatures.

    PubMed

    Rebaudo, François; Faye, Emile; Dangles, Olivier

    2016-01-01

    A large body of literature has recently recognized the role of microclimates in controlling the physiology and ecology of species, yet the relevance of fine-scale climatic data for modeling species performance and distribution remains a matter of debate. Using a 6-year monitoring of three potato moth species, major crop pests in the tropical Andes, we asked whether the spatiotemporal resolution of temperature data affect the predictions of models of moth performance and distribution. For this, we used three different climatic data sets: (i) the WorldClim dataset (global dataset), (ii) air temperature recorded using data loggers (weather station dataset), and (iii) air crop canopy temperature (microclimate dataset). We developed a statistical procedure to calibrate all datasets to monthly and yearly variation in temperatures, while keeping both spatial and temporal variances (air monthly temperature at 1 km² for the WorldClim dataset, air hourly temperature for the weather station, and air minute temperature over 250 m radius disks for the microclimate dataset). Then, we computed pest performances based on these three datasets. Results for temperature ranging from 9 to 11°C revealed discrepancies in the simulation outputs in both survival and development rates depending on the spatiotemporal resolution of the temperature dataset. Temperature and simulated pest performances were then combined into multiple linear regression models to compare predicted vs. field data. We used an additional set of study sites to test the ability of the results of our model to be extrapolated over larger scales. Results showed that the model implemented with microclimatic data best predicted observed pest abundances for our study sites, but was less accurate than the global dataset model when performed at larger scales. Our simulations therefore stress the importance to consider different temperature datasets depending on the issue to be solved in order to accurately predict species

  20. The Effect of Rainfall Measurement Technique and Its Spatiotemporal Resolution on Discharge Predictions in the Netherlands

    NASA Astrophysics Data System (ADS)

    Uijlenhoet, R.; Brauer, C.; Overeem, A.; Sassi, M.; Rios Gaona, M. F.

    2014-12-01

    Several rainfall measurement techniques are available for hydrological applications, each with its own spatial and temporal resolution. We investigated the effect of these spatiotemporal resolutions on discharge simulations in lowland catchments by forcing a novel rainfall-runoff model (WALRUS) with rainfall data from gauges, radars and microwave links. The hydrological model used for this analysis is the recently developed Wageningen Lowland Runoff Simulator (WALRUS). WALRUS is a rainfall-runoff model accounting for hydrological processes relevant to areas with shallow groundwater (e.g. groundwater-surface water feedback). Here, we used WALRUS for case studies in a freely draining lowland catchment and a polder with controlled water levels. We used rain gauge networks with automatic (hourly resolution but low spatial density) and manual gauges (high spatial density but daily resolution). Operational (real-time) and climatological (gauge-adjusted) C-band radar products and country-wide rainfall maps derived from microwave link data from a cellular telecommunication network were also used. Discharges simulated with these different inputs were compared to observations. We also investigated the effect of spatiotemporal resolution with a high-resolution X-band radar data set for catchments with different sizes. Uncertainty in rainfall forcing is a major source of uncertainty in discharge predictions, both with lumped and with distributed models. For lumped rainfall-runoff models, the main source of input uncertainty is associated with the way in which (effective) catchment-average rainfall is estimated. When catchments are divided into sub-catchments, rainfall spatial variability can become more important, especially during convective rainfall events, leading to spatially varying catchment wetness and spatially varying contribution of quick flow routes. Improving rainfall measurements and their spatiotemporal resolution can improve the performance of rainfall

  1. Spatiotemporal models for predicting high pollen concentration level of Corylus, Alnus, and Betula

    NASA Astrophysics Data System (ADS)

    Nowosad, Jakub

    2016-06-01

    Corylus, Alnus, and Betula trees are among the most important sources of allergic pollen in the temperate zone of the Northern Hemisphere and have a large impact on the quality of life and productivity of allergy sufferers. Therefore, it is important to predict high pollen concentrations, both in time and space. The aim of this study was to create and evaluate spatiotemporal models for predicting high Corylus, Alnus, and Betula pollen concentration levels, based on gridded meteorological data. Aerobiological monitoring was carried out in 11 cities in Poland and gathered, depending on the site, between 2 and 16 years of measurements. According to the first allergy symptoms during exposure, a high pollen count level was established for each taxon. An optimizing probability threshold technique was used for mitigation of the problem of imbalance in the pollen concentration levels. For each taxon, the model was built using a random forest method. The study revealed the possibility of moderately reliable prediction of Corylus and highly reliable prediction of Alnus and Betula high pollen concentration levels, using preprocessed gridded meteorological data. Cumulative growing degree days and potential evaporation proved to be two of the most important predictor variables in the models. The final models predicted not only for single locations but also for continuous areas. Furthermore, the proposed modeling framework could be used to predict high pollen concentrations of Corylus, Alnus, Betula, and other taxa, and in other countries.

  2. Spatiotemporal models for predicting high pollen concentration level of Corylus, Alnus, and Betula.

    PubMed

    Nowosad, Jakub

    2016-06-01

    Corylus, Alnus, and Betula trees are among the most important sources of allergic pollen in the temperate zone of the Northern Hemisphere and have a large impact on the quality of life and productivity of allergy sufferers. Therefore, it is important to predict high pollen concentrations, both in time and space. The aim of this study was to create and evaluate spatiotemporal models for predicting high Corylus, Alnus, and Betula pollen concentration levels, based on gridded meteorological data. Aerobiological monitoring was carried out in 11 cities in Poland and gathered, depending on the site, between 2 and 16 years of measurements. According to the first allergy symptoms during exposure, a high pollen count level was established for each taxon. An optimizing probability threshold technique was used for mitigation of the problem of imbalance in the pollen concentration levels. For each taxon, the model was built using a random forest method. The study revealed the possibility of moderately reliable prediction of Corylus and highly reliable prediction of Alnus and Betula high pollen concentration levels, using preprocessed gridded meteorological data. Cumulative growing degree days and potential evaporation proved to be two of the most important predictor variables in the models. The final models predicted not only for single locations but also for continuous areas. Furthermore, the proposed modeling framework could be used to predict high pollen concentrations of Corylus, Alnus, Betula, and other taxa, and in other countries.

  3. Spatiotemporal models for predicting high pollen concentration level of Corylus, Alnus, and Betula.

    PubMed

    Nowosad, Jakub

    2016-06-01

    Corylus, Alnus, and Betula trees are among the most important sources of allergic pollen in the temperate zone of the Northern Hemisphere and have a large impact on the quality of life and productivity of allergy sufferers. Therefore, it is important to predict high pollen concentrations, both in time and space. The aim of this study was to create and evaluate spatiotemporal models for predicting high Corylus, Alnus, and Betula pollen concentration levels, based on gridded meteorological data. Aerobiological monitoring was carried out in 11 cities in Poland and gathered, depending on the site, between 2 and 16 years of measurements. According to the first allergy symptoms during exposure, a high pollen count level was established for each taxon. An optimizing probability threshold technique was used for mitigation of the problem of imbalance in the pollen concentration levels. For each taxon, the model was built using a random forest method. The study revealed the possibility of moderately reliable prediction of Corylus and highly reliable prediction of Alnus and Betula high pollen concentration levels, using preprocessed gridded meteorological data. Cumulative growing degree days and potential evaporation proved to be two of the most important predictor variables in the models. The final models predicted not only for single locations but also for continuous areas. Furthermore, the proposed modeling framework could be used to predict high pollen concentrations of Corylus, Alnus, Betula, and other taxa, and in other countries. PMID:26487352

  4. Development of Spatiotemporal Bias-Correction Techniques for Downscaling GCM Predictions

    NASA Astrophysics Data System (ADS)

    Hwang, S.; Graham, W. D.; Geurink, J.; Adams, A.; Martinez, C. J.

    2010-12-01

    Accurately representing the spatial variability of precipitation is an important factor for predicting watershed response to climatic forcing, particularly in small, low-relief watersheds affected by convective storm systems. Although Global Circulation Models (GCMs) generally preserve spatial relationships between large-scale and local-scale mean precipitation trends, most GCM downscaling techniques focus on preserving only observed temporal variability on point by point basis, not spatial patterns of events. Downscaled GCM results (e.g., CMIP3 ensembles) have been widely used to predict hydrologic implications of climate variability and climate change in large snow-dominated river basins in the western United States (Diffenbaugh et al., 2008; Adam et al., 2009). However fewer applications to smaller rain-driven river basins in the southeastern US (where preserving spatial variability of rainfall patterns may be more important) have been reported. In this study a new method was developed to bias-correct GCMs to preserve both the long term temporal mean and variance of the precipitation data, and the spatial structure of daily precipitation fields. Forty-year retrospective simulations (1960-1999) from 16 GCMs were collected (IPCC, 2007; WCRP CMIP3 multi-model database: https://esg.llnl.gov:8443/), and the daily precipitation data at coarse resolution (i.e., 280km) were interpolated to 12km spatial resolution and bias corrected using gridded observations over the state of Florida (Maurer et al., 2002; Wood et al, 2002; Wood et al, 2004). In this method spatial random fields which preserved the observed spatial correlation structure of the historic gridded observations and the spatial mean corresponding to the coarse scale GCM daily rainfall were generated. The spatiotemporal variability of the spatio-temporally bias-corrected GCMs were evaluated against gridded observations, and compared to the original temporally bias-corrected and downscaled CMIP3 data for the

  5. Serial interactome capture of the human cell nucleus.

    PubMed

    Conrad, Thomas; Albrecht, Anne-Susann; de Melo Costa, Veronica Rodrigues; Sauer, Sascha; Meierhofer, David; Ørom, Ulf Andersson

    2016-04-04

    Novel RNA-guided cellular functions are paralleled by an increasing number of RNA-binding proteins (RBPs). Here we present 'serial RNA interactome capture' (serIC), a multiple purification procedure of ultraviolet-crosslinked poly(A)-RNA-protein complexes that enables global RBP detection with high specificity. We apply serIC to the nuclei of proliferating K562 cells to obtain the first human nuclear RNA interactome. The domain composition of the 382 identified nuclear RBPs markedly differs from previous IC experiments, including few factors without known RNA-binding domains that are in good agreement with computationally predicted RNA binding. serIC extends the number of DNA-RNA-binding proteins (DRBPs), and reveals a network of RBPs involved in p53 signalling and double-strand break repair. serIC is an effective tool to couple global RBP capture with additional selection or labelling steps for specific detection of highly purified RBPs.

  6. Serial interactome capture of the human cell nucleus.

    PubMed

    Conrad, Thomas; Albrecht, Anne-Susann; de Melo Costa, Veronica Rodrigues; Sauer, Sascha; Meierhofer, David; Ørom, Ulf Andersson

    2016-01-01

    Novel RNA-guided cellular functions are paralleled by an increasing number of RNA-binding proteins (RBPs). Here we present 'serial RNA interactome capture' (serIC), a multiple purification procedure of ultraviolet-crosslinked poly(A)-RNA-protein complexes that enables global RBP detection with high specificity. We apply serIC to the nuclei of proliferating K562 cells to obtain the first human nuclear RNA interactome. The domain composition of the 382 identified nuclear RBPs markedly differs from previous IC experiments, including few factors without known RNA-binding domains that are in good agreement with computationally predicted RNA binding. serIC extends the number of DNA-RNA-binding proteins (DRBPs), and reveals a network of RBPs involved in p53 signalling and double-strand break repair. serIC is an effective tool to couple global RBP capture with additional selection or labelling steps for specific detection of highly purified RBPs. PMID:27040163

  7. Predicted spatio-temporal dynamics of radiocesium deposited onto forests following the Fukushima nuclear accident

    PubMed Central

    Hashimoto, Shoji; Matsuura, Toshiya; Nanko, Kazuki; Linkov, Igor; Shaw, George; Kaneko, Shinji

    2013-01-01

    The majority of the area contaminated by the Fukushima Dai-ichi nuclear power plant accident is covered by forest. To facilitate effective countermeasure strategies to mitigate forest contamination, we simulated the spatio-temporal dynamics of radiocesium deposited into Japanese forest ecosystems in 2011 using a model that was developed after the Chernobyl accident in 1986. The simulation revealed that the radiocesium inventories in tree and soil surface organic layer components drop rapidly during the first two years after the fallout. Over a period of one to two years, the radiocesium is predicted to move from the tree and surface organic soil to the mineral soil, which eventually becomes the largest radiocesium reservoir within forest ecosystems. Although the uncertainty of our simulations should be considered, the results provide a basis for understanding and anticipating the future dynamics of radiocesium in Japanese forests following the Fukushima accident. PMID:23995073

  8. The HTLV-1 Tax interactome

    PubMed Central

    Boxus, Mathieu; Twizere, Jean-Claude; Legros, Sébastien; Dewulf, Jean-François; Kettmann, Richard; Willems, Luc

    2008-01-01

    The Tax1 oncoprotein encoded by Human T-lymphotropic virus type I is a major determinant of viral persistence and pathogenesis. Tax1 affects a wide variety of cellular signalling pathways leading to transcriptional activation, proliferation and ultimately transformation. To carry out these functions, Tax1 interacts with and modulates activity of a number of cellular proteins. In this review, we summarize the present knowledge of the Tax1 interactome and propose a rationale for the broad range of cellular proteins identified so far. PMID:18702816

  9. Network Organization of the Huntingtin Proteomic Interactome in Mammalian Brain

    PubMed Central

    Shirasaki, Dyna I.; Greiner, Erin R.; Al-Ramahi, Ismael; Gray, Michelle; Boontheung, Pinmanee; Geschwind, Daniel H.; Botas, Juan; Coppola, Giovanni; Horvath, Steve; Loo, Joseph A.; Yang, X. William

    2012-01-01

    SUMMARY We used affinity-purification mass spectrometry to identify 747 candidate proteins that are complexed with Huntingtin (Htt) in distinct brain regions and ages in Huntington’s disease (HD) and wildtype mouse brains. To gain a systems-level view of the Htt interactome, we applied Weighted Gene Correlation Network Analysis (WGCNA) to the entire proteomic dataset to unveil a verifiable rank of Htt-correlated proteins and a network of Htt-interacting protein modules, with each module highlighting distinct aspects of Htt biology. Importantly, the Htt-containing module is highly enriched with proteins involved in 14-3-3 signaling, microtubule-based transport, and proteostasis. Top-ranked proteins in this module were validated as novel Htt interactors and genetic modifiers in an HD Drosophila model. Together, our study provides a compendium of spatiotemporal Htt-interacting proteins in the mammalian brain, and presents a conceptually novel approach to analyze proteomic interactome datasets to build in vivo protein networks in complex tissues such as the brain. PMID:22794259

  10. A comparison of predictive soil-carbon models across multiple spatio-temporal catchment scales.

    NASA Astrophysics Data System (ADS)

    Hancock, G. R.; Kunkel, V.; Wells, T.

    2014-12-01

    Soil's potential as a carbon sink for atmospheric CO2 has been widely discussed. Studies of soil organic carbon (SOC) controls, and the subsequent models derived from their findings, have focussed mainly on North American and European regions, and more recently, in regions such as China. In Australia, agricultural practices have led to losses in SOC. This implies that Australian soils have a large potential for increases in SOC. Building on previous work, here we examine the spatial and temporal variation in soil organic carbon (SOC) and its controlling factors controls across a large catchment of approximately 600 km2 in the Upper Hunter Valley, New South Wales, Australia, using data collected from two sampling campaigns, (April 2006 and June-July 2014). Remote sensing using Landsat (30m) and MODIS (250m) NDVI was used to determine if catchment SOC could be predicted using both low and high resolution remote sensing . Relationships between SOC and elevation, aboveground biomass (as represented by NDVI), topographic wetness index (TWI), and incident solar radiation as a surrogate for soil temperature were compared. Initial results demonstrate that higher spatio-temporal resolution may not be necessary for predicting SOC at larger scales. The relationship between SOC and the environmental tracer 137-Cesium as a surrogate for the loss of SOC by erosion also suggests that sediment transport and deposition influences the distribution of SOC. A model developed for the site suggests that simple linear relationships between vegetation, climate and sediment transport could improve SOC predictions.

  11. An online spatio-temporal prediction model for dengue fever epidemic in Kaohsiung,Taiwan

    NASA Astrophysics Data System (ADS)

    Cheng, Ming-Hung; Yu, Hwa-Lung; Angulo, Jose; Christakos, George

    2013-04-01

    Dengue Fever (DF) is one of the most serious vector-borne infectious diseases in tropical and subtropical areas. DF epidemics occur in Taiwan annually especially during summer and fall seasons. Kaohsiung city has been one of the major DF hotspots in decades. The emergence and re-emergence of the DF epidemic is complex and can be influenced by various factors including space-time dynamics of human and vector populations and virus serotypes as well as the associated uncertainties. This study integrates a stochastic space-time "Susceptible-Infected-Recovered" model under Bayesian maximum entropy framework (BME-SIR) to perform real-time prediction of disease diffusion across space-time. The proposed model is applied for spatiotemporal prediction of the DF epidemic at Kaohsiung city during 2002 when the historical series of high DF cases was recorded. The online prediction by BME-SIR model updates the parameters of SIR model and infected cases across districts over time. Results show that the proposed model is rigorous to initial guess of unknown model parameters, i.e. transmission and recovery rates, which can depend upon the virus serotypes and various human interventions. This study shows that spatial diffusion can be well characterized by BME-SIR model, especially at the district surrounding the disease outbreak locations. The prediction performance at DF hotspots, i.e. Cianjhen and Sanmin, can be degraded due to the implementation of various disease control strategies during the epidemics. The proposed online disease prediction BME-SIR model can provide the governmental agency with a valuable reference to timely identify, control, and efficiently prevent DF spread across space-time.

  12. Proteomic-coupled-network analysis of T877A-androgen receptor interactomes can predict clinical prostate cancer outcomes between White (non-Hispanic) and African-American groups.

    PubMed

    Zaman, Naif; Giannopoulos, Paresa N; Chowdhury, Shafinaz; Bonneil, Eric; Thibault, Pierre; Wang, Edwin; Trifiro, Mark; Paliouras, Miltiadis

    2014-01-01

    The androgen receptor (AR) remains an important contributor to the neoplastic evolution of prostate cancer (CaP). CaP progression is linked to several somatic AR mutational changes that endow upon the AR dramatic gain-of-function properties. One of the most common somatic mutations identified is Thr877-to-Ala (T877A), located in the ligand-binding domain, that results in a receptor capable of promiscuous binding and activation by a variety of steroid hormones and ligands including estrogens, progestins, glucocorticoids, and several anti-androgens. In an attempt to further define somatic mutated AR gain-of-function properties, as a consequence of its promiscuous ligand binding, we undertook a proteomic/network analysis approach to characterize the protein interactome of the mutant T877A-AR in LNCaP cells under eight different ligand-specific treatments (dihydrotestosterone, mibolerone, R1881, testosterone, estradiol, progesterone, dexamethasone, and cyproterone acetate). In extending the analysis of our multi-ligand complexes of the mutant T877A-AR we observed significant enrichment of specific complexes between normal and primary prostatic tumors, which were furthermore correlated with known clinical outcomes. Further analysis of certain mutant T877A-AR complexes showed specific population preferences distinguishing primary prostatic disease between white (non-Hispanic) vs. African-American males. Moreover, these cancer-related AR-protein complexes demonstrated predictive survival outcomes specific to CaP, and not for breast, lung, lymphoma or medulloblastoma cancers. Our study, by coupling data generated by our proteomics to network analysis of clinical samples, has helped to define real and novel biological pathways in complicated gain-of-function AR complex systems.

  13. Proteomic-Coupled-Network Analysis of T877A-Androgen Receptor Interactomes Can Predict Clinical Prostate Cancer Outcomes between White (Non-Hispanic) and African-American Groups

    PubMed Central

    Zaman, Naif; Giannopoulos, Paresa N.; Chowdhury, Shafinaz; Bonneil, Eric; Thibault, Pierre; Wang, Edwin; Trifiro, Mark; Paliouras, Miltiadis

    2014-01-01

    The androgen receptor (AR) remains an important contributor to the neoplastic evolution of prostate cancer (CaP). CaP progression is linked to several somatic AR mutational changes that endow upon the AR dramatic gain-of-function properties. One of the most common somatic mutations identified is Thr877-to-Ala (T877A), located in the ligand-binding domain, that results in a receptor capable of promiscuous binding and activation by a variety of steroid hormones and ligands including estrogens, progestins, glucocorticoids, and several anti-androgens. In an attempt to further define somatic mutated AR gain-of-function properties, as a consequence of its promiscuous ligand binding, we undertook a proteomic/network analysis approach to characterize the protein interactome of the mutant T877A-AR in LNCaP cells under eight different ligand-specific treatments (dihydrotestosterone, mibolerone, R1881, testosterone, estradiol, progesterone, dexamethasone, and cyproterone acetate). In extending the analysis of our multi-ligand complexes of the mutant T877A-AR we observed significant enrichment of specific complexes between normal and primary prostatic tumors, which were furthermore correlated with known clinical outcomes. Further analysis of certain mutant T877A-AR complexes showed specific population preferences distinguishing primary prostatic disease between white (non-Hispanic) vs. African-American males. Moreover, these cancer-related AR-protein complexes demonstrated predictive survival outcomes specific to CaP, and not for breast, lung, lymphoma or medulloblastoma cancers. Our study, by coupling data generated by our proteomics to network analysis of clinical samples, has helped to define real and novel biological pathways in complicated gain-of-function AR complex systems. PMID:25409505

  14. Comprehensive analysis of TGF-β and BMP receptor interactomes.

    PubMed

    Poorgholi Belverdi, Mohammad; Krause, Carola; Guzman, Asja; Knaus, Petra

    2012-04-01

    An immense number of cellular processes are initiated by cell surface serine/threonine kinase receptors belonging to the TGF-β/BMP family. Subsequent downstream signalling cascades, as well as their crosstalk results in enormous specificity in terms of phenotypic outcome, e.g. proliferation, differentiation, migration or apoptosis. Such signalling diversity is achieved by the ability of receptors to interact with distinct proteins in a spatio-temporal manner. Following the cloning of the TGF-β/BMP receptors a variety of different technologies were applied to identify such interacting proteins. Here we present a comprehensive survey of known interactome analyses, including our own data, on these receptors and discuss advantages and disadvantages of the applied technologies. PMID:21715044

  15. Geomagnetic imprinting predicts spatio-temporal variation in homing migration of pink and sockeye salmon.

    PubMed

    Putman, Nathan F; Jenkins, Erica S; Michielsens, Catherine G J; Noakes, David L G

    2014-10-01

    Animals navigate using a variety of sensory cues, but how each is weighted during different phases of movement (e.g. dispersal, foraging, homing) is controversial. Here, we examine the geomagnetic and olfactory imprinting hypotheses of natal homing with datasets that recorded variation in the migratory routes of sockeye (Oncorhynchus nerka) and pink (Oncorhynchus gorbuscha) salmon returning from the Pacific Ocean to the Fraser River, British Columbia. Drift of the magnetic field (i.e. geomagnetic imprinting) uniquely accounted for 23.2% and 44.0% of the variation in migration routes for sockeye and pink salmon, respectively. Ocean circulation (i.e. olfactory imprinting) predicted 6.1% and 0.1% of the variation in sockeye and pink migration routes, respectively. Sea surface temperature (a variable influencing salmon distribution but not navigation, directly) accounted for 13.0% of the variation in sockeye migration but was unrelated to pink migration. These findings suggest that geomagnetic navigation plays an important role in long-distance homing in salmon and that consideration of navigation mechanisms can aid in the management of migratory fishes by better predicting movement patterns. Finally, given the diversity of animals that use the Earth's magnetic field for navigation, geomagnetic drift may provide a unifying explanation for spatio-temporal variation in the movement patterns of many species. PMID:25056214

  16. Tumor site prediction using spatiotemporal detection of subclinical hyperemia in experimental photocarcinogenesis

    NASA Astrophysics Data System (ADS)

    Konger, Raymond L.; Xu, Zhengbin; Sahu, Ravi P.; Kim, Young L.

    2014-03-01

    We demonstrate that a spatial and temporal analysis of subclinical hyperemia reliably predicts specific areas at high risk for skin tumor development during photocarcinogenesis. To determine detailed spatiotemporal patterns of inflammatory angiogenesis foci in a relatively large area, we developed a mesoscopic (between microscopic and macroscopic) imaging approach. This method relies on our earlier finding that the combination of a spectral analysis of hemoglobin with diffuse-light-suppressed imaging can increase the image resolution, contrast and penetration depth to visualize microvasculature Hgb content in the large tissue area. In our recent study, SKH1 hairless albino mice were irradiated for 10 weeks with a carcinogen dose of UVB. Using our newly developed mesoscopic imaging methods, we imaged the mice over 20 - 30 weeks after stopping UVB, and excised hyperemic/non-hyperemic areas at several different timepoints. We show that persistent hyperemic foci can predict future tumor formation. In particular, our imaging approach allows us to assess the spatial and temporal extent of subclinical inflammatory foci, which in turn can predict sites of future overlying tumor formation. In addition, although COX-2 inhibitors are known to suppress skin cancer development in humans, it remains unclear whether the chemopreventive activity of COX-2 inhibitors are chiefly attributable to their anti-inflammatory effects. Our study provides evidence that subclinical subepithelial inflammatory foci occur prior to overt tumor formation, and that these areas are highly predictive for future tumor formation, that celecoxib's ability to suppress tumorigenesis is tightly linked to its ability to reduce the area of subclinical inflammatory foci.

  17. Disease networks. Uncovering disease-disease relationships through the incomplete interactome.

    PubMed

    Menche, Jörg; Sharma, Amitabh; Kitsak, Maksim; Ghiassian, Susan Dina; Vidal, Marc; Loscalzo, Joseph; Barabási, Albert-László

    2015-02-20

    According to the disease module hypothesis, the cellular components associated with a disease segregate in the same neighborhood of the human interactome, the map of biologically relevant molecular interactions. Yet, given the incompleteness of the interactome and the limited knowledge of disease-associated genes, it is not obvious if the available data have sufficient coverage to map out modules associated with each disease. Here we derive mathematical conditions for the identifiability of disease modules and show that the network-based location of each disease module determines its pathobiological relationship to other diseases. For example, diseases with overlapping network modules show significant coexpression patterns, symptom similarity, and comorbidity, whereas diseases residing in separated network neighborhoods are phenotypically distinct. These tools represent an interactome-based platform to predict molecular commonalities between phenotypically related diseases, even if they do not share primary disease genes.

  18. Evolution of protein interactions: from interactomes to interfaces.

    PubMed

    Andreani, Jessica; Guerois, Raphael

    2014-07-15

    Protein-protein interactions lie at the heart of most cellular processes. Many experimental and computational studies aim to deepen our understanding of these interactions and improve our capacity to predict them. In this respect, the evolutionary perspective is most interesting, since the preservation of structure and function puts constraints on the evolution of proteins and their interactions. However, uncovering these constraints remains a challenge, and the description and detection of evolutionary signals in protein-protein interactions is currently a very active field of research. Here, we review recent works dissecting the mechanisms of protein-protein interaction evolution and exploring how to use evolutionary information to predict interactions, both at the global level of the interactome and at the detailed level of protein-protein interfaces. We first present to what extent protein-protein interactions are found to be conserved within interactomes and which properties can influence their conservation. We then discuss the evolutionary and co-evolutionary pressures applied on protein-protein interfaces. Finally, we describe how the computational prediction of interfaces can benefit from evolutionary inputs. PMID:24853495

  19. Serial interactome capture of the human cell nucleus

    PubMed Central

    Conrad, Thomas; Albrecht, Anne-Susann; de Melo Costa, Veronica Rodrigues; Sauer, Sascha; Meierhofer, David; Ørom, Ulf Andersson

    2016-01-01

    Novel RNA-guided cellular functions are paralleled by an increasing number of RNA-binding proteins (RBPs). Here we present ‘serial RNA interactome capture' (serIC), a multiple purification procedure of ultraviolet-crosslinked poly(A)–RNA–protein complexes that enables global RBP detection with high specificity. We apply serIC to the nuclei of proliferating K562 cells to obtain the first human nuclear RNA interactome. The domain composition of the 382 identified nuclear RBPs markedly differs from previous IC experiments, including few factors without known RNA-binding domains that are in good agreement with computationally predicted RNA binding. serIC extends the number of DNA–RNA-binding proteins (DRBPs), and reveals a network of RBPs involved in p53 signalling and double-strand break repair. serIC is an effective tool to couple global RBP capture with additional selection or labelling steps for specific detection of highly purified RBPs. PMID:27040163

  20. Utilizing the eigenvectors of freeway loop data spatiotemporal schematic for real time crash prediction.

    PubMed

    Fang, Shou'en; Xie, Wenjing; Wang, Junhua; Ragland, David R

    2016-09-01

    The concept of crash precursor identification is gaining more practicality due to the recent advancements in Advanced Transportation Management and Information Systems. Investigating the shortcomings of the existing models, this paper proposes a new method to model the real time crash likelihood based on loop data through schematic eigenvectors. Firstly, traffic volume, occupancy and density spatiotemporal schematics in certain duration before an accident occurrence were constructed to describe the traffic flow status. Secondly, eigenvectors and eigenvalues of the spatiotemporal schematics were extracted to represent traffic volume, occupancy and density situation before the crash occurrence. Thirdly, by setting the vectors in crash time as case and those at crash free time as control, a logistic model is constructed to identify the crash precursors. Results show that both the eigenvectors and eigenvalues can significantly impact the accident likelihood compared to the previous study, the proposed model has the advantage of avoiding multicollinearity, better reflection of the overall traffic flow status before the crash, and improving missing data problem of loop detectors.

  1. Utilizing the eigenvectors of freeway loop data spatiotemporal schematic for real time crash prediction.

    PubMed

    Fang, Shou'en; Xie, Wenjing; Wang, Junhua; Ragland, David R

    2016-09-01

    The concept of crash precursor identification is gaining more practicality due to the recent advancements in Advanced Transportation Management and Information Systems. Investigating the shortcomings of the existing models, this paper proposes a new method to model the real time crash likelihood based on loop data through schematic eigenvectors. Firstly, traffic volume, occupancy and density spatiotemporal schematics in certain duration before an accident occurrence were constructed to describe the traffic flow status. Secondly, eigenvectors and eigenvalues of the spatiotemporal schematics were extracted to represent traffic volume, occupancy and density situation before the crash occurrence. Thirdly, by setting the vectors in crash time as case and those at crash free time as control, a logistic model is constructed to identify the crash precursors. Results show that both the eigenvectors and eigenvalues can significantly impact the accident likelihood compared to the previous study, the proposed model has the advantage of avoiding multicollinearity, better reflection of the overall traffic flow status before the crash, and improving missing data problem of loop detectors. PMID:27258946

  2. Mapping the functional yeast ABC transporter interactome

    PubMed Central

    Snider, Jamie; Hanif, Asad; Lee, Mid Eum; Jin, Ke; Yu, Analyn R.; Graham, Chris; Chuk, Matthew; Damjanovic, Dunja; Wierzbicka, Marta; Tang, Priscilla; Balderes, Dina; Wong, Victoria; Jessulat, Matthew; Darowski, Katelyn D.; Luis, Bryan-Joseph San; Shevelev, Igor; Sturley, Stephen L; Boone, Charles; Greenblatt, Jack F.; Zhang, Zhaolei; Paumi, Christian M.; Babu, Mohan; Park, Hay-Oak; Michaelis, Susan; Stagljar, Igor

    2013-01-01

    ABC transporters are a ubiquitous class of integral membrane proteins of immense clinical interest because of their strong association with human disease and pharmacology. To improve our understanding of these proteins, we used Membrane Yeast Two-Hybrid (MYTH) technology to map the protein interactome of all non-mitochondrial ABC transporters in the model organism Saccharomy cescerevisiae, and combined this data with previously reported yeast ABC transporter interactions in the BioGRID database to generate a comprehensive, integrated interactome. We show that ABC transporters physically associate with proteins involved in a surprisingly diverse range of functions. We specifically examine the importance of the physical interactions of ABC transporters in both the regulation of one another and in the modulation of proteins involved in zinc homeostasis. The interaction network presented here will be a powerful resource for increasing our fundamental understanding of the cellular role and regulation of ABC transporters. PMID:23831759

  3. The Levinthal paradox of the interactome.

    PubMed

    Tompa, Peter; Rose, George D

    2011-12-01

    The central biological question of the 21st century is: how does a viable cell emerge from the bewildering combinatorial complexity of its molecular components? Here, we estimate the combinatorics of self-assembling the protein constituents of a yeast cell, a number so vast that the functional interactome could only have emerged by iterative hierarchic assembly of its component sub-assemblies. A protein can undergo both reversible denaturation and hierarchic self-assembly spontaneously, but a functioning interactome must expend energy to achieve viability. Consequently, it is implausible that a completely "denatured" cell could be reversibly renatured spontaneously, like a protein. Instead, new cells are generated by the division of pre-existing cells, an unbroken chain of renewal tracking back through contingent conditions and evolving responses to the origin of life on the prebiotic earth. We surmise that this non-deterministic temporal continuum could not be reconstructed de novo under present conditions. PMID:21987416

  4. Inferring the Brassica rapa Interactome Using Protein-Protein Interaction Data from Arabidopsis thaliana.

    PubMed

    Yang, Jianhua; Osman, Kim; Iqbal, Mudassar; Stekel, Dov J; Luo, Zewei; Armstrong, Susan J; Franklin, F Chris H

    2012-01-01

    Following successful completion of the Brassica rapa sequencing project, the next step is to investigate functions of individual genes/proteins. For Arabidopsis thaliana, large amounts of protein-protein interaction (PPI) data are available from the major PPI databases (DBs). It is known that Brassica crop species are closely related to A. thaliana. This provides an opportunity to infer the B. rapa interactome using PPI data available from A. thaliana. In this paper, we present an inferred B. rapa interactome that is based on the A. thaliana PPI data from two resources: (i) A. thaliana PPI data from three major DBs, BioGRID, IntAct, and TAIR. (ii) ortholog-based A. thaliana PPI predictions. Linking between B. rapa and A. thaliana was accomplished in three complementary ways: (i) ortholog predictions, (ii) identification of gene duplication based on synteny and collinearity, and (iii) BLAST sequence similarity search. A complementary approach was also applied, which used known/predicted domain-domain interaction data. Specifically, since the two species are closely related, we used PPI data from A. thaliana to predict interacting domains that might be conserved between the two species. The predicted interactome was investigated for the component that contains known A. thaliana meiotic proteins to demonstrate its usability.

  5. APID interactomes: providing proteome-based interactomes with controlled quality for multiple species and derived networks

    PubMed Central

    Alonso-López, Diego; Gutiérrez, Miguel A.; Lopes, Katia P.; Prieto, Carlos; Santamaría, Rodrigo; De Las Rivas, Javier

    2016-01-01

    APID (Agile Protein Interactomes DataServer) is an interactive web server that provides unified generation and delivery of protein interactomes mapped to their respective proteomes. This resource is a new, fully redesigned server that includes a comprehensive collection of protein interactomes for more than 400 organisms (25 of which include more than 500 interactions) produced by the integration of only experimentally validated protein–protein physical interactions. For each protein–protein interaction (PPI) the server includes currently reported information about its experimental validation to allow selection and filtering at different quality levels. As a whole, it provides easy access to the interactomes from specific species and includes a global uniform compendium of 90,379 distinct proteins and 678,441 singular interactions. APID integrates and unifies PPIs from major primary databases of molecular interactions, from other specific repositories and also from experimentally resolved 3D structures of protein complexes where more than two proteins were identified. For this purpose, a collection of 8,388 structures were analyzed to identify specific PPIs. APID also includes a new graph tool (based on Cytoscape.js) for visualization and interactive analyses of PPI networks. The server does not require registration and it is freely available for use at http://apid.dep.usal.es. PMID:27131791

  6. Spatiotemporal prediction of fine particulate matter using high-resolution satellite images in the Southeastern US 2003-2011.

    PubMed

    Lee, Mihye; Kloog, Itai; Chudnovsky, Alexandra; Lyapustin, Alexei; Wang, Yujie; Melly, Steven; Coull, Brent; Koutrakis, Petros; Schwartz, Joel

    2016-06-01

    Numerous studies have demonstrated that fine particulate matter (PM2.5, particles smaller than 2.5 μm in aerodynamic diameter) is associated with adverse health outcomes. The use of ground monitoring stations of PM2.5 to assess personal exposure, however, induces measurement error. Land-use regression provides spatially resolved predictions but land-use terms do not vary temporally. Meanwhile, the advent of satellite-retrieved aerosol optical depth (AOD) products have made possible to predict the spatial and temporal patterns of PM2.5 exposures. In this paper, we used AOD data with other PM2.5 variables, such as meteorological variables, land-use regression, and spatial smoothing to predict daily concentrations of PM2.5 at a 1-km(2) resolution of the Southeastern United States including the seven states of Georgia, North Carolina, South Carolina, Alabama, Tennessee, Mississippi, and Florida for the years from 2003 to 2011. We divided the study area into three regions and applied separate mixed-effect models to calibrate AOD using ground PM2.5 measurements and other spatiotemporal predictors. Using 10-fold cross-validation, we obtained out of sample R(2) values of 0.77, 0.81, and 0.70 with the square root of the mean squared prediction errors of 2.89, 2.51, and 2.82 μg/m(3) for regions 1, 2, and 3, respectively. The slopes of the relationships between predicted PM2.5 and held out measurements were approximately 1 indicating no bias between the observed and modeled PM2.5 concentrations. Predictions can be used in epidemiological studies investigating the effects of both acute and chronic exposures to PM2.5. Our model results will also extend the existing studies on PM2.5 which have mostly focused on urban areas because of the paucity of monitors in rural areas.

  7. Using spatio-temporal modeling to predict long-term exposure to black smoke at fine spatial and temporal scale

    NASA Astrophysics Data System (ADS)

    Dadvand, Payam; Rushton, Stephen; Diggle, Peter J.; Goffe, Louis; Rankin, Judith; Pless-Mulloli, Tanja

    2011-01-01

    Whilst exposure to air pollution is linked to a wide range of adverse health outcomes, assessing levels of this exposure has remained a challenge. This study reports a modeling approach for the estimation of weekly levels of ambient black smoke (BS) at residential postcodes across Northeast England (2055 km 2) over a 12 year period (1985-1996). A two-stage modeling strategy was developed using monitoring data on BS together with a range of covariates including data on traffic, population density, industrial activity, land cover (remote sensing), and meteorology. The first stage separates the temporal trend in BS for the region as a whole from within-region spatial variation and the second stage is a linear model which predicts BS levels at all locations in the region using spatially referenced covariate data as predictors and the regional predicted temporal trend as an offset. Traffic and land cover predictors were included in the final model, which predicted 70% of the spatio-temporal variation in BS across the study region over the study period. This modeling approach appears to provide a robust way of estimating exposure to BS at an inter-urban scale.

  8. Air temperature suitability for Plasmodium falciparum malaria transmission in Africa 2000-2012: a high-resolution spatiotemporal prediction

    PubMed Central

    2014-01-01

    Background Temperature suitability for malaria transmission is a useful predictor variable for spatial models of malaria infection prevalence. Existing continental or global models, however, are synoptic in nature and so do not characterize inter-annual variability in seasonal patterns of temperature suitability, reducing their utility for predicting malaria risk. Methods A malaria Temperature Suitability Index (TSI) was created by first modeling minimum and maximum air temperature with an eight-day temporal resolution from gap-filled MODerate Resolution Imaging Spectroradiometer (MODIS) daytime and night-time Land Surface Temperature (LST) datasets. An improved version of an existing biological model for malaria temperature suitability was then applied to the resulting temperature information for a 13-year data series. The mechanism underlying this biological model is simulation of emergent mosquito cohorts on a two-hour time-step and tracking of each cohort throughout its life to quantify the impact air temperature has on both mosquito survival and sporozoite development. Results The results of this research consist of 154 monthly raster surfaces that characterize spatiotemporal patterns in TSI across Africa from April 2000 through December 2012 at a 1 km spatial resolution. Generalized TSI patterns were as expected, with consistently high values in equatorial rain forests, seasonally variable values in tropical savannas (wet and dry) and montane areas, and low values in arid, subtropical regions. Comparisons with synoptic approaches demonstrated the additional information available within the dynamic TSI dataset that is lost in equivalent synoptic products derived from long-term monthly averages. Conclusions The dynamic TSI dataset presented here provides a new product with far richer spatial and temporal information than any other presently available for Africa. As spatiotemporal malaria modeling endeavors evolve, dynamic predictor variables such as the malaria

  9. Comparative interactomics: comparing apples and pears?

    PubMed

    Kiemer, Lars; Cesareni, Gianni

    2007-10-01

    The study of the complex web of interactions that link biological molecules in a cell is the subject of interactomics--currently one of the fastest moving fields in molecular biology. The recent completion of high-throughput studies to investigate systematically all the possible interactions in a variety of model organisms has provided unique opportunities to compare interaction networks and ask questions about their conservation during evolution. It is expected that this approach will yield a scientific return as rich as that obtained in the past decade from comparing genomes and proteomes from different organisms.

  10. Spatiotemporal Context Awareness for Urban Traffic Modeling and Prediction: Sparse Representation Based Variable Selection.

    PubMed

    Yang, Su; Shi, Shixiong; Hu, Xiaobing; Wang, Minjie

    2015-01-01

    Spatial-temporal correlations among the data play an important role in traffic flow prediction. Correspondingly, traffic modeling and prediction based on big data analytics emerges due to the city-scale interactions among traffic flows. A new methodology based on sparse representation is proposed to reveal the spatial-temporal dependencies among traffic flows so as to simplify the correlations among traffic data for the prediction task at a given sensor. Three important findings are observed in the experiments: (1) Only traffic flows immediately prior to the present time affect the formation of current traffic flows, which implies the possibility to reduce the traditional high-order predictors into an 1-order model. (2) The spatial context relevant to a given prediction task is more complex than what is assumed to exist locally and can spread out to the whole city. (3) The spatial context varies with the target sensor undergoing prediction and enlarges with the increment of time lag for prediction. Because the scope of human mobility is subject to travel time, identifying the varying spatial context against time lag is crucial for prediction. Since sparse representation can capture the varying spatial context to adapt to the prediction task, it outperforms the traditional methods the inputs of which are confined as the data from a fixed number of nearby sensors. As the spatial-temporal context for any prediction task is fully detected from the traffic data in an automated manner, where no additional information regarding network topology is needed, it has good scalability to be applicable to large-scale networks.

  11. Spatiotemporal Context Awareness for Urban Traffic Modeling and Prediction: Sparse Representation Based Variable Selection.

    PubMed

    Yang, Su; Shi, Shixiong; Hu, Xiaobing; Wang, Minjie

    2015-01-01

    Spatial-temporal correlations among the data play an important role in traffic flow prediction. Correspondingly, traffic modeling and prediction based on big data analytics emerges due to the city-scale interactions among traffic flows. A new methodology based on sparse representation is proposed to reveal the spatial-temporal dependencies among traffic flows so as to simplify the correlations among traffic data for the prediction task at a given sensor. Three important findings are observed in the experiments: (1) Only traffic flows immediately prior to the present time affect the formation of current traffic flows, which implies the possibility to reduce the traditional high-order predictors into an 1-order model. (2) The spatial context relevant to a given prediction task is more complex than what is assumed to exist locally and can spread out to the whole city. (3) The spatial context varies with the target sensor undergoing prediction and enlarges with the increment of time lag for prediction. Because the scope of human mobility is subject to travel time, identifying the varying spatial context against time lag is crucial for prediction. Since sparse representation can capture the varying spatial context to adapt to the prediction task, it outperforms the traditional methods the inputs of which are confined as the data from a fixed number of nearby sensors. As the spatial-temporal context for any prediction task is fully detected from the traffic data in an automated manner, where no additional information regarding network topology is needed, it has good scalability to be applicable to large-scale networks. PMID:26496370

  12. Spatiotemporal Context Awareness for Urban Traffic Modeling and Prediction: Sparse Representation Based Variable Selection

    PubMed Central

    Yang, Su; Shi, Shixiong; Hu, Xiaobing; Wang, Minjie

    2015-01-01

    Spatial-temporal correlations among the data play an important role in traffic flow prediction. Correspondingly, traffic modeling and prediction based on big data analytics emerges due to the city-scale interactions among traffic flows. A new methodology based on sparse representation is proposed to reveal the spatial-temporal dependencies among traffic flows so as to simplify the correlations among traffic data for the prediction task at a given sensor. Three important findings are observed in the experiments: (1) Only traffic flows immediately prior to the present time affect the formation of current traffic flows, which implies the possibility to reduce the traditional high-order predictors into an 1-order model. (2) The spatial context relevant to a given prediction task is more complex than what is assumed to exist locally and can spread out to the whole city. (3) The spatial context varies with the target sensor undergoing prediction and enlarges with the increment of time lag for prediction. Because the scope of human mobility is subject to travel time, identifying the varying spatial context against time lag is crucial for prediction. Since sparse representation can capture the varying spatial context to adapt to the prediction task, it outperforms the traditional methods the inputs of which are confined as the data from a fixed number of nearby sensors. As the spatial-temporal context for any prediction task is fully detected from the traffic data in an automated manner, where no additional information regarding network topology is needed, it has good scalability to be applicable to large-scale networks. PMID:26496370

  13. Prediction of high spatio-temporal resolution land surface temperature under cloudy conditions using microwave vegetation index and ANN

    NASA Astrophysics Data System (ADS)

    Shwetha, H. R.; Kumar, D. Nagesh

    2016-07-01

    Land Surface Temperature (LST) with high spatio-temporal resolution is in demand for hydrology, climate change, ecology, urban climate and environmental studies, etc. Moderate Resolution Imaging Spectroradiometer (MODIS) is one of the most commonly used sensors owing to its high spatial and temporal availability over the globe, but is incapable of providing LST data under cloudy conditions, resulting in gaps in the data. In contrast, microwave measurements have a capability to penetrate under clouds. The current study proposes a methodology by exploring this property to predict high spatio-temporal resolution LST under cloudy conditions during daytime and nighttime without employing in-situ LST measurements. To achieve this, Artificial Neural Networks (ANNs) based models are employed for different land cover classes, utilizing Microwave Polarization Difference Index (MPDI) at finer resolution with ancillary data. MPDI was derived using resampled (from 0.25° to 1 km) brightness temperatures (Tb) at 36.5 GHz channel of dual polarization from Advance Microwave Scanning Radiometer (AMSR)-Earth Observing System and AMSR2 sensors. The proposed methodology is tested over Cauvery basin in India and the performance of the model is quantitatively evaluated through performance measures such as correlation coefficient (r), Nash Sutcliffe Efficiency (NSE) and Root Mean Square Error (RMSE). Results revealed that during daytime, AMSR-E(AMSR2) derived LST under clear sky conditions corresponds well with MODIS LST resulting in values of r ranging from 0.76(0.78) to 0.90(0.96), RMSE from 1.76(1.86) K to 4.34(4.00) K and NSE from 0.58(0.61) to 0.81(0.90) for different land cover classes. During nighttime, r values ranged from 0.76(0.56) to 0.87(0.90), RMSE from 1.71(1.70) K to 2.43(2.12) K and NSE from 0.43(0.28) to 0.80(0.81) for different land cover classes. RMSE values found between predicted LST and MODIS LST during daytime under clear sky conditions were within acceptable

  14. Computational analysis of the LRRK2 interactome.

    PubMed

    Manzoni, Claudia; Denny, Paul; Lovering, Ruth C; Lewis, Patrick A

    2015-01-01

    LRRK2 was identified in 2004 as the causative protein product of the Parkinson's disease locus designated PARK8. In the decade since then, genetic studies have revealed at least 6 dominant mutations in LRRK2 linked to Parkinson's disease, alongside one associated with cancer. It is now well established that coding changes in LRRK2 are one of the most common causes of Parkinson's. Genome-wide association studies (GWAs) have, more recently, reported single nucleotide polymorphisms (SNPs) around the LRRK2 locus to be associated with risk of developing sporadic Parkinson's disease and inflammatory bowel disorder. The functional research that has followed these genetic breakthroughs has generated an extensive literature regarding LRRK2 pathophysiology; however, there is still no consensus as to the biological function of LRRK2. To provide insight into the aspects of cell biology that are consistently related to LRRK2 activity, we analysed the plethora of candidate LRRK2 interactors available through the BioGRID and IntAct data repositories. We then performed GO terms enrichment for the LRRK2 interactome. We found that, in two different enrichment portals, the LRRK2 interactome was associated with terms referring to transport, cellular organization, vesicles and the cytoskeleton. We also verified that 21 of the LRRK2 interactors are genetically linked to risk for Parkinson's disease or inflammatory bowel disorder. The implications of these findings are discussed, with particular regard to potential novel areas of investigation.

  15. An online spatiotemporal prediction model for dengue fever epidemic in Kaohsiung (Taiwan).

    PubMed

    Yu, Hwa-Lung; Angulo, José M; Cheng, Ming-Hung; Wu, Jiaping; Christakos, George

    2014-05-01

    The emergence and re-emergence of disease epidemics is a complex question that may be influenced by diverse factors, including the space-time dynamics of human populations, environmental conditions, and associated uncertainties. This study proposes a stochastic framework to integrate space-time dynamics in the form of a Susceptible-Infected-Recovered (SIR) model, together with uncertain disease observations, into a Bayesian maximum entropy (BME) framework. The resulting model (BME-SIR) can be used to predict space-time disease spread. Specifically, it was applied to obtain a space-time prediction of the dengue fever (DF) epidemic that took place in Kaohsiung City (Taiwan) during 2002. In implementing the model, the SIR parameters were continually updated and information on new cases of infection was incorporated. The results obtained show that the proposed model is rigorous to user-specified initial values of unknown model parameters, that is, transmission and recovery rates. In general, this model provides a good characterization of the spatial diffusion of the DF epidemic, especially in the city districts proximal to the location of the outbreak. Prediction performance may be affected by various factors, such as virus serotypes and human intervention, which can change the space-time dynamics of disease diffusion. The proposed BME-SIR disease prediction model can provide government agencies with a valuable reference for the timely identification, control, and prevention of DF spread in space and time.

  16. Interactome analysis of myeloid-derived suppressor cells in murine models of colon and breast cancer.

    PubMed

    Aliper, Alexander M; Frieden-Korovkina, Victoria P; Buzdin, Anton; Roumiantsev, Sergey A; Zhavoronkov, Alex

    2014-11-30

    In solid cancers, myeloid derived suppressor cells (MDSC) infiltrate (peri)tumoral tissues to induce immune tolerance and hence to establish a microenvironment permissive to tumor growth. Importantly, the mechanisms that facilitate such infiltration or a subsequent immune suppression are not fully understood. Hence, in this study, we aimed to delineate disparate molecular pathways which MDSC utilize in murine models of colon or breast cancer. Using pathways enrichment analysis, we completed interactome maps of multiple signaling pathways in CD11b+/Gr1(high/low) MDSC from spleens and tumor infiltrates of mice with c26GM colon cancer and tumor infiltrates of MDSC in 4T1 breast cancer. In both cancer models, infiltrating MDSC, but not CD11b+ splenic cells, have been found to be enriched in multiple signaling molecules suggestive of their enhanced proliferative and invasive phenotypes. The interactome data has been subsequently used to reconstruct a previously unexplored regulation of MDSC cell cycle by the c-myc transcription factor which was predicted by the analysis. Thus, this study represents a first interactome mapping of distinct multiple molecular pathways whereby MDSC sustain cancer progression. PMID:25294811

  17. Mining protein interactomes to improve their reliability and support the advancement of network medicine.

    PubMed

    Alanis-Lobato, Gregorio

    2015-01-01

    High-throughput detection of protein interactions has had a major impact in our understanding of the intricate molecular machinery underlying the living cell, and has permitted the construction of very large protein interactomes. The protein networks that are currently available are incomplete and a significant percentage of their interactions are false positives. Fortunately, the structural properties observed in good quality social or technological networks are also present in biological systems. This has encouraged the development of tools, to improve the reliability of protein networks and predict new interactions based merely on the topological characteristics of their components. Since diseases are rarely caused by the malfunction of a single protein, having a more complete and reliable interactome is crucial in order to identify groups of inter-related proteins involved in disease etiology. These system components can then be targeted with minimal collateral damage. In this article, an important number of network mining tools is reviewed, together with resources from which reliable protein interactomes can be constructed. In addition to the review, a few representative examples of how molecular and clinical data can be integrated to deepen our understanding of pathogenesis are discussed.

  18. Spatiotemporal Bayesian Networks for Malaria Prediction: Case Study of Northern Thailand.

    PubMed

    Haddawy, Peter; Kasantikul, Rangwan; Hasan, A H M Imrul; Rattanabumrung, Chunyanuch; Rungrun, Pichamon; Suksopee, Natwipa; Tantiwaranpant, Saran; Niruntasuk, Natcha

    2016-01-01

    While a diversity of modeling technique have been used to create predictive models of malaria, no work has made use of Bayesian networks. Bayes nets are attractive due to their ability to represent uncertainty, model time lagged and nonlinear relations, and provide explanations of inferences. This paper explores the use of Bayesian networks to model malaria, demonstrating the approach by creating a village level model with weekly temporal resolution for Tha Song Yang district in northern Thailand. The network is learned using data on cases and environmental covariates. The network models incidence over time as well as evolution of the environmental variables, and captures time lagged and nonlinear effects. Out of sample evaluation shows the model to have high accuracy for one and two week predictions. PMID:27577491

  19. The simulation and prediction of spatio-temporal urban growth trends using cellular automata models: A review

    NASA Astrophysics Data System (ADS)

    Aburas, Maher Milad; Ho, Yuek Ming; Ramli, Mohammad Firuz; Ash'aari, Zulfa Hanan

    2016-10-01

    In recent years, several types of simulation and prediction models have been used within a GIS environment to determine a realistic future for urban growth patterns. These models include quantitative and spatio-temporal techniques that are implemented to monitor urban growth. The results derived through these techniques are used to create future policies that take into account sustainable development and the demands of future generations. The aim of this paper is to provide a basis for a literature review of urban Cellular Automata (CA) models to find the most suitable approach for a realistic simulation of land use changes. The general characteristics of simulation models of urban growth and urban CA models are described, and the different techniques used in the design of these models are classified. The strengths and weaknesses of the various models are identified based on the analysis and discussion of the characteristics of these models. The results of the review confirm that the CA model is one of the strongest models for simulating urban growth patterns owing to its structure, simplicity, and possibility of evolution. Limitations of the CA model, namely weaknesses in the quantitative aspect, and the inability to include the driving forces of urban growth in the simulation process, may be minimized by integrating it with other quantitative models, such as via the Analytic Hierarchy Process (AHP), Markov Chain and frequency ratio models. Realistic simulation can be achieved when socioeconomic factors and spatial and temporal dimensions are integrated in the simulation process.

  20. Spatiotemporal variability and predictability of Normalized Difference Vegetation Index (NDVI) in Alberta, Canada.

    PubMed

    Jiang, Rengui; Xie, Jiancang; He, Hailong; Kuo, Chun-Chao; Zhu, Jiwei; Yang, Mingxiang

    2016-09-01

    As one of the most popular vegetation indices to monitor terrestrial vegetation productivity, Normalized Difference Vegetation Index (NDVI) has been widely used to study the plant growth and vegetation productivity around the world, especially the dynamic response of vegetation to climate change in terms of precipitation and temperature. Alberta is the most important agricultural and forestry province and with the best climatic observation systems in Canada. However, few studies pertaining to climate change and vegetation productivity are found. The objectives of this paper therefore were to better understand impacts of climate change on vegetation productivity in Alberta using the NDVI and provide reference for policy makers and stakeholders. We investigated the following: (1) the variations of Alberta's smoothed NDVI (sNDVI, eliminated noise compared to NDVI) and two climatic variables (precipitation and temperature) using non-parametric Mann-Kendall monotonic test and Thiel-Sen's slope; (2) the relationships between sNDVI and climatic variables, and the potential predictability of sNDVI using climatic variables as predictors based on two predicted models; and (3) the use of a linear regression model and an artificial neural network calibrated by the genetic algorithm (ANN-GA) to estimate Alberta's sNDVI using precipitation and temperature as predictors. The results showed that (1) the monthly sNDVI has increased during the past 30 years and a lengthened growing season was detected; (2) vegetation productivity in northern Alberta was mainly temperature driven and the vegetation in southern Alberta was predominantly precipitation driven for the period of 1982-2011; and (3) better performances of the sNDVI-climate relationships were obtained by nonlinear model (ANN-GA) than using linear (regression) model. Similar results detected in both monthly and summer sNDVI prediction using climatic variables as predictors revealed the applicability of two models for

  1. Spatiotemporal variability and predictability of Normalized Difference Vegetation Index (NDVI) in Alberta, Canada

    NASA Astrophysics Data System (ADS)

    Jiang, Rengui; Xie, Jiancang; He, Hailong; Kuo, Chun-Chao; Zhu, Jiwei; Yang, Mingxiang

    2016-09-01

    As one of the most popular vegetation indices to monitor terrestrial vegetation productivity, Normalized Difference Vegetation Index (NDVI) has been widely used to study the plant growth and vegetation productivity around the world, especially the dynamic response of vegetation to climate change in terms of precipitation and temperature. Alberta is the most important agricultural and forestry province and with the best climatic observation systems in Canada. However, few studies pertaining to climate change and vegetation productivity are found. The objectives of this paper therefore were to better understand impacts of climate change on vegetation productivity in Alberta using the NDVI and provide reference for policy makers and stakeholders. We investigated the following: (1) the variations of Alberta's smoothed NDVI (sNDVI, eliminated noise compared to NDVI) and two climatic variables (precipitation and temperature) using non-parametric Mann-Kendall monotonic test and Thiel-Sen's slope; (2) the relationships between sNDVI and climatic variables, and the potential predictability of sNDVI using climatic variables as predictors based on two predicted models; and (3) the use of a linear regression model and an artificial neural network calibrated by the genetic algorithm (ANN-GA) to estimate Alberta's sNDVI using precipitation and temperature as predictors. The results showed that (1) the monthly sNDVI has increased during the past 30 years and a lengthened growing season was detected; (2) vegetation productivity in northern Alberta was mainly temperature driven and the vegetation in southern Alberta was predominantly precipitation driven for the period of 1982-2011; and (3) better performances of the sNDVI-climate relationships were obtained by nonlinear model (ANN-GA) than using linear (regression) model. Similar results detected in both monthly and summer sNDVI prediction using climatic variables as predictors revealed the applicability of two models for

  2. Spatiotemporal variability and predictability of Normalized Difference Vegetation Index (NDVI) in Alberta, Canada.

    PubMed

    Jiang, Rengui; Xie, Jiancang; He, Hailong; Kuo, Chun-Chao; Zhu, Jiwei; Yang, Mingxiang

    2016-09-01

    As one of the most popular vegetation indices to monitor terrestrial vegetation productivity, Normalized Difference Vegetation Index (NDVI) has been widely used to study the plant growth and vegetation productivity around the world, especially the dynamic response of vegetation to climate change in terms of precipitation and temperature. Alberta is the most important agricultural and forestry province and with the best climatic observation systems in Canada. However, few studies pertaining to climate change and vegetation productivity are found. The objectives of this paper therefore were to better understand impacts of climate change on vegetation productivity in Alberta using the NDVI and provide reference for policy makers and stakeholders. We investigated the following: (1) the variations of Alberta's smoothed NDVI (sNDVI, eliminated noise compared to NDVI) and two climatic variables (precipitation and temperature) using non-parametric Mann-Kendall monotonic test and Thiel-Sen's slope; (2) the relationships between sNDVI and climatic variables, and the potential predictability of sNDVI using climatic variables as predictors based on two predicted models; and (3) the use of a linear regression model and an artificial neural network calibrated by the genetic algorithm (ANN-GA) to estimate Alberta's sNDVI using precipitation and temperature as predictors. The results showed that (1) the monthly sNDVI has increased during the past 30 years and a lengthened growing season was detected; (2) vegetation productivity in northern Alberta was mainly temperature driven and the vegetation in southern Alberta was predominantly precipitation driven for the period of 1982-2011; and (3) better performances of the sNDVI-climate relationships were obtained by nonlinear model (ANN-GA) than using linear (regression) model. Similar results detected in both monthly and summer sNDVI prediction using climatic variables as predictors revealed the applicability of two models for

  3. Towards a Predictive Theory of Malaria: Connections to Spatio-temporal Variability of Climate and Hydrology

    NASA Astrophysics Data System (ADS)

    Endo, N.; Eltahir, E. A. B.

    2015-12-01

    Malaria transmission is closely linked to climatology, hydrology, environment, and the biology of local vectors. These factors interact with each other and non-linearly influence malaria transmission dynamics, making prediction and prevention challenging. Our work attempts to find a universality in the multi-dimensional system of malaria transmission and to develop a theory to predict emergence of malaria given a limited set of environmental and biological inputs.A credible malaria transmission dynamics model, HYDREMATS (Bomblies et al., 2008), was used under hypothetical settings to investigate the role of spatial and temporal distribution of vector breeding pools. HYDREMATS is a mechanistic model and capable of simulating the basic reproduction rate (Ro) without bold assumptions even under dynamic conditions. The spatial distribution of pools is mainly governed by hydrological factors; the impact of pool persistence and rainy season length on malaria transmission were investigated. Also analyzed was the impact of the temporal distribution of pools relative to human houses. We developed non-dimensional variables combining the hydrological and biological parameters. Simulated values of Ro from HYDREMATS are presented in a newly-introduced non-dimensional plane, which leads to a some-what universal theory describing the condition for sustainable malaria transmission. The findings were tested against observations both from the West Africa and the Ethiopian Highland, representing diverse hydroclimatological conditions. Predicated Ro values from the theory over the two regions are in good agreement with the observed malaria transmission data.

  4. 5D Modelling: An Efficient Approach for Creating Spatiotemporal Predictive 3D Maps of Large-Scale Cultural Resources

    NASA Astrophysics Data System (ADS)

    Doulamis, A.; Doulamis, N.; Ioannidis, C.; Chrysouli, C.; Grammalidis, N.; Dimitropoulos, K.; Potsiou, C.; Stathopoulou, E.-K.; Ioannides, M.

    2015-08-01

    Outdoor large-scale cultural sites are mostly sensitive to environmental, natural and human made factors, implying an imminent need for a spatio-temporal assessment to identify regions of potential cultural interest (material degradation, structuring, conservation). On the other hand, in Cultural Heritage research quite different actors are involved (archaeologists, curators, conservators, simple users) each of diverse needs. All these statements advocate that a 5D modelling (3D geometry plus time plus levels of details) is ideally required for preservation and assessment of outdoor large scale cultural sites, which is currently implemented as a simple aggregation of 3D digital models at different time and levels of details. The main bottleneck of such an approach is its complexity, making 5D modelling impossible to be validated in real life conditions. In this paper, a cost effective and affordable framework for 5D modelling is proposed based on a spatial-temporal dependent aggregation of 3D digital models, by incorporating a predictive assessment procedure to indicate which regions (surfaces) of an object should be reconstructed at higher levels of details at next time instances and which at lower ones. In this way, dynamic change history maps are created, indicating spatial probabilities of regions needed further 3D modelling at forthcoming instances. Using these maps, predictive assessment can be made, that is, to localize surfaces within the objects where a high accuracy reconstruction process needs to be activated at the forthcoming time instances. The proposed 5D Digital Cultural Heritage Model (5D-DCHM) is implemented using open interoperable standards based on the CityGML framework, which also allows the description of additional semantic metadata information. Visualization aspects are also supported to allow easy manipulation, interaction and representation of the 5D-DCHM geometry and the respective semantic information. The open source 3DCity

  5. A Bayesian Hierarchical Model for Spatio-Temporal Prediction and Uncertainty Assessment Using Repeat LiDAR Acquisitions for the Kenai Peninsula, AK, USA

    NASA Astrophysics Data System (ADS)

    Babcock, C. R.; Andersen, H. E.; Finley, A. O.; Cook, B.; Morton, D. C.

    2015-12-01

    Models using repeat LiDAR and field campaigns may be one mechanism to monitor carbon storage and flux in forested regions. Considering the ability of multi-temporal LiDAR to estimate growth, it is not surprising that there is great interest in developing forest carbon monitoring strategies that rely on repeated LiDAR acquisitions. Allowing for sparser field campaigns, LiDAR stands to make monitoring forest carbon cheaper and more efficient than field-only sampling procedures. Here, we look to the spatio-temporally data-rich Kenai Peninsula in Alaska to examine the potential for Bayesian spatio-temporal mapping of forest carbon storage and uncertainty. The framework explored here can predict forest carbon through space and time, while formally propagating uncertainty through to prediction. Bayesian spatio-temporal models are flexible frameworks allowing for forest growth processes to be formally integrated into the model. By incorporating a mechanism for growth---using temporally repeated field and LiDAR data---we can more fully exploit the information-rich inventory network to improve prediction accuracy. LiDAR data for the Kenai Peninsula has been collected on four different occasions---spatially coincident LiDAR strip samples in 2004, 09 and 14, along with a wall-to-wall collection in 2008. There were 436 plots measured twice between 2002 and 2014. LiDAR was acquired at least once over most inventory plots with many having LiDAR collected during 2, 3 or 4 different campaigns. Results from this research will impact how forests are inventoried. It is too expensive to monitor terrestrial carbon using field-only sampling strategies and currently proposed LiDAR model-based techniques lack the ability to properly utilize temporally repeated and misaligned data. Bayesian hierarchical spatio-temporal models offer a solution to these shortcomings and allow for formal predictive error assessment, which is useful for policy development and decision making.

  6. Predicting breeding habitat for amphibians: A spatiotemporal analysis across Yellowstone National Park

    USGS Publications Warehouse

    Bartelt, P.E.; Gallant, A.L.; Klaver, R.W.; Wright, C.K.; Patla, D.A.; Peterson, C.R.

    2011-01-01

    The ability to predict amphibian breeding across landscapes is important for informing land management decisions and helping biologists better understand and remediate factors contributing to declines in amphibian populations. We built geospatial models of likely breeding habitats for each of four amphibian species that breed in Yellowstone National Park (YNP). We used field data collected in 2000-2002 from 497 sites among 16 basins and predictor variables from geospatial models produced from remotely sensed data (e.g., digital elevation model, complex topographic index, landform data, wetland probability, and vegetative cover). Except for 31 sites in one basin that were surveyed in both 2000 and 2002, all sites were surveyed once. We used polytomous regression to build statistical models for each species of amphibian from (1) field survey site data only, (2) field data combined with data from geospatial models, and (3) data from geospatial models only. Based on measures of receiver operating characteristic (ROC) scores, models of the second type best explained likely breeding habitat because they contained the most information (ROC values ranged from 0.70 to 0.88). However, models of the third type could be applied to the entire YNP landscape and produced maps that could be verified with reserve field data. Accuracy rates for models built for single years were highly variable, ranging from 0.30 to 0.78. Accuracy rates for models built with data combined from multiple years were higher and less variable, ranging from 0.60 to 0.80. Combining results from the geospatial multiyear models yielded maps of "core" breeding areas (areas with high probability values for all three years) surrounded by areas that scored high for only one or two years, providing an estimate of variability among years. Such information can highlight landscape options for amphibian conservation. For example, our models identify alternative areas that could be protected for each species

  7. Predicting breeding habitat for amphibians: a spatiotemporal analysis across Yellowstone National Park

    USGS Publications Warehouse

    Bartelt, Paul E.; Gallant, Alisa L.; Klaver, Robert W.; Wright, Christopher K.; Patla, Debra A.; Peterson, Charles R.

    2011-01-01

    The ability to predict amphibian breeding across landscapes is important for informing land management decisions and helping biologists better understand and remediate factors contributing to declines in amphibian populations. We built geospatial models of likely breeding habitats for each of four amphibian species that breed in Yellowstone National Park (YNP). We used field data collected in 2000-2002 from 497 sites among 16 basins and predictor variables from geospatial models produced from remotely sensed data (e.g., digital elevation model, complex topographic index, landform data, wetland probabililty, and vegetative cover). Except for 31 sites in one basin that were surveyed in both 2000 and 2002, all sites were surveyed once. We used polytomous regression to build statistical models for each species of amphibian from 1) field survey site data only, 2) field data combined with data from geospatial models, and 3) data from geospatial models only. Based on measures of receiver operating characteristic (ROC) scores, models of the second type best explained likely breeding habitat because they contained the most information (ROC values ranged from 0.70 - 0.88). However, models of the third type could be applied to the entire YNP landscape and produced maps that could be verified with reserve field data. Accuracy rates for models built for single years were highly variable, ranging from 0.30 to 0.78. Accuracy rates for models built with data combined from multiple years were higher and less variable, ranging from 0.60 to 0.80. Combining results from the geospatial multiyear models yielded maps of "core" breeding areas (areas with high probability values for all three years) surrounded by areas that scored high for only one or two years, providing an estimate of variability among years. Such information can highlight landscape options for amphibian conservation. For example, our models identify alternative for areas that could be protected for each species

  8. Predicting breeding habitat for amphibians: a spatiotemporal analysis across Yellowstone National Park.

    PubMed

    Bartelt, Paul E; Gallant, Alisa L; Klaver, Robert W; Wright, Chris K; Patla, Debra A; Peterson, Charles R

    2011-10-01

    The ability to predict amphibian breeding across landscapes is important for informing land management decisions and helping biologists better understand and remediate factors contributing to declines in amphibian populations. We built geospatial models of likely breeding habitats for each of four amphibian species that breed in Yellowstone National Park (YNP). We used field data collected in 2000-2002 from 497 sites among 16 basins and predictor variables from geospatial models produced from remotely sensed data (e.g., digital elevation model, complex topographic index, landform data, wetland probability, and vegetative cover). Except for 31 sites in one basin that were surveyed in both 2000 and 2002, all sites were surveyed once. We used polytomous regression to build statistical models for each species of amphibian from (1) field survey site data only, (2) field data combined with data from geospatial models, and (3) data from geospatial models only. Based on measures of receiver operating characteristic (ROC) scores, models of the second type best explained likely breeding habitat because they contained the most information (ROC values ranged from 0.70 to 0.88). However, models of the third type could be applied to the entire YNP landscape and produced maps that could be verified with reserve field data. Accuracy rates for models built for single years were highly variable, ranging from 0.30 to 0.78. Accuracy rates for models built with data combined from multiple years were higher and less variable, ranging from 0.60 to 0.80. Combining results from the geospatial multiyear models yielded maps of "core" breeding areas (areas with high probability values for all three years) surrounded by areas that scored high for only one or two years, providing an estimate of variability among years. Such information can highlight landscape options for amphibian conservation. For example, our models identify alternative areas that could be protected for each species

  9. Toward high-resolution flash flood prediction in large urban areas - Analysis of sensitivity to spatiotemporal resolution of rainfall input and hydrologic modeling

    NASA Astrophysics Data System (ADS)

    Rafieeinasab, Arezoo; Norouzi, Amir; Kim, Sunghee; Habibi, Hamideh; Nazari, Behzad; Seo, Dong-Jun; Lee, Haksu; Cosgrove, Brian; Cui, Zhengtao

    2015-12-01

    Urban flash flooding is a serious problem in large, highly populated areas such as the Dallas-Fort Worth Metroplex (DFW). Being able to monitor and predict flash flooding at a high spatiotemporal resolution is critical to providing location-specific early warnings and cost-effective emergency management in such areas. Under the idealized conditions of perfect models and precipitation input, one may expect that spatiotemporal specificity and accuracy of the model output improve as the resolution of the models and precipitation input increases. In reality, however, due to the errors in the precipitation input, and in the structures, parameters and states of the models, there are practical limits to the model resolution. In this work, we assess the sensitivity of streamflow simulation in urban catchments to the spatiotemporal resolution of precipitation input and hydrologic modeling to identify the resolution at which the simulation errors may be at minimum given the quality of the precipitation input and hydrologic models used, and the response time of the catchment. The hydrologic modeling system used in this work is the National Weather Service (NWS) Hydrology Laboratory's Research Distributed Hydrologic Model (HLRDHM) applied at spatiotemporal resolutions ranging from 250 m to 2 km and from 1 min to 1 h applied over the Cities of Fort Worth, Arlington and Grand Prairie in DFW. The high-resolution precipitation input is from the DFW Demonstration Network of the Collaborative Adaptive Sensing of the Atmosphere (CASA) radars. For comparison, the NWS Multisensor Precipitation Estimator (MPE) product, which is available at a 4-km 1-h resolution, was also used. The streamflow simulation results are evaluated for 5 urban catchments ranging in size from 3.4 to 54.6 km2 and from about 45 min to 3 h in time-to-peak in the Cities of Fort Worth, Arlington and Grand Prairie. The streamflow observations used in evaluation were obtained from water level measurements via rating

  10. A process-level evaluation of the spatiotemporal variability of CO2 fluxes predicted by terrestrial biosphere models using atmospheric data

    NASA Astrophysics Data System (ADS)

    Fang, Y.; Michalak, A. M.; Shiga, Y. P.; Yadav, V.

    2013-12-01

    Terrestrial biosphere models (TBMs) are used to extrapolate local observations and process-level understanding of land-atmosphere carbon exchange to larger regions, and can serve as a predictive tool for examining carbon-climate interactions and global change. Understanding and improving the performance of TBMs is thus crucial to the carbon cycle research community. In this work, we evaluate the spatiotemporal patterns of net ecosystem exchange (NEE) simulated by TBMs using atmospheric CO2 observations and a Geostatistical Inverse Modeling (GIM) framework. The evaluation methodology is based on the ability (or inability) of the spatiotemporal patterns in NEE estimates to explain the variability observed in atmospheric CO2 distribution. More simply, we examine whether the spatiotemporal patterns of NEE simulated by TBMs (including CASA-GFED, ORCHIDEE, VEGAS2 and SiB3) are consistent with the variations observed in the atmosphere. A similar GIM methodology is also applied using environmental variables (such as water availability, temperature, radiation, etc.) rather than TBMs, to explore the environmental processes associated with the variability of NEE, and determine which processes are associated with good/poor performance in TBMs. We find that NEE simulated by TBMs is consistent with that seen by atmospheric measurements more often during growing season months (Apr-Sept) than during the non-growing season. Over Temperate Broadleaf and Mixed Forests, Temperate Coniferous Forests and Temperate Grasslands, Savannas and Shrublands, atmospheric measurements are sufficiently sensitive to NEE fluxes to constrain the evaluation of model performance during the majority of the year (about 7-8 months in a year, mostly in growing season). For these regions and months, at least one of the TBMs is found to be able to reproduce the observed variability, but the most representative TBM varies by region and month. For the remaining months, none of the TBMs are able to reproduce

  11. A proteome-scale map of the human interactome network

    PubMed Central

    Rolland, Thomas; Taşan, Murat; Charloteaux, Benoit; Pevzner, Samuel J.; Zhong, Quan; Sahni, Nidhi; Yi, Song; Lemmens, Irma; Fontanillo, Celia; Mosca, Roberto; Kamburov, Atanas; Ghiassian, Susan D.; Yang, Xinping; Ghamsari, Lila; Balcha, Dawit; Begg, Bridget E.; Braun, Pascal; Brehme, Marc; Broly, Martin P.; Carvunis, Anne-Ruxandra; Convery-Zupan, Dan; Corominas, Roser; Coulombe-Huntington, Jasmin; Dann, Elizabeth; Dreze, Matija; Dricot, Amélie; Fan, Changyu; Franzosa, Eric; Gebreab, Fana; Gutierrez, Bryan J.; Hardy, Madeleine F.; Jin, Mike; Kang, Shuli; Kiros, Ruth; Lin, Guan Ning; Luck, Katja; MacWilliams, Andrew; Menche, Jörg; Murray, Ryan R.; Palagi, Alexandre; Poulin, Matthew M.; Rambout, Xavier; Rasla, John; Reichert, Patrick; Romero, Viviana; Ruyssinck, Elien; Sahalie, Julie M.; Scholz, Annemarie; Shah, Akash A.; Sharma, Amitabh; Shen, Yun; Spirohn, Kerstin; Tam, Stanley; Tejeda, Alexander O.; Trigg, Shelly A.; Twizere, Jean-Claude; Vega, Kerwin; Walsh, Jennifer; Cusick, Michael E.; Xia, Yu; Barabási, Albert-László; Iakoucheva, Lilia M.; Aloy, Patrick; De Las Rivas, Javier; Tavernier, Jan; Calderwood, Michael A.; Hill, David E.; Hao, Tong; Roth, Frederick P.; Vidal, Marc

    2014-01-01

    SUMMARY Just as reference genome sequences revolutionized human genetics, reference maps of interactome networks will be critical to fully understand genotype-phenotype relationships. Here, we describe a systematic map of ~14,000 high-quality human binary protein-protein interactions. At equal quality, this map is ~30% larger than what is available from small-scale studies published in the literature in the last few decades. While currently available information is highly biased and only covers a relatively small portion of the proteome, our systematic map appears strikingly more homogeneous, revealing a “broader” human interactome network than currently appreciated. The map also uncovers significant inter-connectivity between known and candidate cancer gene products, providing unbiased evidence for an expanded functional cancer landscape, while demonstrating how high quality interactome models will help “connect the dots” of the genomic revolution. PMID:25416956

  12. A proteome-scale map of the human interactome network.

    PubMed

    Rolland, Thomas; Taşan, Murat; Charloteaux, Benoit; Pevzner, Samuel J; Zhong, Quan; Sahni, Nidhi; Yi, Song; Lemmens, Irma; Fontanillo, Celia; Mosca, Roberto; Kamburov, Atanas; Ghiassian, Susan D; Yang, Xinping; Ghamsari, Lila; Balcha, Dawit; Begg, Bridget E; Braun, Pascal; Brehme, Marc; Broly, Martin P; Carvunis, Anne-Ruxandra; Convery-Zupan, Dan; Corominas, Roser; Coulombe-Huntington, Jasmin; Dann, Elizabeth; Dreze, Matija; Dricot, Amélie; Fan, Changyu; Franzosa, Eric; Gebreab, Fana; Gutierrez, Bryan J; Hardy, Madeleine F; Jin, Mike; Kang, Shuli; Kiros, Ruth; Lin, Guan Ning; Luck, Katja; MacWilliams, Andrew; Menche, Jörg; Murray, Ryan R; Palagi, Alexandre; Poulin, Matthew M; Rambout, Xavier; Rasla, John; Reichert, Patrick; Romero, Viviana; Ruyssinck, Elien; Sahalie, Julie M; Scholz, Annemarie; Shah, Akash A; Sharma, Amitabh; Shen, Yun; Spirohn, Kerstin; Tam, Stanley; Tejeda, Alexander O; Trigg, Shelly A; Twizere, Jean-Claude; Vega, Kerwin; Walsh, Jennifer; Cusick, Michael E; Xia, Yu; Barabási, Albert-László; Iakoucheva, Lilia M; Aloy, Patrick; De Las Rivas, Javier; Tavernier, Jan; Calderwood, Michael A; Hill, David E; Hao, Tong; Roth, Frederick P; Vidal, Marc

    2014-11-20

    Just as reference genome sequences revolutionized human genetics, reference maps of interactome networks will be critical to fully understand genotype-phenotype relationships. Here, we describe a systematic map of ?14,000 high-quality human binary protein-protein interactions. At equal quality, this map is ?30% larger than what is available from small-scale studies published in the literature in the last few decades. While currently available information is highly biased and only covers a relatively small portion of the proteome, our systematic map appears strikingly more homogeneous, revealing a "broader" human interactome network than currently appreciated. The map also uncovers significant interconnectivity between known and candidate cancer gene products, providing unbiased evidence for an expanded functional cancer landscape, while demonstrating how high-quality interactome models will help "connect the dots" of the genomic revolution.

  13. Enhanced Prediction of Src Homology 2 (SH2) Domain Binding Potentials Using a Fluorescence Polarization-derived c-Met, c-Kit, ErbB, and Androgen Receptor Interactome*

    PubMed Central

    Leung, Kin K.; Hause, Ronald J.; Barkinge, John L.; Ciaccio, Mark F.; Chuu, Chih-Pin; Jones, Richard B.

    2014-01-01

    Many human diseases are associated with aberrant regulation of phosphoprotein signaling networks. Src homology 2 (SH2) domains represent the major class of protein domains in metazoans that interact with proteins phosphorylated on the amino acid residue tyrosine. Although current SH2 domain prediction algorithms perform well at predicting the sequences of phosphorylated peptides that are likely to result in the highest possible interaction affinity in the context of random peptide library screens, these algorithms do poorly at predicting the interaction potential of SH2 domains with physiologically derived protein sequences. We employed a high throughput interaction assay system to empirically determine the affinity between 93 human SH2 domains and phosphopeptides abstracted from several receptor tyrosine kinases and signaling proteins. The resulting interaction experiments revealed over 1000 novel peptide-protein interactions and provided a glimpse into the common and specific interaction potentials of c-Met, c-Kit, GAB1, and the human androgen receptor. We used these data to build a permutation-based logistic regression classifier that performed considerably better than existing algorithms for predicting the interaction potential of several SH2 domains. PMID:24728074

  14. Intrinsic Disorder in the BK Channel and Its Interactome

    PubMed Central

    Peng, Zhenling; Sakai, Yoshihisa; Kurgan, Lukasz; Sokolowski, Bernd; Uversky, Vladimir

    2014-01-01

    The large-conductance Ca2+-activated K+ (BK) channel is broadly expressed in various mammalian cells and tissues such as neurons, skeletal and smooth muscles, exocrine cells, and sensory cells of the inner ear. Previous studies suggest that BK channels are promiscuous binders involved in a multitude of protein-protein interactions. To gain a better understanding of the potential mechanisms underlying BK interactions, we analyzed the abundance, distribution, and potential mechanisms of intrinsic disorder in 27 BK channel variants from mouse cochlea, 104 previously reported BK-associated proteins (BKAPS) from cytoplasmic and membrane/cytoskeletal regions, plus BK β- and γ-subunits. Disorder was evaluated using the MFDp algorithm, which is a consensus-based predictor that provides a strong and competitive predictive quality and PONDR, which can determine long intrinsically disordered regions (IDRs). Disorder-based binding sites or molecular recognition features (MoRFs) were found using MoRFpred and ANCHOR. BKAP functions were categorized based on Gene Ontology (GO) terms. The analyses revealed that the BK variants contain a number of IDRs. Intrinsic disorder is also common in BKAPs, of which ∼5% are completely disordered. However, intrinsic disorder is very differently distributed within BK and its partners. Approximately 65% of the disordered segments in BK channels are long (IDRs) (>50 residues), whereas >60% of the disordered segments in BKAPs are short IDRs that range in length from 4 to 30 residues. Both α and γ subunits showed various amounts of disorder as did hub proteins of the BK interactome. Our analyses suggest that intrinsic disorder is important for the function of BK and its BKAPs. Long IDRs in BK are engaged in protein-protein and protein-ligand interactions, contain multiple post-translational modification sites, and are subjected to alternative splicing. The disordered structure of BK and its BKAPs suggests one of the underlying mechanisms of

  15. Geomapping generalized eigenvalue frequency distributions for predicting prolific Aedes albopictus and Culex quinquefasciatus habitats based on spatiotemporal field-sampled count data.

    PubMed

    Jacob, Benjamin G; Morris, Joel A; Caamano, Erick X; Griffith, Daniel A; Novak, Robert J

    2011-02-01

    Marked spatiotemporal variabilities in mosquito infection of arboviruses require adaptive strategies for determining optimal field-sampling timeframes, pool screening, and data analyses. In particular, the error distribution and aggregation patterns of adult arboviral mosquitoes can vary significantly by species, which can statistically bias analyses of spatiotemporal-sampled predictor variables generating misinterpretation of prolific habitat surveillance locations. Currently, there is a lack of reliable and consistent measures of risk exposure based on field-sampled georeferenced explanatory covariates which can compromise quantitative predictions generated from arboviral mosquito surveillance models for implementing larval control strategies targeting productive habitats. In this research we used spatial statistics and QuickBird visible and near-infra-red data for determining trapping sites that were related to Culex quinquefasciatus and Aedes albopictus species abundance and distribution in Birmingham, Alabama. Initially, a Land Use Land Cover (LULC) model was constructed from multiple spatiotemporal-sampled georeferenced predictors and the QuickBird data. A Poisson regression model with a non-homogenous, gamma-distributed mean then decomposed the data into positive and negative spatial filter eigenvectors. An autoregressive process in the error term then was used to derive the sample distribution of the Moran's I statistic for determining latent autocorrelation components in the model. Spatial filter algorithms established means, variances, distributional functions, and pairwise correlations for the predictor variables. In doing so, the eigenfunction spatial filter quantified the residual autocorrelation error in the mean response term of the model as a linear combination of various distinct Cx. quinquefasciatus and Ae. albopictus habitat map patterns. The analyses revealed 18-27% redundant information in the data. Prolific habitats of Cx. quinquefasciatus and

  16. Dynamic Zebrafish Interactome Reveals Transcriptional Mechanisms of Dioxin Toxicity

    PubMed Central

    Alexeyenko, Andrey; Wassenberg, Deena M.; Lobenhofer, Edward K.; Yen, Jerry; Linney, Elwood; Sonnhammer, Erik L. L.; Meyer, Joel N.

    2010-01-01

    Background In order to generate hypotheses regarding the mechanisms by which 2,3,7,8-tetrachlorodibenzo-p-dioxin (dioxin) causes toxicity, we analyzed global gene expression changes in developing zebrafish embryos exposed to this potent toxicant in the context of a dynamic gene network. For this purpose, we also computationally inferred a zebrafish (Danio rerio) interactome based on orthologs and interaction data from other eukaryotes. Methodology/Principal Findings Using novel computational tools to analyze this interactome, we distinguished between dioxin-dependent and dioxin-independent interactions between proteins, and tracked the temporal propagation of dioxin-dependent transcriptional changes from a few genes that were altered initially, to large groups of biologically coherent genes at later times. The most notable processes altered at later developmental stages were calcium and iron metabolism, embryonic morphogenesis including neuronal and retinal development, a variety of mitochondria-related functions, and generalized stress response (not including induction of antioxidant genes). Within the interactome, many of these responses were connected to cytochrome P4501A (cyp1a) as well as other genes that were dioxin-regulated one day after exposure. This suggests that cyp1a may play a key role initiating the toxic dysregulation of those processes, rather than serving simply as a passive marker of dioxin exposure, as suggested by earlier research. Conclusions/Significance Thus, a powerful microarray experiment coupled with a flexible interactome and multi-pronged interactome tools (which are now made publicly available for microarray analysis and related work) suggest the hypothesis that dioxin, best known in fish as a potent cardioteratogen, has many other targets. Many of these types of toxicity have been observed in mammalian species and are potentially caused by alterations to cyp1a. PMID:20463971

  17. Crowd Sourcing a New Paradigm for Interactome Driven Drug Target Identification in Mycobacterium tuberculosis

    PubMed Central

    Rohira, Harsha; Bhat, Ashwini G.; Passi, Anurag; Mukherjee, Keya; Choudhary, Kumari Sonal; Kumar, Vikas; Arora, Anshula; Munusamy, Prabhakaran; Subramanian, Ahalyaa; Venkatachalam, Aparna; S, Gayathri; Raj, Sweety; Chitra, Vijaya; Verma, Kaveri; Zaheer, Salman; J, Balaganesh; Gurusamy, Malarvizhi; Razeeth, Mohammed; Raja, Ilamathi; Thandapani, Madhumohan; Mevada, Vishal; Soni, Raviraj; Rana, Shruti; Ramanna, Girish Muthagadhalli; Raghavan, Swetha; Subramanya, Sunil N.; Kholia, Trupti; Patel, Rajesh; Bhavnani, Varsha; Chiranjeevi, Lakavath; Sengupta, Soumi; Singh, Pankaj Kumar; Atray, Naresh; Gandhi, Swati; Avasthi, Tiruvayipati Suma; Nisthar, Shefin; Anurag, Meenakshi; Sharma, Pratibha; Hasija, Yasha; Dash, Debasis; Sharma, Arun; Scaria, Vinod; Thomas, Zakir; Chandra, Nagasuma; Brahmachari, Samir K.; Bhardwaj, Anshu

    2012-01-01

    A decade since the availability of Mycobacterium tuberculosis (Mtb) genome sequence, no promising drug has seen the light of the day. This not only indicates the challenges in discovering new drugs but also suggests a gap in our current understanding of Mtb biology. We attempt to bridge this gap by carrying out extensive re-annotation and constructing a systems level protein interaction map of Mtb with an objective of finding novel drug target candidates. Towards this, we synergized crowd sourcing and social networking methods through an initiative ‘Connect to Decode’ (C2D) to generate the first and largest manually curated interactome of Mtb termed ‘interactome pathway’ (IPW), encompassing a total of 1434 proteins connected through 2575 functional relationships. Interactions leading to gene regulation, signal transduction, metabolism, structural complex formation have been catalogued. In the process, we have functionally annotated 87% of the Mtb genome in context of gene products. We further combine IPW with STRING based network to report central proteins, which may be assessed as potential drug targets for development of drugs with least possible side effects. The fact that five of the 17 predicted drug targets are already experimentally validated either genetically or biochemically lends credence to our unique approach. PMID:22808064

  18. Arabidopsis G-protein interactome reveals connections to cell wall carbohydrates and morphogenesis.

    PubMed

    Klopffleisch, Karsten; Phan, Nguyen; Augustin, Kelsey; Bayne, Robert S; Booker, Katherine S; Botella, Jose R; Carpita, Nicholas C; Carr, Tyrell; Chen, Jin-Gui; Cooke, Thomas Ryan; Frick-Cheng, Arwen; Friedman, Erin J; Fulk, Brandon; Hahn, Michael G; Jiang, Kun; Jorda, Lucia; Kruppe, Lydia; Liu, Chenggang; Lorek, Justine; McCann, Maureen C; Molina, Antonio; Moriyama, Etsuko N; Mukhtar, M Shahid; Mudgil, Yashwanti; Pattathil, Sivakumar; Schwarz, John; Seta, Steven; Tan, Matthew; Temp, Ulrike; Trusov, Yuri; Urano, Daisuke; Welter, Bastian; Yang, Jing; Panstruga, Ralph; Uhrig, Joachim F; Jones, Alan M

    2011-09-27

    The heterotrimeric G-protein complex is minimally composed of Gα, Gβ, and Gγ subunits. In the classic scenario, the G-protein complex is the nexus in signaling from the plasma membrane, where the heterotrimeric G-protein associates with heptahelical G-protein-coupled receptors (GPCRs), to cytoplasmic target proteins called effectors. Although a number of effectors are known in metazoans and fungi, none of these are predicted to exist in their canonical forms in plants. To identify ab initio plant G-protein effectors and scaffold proteins, we screened a set of proteins from the G-protein complex using two-hybrid complementation in yeast. After deep and exhaustive interrogation, we detected 544 interactions between 434 proteins, of which 68 highly interconnected proteins form the core G-protein interactome. Within this core, over half of the interactions comprising two-thirds of the nodes were retested and validated as genuine in planta. Co-expression analysis in combination with phenotyping of loss-of-function mutations in a set of core interactome genes revealed a novel role for G-proteins in regulating cell wall modification.

  19. Arabidopsis G-protein interactome reveals connections to cell wall carbohydrates and morphogenesis

    PubMed Central

    Klopffleisch, Karsten; Phan, Nguyen; Augustin, Kelsey; Bayne, Robert S; Booker, Katherine S; Botella, Jose R; Carpita, Nicholas C; Carr, Tyrell; Chen, Jin-Gui; Cooke, Thomas Ryan; Frick-Cheng, Arwen; Friedman, Erin J; Fulk, Brandon; Hahn, Michael G; Jiang, Kun; Jorda, Lucia; Kruppe, Lydia; Liu, Chenggang; Lorek, Justine; McCann, Maureen C; Molina, Antonio; Moriyama, Etsuko N; Mukhtar, M Shahid; Mudgil, Yashwanti; Pattathil, Sivakumar; Schwarz, John; Seta, Steven; Tan, Matthew; Temp, Ulrike; Trusov, Yuri; Urano, Daisuke; Welter, Bastian; Yang, Jing; Panstruga, Ralph; Uhrig, Joachim F; Jones, Alan M

    2011-01-01

    The heterotrimeric G-protein complex is minimally composed of Gα, Gβ, and Gγ subunits. In the classic scenario, the G-protein complex is the nexus in signaling from the plasma membrane, where the heterotrimeric G-protein associates with heptahelical G-protein-coupled receptors (GPCRs), to cytoplasmic target proteins called effectors. Although a number of effectors are known in metazoans and fungi, none of these are predicted to exist in their canonical forms in plants. To identify ab initio plant G-protein effectors and scaffold proteins, we screened a set of proteins from the G-protein complex using two-hybrid complementation in yeast. After deep and exhaustive interrogation, we detected 544 interactions between 434 proteins, of which 68 highly interconnected proteins form the core G-protein interactome. Within this core, over half of the interactions comprising two-thirds of the nodes were retested and validated as genuine in planta. Co-expression analysis in combination with phenotyping of loss-of-function mutations in a set of core interactome genes revealed a novel role for G-proteins in regulating cell wall modification. PMID:21952135

  20. Arabidopsis G-protein interactome reveals connections to cell wall carbohydrates and morphogenesis

    SciTech Connect

    Klopffleisch, Karsten; Phan, Nguyen; Chen, Jay; Panstruga, Ralph; Uhrig, Joachim; Jones, Alan M

    2011-01-01

    The heterotrimeric G-protein complex is minimally composed of G{alpha}, G{beta}, and G{gamma} subunits. In the classic scenario, the G-protein complex is the nexus in signaling from the plasma membrane, where the heterotrimeric G-protein associates with heptahelical G-protein-coupled receptors (GPCRs), to cytoplasmic target proteins called effectors. Although a number of effectors are known in metazoans and fungi, none of these are predicted to exist in their canonical forms in plants. To identify ab initio plant G-protein effectors and scaffold proteins, we screened a set of proteins from the G-protein complex using two-hybrid complementation in yeast. After deep and exhaustive interrogation, we detected 544 interactions between 434 proteins, of which 68 highly interconnected proteins form the core G-protein interactome. Within this core, over half of the interactions comprising two-thirds of the nodes were retested and validated as genuine in planta. Co-expression analysis in combination with phenotyping of loss-of-function mutations in a set of core interactome genes revealed a novel role for G-proteins in regulating cell wall modification.

  1. Charting the NF-κB Pathway Interactome Map

    PubMed Central

    Tieri, Paolo; Termanini, Alberto; Bellavista, Elena; Salvioli, Stefano; Capri, Miriam; Franceschi, Claudio

    2012-01-01

    Inflammation is part of a complex physiological response to harmful stimuli and pathogenic stress. The five components of the Nuclear Factor κB (NF-κB) family are prominent mediators of inflammation, acting as key transcriptional regulators of hundreds of genes. Several signaling pathways activated by diverse stimuli converge on NF-κB activation, resulting in a regulatory system characterized by high complexity. It is increasingly recognized that the number of components that impinges upon phenotypic outcomes of signal transduction pathways may be higher than those taken into consideration from canonical pathway representations. Scope of the present analysis is to provide a wider, systemic picture of the NF-κB signaling system. Data from different sources such as literature, functional enrichment web resources, protein-protein interaction and pathway databases have been gathered, curated, integrated and analyzed in order to reconstruct a single, comprehensive picture of the proteins that interact with, and participate to the NF-κB activation system. Such a reconstruction shows that the NF-κB interactome is substantially different in quantity and quality of components with respect to canonical representations. The analysis highlights that several neglected but topologically central proteins may play a role in the activation of NF-κB mediated responses. Moreover the interactome structure fits with the characteristics of a bow tie architecture. This interactome is intended as an open network resource available for further development, refinement and analysis. PMID:22403694

  2. Schizophrenia interactome with 504 novel protein-protein interactions.

    PubMed

    Ganapathiraju, Madhavi K; Thahir, Mohamed; Handen, Adam; Sarkar, Saumendra N; Sweet, Robert A; Nimgaonkar, Vishwajit L; Loscher, Christine E; Bauer, Eileen M; Chaparala, Srilakshmi

    2016-01-01

    Genome-wide association studies of schizophrenia (GWAS) have revealed the role of rare and common genetic variants, but the functional effects of the risk variants remain to be understood. Protein interactome-based studies can facilitate the study of molecular mechanisms by which the risk genes relate to schizophrenia (SZ) genesis, but protein-protein interactions (PPIs) are unknown for many of the liability genes. We developed a computational model to discover PPIs, which is found to be highly accurate according to computational evaluations and experimental validations of selected PPIs. We present here, 365 novel PPIs of liability genes identified by the SZ Working Group of the Psychiatric Genomics Consortium (PGC). Seventeen genes that had no previously known interactions have 57 novel interactions by our method. Among the new interactors are 19 drug targets that are targeted by 130 drugs. In addition, we computed 147 novel PPIs of 25 candidate genes investigated in the pre-GWAS era. While there is little overlap between the GWAS genes and the pre-GWAS genes, the interactomes reveal that they largely belong to the same pathways, thus reconciling the apparent disparities between the GWAS and prior gene association studies. The interactome including 504 novel PPIs overall, could motivate other systems biology studies and trials with repurposed drugs. The PPIs are made available on a webserver, called Schizo-Pi at http://severus.dbmi.pitt.edu/schizo-pi with advanced search capabilities. PMID:27336055

  3. Proteomic data on the nuclear interactome of human MCM9

    PubMed Central

    Hutchins, James R.A.; Traver, Sabine; Coulombe, Philippe; Peiffer, Isabelle; Kitzmann, Magali; Latreille, Daniel; Méchali, Marcel

    2015-01-01

    We present data relating to the interactome of MCM9 from the nuclei of human cells. MCM9 belongs to the AAA+ superfamily, and contains an MCM domain and motifs that may confer DNA helicase activity. MCM9 has been shown to bind MCM8, and has been implicated in DNA replication and homologous recombination. However, the mechanistic basis of MCM9’s role in DNA repair is poorly understood, and proteins with which it interacts were hitherto unknown. We performed tandem affinity purification of MCM9 and its interacting proteins from nuclear extracts of human cells, followed by proteomic analysis, thereby generating a set of mass spectrometry data corresponding to the MCM9 interactome [1]. The proteomic data set comprises 29 mass spectrometry RAW files, deposited to the ProteomeXchange Consortium, and freely available from the PRIDE partner repository with the data set identifier PXD000212. A set of 22 interacting proteins identified from the proteomic data was used to create an MCM9-centered interactive network diagram, using the Cytoscape program. These data allow the scientific community to access, mine and explore the human nuclear MCM9 interactome. PMID:26870752

  4. Charting the NF-κB pathway interactome map.

    PubMed

    Tieri, Paolo; Termanini, Alberto; Bellavista, Elena; Salvioli, Stefano; Capri, Miriam; Franceschi, Claudio

    2012-01-01

    Inflammation is part of a complex physiological response to harmful stimuli and pathogenic stress. The five components of the Nuclear Factor κB (NF-κB) family are prominent mediators of inflammation, acting as key transcriptional regulators of hundreds of genes. Several signaling pathways activated by diverse stimuli converge on NF-κB activation, resulting in a regulatory system characterized by high complexity. It is increasingly recognized that the number of components that impinges upon phenotypic outcomes of signal transduction pathways may be higher than those taken into consideration from canonical pathway representations. Scope of the present analysis is to provide a wider, systemic picture of the NF-κB signaling system. Data from different sources such as literature, functional enrichment web resources, protein-protein interaction and pathway databases have been gathered, curated, integrated and analyzed in order to reconstruct a single, comprehensive picture of the proteins that interact with, and participate to the NF-κB activation system. Such a reconstruction shows that the NF-κB interactome is substantially different in quantity and quality of components with respect to canonical representations. The analysis highlights that several neglected but topologically central proteins may play a role in the activation of NF-κB mediated responses. Moreover the interactome structure fits with the characteristics of a bow tie architecture. This interactome is intended as an open network resource available for further development, refinement and analysis.

  5. Schizophrenia interactome with 504 novel protein–protein interactions

    PubMed Central

    Ganapathiraju, Madhavi K; Thahir, Mohamed; Handen, Adam; Sarkar, Saumendra N; Sweet, Robert A; Nimgaonkar, Vishwajit L; Loscher, Christine E; Bauer, Eileen M; Chaparala, Srilakshmi

    2016-01-01

    Genome-wide association studies of schizophrenia (GWAS) have revealed the role of rare and common genetic variants, but the functional effects of the risk variants remain to be understood. Protein interactome-based studies can facilitate the study of molecular mechanisms by which the risk genes relate to schizophrenia (SZ) genesis, but protein–protein interactions (PPIs) are unknown for many of the liability genes. We developed a computational model to discover PPIs, which is found to be highly accurate according to computational evaluations and experimental validations of selected PPIs. We present here, 365 novel PPIs of liability genes identified by the SZ Working Group of the Psychiatric Genomics Consortium (PGC). Seventeen genes that had no previously known interactions have 57 novel interactions by our method. Among the new interactors are 19 drug targets that are targeted by 130 drugs. In addition, we computed 147 novel PPIs of 25 candidate genes investigated in the pre-GWAS era. While there is little overlap between the GWAS genes and the pre-GWAS genes, the interactomes reveal that they largely belong to the same pathways, thus reconciling the apparent disparities between the GWAS and prior gene association studies. The interactome including 504 novel PPIs overall, could motivate other systems biology studies and trials with repurposed drugs. The PPIs are made available on a webserver, called Schizo-Pi at http://severus.dbmi.pitt.edu/schizo-pi with advanced search capabilities. PMID:27336055

  6. Charting the NF-κB pathway interactome map.

    PubMed

    Tieri, Paolo; Termanini, Alberto; Bellavista, Elena; Salvioli, Stefano; Capri, Miriam; Franceschi, Claudio

    2012-01-01

    Inflammation is part of a complex physiological response to harmful stimuli and pathogenic stress. The five components of the Nuclear Factor κB (NF-κB) family are prominent mediators of inflammation, acting as key transcriptional regulators of hundreds of genes. Several signaling pathways activated by diverse stimuli converge on NF-κB activation, resulting in a regulatory system characterized by high complexity. It is increasingly recognized that the number of components that impinges upon phenotypic outcomes of signal transduction pathways may be higher than those taken into consideration from canonical pathway representations. Scope of the present analysis is to provide a wider, systemic picture of the NF-κB signaling system. Data from different sources such as literature, functional enrichment web resources, protein-protein interaction and pathway databases have been gathered, curated, integrated and analyzed in order to reconstruct a single, comprehensive picture of the proteins that interact with, and participate to the NF-κB activation system. Such a reconstruction shows that the NF-κB interactome is substantially different in quantity and quality of components with respect to canonical representations. The analysis highlights that several neglected but topologically central proteins may play a role in the activation of NF-κB mediated responses. Moreover the interactome structure fits with the characteristics of a bow tie architecture. This interactome is intended as an open network resource available for further development, refinement and analysis. PMID:22403694

  7. AIM: A comprehensive Arabidopsis Interactome Module database and related interologs in plants

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Systems biology analysis of protein modules is important for understanding the functional relationships between proteins in the interactome. Here, we present a comprehensive database named AIM for Arabidopsis (Arabidopsis thaliana) interactome modules. The database contains almost 250,000 modules th...

  8. Spatio-temporal prediction of leaf area index of rubber plantation using HJ-1A/1B CCD images and recurrent neural network

    NASA Astrophysics Data System (ADS)

    Chen, Bangqian; Wu, Zhixiang; Wang, Jikun; Dong, Jinwei; Guan, Liming; Chen, Junming; Yang, Kai; Xie, Guishui

    2015-04-01

    Rubber (Hevea brasiliensis) plantations are one of the most important economic forest in tropical area. Retrieving leaf area index (LAI) and its dynamics by remote sensing is of great significance in ecological study and production management, such as yield prediction and post-hurricane damage evaluation. Thirteen HJ-1A/1B CCD images, which possess the spatial advantage of Landsat TM/ETM+ and 2-days temporal resolution of MODIS, were introduced to predict the spatial-temporal LAI of rubber plantation on Hainan Island by Nonlinear AutoRegressive networks with eXogenous inputs (NARX) model. Monthly measured LAIs at 30 stands by LAI-2000 between 2012 and 2013 were used to explore the LAI dynamics and their relationship with spectral bands and seven vegetation indices, and to develop and validate model. The NARX model, which was built base on input variables of day of year (DOY), four spectral bands and weight difference vegetation index (WDVI), possessed good accuracies during the model building for the data set of training (N = 202, R2 = 0.98, RMSE = 0.13), validation (N = 43, R2 = 0.93, RMSE = 0.24) and testing (N = 43, R2 = 0.87, RMSE = 0.31), respectively. The model performed well during field validation (N = 24, R2 = 0.88, RMSE = 0.24) and most of its mapping results showed better agreement (R2 = 0.54-0.58, RMSE = 0.47-0.71) with the field data than the results of corresponding stepwise regression models (R2 = 0.43-0.51, RMSE = 0.52-0.82). Besides, the LAI statistical values from the spatio-temporal LAI maps and their dynamics, which increased dramatically from late March (2.36 ± 0.59) to early May (3.22 ± 0.64) and then gradually slow down until reached the maximum value in early October (4.21 ± 0.87), were quite consistent with the statistical results of the field data. The study demonstrates the feasibility and reliability of retrieving spatio-temporal LAI of rubber plantations by an artificial neural network (ANN) approach, and provides some insight on the

  9. HIV-host interactome revealed directly from infected cells.

    PubMed

    Luo, Yang; Jacobs, Erica Y; Greco, Todd M; Mohammed, Kevin D; Tong, Tommy; Keegan, Sarah; Binley, James M; Cristea, Ileana M; Fenyö, David; Rout, Michael P; Chait, Brian T; Muesing, Mark A

    2016-01-01

    Although genetically compact, HIV-1 commandeers vast arrays of cellular machinery to sustain and protect it during cycles of viral outgrowth. Transposon-mediated saturation linker scanning mutagenesis was used to isolate fully replication-competent viruses harbouring a potent foreign epitope tag. Using these viral isolates, we performed differential isotopic labelling and affinity-capture mass spectrometric analyses on samples obtained from cultures of human lymphocytes to classify the vicinal interactomes of the viral Env and Vif proteins as they occur during natural infection. Importantly, interacting proteins were recovered without bias, regardless of their potential for positive, negative or neutral impact on viral replication. We identified specific host associations made with trimerized Env during its biosynthesis, at virological synapses, with innate immune effectors (such as HLA-E) and with certain cellular signalling pathways (for example, Notch1). We also defined Vif associations with host proteins involved in the control of nuclear transcription and nucleoside biosynthesis as well as those interacting stably or transiently with the cytoplasmic protein degradation apparatus. Our approach is broadly applicable to elucidating pathogen-host interactomes, providing high-certainty identification of interactors by their direct access during cycling infection. Understanding the pathophysiological consequences of these associations is likely to provide strategic targets for antiviral intervention. PMID:27572969

  10. HIV–host interactome revealed directly from infected cells

    PubMed Central

    Luo, Yang; Jacobs, Erica Y.; Greco, Todd M.; Mohammed, Kevin D.; Tong, Tommy; Keegan, Sarah; Binley, James M.; Cristea, Ileana M.; Fenyö, David; Rout, Michael P.; Chait, Brian T.; Muesing, Mark A.

    2016-01-01

    Although genetically compact, HIV-1 commandeers vast arrays of cellular machinery to sustain and protect it during cycles of viral outgrowth. Transposon-mediated saturation linker scanning mutagenesis was used to isolate fully replication-competent viruses harbouring a potent foreign epitope tag. Using these viral isolates, we performed differential isotopic labelling and affinity-capture mass spectrometric analyses on samples obtained from cultures of human lymphocytes to classify the vicinal interactomes of the viral Env and Vif proteins as they occur during natural infection. Importantly, interacting proteins were recovered without bias, regardless of their potential for positive, negative or neutral impact on viral replication. We identified specific host associations made with trimerized Env during its biosynthesis, at virological synapses, with innate immune effectors (such as HLA-E) and with certain cellular signalling pathways (for example, Notch1). We also defined Vif associations with host proteins involved in the control of nuclear transcription and nucleoside biosynthesis as well as those interacting stably or transiently with the cytoplasmic protein degradation apparatus. Our approach is broadly applicable to elucidating pathogen–host interactomes, providing high-certainty identification of interactors by their direct access during cycling infection. Understanding the pathophysiological consequences of these associations is likely to provide strategic targets for antiviral intervention. PMID:27375898

  11. Understanding and Predicting Spatio-Temporal Variability of Temperature in Scotland's Rivers: Implications for Riparian Land Management

    NASA Astrophysics Data System (ADS)

    Jackson, F. L.; Malcolm, I.; Hannah, D. M.

    2015-12-01

    Freshwater fish are frequently the focus of river management, and rising water temperature (Tw) has the potential to negatively influence the suitability of habitats for many species, including salmonids. Consequently, an improved understanding of spatial and temporal variability in Tw is required at the river basin, hydrometric region and national scales concurrent with the scales at which management decisions are made. The Scotland River Temperature Monitoring Network (SRTMN) was designed to record Tw variability across the observed environmental range of a suite of landscape characteristics. These characteristics act as proxies for controls known to affect heat and water exchange processes. This national-scale monitoring network provides quality controlled data that enables the scaling up of small-scale process understanding to larger spatial scales. This dataset provided the input to statistical models which were used to investigate controls on summary metrics describing Tw and to predict future change. Following model selection procedures, the most significant and influential variables were found to vary seasonally and in relation to the temperature metric being described, reflecting the time varying importance of landscape controls and their influence on energy exchange processes. The presence of riparian woodland was a significant control on temperature that is also amenable to management control. Future work will focus on applying these models to unmonitored locations and highlighting sensitive areas where riparian management (planting or protecting woodland) could be beneficial to reduce the risks of potentially damaging high temperatures. This large-scale scientific understanding will be important for informing the management of Scottish rivers under a changing climate.

  12. Summer rains and dry seasons in the upper Blue Nile Basin: the predictability of half a century of past and future spatiotemporal patterns.

    PubMed

    Mellander, Per-Erik; Gebrehiwot, Solomon G; Gärdenäs, Annemieke I; Bewket, Woldeamlak; Bishop, Kevin

    2013-01-01

    During the last 100 years the Ethiopian upper Blue Nile Basin (BNB) has undergone major changes in land use, and is now potentially facing changes in climate. Rainfall over BNB supplies over two-thirds of the water to the Nile and supports a large local population living mainly on subsistence agriculture. Regional food security is sensitive to both the amount and timing of rain and is already an important political challenge that will be further complicated if scenarios of climate change are realized. In this study a simple spatial model of the timing and duration of summer rains (Kiremt) and dry season (Bega), and annual rain over the upper BNB was established from observed data between 1952 and 2004. The model was used to explore potential impacts of climate change on these rains, using a down-scaled ECHAM5/MP1-OM scenario between 2050 and 2100. Over the observed period the amount, onset and duration of Kiremt rains and rain-free Bega days have exhibited a consistent spatial pattern. The spatially averaged annual rainfall was 1490 mm of which 93% was Kiremt rain. The average Kiremt rain and number of rainy days was higher in the southwest (322 days) and decreased towards the north (136 days). Under the 2050-2100 scenario, the annual mean rainfall is predicted to increase by 6% and maintain the same spatial pattern as in the past. A larger change in annual rainfall is expected in the southwest (ca. +130 mm) with a gradually smaller change towards the north (ca. +70 mm). Results highlight the need to account for the characteristic spatiotemporal zonation when planning water management and climate adaptation within the upper BNB. The presented simple spatial resolved models of the presence of Kiremt and annual total rainfall could be used as a baseline for such long-term planning.

  13. Functional proteomic and interactome analysis of proteins associated with beef tenderness in angus cattle

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Beef is a source of high quality protein for the human population, and beef tenderness has significant influence on beef palatability, consumer expectation and industry profitability. To further elucidate the factors affecting beef tenderness, functional proteomics and bioinformatics interactome ana...

  14. The extended pluripotency protein interactome and its links to reprogramming

    PubMed Central

    Huang, Xin; Wang, Jianlong

    2014-01-01

    A pluripotent state of embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs) is maintained through the combinatorial activity of core transcriptional factors (TFs) such as Oct4, Sox2, and Nanog in conjunction with many other factors including epigenetic regulators. Proteins rarely act alone, and knowledge of protein-protein interaction network (interactome) provides an extraordinary resource about how pluripotency TFs collaborate and crosstalk with epigenetic regulators in ESCs. Recent advances in affinity purification coupled with mass spectrometry (AP-MS) allow for efficient, high-throughput identification of hundreds of interacting protein partners, which can be used to map the pluripotency landscape. Here we review recent publications employing AP-MS to investigate protein interaction networks in ESCs, discuss how protein-protein connections reveal novel pluripotency regulatory circuits and new factors for efficient reprogramming of somatic cells. PMID:25173149

  15. STPMiner: A Highperformance Spatiotemporal Pattern Mining Toolbox

    SciTech Connect

    Vatsavai, Raju

    2011-01-01

    The volume of spatiotemporal data being generated from scientific simulations and observations from sensors is growing at an astronomical rate. This data explosion is going to pose three challenges to the existing data mining infrastructure: algorithmic, computational, and I/O. Over the years we have implemented several spatiotemporal data mining algorithms including: outliers/anomalies, colocation patterns, change patterns, clustering, classification, and prediction algorithms. In this paper we briefly discuss the core spatiotemporal pattern mining algorithms along with some of the computational and I/O challenges associated with the big data.

  16. ANIA: ANnotation and Integrated Analysis of the 14-3-3 interactome

    PubMed Central

    Tinti, Michele; Madeira, Fábio; Murugesan, Gavuthami; Hoxhaj, Gerta; Toth, Rachel; MacKintosh, Carol

    2014-01-01

    The dimeric 14-3-3 proteins dock onto pairs of phosphorylated Ser and Thr residues on hundreds of proteins, and thereby regulate many events in mammalian cells. To facilitate global analyses of these interactions, we developed a web resource named ANIA: ANnotation and Integrated Analysis of the 14-3-3 interactome, which integrates multiple data sets on 14-3-3-binding phosphoproteins. ANIA also pinpoints candidate 14-3-3-binding phosphosites using predictor algorithms, assisted by our recent discovery that the human 14-3-3-interactome is highly enriched in 2R-ohnologues. 2R-ohnologues are proteins in families of two to four, generated by two rounds of whole genome duplication at the origin of the vertebrate animals. ANIA identifies candidate ‘lynchpins’, which are 14-3-3-binding phosphosites that are conserved across members of a given 2R-ohnologue protein family. Other features of ANIA include a link to the catalogue of somatic mutations in cancer database to find cancer polymorphisms that map to 14-3-3-binding phosphosites, which would be expected to interfere with 14-3-3 interactions. We used ANIA to map known and candidate 14-3-3-binding enzymes within the 2R-ohnologue complement of the human kinome. Our projections indicate that 14-3-3s dock onto many more human kinases than has been realized. Guided by ANIA, PAK4, 6 and 7 (p21-activated kinases 4, 6 and 7) were experimentally validated as a 2R-ohnologue family of 14-3-3-binding phosphoproteins. PAK4 binding to 14-3-3 is stimulated by phorbol ester, and involves the ‘lynchpin’ site phosphoSer99 and a major contribution from Ser181. In contrast, PAK6 and PAK7 display strong phorbol ester-independent binding to 14-3-3, with Ser113 critical for the interaction with PAK6. These data point to differential 14-3-3 regulation of PAKs in control of cell morphology. Database URL: https://ania-1433.lifesci.dundee.ac.uk/prediction/webserver/index.py PMID:24501395

  17. ANIA: ANnotation and Integrated Analysis of the 14-3-3 interactome.

    PubMed

    Tinti, Michele; Madeira, Fábio; Murugesan, Gavuthami; Hoxhaj, Gerta; Toth, Rachel; Mackintosh, Carol

    2014-01-01

    The dimeric 14-3-3 proteins dock onto pairs of phosphorylated Ser and Thr residues on hundreds of proteins, and thereby regulate many events in mammalian cells. To facilitate global analyses of these interactions, we developed a web resource named ANIA: ANnotation and Integrated Analysis of the 14-3-3 interactome, which integrates multiple data sets on 14-3-3-binding phosphoproteins. ANIA also pinpoints candidate 14-3-3-binding phosphosites using predictor algorithms, assisted by our recent discovery that the human 14-3-3-interactome is highly enriched in 2R-ohnologues. 2R-ohnologues are proteins in families of two to four, generated by two rounds of whole genome duplication at the origin of the vertebrate animals. ANIA identifies candidate 'lynchpins', which are 14-3-3-binding phosphosites that are conserved across members of a given 2R-ohnologue protein family. Other features of ANIA include a link to the catalogue of somatic mutations in cancer database to find cancer polymorphisms that map to 14-3-3-binding phosphosites, which would be expected to interfere with 14-3-3 interactions. We used ANIA to map known and candidate 14-3-3-binding enzymes within the 2R-ohnologue complement of the human kinome. Our projections indicate that 14-3-3s dock onto many more human kinases than has been realized. Guided by ANIA, PAK4, 6 and 7 (p21-activated kinases 4, 6 and 7) were experimentally validated as a 2R-ohnologue family of 14-3-3-binding phosphoproteins. PAK4 binding to 14-3-3 is stimulated by phorbol ester, and involves the 'lynchpin' site phosphoSer99 and a major contribution from Ser181. In contrast, PAK6 and PAK7 display strong phorbol ester-independent binding to 14-3-3, with Ser113 critical for the interaction with PAK6. These data point to differential 14-3-3 regulation of PAKs in control of cell morphology. Database URL: https://ania-1433.lifesci.dundee.ac.uk/prediction/webserver/index.py.

  18. The membrane- and soluble-protein helix-helix interactome: similar geometry via different interactions.

    PubMed

    Zhang, Shao-Qing; Kulp, Daniel W; Schramm, Chaim A; Mravic, Marco; Samish, Ilan; DeGrado, William F

    2015-03-01

    α Helices are a basic unit of protein secondary structure and therefore the interaction between helices is crucial to understanding tertiary and higher-order folds. Comparing subtle variations in the structural and sequence motifs between membrane and soluble proteins sheds light on the different constraints faced by each environment and elucidates the complex puzzle of membrane protein folding. Here, we demonstrate that membrane and water-soluble helix pairs share a small number of similar folds with various interhelical distances. The composition of the residues that pack at the interface between corresponding motifs shows that hydrophobic residues tend to be more enriched in the water-soluble class of structures and small residues in the transmembrane class. The latter group facilitates packing via sidechain- and backbone-mediated hydrogen bonds within the low-dielectric membrane milieu. The helix-helix interactome space, with its associated sequence preferences and accompanying hydrogen-bonding patterns, should be useful for engineering, prediction, and design of protein structure.

  19. The membrane- and soluble-protein helix-helix interactome: similar geometry via different interactions.

    PubMed

    Zhang, Shao-Qing; Kulp, Daniel W; Schramm, Chaim A; Mravic, Marco; Samish, Ilan; DeGrado, William F

    2015-03-01

    α Helices are a basic unit of protein secondary structure and therefore the interaction between helices is crucial to understanding tertiary and higher-order folds. Comparing subtle variations in the structural and sequence motifs between membrane and soluble proteins sheds light on the different constraints faced by each environment and elucidates the complex puzzle of membrane protein folding. Here, we demonstrate that membrane and water-soluble helix pairs share a small number of similar folds with various interhelical distances. The composition of the residues that pack at the interface between corresponding motifs shows that hydrophobic residues tend to be more enriched in the water-soluble class of structures and small residues in the transmembrane class. The latter group facilitates packing via sidechain- and backbone-mediated hydrogen bonds within the low-dielectric membrane milieu. The helix-helix interactome space, with its associated sequence preferences and accompanying hydrogen-bonding patterns, should be useful for engineering, prediction, and design of protein structure. PMID:25703378

  20. Exploring Bacterial Organelle Interactomes: A Model of the Protein-Protein Interaction Network in the Pdu Microcompartment

    PubMed Central

    Jorda, Julien; Liu, Yu; Bobik, Thomas A.; Yeates, Todd O.

    2015-01-01

    Bacterial microcompartments (MCPs) are protein-bound organelles that carry out diverse metabolic pathways in a wide range of bacteria. These supramolecular assemblies consist of a thin outer protein shell, reminiscent of a viral capsid, which encapsulates sequentially acting enzymes. The most complex MCP elucidated so far is the propanediol utilizing (Pdu) microcompartment. It contains the reactions for degrading 1,2-propanediol. While several experimental studies on the Pdu system have provided hints about its organization, a clear picture of how all the individual components interact has not emerged yet. Here we use co-evolution-based methods, involving pairwise comparisons of protein phylogenetic trees, to predict the protein-protein interaction (PPI) network governing the assembly of the Pdu MCP. We propose a model of the Pdu interactome, from which selected PPIs are further inspected via computational docking simulations. We find that shell protein PduA is able to serve as a “universal hub” for targeting an array of enzymes presenting special N-terminal extensions, namely PduC, D, E, L and P. The varied N-terminal peptides are predicted to bind in the same cleft on the presumptive luminal face of the PduA hexamer. We also propose that PduV, a protein of unknown function with remote homology to the Ras-like GTPase superfamily, is likely to localize outside the MCP, interacting with the protruding β-barrel of the hexameric PduU shell protein. Preliminary experiments involving a bacterial two-hybrid assay are presented that corroborate the existence of a PduU-PduV interaction. This first systematic computational study aimed at characterizing the interactome of a bacterial microcompartment provides fresh insight into the organization of the Pdu MCP. PMID:25646976

  1. A convex optimization approach for identification of human tissue-specific interactomes

    PubMed Central

    Mohammadi, Shahin; Grama, Ananth

    2016-01-01

    Motivation: Analysis of organism-specific interactomes has yielded novel insights into cellular function and coordination, understanding of pathology, and identification of markers and drug targets. Genes, however, can exhibit varying levels of cell type specificity in their expression, and their coordinated expression manifests in tissue-specific function and pathology. Tissue-specific/tissue-selective interaction mechanisms have significant applications in drug discovery, as they are more likely to reveal drug targets. Furthermore, tissue-specific transcription factors (tsTFs) are significantly implicated in human disease, including cancers. Finally, disease genes and protein complexes have the tendency to be differentially expressed in tissues in which defects cause pathology. These observations motivate the construction of refined tissue-specific interactomes from organism-specific interactomes. Results: We present a novel technique for constructing human tissue-specific interactomes. Using a variety of validation tests (Edge Set Enrichment Analysis, Gene Ontology Enrichment, Disease-Gene Subnetwork Compactness), we show that our proposed approach significantly outperforms state-of-the-art techniques. Finally, using case studies of Alzheimer’s and Parkinson’s diseases, we show that tissue-specific interactomes derived from our study can be used to construct pathways implicated in pathology and demonstrate the use of these pathways in identifying novel targets. Availability and implementation: http://www.cs.purdue.edu/homes/mohammas/projects/ActPro.html Contact: mohammadi@purdue.edu PMID:27307623

  2. Global De Novo Protein-Protein Interactome Elucidates Interactions of Drought-Responsive Proteins in Horse Gram (Macrotyloma uniflorum).

    PubMed

    Bhardwaj, Jyoti; Gangwar, Indu; Panzade, Ganesh; Shankar, Ravi; Yadav, Sudesh Kumar

    2016-06-01

    Inspired by the availability of de novo transcriptome of horse gram (Macrotyloma uniflorum) and recent developments in systems biology studies, the first ever global protein-protein interactome (PPI) map was constructed for this highly drought-tolerant legume. Large-scale studies of PPIs and the constructed database would provide rationale behind the interplay at cascading translational levels for drought stress-adaptive mechanisms in horse gram. Using a bidirectional approach (interolog and domain-based), a high-confidence interactome map and database for horse gram was constructed. Available transcriptomic information for shoot and root tissues of a sensitive (M-191; genotype 1) and a drought-tolerant (M-249; genotype 2) genotype of horse gram was utilized to draw comparative PPI subnetworks under drought stress. High-confidence 6804 interactions were predicted among 1812 proteins covering about one-fourth of the horse gram proteome. The highest number of interactions (33.86%) in horse gram interactome matched with Arabidopsis PPI data. The top five hub nodes mostly included ubiquitin and heat-shock-related proteins. Higher numbers of PPIs were found to be responsive in shoot tissue (416) and root tissue (2228) of genotype 2 compared with shoot tissue (136) and root tissue (579) of genotype 1. Characterization of PPIs using gene ontology analysis revealed that kinase and transferase activities involved in signal transduction, cellular processes, nucleocytoplasmic transport, protein ubiquitination, and localization of molecules were most responsive to drought stress. Hence, these could be framed in stress adaptive mechanisms of horse gram. Being the first legume global PPI map, it would provide new insights into gene and protein regulatory networks for drought stress tolerance mechanisms in horse gram. Information compiled in the form of database (MauPIR) will provide the much needed high-confidence systems biology information for horse gram genes, proteins, and

  3. Global De Novo Protein-Protein Interactome Elucidates Interactions of Drought-Responsive Proteins in Horse Gram (Macrotyloma uniflorum).

    PubMed

    Bhardwaj, Jyoti; Gangwar, Indu; Panzade, Ganesh; Shankar, Ravi; Yadav, Sudesh Kumar

    2016-06-01

    Inspired by the availability of de novo transcriptome of horse gram (Macrotyloma uniflorum) and recent developments in systems biology studies, the first ever global protein-protein interactome (PPI) map was constructed for this highly drought-tolerant legume. Large-scale studies of PPIs and the constructed database would provide rationale behind the interplay at cascading translational levels for drought stress-adaptive mechanisms in horse gram. Using a bidirectional approach (interolog and domain-based), a high-confidence interactome map and database for horse gram was constructed. Available transcriptomic information for shoot and root tissues of a sensitive (M-191; genotype 1) and a drought-tolerant (M-249; genotype 2) genotype of horse gram was utilized to draw comparative PPI subnetworks under drought stress. High-confidence 6804 interactions were predicted among 1812 proteins covering about one-fourth of the horse gram proteome. The highest number of interactions (33.86%) in horse gram interactome matched with Arabidopsis PPI data. The top five hub nodes mostly included ubiquitin and heat-shock-related proteins. Higher numbers of PPIs were found to be responsive in shoot tissue (416) and root tissue (2228) of genotype 2 compared with shoot tissue (136) and root tissue (579) of genotype 1. Characterization of PPIs using gene ontology analysis revealed that kinase and transferase activities involved in signal transduction, cellular processes, nucleocytoplasmic transport, protein ubiquitination, and localization of molecules were most responsive to drought stress. Hence, these could be framed in stress adaptive mechanisms of horse gram. Being the first legume global PPI map, it would provide new insights into gene and protein regulatory networks for drought stress tolerance mechanisms in horse gram. Information compiled in the form of database (MauPIR) will provide the much needed high-confidence systems biology information for horse gram genes, proteins, and

  4. Integrative analysis of cancer genes in a functional interactome.

    PubMed

    Ung, Matthew H; Liu, Chun-Chi; Cheng, Chao

    2016-01-01

    The post-genomic era has resulted in the accumulation of high-throughput cancer data from a vast array of genomic technologies including next-generation sequencing and microarray. As such, the large amounts of germline variant and somatic mutation data that have been generated from GWAS and sequencing projects, respectively, show great promise in providing a systems-level view of these genetic aberrations. In this study, we analyze publicly available GWAS, somatic mutation, and drug target data derived from large databanks using a network-based approach that incorporates directed edge information under a randomized network hypothesis testing procedure. We show that these three classes of disease-associated nodes exhibit non-random topological characteristics in the context of a functional interactome. Specifically, we show that drug targets tend to lie upstream of somatic mutations and disease susceptibility germline variants. In addition, we introduce a new approach to measuring hierarchy between drug targets, somatic mutants, and disease susceptibility genes by utilizing directionality and path length information. Overall, our results provide new insight into the intrinsic relationships between these node classes that broaden our understanding of cancer. In addition, our results align with current knowledge on the therapeutic actionability of GWAS and somatic mutant nodes, while demonstrating relationships between node classes from a global network perspective. PMID:27356765

  5. SInCRe-structural interactome computational resource for Mycobacterium tuberculosis.

    PubMed

    Metri, Rahul; Hariharaputran, Sridhar; Ramakrishnan, Gayatri; Anand, Praveen; Raghavender, Upadhyayula S; Ochoa-Montaño, Bernardo; Higueruelo, Alicia P; Sowdhamini, Ramanathan; Chandra, Nagasuma R; Blundell, Tom L; Srinivasan, Narayanaswamy

    2015-01-01

    We have developed an integrated database for Mycobacterium tuberculosis H37Rv (Mtb) that collates information on protein sequences, domain assignments, functional annotation and 3D structural information along with protein-protein and protein-small molecule interactions. SInCRe (Structural Interactome Computational Resource) is developed out of CamBan (Cambridge and Bangalore) collaboration. The motivation for development of this database is to provide an integrated platform to allow easily access and interpretation of data and results obtained by all the groups in CamBan in the field of Mtb informatics. In-house algorithms and databases developed independently by various academic groups in CamBan are used to generate Mtb-specific datasets and are integrated in this database to provide a structural dimension to studies on tuberculosis. The SInCRe database readily provides information on identification of functional domains, genome-scale modelling of structures of Mtb proteins and characterization of the small-molecule binding sites within Mtb. The resource also provides structure-based function annotation, information on small-molecule binders including FDA (Food and Drug Administration)-approved drugs, protein-protein interactions (PPIs) and natural compounds that bind to pathogen proteins potentially and result in weakening or elimination of host-pathogen protein-protein interactions. Together they provide prerequisites for identification of off-target binding. PMID:26130660

  6. SInCRe—structural interactome computational resource for Mycobacterium tuberculosis

    PubMed Central

    Metri, Rahul; Hariharaputran, Sridhar; Ramakrishnan, Gayatri; Anand, Praveen; Raghavender, Upadhyayula S.; Ochoa-Montaño, Bernardo; Higueruelo, Alicia P.; Sowdhamini, Ramanathan; Chandra, Nagasuma R.; Blundell, Tom L.; Srinivasan, Narayanaswamy

    2015-01-01

    We have developed an integrated database for Mycobacterium tuberculosis H37Rv (Mtb) that collates information on protein sequences, domain assignments, functional annotation and 3D structural information along with protein–protein and protein–small molecule interactions. SInCRe (Structural Interactome Computational Resource) is developed out of CamBan (Cambridge and Bangalore) collaboration. The motivation for development of this database is to provide an integrated platform to allow easily access and interpretation of data and results obtained by all the groups in CamBan in the field of Mtb informatics. In-house algorithms and databases developed independently by various academic groups in CamBan are used to generate Mtb-specific datasets and are integrated in this database to provide a structural dimension to studies on tuberculosis. The SInCRe database readily provides information on identification of functional domains, genome-scale modelling of structures of Mtb proteins and characterization of the small-molecule binding sites within Mtb. The resource also provides structure-based function annotation, information on small-molecule binders including FDA (Food and Drug Administration)-approved drugs, protein–protein interactions (PPIs) and natural compounds that bind to pathogen proteins potentially and result in weakening or elimination of host–pathogen protein–protein interactions. Together they provide prerequisites for identification of off-target binding. Database URL: http://proline.biochem.iisc.ernet.in/sincre PMID:26130660

  7. Current Approaches Toward Quantitative Mapping of the Interactome

    PubMed Central

    Buntru, Alexander; Trepte, Philipp; Klockmeier, Konrad; Schnoegl, Sigrid; Wanker, Erich E.

    2016-01-01

    Protein–protein interactions (PPIs) play a key role in many, if not all, cellular processes. Disease is often caused by perturbation of PPIs, as recently indicated by studies of missense mutations. To understand the associations of proteins and to unravel the global picture of PPIs in the cell, different experimental detection techniques for PPIs have been established. Genetic and biochemical methods such as the yeast two-hybrid system or affinity purification-based approaches are well suited to high-throughput, proteome-wide screening and are mainly used to obtain qualitative results. However, they have been criticized for not reflecting the cellular situation or the dynamic nature of PPIs. In this review, we provide an overview of various genetic methods that go beyond qualitative detection and allow quantitative measuring of PPIs in mammalian cells, such as dual luminescence-based co-immunoprecipitation, Förster resonance energy transfer or luminescence-based mammalian interactome mapping with bait control. We discuss the strengths and weaknesses of different techniques and their potential applications in biomedical research. PMID:27200083

  8. Integrative analysis of cancer genes in a functional interactome

    PubMed Central

    Ung, Matthew H.; Liu, Chun-Chi; Cheng, Chao

    2016-01-01

    The post-genomic era has resulted in the accumulation of high-throughput cancer data from a vast array of genomic technologies including next-generation sequencing and microarray. As such, the large amounts of germline variant and somatic mutation data that have been generated from GWAS and sequencing projects, respectively, show great promise in providing a systems-level view of these genetic aberrations. In this study, we analyze publicly available GWAS, somatic mutation, and drug target data derived from large databanks using a network-based approach that incorporates directed edge information under a randomized network hypothesis testing procedure. We show that these three classes of disease-associated nodes exhibit non-random topological characteristics in the context of a functional interactome. Specifically, we show that drug targets tend to lie upstream of somatic mutations and disease susceptibility germline variants. In addition, we introduce a new approach to measuring hierarchy between drug targets, somatic mutants, and disease susceptibility genes by utilizing directionality and path length information. Overall, our results provide new insight into the intrinsic relationships between these node classes that broaden our understanding of cancer. In addition, our results align with current knowledge on the therapeutic actionability of GWAS and somatic mutant nodes, while demonstrating relationships between node classes from a global network perspective. PMID:27356765

  9. A Tumorigenic Factor Interactome Connected Through Tumor Suppressor MicroRNA-198 in Human Pancreatic Cancer

    PubMed Central

    Marin-Muller, Christian; Li, Dali; Bharadwaj, Uddalak; Li, Min; Chen, Changyi; Hodges, Sally E.; Fisher, William E.; Mo, Qianxing; Hung, Mien-Chie; Yao, Qizhi

    2013-01-01

    Purpose The majority of pancreatic cancers (PCs) overexpress mesothelin (MSLN), which contributes to enhanced proliferation, invasion and migration. However, the MSLN regulatory network is still unclear. Here, we investigated the regulation of a panel of tumorigenic factors, and explored the potential of MSLN regulated miR-198 treatment in vivo. Experimental Design The expression and functional regulation of the tumorigenic factors MSLN, NF-κB, and the homeobox transcription factors (TFs) POU2F2 (OCT-2), Pre-B-cell leukemia homeobox factor 1 (PBX-1), valosin-containing protein (VCP), and miR-198 were studied in PC cell lines, patient tumor samples and in xenograft PC mouse models. Results We found that miR-198 is downregulated in PC and is involved in an intricate reciprocal regulatory loop with MSLN, which represses miR-198 through NF-κB-mediated OCT-2 induction. Furthermore, miR-198 repression leads to overexpression of PBX-1 and VCP. The dysregulated PBX-1/VCP axis leads to increased tumorigenicity. Reconstitution of miR-198 in PC cells results in reduced tumor growth, metastasis, and increased survival through direct targeting MSLN, PBX-1, and VCP. Most interestingly, reduced levels of miR-198 in human tissue samples are associated with upregulation of these tumorigenic factors (MSLN, OCT-2, PBX-1, VCP) and predict poor survival. Reduced miR-198 expression links this tumor network signature and prognosticates poor patient outcome. High miR-198 disrupts the network and predicts better prognosis and increased survival. Conclusions MiR-198 acts as a central tumor suppressor and modulates the molecular makeup of a critical interactome in PC, indicating a potential prognostic marker signature and the therapeutic potential of attacking this tumorigenic network through a central vantage point. PMID:23989979

  10. Spatiotemporal hemodynamic response functions derived from physiology.

    PubMed

    Aquino, K M; Robinson, P A; Drysdale, P M

    2014-04-21

    Probing neural activity with functional magnetic resonance imaging (fMRI) relies upon understanding the hemodynamic response to changes in neural activity. Although existing studies have extensively characterized the temporal hemodynamic response, less is understood about the spatial and spatiotemporal hemodynamic responses. This study systematically characterizes the spatiotemporal response by deriving the hemodynamic response due to a short localized neural drive, i.e., the spatiotemporal hemodynamic response function (stHRF) from a physiological model of hemodynamics based on a poroelastic model of cortical tissue. In this study, the model's boundary conditions are clarified and a resulting nonlinear hemodynamic wave equation is derived. From this wave equation, damped linear hemodynamic waves are predicted from the stHRF. The main features of these waves depend on two physiological parameters: wave propagation speed, which depends on mean cortical stiffness, and damping which depends on effective viscosity. Some of these predictions were applied and validated in a companion study (Aquino et al., 2012). The advantages of having such a theory for the stHRF include improving the interpretation of spatiotemporal dynamics in fMRI data; improving estimates of neural activity with fMRI spatiotemporal deconvolution; and enabling wave interactions between hemodynamic waves to be predicted and exploited to improve the signal to noise ratio of fMRI. PMID:24398024

  11. Forward Individualized Medicine from Personal Genomes to Interactomes

    PubMed Central

    Zhang, Xiang; Kuivenhoven, Jan A.; Groen, Albert K.

    2015-01-01

    When considering the variation in the genome, transcriptome, proteome and metabolome, and their interaction with the environment, every individual can be rightfully considered as a unique biological entity. Individualized medicine promises to take this uniqueness into account to optimize disease treatment and thereby improve health benefits for every patient. The success of individualized medicine relies on a precise understanding of the genotype-phenotype relationship. Although omics technologies advance rapidly, there are several challenges that need to be overcome: Next generation sequencing can efficiently decipher genomic sequences, epigenetic changes, and transcriptomic variation in patients, but it does not automatically indicate how or whether the identified variation will cause pathological changes. This is likely due to the inability to account for (1) the consequences of gene-gene and gene-environment interactions, and (2) (post)transcriptional as well as (post)translational processes that eventually determine the concentration of key metabolites. The technologies to accurately measure changes in these latter layers are still under development, and such measurements in humans are also mainly restricted to blood and circulating cells. Despite these challenges, it is already possible to track dynamic changes in the human interactome in healthy and diseased states by using the integration of multi-omics data. In this review, we evaluate the potential value of current major bioinformatics and systems biology-based approaches, including genome wide association studies, epigenetics, gene regulatory and protein-protein interaction networks, and genome-scale metabolic modeling. Moreover, we address the question whether integrative analysis of personal multi-omics data will help understanding of personal genotype-phenotype relationships. PMID:26696898

  12. Pushing Structural Information into the Yeast Interactome by High-Throughput Protein Docking Experiments

    PubMed Central

    Mosca, Roberto; Pons, Carles; Fernández-Recio, Juan; Aloy, Patrick

    2009-01-01

    The last several years have seen the consolidation of high-throughput proteomics initiatives to identify and characterize protein interactions and macromolecular complexes in model organisms. In particular, more that 10,000 high-confidence protein-protein interactions have been described between the roughly 6,000 proteins encoded in the budding yeast genome (Saccharomyces cerevisiae). However, unfortunately, high-resolution three-dimensional structures are only available for less than one hundred of these interacting pairs. Here, we expand this structural information on yeast protein interactions by running the first-ever high-throughput docking experiment with some of the best state-of-the-art methodologies, according to our benchmarks. To increase the coverage of the interaction space, we also explore the possibility of using homology models of varying quality in the docking experiments, instead of experimental structures, and assess how it would affect the global performance of the methods. In total, we have applied the docking procedure to 217 experimental structures and 1,023 homology models, providing putative structural models for over 3,000 protein-protein interactions in the yeast interactome. Finally, we analyze in detail the structural models obtained for the interaction between SAM1-anthranilate synthase complex and the MET30-RNA polymerase III to illustrate how our predictions can be straightforwardly used by the scientific community. The results of our experiment will be integrated into the general 3D-Repertoire pipeline, a European initiative to solve the structures of as many as possible protein complexes in yeast at the best possible resolution. All docking results are available at http://gatealoy.pcb.ub.es/HT_docking/. PMID:19714207

  13. Exploring a structural protein-drug interactome for new therapeutics in lung cancer.

    PubMed

    Peng, Xiaodong; Wang, Fang; Li, Liwei; Bum-Erdene, Khuchtumur; Xu, David; Wang, Bo; Sinn, Anthony A; Pollok, Karen E; Sandusky, George E; Li, Lang; Turchi, John J; Jalal, Shadia I; Meroueh, Samy O

    2014-03-01

    The pharmacology of drugs is often defined by more than one protein target. This property can be exploited to use approved drugs to uncover new targets and signaling pathways in cancer. Towards enabling a rational approach to uncover new targets, we expand a structural protein-ligand interactome () by scoring the interaction among 1000 FDA-approved drugs docked to 2500 pockets on protein structures of the human genome. This afforded a drug-target network whose properties compared favorably with previous networks constructed using experimental data. Among drugs with the highest degree and betweenness two are cancer drugs and one is currently used for treatment of lung cancer. Comparison of predicted cancer and non-cancer targets reveals that the most cancer-specific compounds were also the most selective compounds. Analysis of compound flexibility, hydrophobicity, and size showed that the most selective compounds were low molecular weight fragment-like heterocycles. We use a previously-developed screening approach using the cancer drug erlotinib as a template to screen other approved drugs that mimic its properties. Among the top 12 ranking candidates, four are cancer drugs, two of them kinase inhibitors (like erlotinib). Cellular studies using non-small cell lung cancer (NSCLC) cells revealed that several drugs inhibited lung cancer cell proliferation. We mined patient records at the Regenstrief Medical Record System to explore the possible association of exposure to three of these drugs with occurrence of lung cancer. Preliminary in vivo studies using the non-small cell lung cancer (NCLSC) xenograft model showed that losartan- and astemizole-treated mice had tumors that weighed 50 (p < 0.01) and 15 (p < 0.01) percent less than the treated controls. These results set the stage for further exploration of these drugs and to uncover new drugs for lung cancer therapy. PMID:24402119

  14. A Highly Efficient Approach to Protein Interactome Mapping Based on Collaborative Filtering Framework

    PubMed Central

    Luo, Xin; You, Zhuhong; Zhou, Mengchu; Li, Shuai; Leung, Hareton; Xia, Yunni; Zhu, Qingsheng

    2015-01-01

    The comprehensive mapping of protein-protein interactions (PPIs) is highly desired for one to gain deep insights into both fundamental cell biology processes and the pathology of diseases. Finely-set small-scale experiments are not only very expensive but also inefficient to identify numerous interactomes despite their high accuracy. High-throughput screening techniques enable efficient identification of PPIs; yet the desire to further extract useful knowledge from these data leads to the problem of binary interactome mapping. Network topology-based approaches prove to be highly efficient in addressing this problem; however, their performance deteriorates significantly on sparse putative PPI networks. Motivated by the success of collaborative filtering (CF)-based approaches to the problem of personalized-recommendation on large, sparse rating matrices, this work aims at implementing a highly efficient CF-based approach to binary interactome mapping. To achieve this, we first propose a CF framework for it. Under this framework, we model the given data into an interactome weight matrix, where the feature-vectors of involved proteins are extracted. With them, we design the rescaled cosine coefficient to model the inter-neighborhood similarity among involved proteins, for taking the mapping process. Experimental results on three large, sparse datasets demonstrate that the proposed approach outperforms several sophisticated topology-based approaches significantly. PMID:25572661

  15. ΔF508 CFTR interactome remodeling promotes rescue of Cystic Fibrosis

    PubMed Central

    Pankow, Sandra; Bamberger, Casimir; Calzolari, Diego; Martínez-Bartolomé, Salvador; Lavallée-Adam, Mathieu; Balch, William E.; Yates, John R.

    2015-01-01

    Summary Deletion of phenylalanine 508 of the Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) is the major cause of Cystic Fibrosis (CF), one of the most common inherited childhood diseases. The mutated CFTR anion channel is not fully glycosylated and shows minimal activity in bronchial epithelial cells of CF patients. Low temperature or inhibition of histone deacetylases (HDACi) can partially rescue ΔF508 CFTR cellular processing defects and function. A favorable change of ΔF508 CFTR protein-protein interactions was proposed as mechanism of rescue, however CFTR interactome dynamics during temperature-shift and HDACi rescue are unknown. Here, we report the first comprehensive analysis of the wt and ΔF508 CFTR interactome and its dynamics during temperature shift and HDACi. By using a novel deep proteomic analysis method (CoPIT), we identified 638 individual high-confidence CFTR interactors and discovered a mutation-specific interactome, which is extensively remodeled upon rescue. Detailed analysis of the interactome remodeling identified key novel interactors, whose loss promoted enhanced CFTR channel function in primary CF epithelia or which were critical for normal CFTR biogenesis. Our results demonstrate that global remodeling of ΔF508 CFTR interactions is crucial for rescue, and provide comprehensive insight into the molecular disease mechanisms of CF caused by deletion of F508. PMID:26618866

  16. ∆F508 CFTR interactome remodelling promotes rescue of cystic fibrosis.

    PubMed

    Pankow, Sandra; Bamberger, Casimir; Calzolari, Diego; Martínez-Bartolomé, Salvador; Lavallée-Adam, Mathieu; Balch, William E; Yates, John R

    2015-12-24

    Deletion of phenylalanine 508 of the cystic fibrosis transmembrane conductance regulator (∆F508 CFTR) is the major cause of cystic fibrosis, one of the most common inherited childhood diseases. The mutated CFTR anion channel is not fully glycosylated and shows minimal activity in bronchial epithelial cells of patients with cystic fibrosis. Low temperature or inhibition of histone deacetylases can partly rescue ∆F508 CFTR cellular processing defects and function. A favourable change of ∆F508 CFTR protein-protein interactions was proposed as a mechanism of rescue; however, CFTR interactome dynamics during temperature shift and inhibition of histone deacetylases are unknown. Here we report the first comprehensive analysis of the CFTR and ∆F508 CFTR interactome and its dynamics during temperature shift and inhibition of histone deacetylases. By using a novel deep proteomic analysis method, we identify 638 individual high-confidence CFTR interactors and discover a ∆F508 deletion-specific interactome, which is extensively remodelled upon rescue. Detailed analysis of the interactome remodelling identifies key novel interactors, whose loss promote ∆F508 CFTR channel function in primary cystic fibrosis epithelia or which are critical for CFTR biogenesis. Our results demonstrate that global remodelling of ∆F508 CFTR interactions is crucial for rescue, and provide comprehensive insight into the molecular disease mechanisms of cystic fibrosis caused by deletion of F508.

  17. Construction and application of a protein and genetic interaction network (yeast interactome)

    PubMed Central

    Stuart, Gregory R.; Copeland, William C.; Strand, Micheline K.

    2009-01-01

    Cytoscape is a bioinformatic data analysis and visualization platform that is well-suited to the analysis of gene expression data. To facilitate the analysis of yeast microarray data using Cytoscape, we constructed an interaction network (interactome) using the curated interaction data available from the Saccharomyces Genome Database (www.yeastgenome.org) and the database of yeast transcription factors at YEASTRACT (www.yeastract.com). These data were formatted and imported into Cytoscape using semi-automated methods, including Linux-based scripts, that simplified the process while minimizing the introduction of processing errors. The methods described for the construction of this yeast interactome are generally applicable to the construction of any interactome. Using Cytoscape, we illustrate the use of this interactome through the analysis of expression data from a recent yeast diauxic shift experiment. We also report and briefly describe the complex associations among transcription factors that result in the regulation of thousands of genes through coordinated changes in expression of dozens of transcription factors. These cells are thus able to sensitively regulate cellular metabolism in response to changes in genetic or environmental conditions through relatively small changes in the expression of large numbers of genes, affecting the entire yeast metabolome. PMID:19273534

  18. Construction and application of a protein and genetic interaction network (yeast interactome).

    PubMed

    Stuart, Gregory R; Copeland, William C; Strand, Micheline K

    2009-04-01

    Cytoscape is a bioinformatic data analysis and visualization platform that is well-suited to the analysis of gene expression data. To facilitate the analysis of yeast microarray data using Cytoscape, we constructed an interaction network (interactome) using the curated interaction data available from the Saccharomyces Genome Database (www.yeastgenome.org) and the database of yeast transcription factors at YEASTRACT (www.yeastract.com). These data were formatted and imported into Cytoscape using semi-automated methods, including Linux-based scripts, that simplified the process while minimizing the introduction of processing errors. The methods described for the construction of this yeast interactome are generally applicable to the construction of any interactome. Using Cytoscape, we illustrate the use of this interactome through the analysis of expression data from a recent yeast diauxic shift experiment. We also report and briefly describe the complex associations among transcription factors that result in the regulation of thousands of genes through coordinated changes in expression of dozens of transcription factors. These cells are thus able to sensitively regulate cellular metabolism in response to changes in genetic or environmental conditions through relatively small changes in the expression of large numbers of genes, affecting the entire yeast metabolome.

  19. How much of the human protein interactome remains to be mapped?

    PubMed

    Vidal, Marc

    2016-05-10

    Using systematic approaches, a high-quality reference map of the human protein-protein interactome is within reach. Such a reference will help researchers connect genomic data to cellular phenotypes and enable full exploitation of the output of the genomic revolution for biomedical applications.

  20. Cross-species protein interactome mapping reveals species-specific wiring of stress response pathways.

    PubMed

    Das, Jishnu; Vo, Tommy V; Wei, Xiaomu; Mellor, Joseph C; Tong, Virginia; Degatano, Andrew G; Wang, Xiujuan; Wang, Lihua; Cordero, Nicolas A; Kruer-Zerhusen, Nathan; Matsuyama, Akihisa; Pleiss, Jeffrey A; Lipkin, Steven M; Yoshida, Minoru; Roth, Frederick P; Yu, Haiyuan

    2013-05-21

    The fission yeast Schizosaccharomyces pombe has more metazoan-like features than the budding yeast Saccharomyces cerevisiae, yet it has similarly facile genetics. We present a large-scale verified binary protein-protein interactome network, "StressNet," based on high-throughput yeast two-hybrid screens of interacting proteins classified as part of stress response and signal transduction pathways in S. pombe. We performed systematic, cross-species interactome mapping using StressNet and a protein interactome network of orthologous proteins in S. cerevisiae. With cross-species comparative network studies, we detected a previously unidentified component (Snr1) of the S. pombe mitogen-activated protein kinase Sty1 pathway. Coimmunoprecipitation experiments showed that Snr1 interacted with Sty1 and that deletion of snr1 increased the sensitivity of S. pombe cells to stress. Comparison of StressNet with the interactome network of orthologous proteins in S. cerevisiae showed that most of the interactions among these stress response and signaling proteins are not conserved between species but are "rewired"; orthologous proteins have different binding partners in both species. In particular, transient interactions connecting proteins in different functional modules were more likely to be rewired than conserved. By directly testing interactions between proteins in one yeast species and their corresponding binding partners in the other yeast species with yeast two-hybrid assays, we found that about half of the interactions that are traditionally considered "conserved" form modified interaction interfaces that may potentially accommodate novel functions. PMID:23695164

  1. A "candidate-interactome" aggregate analysis of genome-wide association data in multiple sclerosis.

    PubMed

    Mechelli, Rosella; Umeton, Renato; Policano, Claudia; Annibali, Viviana; Coarelli, Giulia; Ricigliano, Vito A G; Vittori, Danila; Fornasiero, Arianna; Buscarinu, Maria Chiara; Romano, Silvia; Salvetti, Marco; Ristori, Giovanni

    2013-01-01

    Though difficult, the study of gene-environment interactions in multifactorial diseases is crucial for interpreting the relevance of non-heritable factors and prevents from overlooking genetic associations with small but measurable effects. We propose a "candidate interactome" (i.e. a group of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated. The P values of all single nucleotide polymorphism mapping to a given interactome were obtained from the last genome-wide association study of the International Multiple Sclerosis Genetics Consortium & the Wellcome Trust Case Control Consortium, 2. The interaction between genotype and Epstein Barr virus emerges as relevant for multiple sclerosis etiology. However, in line with recent data on the coexistence of common and unique strategies used by viruses to perturb the human molecular system, also other viruses have a similar potential, though probably less relevant in epidemiological terms.

  2. InteractoMIX: a suite of computational tools to exploit interactomes in biological and clinical research.

    PubMed

    Poglayen, Daniel; Marín-López, Manuel Alejandro; Bonet, Jaume; Fornes, Oriol; Garcia-Garcia, Javier; Planas-Iglesias, Joan; Segura, Joan; Oliva, Baldo; Fernandez-Fuentes, Narcis

    2016-06-15

    Virtually all the biological processes that occur inside or outside cells are mediated by protein-protein interactions (PPIs). Hence, the charting and description of the PPI network, initially in organisms, the interactome, but more recently in specific tissues, is essential to fully understand cellular processes both in health and disease. The study of PPIs is also at the heart of renewed efforts in the medical and biotechnological arena in the quest of new therapeutic targets and drugs. Here, we present a mini review of 11 computational tools and resources tools developed by us to address different aspects of PPIs: from interactome level to their atomic 3D structural details. We provided details on each specific resource, aims and purpose and compare with equivalent tools in the literature. All the tools are presented in a centralized, one-stop, web site: InteractoMIX (http://interactomix.com). PMID:27284060

  3. E-cadherin interactome complexity and robustness resolved by quantitative proteomics

    PubMed Central

    Guo, Zhenhuan; Neilson, Lisa J; Zhong, Hang; Murray, Paul S; Rao, Megha Vaman; Zanivan, Sara; Zaidel-Bar, Ronen

    2016-01-01

    E-cadherin-mediated cell-cell adhesion and signaling plays an essential role in development and maintenance of healthy epithelial tissues. Adhesiveness is conferred by cadherin extracellular domains, and is regulated by an assembly of adaptors and enzymes associated with the cytoplasmic tail. Here, we employed proximity biotinylation and quantitative proteomics to isolate and identify 612 proteins in the vicinity of E-cadherin’s cytoplasmic tail. We used a structure-informed database of protein-protein interactions to construct the most comprehensive E-cadherin interactome to date, containing 89 known E-cadhesome components and 346 novel proteins. Moreover, through cloning and expression of GFP-tagged fusion proteins we localized 26 of the novel proteins to adherens junctions. Finally, employing calcium depletion and myosin inhibition we show the E-cadherin interactome to be remarkably robust to perturbation and essentially independent of cell-cell junctions or actomyosin contractility. PMID:25468996

  4. Proteomics, metabolomics, and protein interactomics in the characterization of the molecular features of major depressive disorder.

    PubMed

    Martins-de-Souza, Daniel

    2014-03-01

    Omics technologies emerged as complementary strategies to genomics in the attempt to understand human illnesses. In general, proteomics technologies emerged earlier than those of metabolomics for major depressive disorder (MDD) research, but both are driven by the identification of proteins and/or metabolites that can delineate a comprehensive characterization of MDD's molecular mechanisms, as well as lead to the identification of biomarker candidates of all types-prognosis, diagnosis, treatment, and patient stratification. Also, one can explore protein and metabolite interactomes in order to pinpoint additional molecules associated with the disease that had not been picked up initially. Here, results and methodological aspects of MDD research using proteomics, metabolomics, and protein interactomics are reviewed, focusing on human samples.

  5. Comparative interactomics analysis of different ALS-associated proteins identifies converging molecular pathways.

    PubMed

    Blokhuis, Anna M; Koppers, Max; Groen, Ewout J N; van den Heuvel, Dianne M A; Dini Modigliani, Stefano; Anink, Jasper J; Fumoto, Katsumi; van Diggelen, Femke; Snelting, Anne; Sodaar, Peter; Verheijen, Bert M; Demmers, Jeroen A A; Veldink, Jan H; Aronica, Eleonora; Bozzoni, Irene; den Hertog, Jeroen; van den Berg, Leonard H; Pasterkamp, R Jeroen

    2016-08-01

    Amyotrophic lateral sclerosis (ALS) is a devastating neurological disease with no effective treatment available. An increasing number of genetic causes of ALS are being identified, but how these genetic defects lead to motor neuron degeneration and to which extent they affect common cellular pathways remains incompletely understood. To address these questions, we performed an interactomic analysis to identify binding partners of wild-type (WT) and ALS-associated mutant versions of ATXN2, C9orf72, FUS, OPTN, TDP-43 and UBQLN2 in neuronal cells. This analysis identified several known but also many novel binding partners of these proteins. Interactomes of WT and mutant ALS proteins were very similar except for OPTN and UBQLN2, in which mutations caused loss or gain of protein interactions. Several of the identified interactomes showed a high degree of overlap: shared binding partners of ATXN2, FUS and TDP-43 had roles in RNA metabolism; OPTN- and UBQLN2-interacting proteins were related to protein degradation and protein transport, and C9orf72 interactors function in mitochondria. To confirm that this overlap is important for ALS pathogenesis, we studied fragile X mental retardation protein (FMRP), one of the common interactors of ATXN2, FUS and TDP-43, in more detail in in vitro and in vivo model systems for FUS ALS. FMRP localized to mutant FUS-containing aggregates in spinal motor neurons and bound endogenous FUS in a direct and RNA-sensitive manner. Furthermore, defects in synaptic FMRP mRNA target expression, neuromuscular junction integrity, and motor behavior caused by mutant FUS in zebrafish embryos, could be rescued by exogenous FMRP expression. Together, these results show that interactomics analysis can provide crucial insight into ALS disease mechanisms and they link FMRP to motor neuron dysfunction caused by FUS mutations.

  6. Computer vision profiling of neurite outgrowth dynamics reveals spatiotemporal modularity of Rho GTPase signaling

    PubMed Central

    Fusco, Ludovico; Lefort, Riwal; Smith, Kevin; Benmansour, Fethallah; Gonzalez, German; Barillari, Caterina; Rinn, Bernd; Fleuret, Francois; Fua, Pascal

    2016-01-01

    Rho guanosine triphosphatases (GTPases) control the cytoskeletal dynamics that power neurite outgrowth. This process consists of dynamic neurite initiation, elongation, retraction, and branching cycles that are likely to be regulated by specific spatiotemporal signaling networks, which cannot be resolved with static, steady-state assays. We present NeuriteTracker, a computer-vision approach to automatically segment and track neuronal morphodynamics in time-lapse datasets. Feature extraction then quantifies dynamic neurite outgrowth phenotypes. We identify a set of stereotypic neurite outgrowth morphodynamic behaviors in a cultured neuronal cell system. Systematic RNA interference perturbation of a Rho GTPase interactome consisting of 219 proteins reveals a limited set of morphodynamic phenotypes. As proof of concept, we show that loss of function of two distinct RhoA-specific GTPase-activating proteins (GAPs) leads to opposite neurite outgrowth phenotypes. Imaging of RhoA activation dynamics indicates that both GAPs regulate different spatiotemporal Rho GTPase pools, with distinct functions. Our results provide a starting point to dissect spatiotemporal Rho GTPase signaling networks that regulate neurite outgrowth. PMID:26728857

  7. Spatiotemporal drought forecasting using nonlinear models

    NASA Astrophysics Data System (ADS)

    Vasiliades, Lampros; Loukas, Athanasios

    2010-05-01

    Spatiotemporal data mining is the extraction of unknown and implicit knowledge, structures, spatiotemporal relationships, or patterns not explicitly stored in spatiotemporal databases. As one of data mining techniques, forecasting is widely used to predict the unknown future based upon the patterns hidden in the current and past data. In order to achieve spatiotemporal forecasting, some mature analysis tools, e.g., time series and spatial statistics are extended to the spatial dimension and the temporal dimension, respectively. Drought forecasting plays an important role in the planning and management of natural resources and water resource systems in a river basin. Early and timelines forecasting of a drought event can help to take proactive measures and set out drought mitigation strategies to alleviate the impacts of drought. Despite the widespread application of nonlinear mathematical models, comparative studies on spatiotemporal drought forecasting using different models are still a huge task for modellers. This study uses a promising approach, the Gamma Test (GT), to select the input variables and the training data length, so that the trial and error workload could be greatly reduced. The GT enables to quickly evaluate and estimate the best mean squared error that can be achieved by a smooth model on any unseen data for a given selection of inputs, prior to model construction. The GT is applied to forecast droughts using monthly Standardized Precipitation Index (SPI) timeseries at multiple timescales in several precipitation stations at Pinios river basin in Thessaly region, Greece. Several nonlinear models have been developed efficiently, with the aid of the GT, for 1-month up to 12-month ahead forecasting. Several temporal and spatial statistical indices were considered for the performance evaluation of the models. The predicted results show reasonably good agreement with the actual data for short lead times, whereas the forecasting accuracy decreases with

  8. A Flexible Spatio-Temporal Model for Air Pollution with Spatial and Spatio-Temporal Covariates

    PubMed Central

    Lindström, Johan; Szpiro, Adam A; Sampson, Paul D; Oron, Assaf P; Richards, Mark; Larson, Tim V; Sheppard, Lianne

    2013-01-01

    The development of models that provide accurate spatio-temporal predictions of ambient air pollution at small spatial scales is of great importance for the assessment of potential health effects of air pollution. Here we present a spatio-temporal framework that predicts ambient air pollution by combining data from several different monitoring networks and deterministic air pollution model(s) with geographic information system (GIS) covariates. The model presented in this paper has been implemented in an R package, SpatioTemporal, available on CRAN. The model is used by the EPA funded Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) to produce estimates of ambient air pollution; MESA Air uses the estimates to investigate the relationship between chronic exposure to air pollution and cardiovascular disease. In this paper we use the model to predict long-term average concentrations of NOx in the Los Angeles area during a ten year period. Predictions are based on measurements from the EPA Air Quality System, MESA Air specific monitoring, and output from a source dispersion model for traffic related air pollution (Caline3QHCR). Accuracy in predicting long-term average concentrations is evaluated using an elaborate cross-validation setup that accounts for a sparse spatio-temporal sampling pattern in the data, and adjusts for temporal effects. The predictive ability of the model is good with cross-validated R2 of approximately 0.7 at subject sites. Replacing four geographic covariate indicators of traffic density with the Caline3QHCR dispersion model output resulted in very similar prediction accuracy from a more parsimonious and more interpretable model. Adding traffic-related geographic covariates to the model that included Caline3QHCR did not further improve the prediction accuracy. PMID:25264424

  9. Spatiotemporal multipartite entanglement

    SciTech Connect

    Kolobov, Mikhail I.; Patera, Giuseppe

    2011-05-15

    In this Rapid Communication, we propose, following the spirit of quantum imaging, to generalize the theory of multipartite entanglement for the continuous-variable Gaussian states by considering, instead of the global covariance matrix, the local correlation matrix at two different spatiotemporal points ({rho}-vector,t) and ({rho}-vector{sup '},t{sup '}), with {rho}-vector being the transverse coordinate. Our approach makes it possible to introduce the characteristic spatial length and the characteristic time of the multipartite entanglement, which in general depend on the number of 'parties' in the system. As an example, we consider tripartite entanglement in spontaneous parametric down-conversion with a spatially structured pump. We investigate spatiotemporal properties of such entanglement and calculate its characteristic spatial length and time.

  10. Comparative analysis of nuclear estrogen receptor alpha and beta interactomes in breast cancer cells.

    PubMed

    Nassa, Giovanni; Tarallo, Roberta; Guzzi, Pietro H; Ferraro, Lorenzo; Cirillo, Francesca; Ravo, Maria; Nola, Ernesto; Baumann, Marc; Nyman, Tuula A; Cannataro, Mario; Ambrosino, Concetta; Weisz, Alessandro

    2011-03-01

    Estrogen Receptor alpha and beta (ER-α and -β) are members of the nuclear receptor family of transcriptional regulators with distinct roles in mediating estrogen dependent breast cancer cell growth and differentiation. Following activation by the hormone, these proteins undergo conformation changes and accumulate in the nucleus, where they bind to chromatin at regulatory sites as homo- and/or heterodimers and assemble in large multiprotein complexes. Although the two ERs share a conserved structure, they exert specific and distinct functional roles in normal and transformed mammary epithelial cells and other cell types. To investigate the molecular bases of such differences, we performed a comparative computational analysis of the nuclear interactomes of the two ER subtypes, exploiting two datasets of receptor interacting proteins identified in breast cancer cell nuclei by Tandem Affinity Purification for their ability to associate in vivo with ligand-activated ER-α and/or ER-β. These datasets comprise 498 proteins, of which only 70 are common to both ERs, suggesting that differences in the nature of the two ER interactomes are likely to sustain the distinct roles of the two receptor subtypes. Functional characterization of the two interactomes and their topological analysis, considering node degree and closeness of the networks, confirmed this possibility. Indeed, clustering and network dissection highlighted the presence of distinct and ER subtype-specific subnetworks endowed with defined functions. Altogether, these data provide new insights on the protein-protein interaction networks controlled by ER-α and -β that mediate their ability to transduce estrogen signaling in breast cancer cells. PMID:21173974

  11. Investigation of PARP-1, PARP-2, and PARG interactomes by affinity-purification mass spectrometry

    PubMed Central

    2010-01-01

    Background Poly(ADP-ribose) polymerases (PARPs) catalyze the formation of poly(ADP-ribose) (pADPr), a post-translational modification involved in several important biological processes, namely surveillance of genome integrity, cell cycle progression, initiation of the DNA damage response, apoptosis, and regulation of transcription. Poly(ADP-ribose) glycohydrolase (PARG), on the other hand, catabolizes pADPr and thereby accounts for the transient nature of poly(ADP-ribosyl)ation. Our investigation of the interactomes of PARP-1, PARP-2, and PARG by affinity-purification mass spectrometry (AP-MS) aimed, on the one hand, to confirm current knowledge on these interactomes and, on the other hand, to discover new protein partners which could offer insights into PARPs and PARG functions. Results PARP-1, PARP-2, and PARG were immunoprecipitated from human cells, and pulled-down proteins were separated by gel electrophoresis prior to in-gel trypsin digestion. Peptides were identified by tandem mass spectrometry. Our AP-MS experiments resulted in the identifications of 179 interactions, 139 of which are novel interactions. Gene Ontology analysis of the identified protein interactors points to five biological processes in which PARP-1, PARP-2 and PARG may be involved: RNA metabolism for PARP-1, PARP-2 and PARG; DNA repair and apoptosis for PARP-1 and PARP-2; and glycolysis and cell cycle for PARP-1. Conclusions This study reveals several novel protein partners for PARP-1, PARP-2 and PARG. It provides a global view of the interactomes of these proteins as well as a roadmap to establish the systems biology of poly(ADP-ribose) metabolism. PMID:20388209

  12. Neuregulin 1-erbB4 pathway in schizophrenia: From genes to an interactome.

    PubMed

    Banerjee, Anamika; Macdonald, Mathew L; Borgmann-Winter, Karin E; Hahn, Chang-Gyu

    2010-09-30

    Recently identified candidate susceptibility genes for schizophrenia are likely to play, important roles in the pathophysiology of the illness. It is also clear, however, that the etiologic, contribution of these genes is not only via their own functions but also through interactions with other, genes and environmental factors. Genetic, transgenic and postmortem brain studies support a, potential role for NRG1-erbB4 signaling in schizophrenia. Embedded in the results of these studies, however, are clues to the notion that NRG1-erbB4 signaling does not act alone but in conjunction with, other pathways. This article aims to re-evaluate the evidence for the role of neuregulin 1 (NRG1)-erbB4 signaling in schizophrenia by focusing on its interactions with other candidate susceptibility, pathways. In addition, we consider molecular substrates upon which the NRG1-erbB4 and other, candidate pathways converge contributing to susceptibility for the illness (schizophrenia interactome). Glutamatergic signaling can be an interesting candidate for schizophrenia interactome. Schizophrenia is associated with NMDA receptor hypofunction and moreover, several susceptibility genes for, schizophrenia converge on NMDA receptor signaling. These candidate genes influence NMDA receptor, signaling via diverse mechanisms, yet all eventually impact on protein composition of NMDA receptor, complexes. Likewise, the protein associations in the receptor complexes can themselves modulate, signaling molecules of candidate genes and their pathways. Therefore, protein-protein interactions in the NMDA receptor complexes can mediate reciprocal interactions between NMDA receptor function, and susceptibility candidate pathways including NRG1-erbB4 signaling and thus can be a, schizophrenia interactome.

  13. Impaired autophagy and APP processing in Alzheimer's disease: The potential role of Beclin 1 interactome.

    PubMed

    Salminen, Antero; Kaarniranta, Kai; Kauppinen, Anu; Ojala, Johanna; Haapasalo, Annakaisa; Soininen, Hilkka; Hiltunen, Mikko

    2013-01-01

    The accumulation of amyloid-β-containing neuritic plaques and intracellular tau protein tangles are key histopathological hallmarks of Alzheimer's disease (AD). This type of pathology clearly indicates that the mechanisms of neuronal housekeeping and protein quality control are compromised in AD. There is mounting evidence that the autophagosome-lysosomal degradation is impaired, which could disturb the processing of APP and provoke AD pathology. Beclin 1 is a molecular platform assembling an interactome with stimulating and suppressive components which regulate the initiation of the autophagosome formation. Recent studies have indicated that the expression Beclin 1 is reduced in AD brain. Moreover, the deficiency of Beclin 1 in cultured neurons and transgenic mice provokes the deposition of amyloid-β peptides whereas its overexpression reduces the accumulation of amyloid-β. There are several potential mechanisms, which could inhibit the function of Beclin 1 interactome and thus impair autophagy and promote AD pathology. The mechanisms include (i) reduction of Beclin 1 expression or its increased proteolytic cleavage by caspases, (ii) sequestration of Beclin 1 to non-functional locations, such as tau tangles, (iii) formation of inhibitory complexes between Beclin 1 and antiapoptotic Bcl-2 proteins or inflammasomes, (iv) interaction of Beclin 1 with inhibitory neurovirulent proteins, e.g. herpex simplex ICP34.5, or (v) inhibition of the Beclin 1/Vps34 complex through the activation of CDK1 and CDK5. We will shortly introduce the function of Beclin 1 interactome in autophagy and phagocytosis, review the recent evidence indicating that Beclin 1 regulates autophagy and APP processing in AD, and finally examine the potential mechanisms through which Beclin 1 dysfunction could be involved in the pathogenesis of AD.

  14. Impaired autophagy and APP processing in Alzheimer's disease: The potential role of Beclin 1 interactome.

    PubMed

    Salminen, Antero; Kaarniranta, Kai; Kauppinen, Anu; Ojala, Johanna; Haapasalo, Annakaisa; Soininen, Hilkka; Hiltunen, Mikko

    2013-01-01

    The accumulation of amyloid-β-containing neuritic plaques and intracellular tau protein tangles are key histopathological hallmarks of Alzheimer's disease (AD). This type of pathology clearly indicates that the mechanisms of neuronal housekeeping and protein quality control are compromised in AD. There is mounting evidence that the autophagosome-lysosomal degradation is impaired, which could disturb the processing of APP and provoke AD pathology. Beclin 1 is a molecular platform assembling an interactome with stimulating and suppressive components which regulate the initiation of the autophagosome formation. Recent studies have indicated that the expression Beclin 1 is reduced in AD brain. Moreover, the deficiency of Beclin 1 in cultured neurons and transgenic mice provokes the deposition of amyloid-β peptides whereas its overexpression reduces the accumulation of amyloid-β. There are several potential mechanisms, which could inhibit the function of Beclin 1 interactome and thus impair autophagy and promote AD pathology. The mechanisms include (i) reduction of Beclin 1 expression or its increased proteolytic cleavage by caspases, (ii) sequestration of Beclin 1 to non-functional locations, such as tau tangles, (iii) formation of inhibitory complexes between Beclin 1 and antiapoptotic Bcl-2 proteins or inflammasomes, (iv) interaction of Beclin 1 with inhibitory neurovirulent proteins, e.g. herpex simplex ICP34.5, or (v) inhibition of the Beclin 1/Vps34 complex through the activation of CDK1 and CDK5. We will shortly introduce the function of Beclin 1 interactome in autophagy and phagocytosis, review the recent evidence indicating that Beclin 1 regulates autophagy and APP processing in AD, and finally examine the potential mechanisms through which Beclin 1 dysfunction could be involved in the pathogenesis of AD. PMID:23827971

  15. Ocean plankton. Determinants of community structure in the global plankton interactome.

    PubMed

    Lima-Mendez, Gipsi; Faust, Karoline; Henry, Nicolas; Decelle, Johan; Colin, Sébastien; Carcillo, Fabrizio; Chaffron, Samuel; Ignacio-Espinosa, J Cesar; Roux, Simon; Vincent, Flora; Bittner, Lucie; Darzi, Youssef; Wang, Jun; Audic, Stéphane; Berline, Léo; Bontempi, Gianluca; Cabello, Ana M; Coppola, Laurent; Cornejo-Castillo, Francisco M; d'Ovidio, Francesco; De Meester, Luc; Ferrera, Isabel; Garet-Delmas, Marie-José; Guidi, Lionel; Lara, Elena; Pesant, Stéphane; Royo-Llonch, Marta; Salazar, Guillem; Sánchez, Pablo; Sebastian, Marta; Souffreau, Caroline; Dimier, Céline; Picheral, Marc; Searson, Sarah; Kandels-Lewis, Stefanie; Gorsky, Gabriel; Not, Fabrice; Ogata, Hiroyuki; Speich, Sabrina; Stemmann, Lars; Weissenbach, Jean; Wincker, Patrick; Acinas, Silvia G; Sunagawa, Shinichi; Bork, Peer; Sullivan, Matthew B; Karsenti, Eric; Bowler, Chris; de Vargas, Colomban; Raes, Jeroen

    2015-05-22

    Species interaction networks are shaped by abiotic and biotic factors. Here, as part of the Tara Oceans project, we studied the photic zone interactome using environmental factors and organismal abundance profiles and found that environmental factors are incomplete predictors of community structure. We found associations across plankton functional types and phylogenetic groups to be nonrandomly distributed on the network and driven by both local and global patterns. We identified interactions among grazers, primary producers, viruses, and (mainly parasitic) symbionts and validated network-generated hypotheses using microscopy to confirm symbiotic relationships. We have thus provided a resource to support further research on ocean food webs and integrating biological components into ocean models.

  16. MitProNet: A knowledgebase and analysis platform of proteome, interactome and diseases for mammalian mitochondria.

    PubMed

    Wang, Jiabin; Yang, Jian; Mao, Song; Chai, Xiaoqiang; Hu, Yuling; Hou, Xugang; Tang, Yiheng; Bi, Cheng; Li, Xiao

    2014-01-01

    Mitochondrion plays a central role in diverse biological processes in most eukaryotes, and its dysfunctions are critically involved in a large number of diseases and the aging process. A systematic identification of mitochondrial proteomes and characterization of functional linkages among mitochondrial proteins are fundamental in understanding the mechanisms underlying biological functions and human diseases associated with mitochondria. Here we present a database MitProNet which provides a comprehensive knowledgebase for mitochondrial proteome, interactome and human diseases. First an inventory of mammalian mitochondrial proteins was compiled by widely collecting proteomic datasets, and the proteins were classified by machine learning to achieve a high-confidence list of mitochondrial proteins. The current version of MitProNet covers 1124 high-confidence proteins, and the remainders were further classified as middle- or low-confidence. An organelle-specific network of functional linkages among mitochondrial proteins was then generated by integrating genomic features encoded by a wide range of datasets including genomic context, gene expression profiles, protein-protein interactions, functional similarity and metabolic pathways. The functional-linkage network should be a valuable resource for the study of biological functions of mitochondrial proteins and human mitochondrial diseases. Furthermore, we utilized the network to predict candidate genes for mitochondrial diseases using prioritization algorithms. All proteins, functional linkages and disease candidate genes in MitProNet were annotated according to the information collected from their original sources including GO, GEO, OMIM, KEGG, MIPS, HPRD and so on. MitProNet features a user-friendly graphic visualization interface to present functional analysis of linkage networks. As an up-to-date database and analysis platform, MitProNet should be particularly helpful in comprehensive studies of complicated

  17. A core of kinase-regulated interactomes defines the neoplastic MDSC lineage

    PubMed Central

    Zudaire, Isabel; Liechtenstein, Therese; Arasanz, Hugo; Lozano, Teresa; Casares, Noelia; Chaikuad, Apirat; Knapp, Stefan; Guerrero-Setas, David; Escors, David; Kochan, Grazyna; Santamaría, Enrique

    2015-01-01

    Myeloid-derived suppressor cells (MDSCs) differentiate from bone marrow precursors, expand in cancer-bearing hosts and accelerate tumor progression. MDSCs have become attractive therapeutic targets, as their elimination strongly enhances anti-neoplastic treatments. Here, immature myeloid dendritic cells (DCs), MDSCs modeling tumor-infiltrating subsets or modeling non-cancerous (NC)-MDSCs were compared by in-depth quantitative proteomics. We found that neoplastic MDSCs differentially expressed a core of kinases which controlled lineage-specific (PI3K-AKT and SRC kinases) and cancer-induced (ERK and PKC kinases) protein interaction networks (interactomes). These kinases contributed to some extent to myeloid differentiation. However, only AKT and ERK specifically drove MDSC differentiation from myeloid precursors. Interfering with AKT and ERK with selective small molecule inhibitors or shRNAs selectively hampered MDSC differentiation and viability. Thus, we provide compelling evidence that MDSCs constitute a distinct myeloid lineage distinguished by a “kinase signature” and well-defined interactomes. Our results define new opportunities for the development of anti-cancer treatments targeting these tumor-promoting immune cells. PMID:26320174

  18. A Proteome-wide Fission Yeast Interactome Reveals Network Evolution Principles from Yeasts to Human.

    PubMed

    Vo, Tommy V; Das, Jishnu; Meyer, Michael J; Cordero, Nicolas A; Akturk, Nurten; Wei, Xiaomu; Fair, Benjamin J; Degatano, Andrew G; Fragoza, Robert; Liu, Lisa G; Matsuyama, Akihisa; Trickey, Michelle; Horibata, Sachi; Grimson, Andrew; Yamano, Hiroyuki; Yoshida, Minoru; Roth, Frederick P; Pleiss, Jeffrey A; Xia, Yu; Yu, Haiyuan

    2016-01-14

    Here, we present FissionNet, a proteome-wide binary protein interactome for S. pombe, comprising 2,278 high-quality interactions, of which ∼ 50% were previously not reported in any species. FissionNet unravels previously unreported interactions implicated in processes such as gene silencing and pre-mRNA splicing. We developed a rigorous network comparison framework that accounts for assay sensitivity and specificity, revealing extensive species-specific network rewiring between fission yeast, budding yeast, and human. Surprisingly, although genes are better conserved between the yeasts, S. pombe interactions are significantly better conserved in human than in S. cerevisiae. Our framework also reveals that different modes of gene duplication influence the extent to which paralogous proteins are functionally repurposed. Finally, cross-species interactome mapping demonstrates that coevolution of interacting proteins is remarkably prevalent, a result with important implications for studying human disease in model organisms. Overall, FissionNet is a valuable resource for understanding protein functions and their evolution.

  19. Targeted cross-linking-mass spectrometry determines vicinal interactomes within heterogeneous RNP complexes

    PubMed Central

    Trahan, Christian; Oeffinger, Marlene

    2016-01-01

    Proteomic and RNomic approaches have identified many components of different ribonucleoprotein particles (RNPs), yet still little is known about the organization and protein proximities within these heterogeneous and highly dynamic complexes. Here we describe a targeted cross-linking approach, which combines cross-linking from a known anchor site with affinity purification and mass spectrometry (MS) to identify the changing vicinity interactomes along RNP maturation pathways. Our method confines the reaction radius of a heterobifunctional cross-linker to a specific interaction surface, increasing the probability to capture low abundance conformations and transient vicinal interactors too infrequent for identification by traditional cross-linking-MS approaches, and determine protein proximities within RNPs. Applying the method to two conserved RNA-associated complexes in Saccharomyces cerevisae, the mRNA export receptor Mex67:Mtr2 and the pre-ribosomal Nop7 subcomplex, we identified dynamic vicinal interactomes within those complexes and along their changing pathway milieu. Our results therefore show that this method provides a new tool to study the changing spatial organization of heterogeneous dynamic RNP complexes. PMID:26657640

  20. Mapping RNA–RNA interactome and RNA structure in vivo by MARIO

    PubMed Central

    Nguyen, Tri C.; Cao, Xiaoyi; Yu, Pengfei; Xiao, Shu; Lu, Jia; Biase, Fernando H.; Sridhar, Bharat; Huang, Norman; Zhang, Kang; Zhong, Sheng

    2016-01-01

    The pervasive transcription of our genome presents a possibility of revealing new genomic functions by investigating RNA interactions. Current methods for mapping RNA–RNA interactions have to rely on an ‘anchor' protein or RNA and often require molecular perturbations. Here we present the MARIO (Mapping RNA interactome in vivo) technology to massively reveal RNA–RNA interactions from unperturbed cells. We mapped tens of thousands of endogenous RNA–RNA interactions from mouse embryonic stem cells and brain. We validated seven interactions by RNA antisense purification and one interaction using single-molecule RNA–FISH. The experimentally derived RNA interactome is a scale-free network, which is not expected from currently perceived promiscuity in RNA–RNA interactions. Base pairing is observed at the interacting regions between long RNAs, including transposon transcripts, suggesting a class of regulatory sequences acting in trans. In addition, MARIO data reveal thousands of intra-molecule interactions, providing in vivo data on high-order RNA structures. PMID:27338251

  1. Mapping transcription factor interactome networks using HaloTag protein arrays

    PubMed Central

    Yazaki, Junshi; Galli, Mary; Kim, Alice Y.; Nito, Kazumasa; Aleman, Fernando; Chang, Katherine N.; Quan, Rosa; Nguyen, Hien; Song, Liang; Alvarez, José M.; Huang, Shao-shan Carol; Chen, Huaming; Ramachandran, Niroshan; Altmann, Stefan; Gutiérrez, Rodrigo A.; Schroeder, Julian I.; Chory, Joanne; LaBaer, Joshua; Vidal, Marc; Braun, Pascal; Ecker, Joseph R.

    2016-01-01

    Protein microarrays enable investigation of diverse biochemical properties for thousands of proteins in a single experiment, an unparalleled capacity. Using a high-density system called HaloTag nucleic acid programmable protein array (HaloTag-NAPPA), we created high-density protein arrays comprising 12,000 Arabidopsis ORFs. We used these arrays to query protein–protein interactions for a set of 38 transcription factors and transcriptional regulators (TFs) that function in diverse plant hormone regulatory pathways. The resulting transcription factor interactome network, TF-NAPPA, contains thousands of novel interactions. Validation in a benchmarked in vitro pull-down assay revealed that a random subset of TF-NAPPA validated at the same rate of 64% as a positive reference set of literature-curated interactions. Moreover, using a bimolecular fluorescence complementation (BiFC) assay, we confirmed in planta several interactions of biological interest and determined the interaction localizations for seven pairs. The application of HaloTag-NAPPA technology to plant hormone signaling pathways allowed the identification of many novel transcription factor–protein interactions and led to the development of a proteome-wide plant hormone TF interactome network. PMID:27357687

  2. Mapping transcription factor interactome networks using HaloTag protein arrays.

    PubMed

    Yazaki, Junshi; Galli, Mary; Kim, Alice Y; Nito, Kazumasa; Aleman, Fernando; Chang, Katherine N; Carvunis, Anne-Ruxandra; Quan, Rosa; Nguyen, Hien; Song, Liang; Alvarez, José M; Huang, Shao-Shan Carol; Chen, Huaming; Ramachandran, Niroshan; Altmann, Stefan; Gutiérrez, Rodrigo A; Hill, David E; Schroeder, Julian I; Chory, Joanne; LaBaer, Joshua; Vidal, Marc; Braun, Pascal; Ecker, Joseph R

    2016-07-19

    Protein microarrays enable investigation of diverse biochemical properties for thousands of proteins in a single experiment, an unparalleled capacity. Using a high-density system called HaloTag nucleic acid programmable protein array (HaloTag-NAPPA), we created high-density protein arrays comprising 12,000 Arabidopsis ORFs. We used these arrays to query protein-protein interactions for a set of 38 transcription factors and transcriptional regulators (TFs) that function in diverse plant hormone regulatory pathways. The resulting transcription factor interactome network, TF-NAPPA, contains thousands of novel interactions. Validation in a benchmarked in vitro pull-down assay revealed that a random subset of TF-NAPPA validated at the same rate of 64% as a positive reference set of literature-curated interactions. Moreover, using a bimolecular fluorescence complementation (BiFC) assay, we confirmed in planta several interactions of biological interest and determined the interaction localizations for seven pairs. The application of HaloTag-NAPPA technology to plant hormone signaling pathways allowed the identification of many novel transcription factor-protein interactions and led to the development of a proteome-wide plant hormone TF interactome network.

  3. Interactome Mapping Reveals the Evolutionary History of the Nuclear Pore Complex

    PubMed Central

    Obado, Samson O.; Brillantes, Marc; Uryu, Kunihiro; Zhang, Wenzhu; Ketaren, Natalia E.; Chait, Brian T.; Field, Mark C.; Rout, Michael P.

    2016-01-01

    The nuclear pore complex (NPC) is responsible for nucleocytoplasmic transport and constitutes a hub for control of gene expression. The components of NPCs from several eukaryotic lineages have been determined, but only the yeast and vertebrate NPCs have been extensively characterized at the quaternary level. Significantly, recent evidence indicates that compositional similarity does not necessarily correspond to homologous architecture between NPCs from different taxa. To address this, we describe the interactome of the trypanosome NPC, a representative, highly divergent eukaryote. We identify numerous new NPC components and report an exhaustive interactome, allowing assignment of trypanosome nucleoporins to discrete NPC substructures. Remarkably, despite retaining similar protein composition, there are exceptional architectural dissimilarities between opisthokont (yeast and vertebrates) and excavate (trypanosomes) NPCs. Whilst elements of the inner core are conserved, numerous peripheral structures are highly divergent, perhaps reflecting requirements to interface with divergent nuclear and cytoplasmic functions. Moreover, the trypanosome NPC has almost complete nucleocytoplasmic symmetry, in contrast to the opisthokont NPC; this may reflect divergence in RNA export processes at the NPC cytoplasmic face, as we find evidence supporting Ran-dependent mRNA export in trypanosomes, similar to protein transport. We propose a model of stepwise acquisition of nucleocytoplasmic mechanistic complexity and demonstrate that detailed dissection of macromolecular complexes provides fuller understanding of evolutionary processes. PMID:26891179

  4. Interactome-transcriptome analysis discovers signatures complementary to GWAS Loci of Type 2 Diabetes

    PubMed Central

    Li, Jing-Woei; Lee, Heung-Man; Wang, Ying; Tong, Amy Hin-Yan; Yip, Kevin Y.; Tsui, Stephen Kwok-Wing; Lok, Si; Ozaki, Risa; Luk, Andrea O; Kong, Alice P. S.; So, Wing-Yee; Ma, Ronald C. W.; Chan, Juliana C. N.; Chan, Ting-Fung

    2016-01-01

    Protein interactions play significant roles in complex diseases. We analyzed peripheral blood mononuclear cells (PBMC) transcriptome using a multi-method strategy. We constructed a tissue-specific interactome (T2Di) and identified 420 molecular signatures associated with T2D-related comorbidity and symptoms, mainly implicated in inflammation, adipogenesis, protein phosphorylation and hormonal secretion. Apart from explaining the residual associations within the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) study, the T2Di signatures were enriched in pathogenic cell type-specific regulatory elements related to fetal development, immunity and expression quantitative trait loci (eQTL). The T2Di revealed a novel locus near a well-established GWAS loci AChE, in which SRRT interacts with JAZF1, a T2D-GWAS gene implicated in pancreatic function. The T2Di also included known anti-diabetic drug targets (e.g. PPARD, MAOB) and identified possible druggable targets (e.g. NCOR2, PDGFR). These T2Di signatures were validated by an independent computational method, and by expression data of pancreatic islet, muscle and liver with some of the signatures (CEBPB, SREBF1, MLST8, SRF, SRRT and SLC12A9) confirmed in PBMC from an independent cohort of 66 T2D and 66 control subjects. By combining prior knowledge and transcriptome analysis, we have constructed an interactome to explain the multi-layered regulatory pathways in T2D. PMID:27752041

  5. Mapping transcription factor interactome networks using HaloTag protein arrays.

    PubMed

    Yazaki, Junshi; Galli, Mary; Kim, Alice Y; Nito, Kazumasa; Aleman, Fernando; Chang, Katherine N; Carvunis, Anne-Ruxandra; Quan, Rosa; Nguyen, Hien; Song, Liang; Alvarez, José M; Huang, Shao-Shan Carol; Chen, Huaming; Ramachandran, Niroshan; Altmann, Stefan; Gutiérrez, Rodrigo A; Hill, David E; Schroeder, Julian I; Chory, Joanne; LaBaer, Joshua; Vidal, Marc; Braun, Pascal; Ecker, Joseph R

    2016-07-19

    Protein microarrays enable investigation of diverse biochemical properties for thousands of proteins in a single experiment, an unparalleled capacity. Using a high-density system called HaloTag nucleic acid programmable protein array (HaloTag-NAPPA), we created high-density protein arrays comprising 12,000 Arabidopsis ORFs. We used these arrays to query protein-protein interactions for a set of 38 transcription factors and transcriptional regulators (TFs) that function in diverse plant hormone regulatory pathways. The resulting transcription factor interactome network, TF-NAPPA, contains thousands of novel interactions. Validation in a benchmarked in vitro pull-down assay revealed that a random subset of TF-NAPPA validated at the same rate of 64% as a positive reference set of literature-curated interactions. Moreover, using a bimolecular fluorescence complementation (BiFC) assay, we confirmed in planta several interactions of biological interest and determined the interaction localizations for seven pairs. The application of HaloTag-NAPPA technology to plant hormone signaling pathways allowed the identification of many novel transcription factor-protein interactions and led to the development of a proteome-wide plant hormone TF interactome network. PMID:27357687

  6. A Proteome-wide Fission Yeast Interactome Reveals Network Evolution Principles from Yeasts to Human.

    PubMed

    Vo, Tommy V; Das, Jishnu; Meyer, Michael J; Cordero, Nicolas A; Akturk, Nurten; Wei, Xiaomu; Fair, Benjamin J; Degatano, Andrew G; Fragoza, Robert; Liu, Lisa G; Matsuyama, Akihisa; Trickey, Michelle; Horibata, Sachi; Grimson, Andrew; Yamano, Hiroyuki; Yoshida, Minoru; Roth, Frederick P; Pleiss, Jeffrey A; Xia, Yu; Yu, Haiyuan

    2016-01-14

    Here, we present FissionNet, a proteome-wide binary protein interactome for S. pombe, comprising 2,278 high-quality interactions, of which ∼ 50% were previously not reported in any species. FissionNet unravels previously unreported interactions implicated in processes such as gene silencing and pre-mRNA splicing. We developed a rigorous network comparison framework that accounts for assay sensitivity and specificity, revealing extensive species-specific network rewiring between fission yeast, budding yeast, and human. Surprisingly, although genes are better conserved between the yeasts, S. pombe interactions are significantly better conserved in human than in S. cerevisiae. Our framework also reveals that different modes of gene duplication influence the extent to which paralogous proteins are functionally repurposed. Finally, cross-species interactome mapping demonstrates that coevolution of interacting proteins is remarkably prevalent, a result with important implications for studying human disease in model organisms. Overall, FissionNet is a valuable resource for understanding protein functions and their evolution. PMID:26771498

  7. Recent advances in large-scale protein interactome mapping

    PubMed Central

    Mehta, Virja; Trinkle-Mulcahy, Laura

    2016-01-01

    Protein-protein interactions (PPIs) underlie most, if not all, cellular functions. The comprehensive mapping of these complex networks of stable and transient associations thus remains a key goal, both for systems biology-based initiatives (where it can be combined with other ‘omics’ data to gain a better understanding of functional pathways and networks) and for focused biological studies. Despite the significant challenges of such an undertaking, major strides have been made over the past few years. They include improvements in the computation prediction of PPIs and the literature curation of low-throughput studies of specific protein complexes, but also an increase in the deposition of high-quality data from non-biased high-throughput experimental PPI mapping strategies into publicly available databases. PMID:27158474

  8. Feature Selection, Flaring Size and Time-to-Flare Prediction Using Support Vector Regression, and Automated Prediction of Flaring Behavior Based on Spatio-Temporal Measures Using Hidden Markov Models

    NASA Astrophysics Data System (ADS)

    Al-Ghraibah, Amani

    Solar flares release stored magnetic energy in the form of radiation and can have significant detrimental effects on earth including damage to technological infrastructure. Recent work has considered methods to predict future flare activity on the basis of quantitative measures of the solar magnetic field. Accurate advanced warning of solar flare occurrence is an area of increasing concern and much research is ongoing in this area. Our previous work 111] utilized standard pattern recognition and classification techniques to determine (classify) whether a region is expected to flare within a predictive time window, using a Relevance Vector Machine (RVM) classification method. We extracted 38 features which describing the complexity of the photospheric magnetic field, the result classification metrics will provide the baseline against which we compare our new work. We find a true positive rate (TPR) of 0.8, true negative rate (TNR) of 0.7, and true skill score (TSS) of 0.49. This dissertation proposes three basic topics; the first topic is an extension to our previous work [111, where we consider a feature selection method to determine an appropriate feature subset with cross validation classification based on a histogram analysis of selected features. Classification using the top five features resulting from this analysis yield better classification accuracies across a large unbalanced dataset. In particular, the feature subsets provide better discrimination of the many regions that flare where we find a TPR of 0.85, a TNR of 0.65 sightly lower than our previous work, and a TSS of 0.5 which has an improvement comparing with our previous work. In the second topic, we study the prediction of solar flare size and time-to-flare using support vector regression (SVR). When we consider flaring regions only, we find an average error in estimating flare size of approximately half a GOES class. When we additionally consider non-flaring regions, we find an increased average

  9. Dissecting spatio-temporal protein networks driving human heart development and related disorders.

    PubMed

    Lage, Kasper; Møllgård, Kjeld; Greenway, Steven; Wakimoto, Hiroko; Gorham, Joshua M; Workman, Christopher T; Bendsen, Eske; Hansen, Niclas T; Rigina, Olga; Roque, Francisco S; Wiese, Cornelia; Christoffels, Vincent M; Roberts, Amy E; Smoot, Leslie B; Pu, William T; Donahoe, Patricia K; Tommerup, Niels; Brunak, Søren; Seidman, Christine E; Seidman, Jonathan G; Larsen, Lars A

    2010-06-22

    Aberrant organ development is associated with a wide spectrum of disorders, from schizophrenia to congenital heart disease, but systems-level insight into the underlying processes is very limited. Using heart morphogenesis as general model for dissecting the functional architecture of organ development, we combined detailed phenotype information from deleterious mutations in 255 genes with high-confidence experimental interactome data, and coupled the results to thorough experimental validation. Hereby, we made the first systematic analysis of spatio-temporal protein networks driving many stages of a developing organ identifying several novel signaling modules. Our results show that organ development relies on surprisingly few, extensively recycled, protein modules that integrate into complex higher-order networks. This design allows the formation of a complicated organ using simple building blocks, and suggests how mutations in the same genes can lead to diverse phenotypes. We observe a striking temporal correlation between organ complexity and the number of discrete functional modules coordinating morphogenesis. Our analysis elucidates the organization and composition of spatio-temporal protein networks that drive the formation of organs, which in the future may lay the foundation of novel approaches in treatments, diagnostics, and regenerative medicine. PMID:20571530

  10. Grouping Annotations on the Subcellular Layered Interactome Demonstrates Enhanced Autophagy Activity in a Recurrent Experimental Autoimmune Uveitis T Cell Line

    PubMed Central

    Zhao, Yu; Dong, Yucui; Ju, Huanyu; Yang, Jinfeng; Sun, Jianhua; Li, Xia; Ren, Huan

    2014-01-01

    Human uveitis is a type of T cell-mediated autoimmune disease that often shows relapse–remitting courses affecting multiple biological processes. As a cytoplasmic process, autophagy has been seen as an adaptive response to cell death and survival, yet the link between autophagy and T cell-mediated autoimmunity is not certain. In this study, based on the differentially expressed genes (GSE19652) between the recurrent versus monophasic T cell lines, whose adoptive transfer to susceptible animals may result in respective recurrent or monophasic uveitis, we proposed grouping annotations on a subcellular layered interactome framework to analyze the specific bioprocesses that are linked to the recurrence of T cell autoimmunity. That is, the subcellular layered interactome was established by the Cytoscape and Cerebral plugin based on differential expression, global interactome, and subcellular localization information. Then, the layered interactomes were grouping annotated by the ClueGO plugin based on Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases. The analysis showed that significant bioprocesses with autophagy were orchestrated in the cytoplasmic layered interactome and that mTOR may have a regulatory role in it. Furthermore, by setting up recurrent and monophasic uveitis in Lewis rats, we confirmed by transmission electron microscopy that, in comparison to the monophasic disease, recurrent uveitis in vivo showed significantly increased autophagy activity and extended lymphocyte infiltration to the affected retina. In summary, our framework methodology is a useful tool to disclose specific bioprocesses and molecular targets that can be attributed to a certain disease. Our results indicated that targeted inhibition of autophagy pathways may perturb the recurrence of uveitis. PMID:25116327

  11. Spatiotemporal characteristics of pandemic influenza

    PubMed Central

    2014-01-01

    Background Prediction of timing for the onset and peak of an influenza pandemic is of vital importance for preventive measures. In order to identify common spatiotemporal patterns and climate influences for pandemics in Sweden we have studied the propagation in space and time of A(H1N1)pdm09 (10,000 laboratory verified cases), the Asian Influenza 1957–1958 (275,000 cases of influenza-like illness (ILI), reported by local physicians) and the Russian Influenza 1889–1890 (32,600 ILI cases reported by physicians shortly after the end of the outbreak). Methods All cases were geocoded and analysed in space and time. Animated video sequences, showing weekly incidence per municipality and its geographically weighted mean (GWM), were created to depict and compare the spread of the pandemics. Daily data from 1957–1958 on temperature and precipitation from 39 weather stations were collected and analysed with the case data to examine possible climatological effects on the influenza dissemination. Results The epidemic period lasted 11 weeks for the Russian Influenza, 10 weeks for the Asian Influenza and 9 weeks for the A(H1N1)pdm09. The Russian Influenza arrived in Sweden during the winter and was immediately disseminated, while both the Asian Influenza and the A(H1N1)pdm09 arrived during the spring. They were seeded over the country during the summer, but did not peak until October-November. The weekly GWM of the incidence moved along a line from southwest to northeast for the Russian and Asian Influenza but northeast to southwest for the A(H1N1)pdm09. The local epidemic periods of the Asian Influenza were preceded by falling temperature in all but one of the locations analysed. Conclusions The power of spatiotemporal analysis and modeling for pandemic spread was clearly demonstrated. The epidemic period lasted approximately 10 weeks for all pandemics. None of the pandemics had its epidemic period before late autumn. The epidemic period of the Asian Influenza was

  12. Spatiotemporal chaos from bursting dynamics

    SciTech Connect

    Berenstein, Igal; De Decker, Yannick

    2015-08-14

    In this paper, we study the emergence of spatiotemporal chaos from mixed-mode oscillations, by using an extended Oregonator model. We show that bursting dynamics consisting of fast/slow mixed mode oscillations along a single attractor can lead to spatiotemporal chaotic dynamics, although the spatially homogeneous solution is itself non-chaotic. This behavior is observed far from the Hopf bifurcation and takes the form of a spatiotemporal intermittency where the system locally alternates between the fast and the slow phases of the mixed mode oscillations. We expect this form of spatiotemporal chaos to be generic for models in which one or several slow variables are coupled to activator-inhibitor type of oscillators.

  13. Modeling and characterization of disease associated subnetworks in the human interactome using machine learning

    PubMed Central

    Sam, Lee T.; Michailidis, George

    2009-01-01

    The availability of large-scale, genome-wide data about the molecular interactome of entire organisms has made possible new types of integrative studies, making use of rapidly accumulating knowledge of gene-disease associations. Previous studies have established the presence of functional biomodules in the molecular interaction network of living organisms, a number of which have been associated with the pathogenesis and progression of human disease. While a number of studies have examined the networks and biomodules associated with disease, the properties that contribute to the particular susceptibility of these subnetworks to disruptions leading to disease phenotypes have not been extensively studied. We take a machine learning approach to the characterization of these disease subnetworks associated with complex and single-gene diseases, taking into account both the biological roles of their constituent genes and topological properties of the networks they form. PMID:21347156

  14. Ocean plankton. Determinants of community structure in the global plankton interactome.

    PubMed

    Lima-Mendez, Gipsi; Faust, Karoline; Henry, Nicolas; Decelle, Johan; Colin, Sébastien; Carcillo, Fabrizio; Chaffron, Samuel; Ignacio-Espinosa, J Cesar; Roux, Simon; Vincent, Flora; Bittner, Lucie; Darzi, Youssef; Wang, Jun; Audic, Stéphane; Berline, Léo; Bontempi, Gianluca; Cabello, Ana M; Coppola, Laurent; Cornejo-Castillo, Francisco M; d'Ovidio, Francesco; De Meester, Luc; Ferrera, Isabel; Garet-Delmas, Marie-José; Guidi, Lionel; Lara, Elena; Pesant, Stéphane; Royo-Llonch, Marta; Salazar, Guillem; Sánchez, Pablo; Sebastian, Marta; Souffreau, Caroline; Dimier, Céline; Picheral, Marc; Searson, Sarah; Kandels-Lewis, Stefanie; Gorsky, Gabriel; Not, Fabrice; Ogata, Hiroyuki; Speich, Sabrina; Stemmann, Lars; Weissenbach, Jean; Wincker, Patrick; Acinas, Silvia G; Sunagawa, Shinichi; Bork, Peer; Sullivan, Matthew B; Karsenti, Eric; Bowler, Chris; de Vargas, Colomban; Raes, Jeroen

    2015-05-22

    Species interaction networks are shaped by abiotic and biotic factors. Here, as part of the Tara Oceans project, we studied the photic zone interactome using environmental factors and organismal abundance profiles and found that environmental factors are incomplete predictors of community structure. We found associations across plankton functional types and phylogenetic groups to be nonrandomly distributed on the network and driven by both local and global patterns. We identified interactions among grazers, primary producers, viruses, and (mainly parasitic) symbionts and validated network-generated hypotheses using microscopy to confirm symbiotic relationships. We have thus provided a resource to support further research on ocean food webs and integrating biological components into ocean models. PMID:25999517

  15. A human interactome in three quantitative dimensions organized by stoichiometries and abundances.

    PubMed

    Hein, Marco Y; Hubner, Nina C; Poser, Ina; Cox, Jürgen; Nagaraj, Nagarjuna; Toyoda, Yusuke; Gak, Igor A; Weisswange, Ina; Mansfeld, Jörg; Buchholz, Frank; Hyman, Anthony A; Mann, Matthias

    2015-10-22

    The organization of a cell emerges from the interactions in protein networks. The interactome is critically dependent on the strengths of interactions and the cellular abundances of the connected proteins, both of which span orders of magnitude. However, these aspects have not yet been analyzed globally. Here, we have generated a library of HeLa cell lines expressing 1,125 GFP-tagged proteins under near-endogenous control, which we used as input for a next-generation interaction survey. Using quantitative proteomics, we detect specific interactions, estimate interaction stoichiometries, and measure cellular abundances of interacting proteins. These three quantitative dimensions reveal that the protein network is dominated by weak, substoichiometric interactions that play a pivotal role in defining network topology. The minority of stable complexes can be identified by their unique stoichiometry signature. This study provides a rich interaction dataset connecting thousands of proteins and introduces a framework for quantitative network analysis. PMID:26496610

  16. The Cardiac TBX5 Interactome Reveals a Chromatin Remodeling Network Essential for Cardiac Septation.

    PubMed

    Waldron, Lauren; Steimle, Jeffrey D; Greco, Todd M; Gomez, Nicholas C; Dorr, Kerry M; Kweon, Junghun; Temple, Brenda; Yang, Xinan Holly; Wilczewski, Caralynn M; Davis, Ian J; Cristea, Ileana M; Moskowitz, Ivan P; Conlon, Frank L

    2016-02-01

    Human mutations in the cardiac transcription factor gene TBX5 cause congenital heart disease (CHD), although the underlying mechanism is unknown. We report characterization of the endogenous TBX5 cardiac interactome and demonstrate that TBX5, long considered a transcriptional activator, interacts biochemically and genetically with the nucleosome remodeling and deacetylase (NuRD) repressor complex. Incompatible gene programs are repressed by TBX5 in the developing heart. CHD mis-sense mutations that disrupt the TBX5-NuRD interaction cause depression of a subset of repressed genes. Furthermore, the TBX5-NuRD interaction is required for heart development. Phylogenetic analysis showed that the TBX5-NuRD interaction domain evolved during early diversification of vertebrates, simultaneous with the evolution of cardiac septation. Collectively, this work defines a TBX5-NuRD interaction essential to cardiac development and the evolution of the mammalian heart, and when altered may contribute to human CHD.

  17. Native Piezo2 Interactomics Identifies Pericentrin as a Novel Regulator of Piezo2 in Somatosensory Neurons.

    PubMed

    Narayanan, Pratibha; Sondermann, Julia; Rouwette, Tom; Karaca, Samir; Urlaub, Henning; Mitkovski, Mišo; Gomez-Varela, David; Schmidt, Manuela

    2016-08-01

    The ability of somatosensory neurons to perceive mechanical stimuli relies on specialized mechanotransducing proteins and their molecular environment. Only recently has the identity of a major transducer of mechanical forces in vertebrates been revealed by the discovery of Piezo2. Further work has established its pivotal role for innocuous touch in mice. Therefore, Piezo2 offers a unique platform for the molecular investigation of somatosensory mechanosensation. We performed a mass spectrometry-based interactomics screen on native Piezo2 in somatosensory neurons of mouse dorsal root ganglia (DRG). Stringent and quantitative data analysis yielded the identity of 36 novel binding partners of Piezo2. The biological significance of this data set is reflected by functional experiments demonstrating a role for Pericentrin in modulating Piezo2 activity and membrane expression in somatosensory neurons. Collectively, our findings provide a framework for understanding Piezo2 physiology and serve as a rich resource for the molecular dissection of mouse somatosensation. PMID:27345391

  18. Proteomic analysis of the SIRT6 interactome: novel links to genome maintenance and cellular stress signaling.

    PubMed

    Simeoni, Federica; Tasselli, Luisa; Tanaka, Shinji; Villanova, Lidia; Hayashi, Mayumi; Kubota, Kazuishi; Isono, Fujio; Garcia, Benjamin A; Michishita-Kioi, Eriko; Chua, Katrin F

    2013-01-01

    The chromatin regulatory factor SIRT6 plays pivotal roles in metabolism, tumor suppression, and aging biology. Despite the fundamental roles of SIRT6 in physiology and disease, only a handful of molecular and functional interactions of SIRT6 have been reported. Here, we characterize the SIRT6 interactome and identify 80+ novel SIRT6-interacting proteins. The discovery of these SIRT6-associations considerably expands knowledge of the SIRT6 interaction network, and suggests previously unknown functional interactions of SIRT6 in fundamental cellular processes. These include chromatin remodeling, mitotic chromosome segregation, protein homeostasis, and transcriptional elongation. Extended analysis of the SIRT6 interaction with G3BP1, a master stress response factor, uncovers an unexpected role and mechanism of SIRT6 in regulating stress granule assembly and cellular stress resistance.

  19. Native Piezo2 Interactomics Identifies Pericentrin as a Novel Regulator of Piezo2 in Somatosensory Neurons.

    PubMed

    Narayanan, Pratibha; Sondermann, Julia; Rouwette, Tom; Karaca, Samir; Urlaub, Henning; Mitkovski, Mišo; Gomez-Varela, David; Schmidt, Manuela

    2016-08-01

    The ability of somatosensory neurons to perceive mechanical stimuli relies on specialized mechanotransducing proteins and their molecular environment. Only recently has the identity of a major transducer of mechanical forces in vertebrates been revealed by the discovery of Piezo2. Further work has established its pivotal role for innocuous touch in mice. Therefore, Piezo2 offers a unique platform for the molecular investigation of somatosensory mechanosensation. We performed a mass spectrometry-based interactomics screen on native Piezo2 in somatosensory neurons of mouse dorsal root ganglia (DRG). Stringent and quantitative data analysis yielded the identity of 36 novel binding partners of Piezo2. The biological significance of this data set is reflected by functional experiments demonstrating a role for Pericentrin in modulating Piezo2 activity and membrane expression in somatosensory neurons. Collectively, our findings provide a framework for understanding Piezo2 physiology and serve as a rich resource for the molecular dissection of mouse somatosensation.

  20. Chromosomes. A comprehensive Xist interactome reveals cohesin repulsion and an RNA-directed chromosome conformation.

    PubMed

    Minajigi, Anand; Froberg, John E; Wei, Chunyao; Sunwoo, Hongjae; Kesner, Barry; Colognori, David; Lessing, Derek; Payer, Bernhard; Boukhali, Myriam; Haas, Wilhelm; Lee, Jeannie T

    2015-07-17

    The inactive X chromosome (Xi) serves as a model to understand gene silencing on a global scale. Here, we perform "identification of direct RNA interacting proteins" (iDRiP) to isolate a comprehensive protein interactome for Xist, an RNA required for Xi silencing. We discover multiple classes of interactors-including cohesins, condensins, topoisomerases, RNA helicases, chromatin remodelers, and modifiers-that synergistically repress Xi transcription. Inhibiting two or three interactors destabilizes silencing. Although Xist attracts some interactors, it repels architectural factors. Xist evicts cohesins from the Xi and directs an Xi-specific chromosome conformation. Upon deleting Xist, the Xi acquires the cohesin-binding and chromosomal architecture of the active X. Our study unveils many layers of Xi repression and demonstrates a central role for RNA in the topological organization of mammalian chromosomes.

  1. Contrast Adaptation Implies Two Spatiotemporal Channels but Three Adapting Processes

    ERIC Educational Resources Information Center

    Langley, Keith; Bex, Peter J.

    2007-01-01

    The contrast gain control model of adaptation predicts that the effects of contrast adaptation correlate with contrast sensitivity. This article reports that the effects of high contrast spatiotemporal adaptors are maximum when adapting around 19 Hz, which is a factor of two or more greater than the peak in contrast sensitivity. To explain the…

  2. Spatiotemporal dynamics of HIV infection

    NASA Astrophysics Data System (ADS)

    Strain, Matthew Carl

    during the primary or chronic stages of HIV infection. The nonlinear clearance of HIV DNA therefore predicts lifelong virus production, even in treated patients. Collectively, these results demonstrate that important features of the spatiotemporal dynamics of HIV infection both in vitro and in vivo are best explained with explicit spatial models.

  3. A Transporter Interactome Is Essential for the Acquisition of Antimicrobial Resistance to Antibiotics

    PubMed Central

    Shuster, Yonatan; Steiner-Mordoch, Sonia; Alon Cudkowicz, Noemie; Schuldiner, Shimon

    2016-01-01

    Awareness of the problem of antimicrobial resistance (AMR) has escalated and drug-resistant infections are named among the most urgent problems facing clinicians today. Our experiments here identify a transporter interactome and portray its essential function in acquisition of antimicrobial resistance. By exposing E. coli cells to consecutive increasing concentrations of the fluoroquinolone norfloxacin we generated in the laboratory highly resistant strains that carry multiple mutations, most of them identical to those identified in clinical isolates. With this experimental paradigm, we show that the MDTs function in a coordinated mode to provide an essential first-line defense mechanism, preventing the drug reaching lethal concentrations, until a number of stable efficient alterations occur that allow survival. Single-component efflux transporters remove the toxic compounds from the cytoplasm to the periplasmic space where TolC-dependent transporters expel them from the cell. We postulate a close interaction between the two types of transporters to prevent rapid leak of the hydrophobic substrates back into the cell. The findings change the prevalent concept that in Gram-negative bacteria a single multidrug transporter, AcrAB-TolC type, is responsible for the resistance. The concept of a functional interactome, the process of identification of its members, the elucidation of the nature of the interactions and its role in cell physiology will change the existing paradigms in the field. We anticipate that our work will have an impact on the present strategy searching for inhibitors of AcrAB-TolC as adjuvants of existing antibiotics and provide novel targets for this urgent undertaking. PMID:27050393

  4. Synthesis of an inositol hexakisphosphate (IP6) affinity probe to study the interactome from a colon cancer cell line.

    PubMed

    Yin, Meng-Xin; Catimel, Bruno; Gregory, Mark; Condron, Melanie; Kapp, Eugene; Holmes, Andrew B; Burgess, Antony W

    2016-03-14

    Inositol hexakisphosphate (InsP6 or IP6) is an important signalling molecule in vesicular trafficking, neurotransmission, immune responses, regulation of protein kinases and phosphatases, activation of ion channels, antioxidant functions and anticancer activities. An IP6 probe was synthesised from myo-inositol via a derivatised analogue, which was immobilised through a terminal amino group onto Dynabeads. Systematic analysis of the IP6 interactome has been performed using the IP6 affinity probe using cytosolic extracts from the LIM1215 colonic carcinoma cell line. LC/MS/MS analysis identified 77 proteins or protein complexes that bind to IP6 specifically, including AP-2 complex proteins and β-arrestins as well as a number of novel potential IP6 interacting proteins. Bioinformatic enrichment analysis of the IP6 interactome reinforced the concept that IP6 regulates a number of biological processes including cell cycle and division, signal transduction, intracellular protein transport, vesicle-mediated transport and RNA splicing. PMID:26840369

  5. Systematic Determination of Human Cyclin Dependent Kinase (CDK)-9 Interactome Identifies Novel Functions in RNA Splicing Mediated by the DEAD Box (DDX)-5/17 RNA Helicases.

    PubMed

    Yang, Jun; Zhao, Yingxin; Kalita, Mridul; Li, Xueling; Jamaluddin, Mohammad; Tian, Bing; Edeh, Chukwudi B; Wiktorowicz, John E; Kudlicki, Andrzej; Brasier, Allan R

    2015-10-01

    Inducible transcriptional elongation is a rapid, stereotypic mechanism for activating immediate early immune defense genes by the epithelium in response to viral pathogens. Here, the recruitment of a multifunctional complex containing the cyclin dependent kinase 9 (CDK9) triggers the process of transcriptional elongation activating resting RNA polymerase engaged with innate immune response (IIR) genes. To identify additional functional activity of the CDK9 complex, we conducted immunoprecipitation (IP) enrichment-stable isotope labeling LC-MS/MS of the CDK9 complex in unstimulated cells and from cells activated by a synthetic dsRNA, polyinosinic/polycytidylic acid [poly (I:C)]. 245 CDK9 interacting proteins were identified with high confidence in the basal state and 20 proteins in four functional classes were validated by IP-SRM-MS. These data identified that CDK9 interacts with DDX 5/17, a family of ATP-dependent RNA helicases, important in alternative RNA splicing of NFAT5, and mH2A1 mRNA two proteins controlling redox signaling. A direct comparison of the basal versus activated state was performed using stable isotope labeling and validated by IP-SRM-MS. Recruited into the CDK9 interactome in response to poly(I:C) stimulation are HSPB1, DNA dependent kinases, and cytoskeletal myosin proteins that exchange with 60S ribosomal structural proteins. An integrated human CDK9 interactome map was developed containing all known human CDK9- interacting proteins. These data were used to develop a probabilistic global map of CDK9-dependent target genes that predicted two functional states controlling distinct cellular functions, one important in immune and stress responses. The CDK9-DDX5/17 complex was shown to be functionally important by shRNA-mediated knockdown, where differential accumulation of alternatively spliced NFAT5 and mH2A1 transcripts and alterations in downstream redox signaling were seen. The requirement of CDK9 for DDX5 recruitment to NFAT5 and mH2A1

  6. Sequential Elution Interactome Analysis of the Mind Bomb 1 Ubiquitin Ligase Reveals a Novel Role in Dendritic Spine Outgrowth*

    PubMed Central

    Mertz, Joseph; Tan, Haiyan; Pagala, Vishwajeeth; Bai, Bing; Chen, Ping-Chung; Li, Yuxin; Cho, Ji-Hoon; Shaw, Timothy; Wang, Xusheng; Peng, Junmin

    2015-01-01

    The mind bomb 1 (Mib1) ubiquitin ligase is essential for controlling metazoan development by Notch signaling and possibly the Wnt pathway. It is also expressed in postmitotic neurons and regulates neuronal morphogenesis and synaptic activity by mechanisms that are largely unknown. We sought to comprehensively characterize the Mib1 interactome and study its potential function in neuron development utilizing a novel sequential elution strategy for affinity purification, in which Mib1 binding proteins were eluted under different stringency and then quantified by the isobaric labeling method. The strategy identified the Mib1 interactome with both deep coverage and the ability to distinguish high-affinity partners from low-affinity partners. A total of 817 proteins were identified during the Mib1 affinity purification, including 56 high-affinity partners and 335 low-affinity partners, whereas the remaining 426 proteins are likely copurified contaminants or extremely weak binding proteins. The analysis detected all previously known Mib1-interacting proteins and revealed a large number of novel components involved in Notch and Wnt pathways, endocytosis and vesicle transport, the ubiquitin-proteasome system, cellular morphogenesis, and synaptic activities. Immunofluorescence studies further showed colocalization of Mib1 with five selected proteins: the Usp9x (FAM) deubiquitinating enzyme, alpha-, beta-, and delta-catenins, and CDKL5. Mutations of CDKL5 are associated with early infantile epileptic encephalopathy-2 (EIEE2), a severe form of mental retardation. We found that the expression of Mib1 down-regulated the protein level of CDKL5 by ubiquitination, and antagonized CDKL5 function during the formation of dendritic spines. Thus, the sequential elution strategy enables biochemical characterization of protein interactomes; and Mib1 analysis provides a comprehensive interactome for investigating its role in signaling networks and neuronal development. PMID:25931508

  7. Bacterial Interactomes: Interacting Protein Partners Share Similar Function and Are Validated in Independent Assays More Frequently Than Previously Reported.

    PubMed

    Shatsky, Maxim; Allen, Simon; Gold, Barbara L; Liu, Nancy L; Juba, Thomas R; Reveco, Sonia A; Elias, Dwayne A; Prathapam, Ramadevi; He, Jennifer; Yang, Wenhong; Szakal, Evelin D; Liu, Haichuan; Singer, Mary E; Geller, Jil T; Lam, Bonita R; Saini, Avneesh; Trotter, Valentine V; Hall, Steven C; Fisher, Susan J; Brenner, Steven E; Chhabra, Swapnil R; Hazen, Terry C; Wall, Judy D; Witkowska, H Ewa; Biggin, Mark D; Chandonia, John-Marc; Butland, Gareth

    2016-05-01

    Numerous affinity purification-mass spectrometry (AP-MS) and yeast two-hybrid screens have each defined thousands of pairwise protein-protein interactions (PPIs), most of which are between functionally unrelated proteins. The accuracy of these networks, however, is under debate. Here, we present an AP-MS survey of the bacterium Desulfovibrio vulgaris together with a critical reanalysis of nine published bacterial yeast two-hybrid and AP-MS screens. We have identified 459 high confidence PPIs from D. vulgaris and 391 from Escherichia coli Compared with the nine published interactomes, our two networks are smaller, are much less highly connected, and have significantly lower false discovery rates. In addition, our interactomes are much more enriched in protein pairs that are encoded in the same operon, have similar functions, and are reproducibly detected in other physical interaction assays than the pairs reported in prior studies. Our work establishes more stringent benchmarks for the properties of protein interactomes and suggests that bona fide PPIs much more frequently involve protein partners that are annotated with similar functions or that can be validated in independent assays than earlier studies suggested. PMID:26873250

  8. Targets of drugs are generally, and targets of drugs having side effects are specifically good spreaders of human interactome perturbations

    NASA Astrophysics Data System (ADS)

    Perez-Lopez, Áron R.; Szalay, Kristóf Z.; Türei, Dénes; Módos, Dezső; Lenti, Katalin; Korcsmáros, Tamás; Csermely, Peter

    2015-05-01

    Network-based methods are playing an increasingly important role in drug design. Our main question in this paper was whether the efficiency of drug target proteins to spread perturbations in the human interactome is larger if the binding drugs have side effects, as compared to those which have no reported side effects. Our results showed that in general, drug targets were better spreaders of perturbations than non-target proteins, and in particular, targets of drugs with side effects were also better spreaders of perturbations than targets of drugs having no reported side effects in human protein-protein interaction networks. Colorectal cancer-related proteins were good spreaders and had a high centrality, while type 2 diabetes-related proteins showed an average spreading efficiency and had an average centrality in the human interactome. Moreover, the interactome-distance between drug targets and disease-related proteins was higher in diabetes than in colorectal cancer. Our results may help a better understanding of the network position and dynamics of drug targets and disease-related proteins, and may contribute to develop additional, network-based tests to increase the potential safety of drug candidates.

  9. Targets of drugs are generally, and targets of drugs having side effects are specifically good spreaders of human interactome perturbations

    PubMed Central

    Perez-Lopez, Áron R.; Szalay, Kristóf Z.; Türei, Dénes; Módos, Dezső; Lenti, Katalin; Korcsmáros, Tamás; Csermely, Peter

    2015-01-01

    Network-based methods are playing an increasingly important role in drug design. Our main question in this paper was whether the efficiency of drug target proteins to spread perturbations in the human interactome is larger if the binding drugs have side effects, as compared to those which have no reported side effects. Our results showed that in general, drug targets were better spreaders of perturbations than non-target proteins, and in particular, targets of drugs with side effects were also better spreaders of perturbations than targets of drugs having no reported side effects in human protein-protein interaction networks. Colorectal cancer-related proteins were good spreaders and had a high centrality, while type 2 diabetes-related proteins showed an average spreading efficiency and had an average centrality in the human interactome. Moreover, the interactome-distance between drug targets and disease-related proteins was higher in diabetes than in colorectal cancer. Our results may help a better understanding of the network position and dynamics of drug targets and disease-related proteins, and may contribute to develop additional, network-based tests to increase the potential safety of drug candidates. PMID:25960144

  10. Intranuclear interactomic inhibition of NF-κB suppresses LPS-induced severe sepsis

    SciTech Connect

    Park, Sung-Dong; Cheon, So Yeong; Park, Tae-Yoon; Shin, Bo-Young; Oh, Hyunju; Ghosh, Sankar; Koo, Bon-Nyeo; Lee, Sang-Kyou

    2015-08-28

    Suppression of nuclear factor-κB (NF-κB) activation, which is best known as a major regulator of innate and adaptive immune responses, is a potent strategy for the treatment of endotoxic sepsis. To inhibit NF-κB functions, we designed the intra-nuclear transducible form of transcription modulation domain (TMD) of RelA (p65), called nt-p65-TMD, which can be delivered effectively into the nucleus without influencing the cell viability, and work as interactomic inhibitors via disruption of the endogenous p65-mediated transcription complex. nt-p65-TMD effectively inhibited the secretion of pro-inflammatory cytokines, including TNF-α, IL-1β, or IL-6 from BV2 microglia cells stimulated by lipopolysaccharide (LPS). nt-p65-TMD did not inhibit tyrosine phosphorylation of signaling mediators such as ZAP-70, p38, JNK, or ERK involved in T cell activation, but was capable of suppressing the transcriptional activity of NF-κB without the functional effect on that of NFAT upon T-cell receptor (TCR) stimulation. The transduced nt-p65-TMD in T cell did not affect the expression of CD69, however significantly inhibited the secretion of T cell-specific cytokines such as IL-2, IFN-γ, IL-4, IL-17A, or IL-10. Systemic administration of nt-p65-TMD showed a significant therapeutic effect on LPS-induced sepsis model by inhibiting pro-inflammatory cytokines secretion. Therefore, nt-p65-TMD can be a novel therapeutics for the treatment of various inflammatory diseases, including sepsis, where a transcription factor has a key role in pathogenesis, and further allows us to discover new functions of p65 under normal physiological condition without genetic alteration. - Highlights: • The nt-p65-TMD is intra-nuclear interactomic inhibitor of endogenous p65. • The nt-p65-TMD effectively inhibited the secretion of pro-inflammatory cytokines. • The excellent therapeutic potential of nt-p65-TMD was confirmed in sepsis model.

  11. Spatiotemporal Wave Patterns: Information Dynamics

    SciTech Connect

    Mikhail Rabinovich; Lev Tsimring

    2006-01-20

    Pattern formation has traditionally been studied in non-equilibrium physics from the viewpoint of describing the basic structures and their interactions. While this is still an important area of research, the emphasis in the last few years has shifted towards analysis of specific properties of patterns in various complex media. For example, diverse and unexpected phenomena occur in neuro-like media that are characterized by highly non-trivial local dynamics. We carried out an active research program on analysis of spatio-temporal patterns in various physical systems (convection, oscillating fluid layer, soap film), as well as in neuro-like media, with an emphasis on informational aspects of the dynamics. Nonlinear nonequilibrium media and their discrete analogs have a unique ability to represent, memorize, and process the information contained in spatio-temporal patterns. Recent neurophysiological experiments demonstrated a certain universality of spatio-temporal representation of information by neural ensembles. Information processing is also revealed in the spatio-temporal dynamics of cellular patterns in nonequilibrium media. It is extremely important for many applications to study the informational aspects of these dynamics, including the origins and mechanisms of information generation, propagation and storage. Some of our results are: the discovery of self-organization of periodically oscillatory patterns in chaotic heterogeneous media; the analysis of the propagation of the information along a chaotic media as function of the entropy of the signal; the analysis of wave propagation in discrete non-equilibrium media with autocatalytic properties, which simulates the calcium dynamics in cellular membranes. Based on biological experiments we suggest the mechanism by which the spatial sensory information is transferred into the spatio-temporal code in the neural media. We also found a new mechanism of self-pinning in cellular structures and the related phenomenon

  12. Quantitative study of the interactome of PKCζ involved in the EGF-induced tumor cell chemotaxis.

    PubMed

    Chen, Ruibing; Wang, Yanping; Liu, Yan; Zhang, Qing; Zhang, Xiaofang; Zhang, Fei; Shieh, Chia-Hui Paul; Yang, De; Zhang, Ning

    2013-03-01

    Chemotaxis plays an important role in metastasis. In our previous studies, we reported that protein kinase C ζ (PKCζ) mediated cancer cell chemotaxis by regulating cytoskeleton rearrangement and cell adhesion. To further study the molecular mechanism of chemotaxis, mass spectrometry-based approaches were employed to investigate the interactome of PKCζ and its changes upon stimulation by epidermal growth factor (EGF). As a result, 233 proteins were identified as potential PKCζ binding partners. Label free quantification was applied to examine the quantitative changes of these interactions involved in the EGF induced chemotaxis. Fifteen identified proteins were enriched and 9 proteins were reduced in the presence of EGF (≥ 1.5 folds, p ≤ 0.05). The interaction between cofilin-1 (CFL1) and PKCζ was evidenced and this interaction was enhanced in the EGF induced chemotaxis signaling transduction. In addition, novel PKCζ interacting proteins potentially related with chemotaxis were characterized, such as isoform 1 of nucleophosmin (NPM1). Furthermore, Western blotting and chemotaxis assays were also applied to validate the proteomics result and explore its biological implications. Collectively, the combination of quantitative proteomics and biological assays provides a powerful strategy for elucidating the signaling pathway of tumor cell chemotaxis.

  13. Lamina Associated Polypeptide 1 (LAP1) Interactome and Its Functional Features

    PubMed Central

    Serrano, Joana B.; da Cruz e Silva, Odete A. B.; Rebelo, Sandra

    2016-01-01

    Lamina-associated polypeptide 1 (LAP1) is a type II transmembrane protein of the inner nuclear membrane encoded by the human gene TOR1AIP1. LAP1 is involved in maintaining the nuclear envelope structure and appears be involved in the positioning of lamins and chromatin. To date, LAP1’s precise function has not been fully elucidated but analysis of its interacting proteins will permit unraveling putative associations to specific cellular pathways and cellular processes. By assessing public databases it was possible to identify the LAP1 interactome, and this was curated. In total, 41 interactions were identified. Several functionally relevant proteins, such as TRF2, TERF2IP, RIF1, ATM, MAD2L1 and MAD2L1BP were identified and these support the putative functions proposed for LAP1. Furthermore, by making use of the Ingenuity Pathways Analysis tool and submitting the LAP1 interactors, the top two canonical pathways were “Telomerase signalling” and “Telomere Extension by Telomerase” and the top functions “Cell Morphology”, “Cellular Assembly and Organization” and “DNA Replication, Recombination, and Repair”. Once again, putative LAP1 functions are reinforced but novel functions are emerging. PMID:26784240

  14. Auxotrophy and intrapopulation complementary in the 'interactome' of a cultivated freshwater model community.

    PubMed

    Garcia, Sarahi L; Buck, Moritz; McMahon, Katherine D; Grossart, Hans-Peter; Eiler, Alexander; Warnecke, Falk

    2015-09-01

    Microorganisms are usually studied either in highly complex natural communities or in isolation as monoclonal model populations that we manage to grow in the laboratory. Here, we uncover the biology of some of the most common and yet-uncultured bacteria in freshwater environments using a mixed culture from Lake Grosse Fuchskuhle. From a single shotgun metagenome of a freshwater mixed culture of low complexity, we recovered four high-quality metagenome-assembled genomes (MAGs) for metabolic reconstruction. This analysis revealed the metabolic interconnectedness and niche partitioning of these naturally dominant bacteria. In particular, vitamin- and amino acid biosynthetic pathways were distributed unequally with a member of Crenarchaeota most likely being the sole producer of vitamin B12 in the mixed culture. Using coverage-based partitioning of the genes recovered from a single MAG intrapopulation metabolic complementarity was revealed pointing to 'social' interactions for the common good of populations dominating freshwater plankton. As such, our MAGs highlight the power of mixed cultures to extract naturally occurring 'interactomes' and to overcome our inability to isolate and grow the microbes dominating in nature.

  15. The extracellular interactome of the human adenovirus family reveals diverse strategies for immunomodulation

    PubMed Central

    Martinez-Martin, Nadia; Ramani, Sree R.; Hackney, Jason A.; Tom, Irene; Wranik, Bernd J.; Chan, Michelle; Wu, Johnny; Paluch, Maciej T.; Takeda, Kentaro; Hass, Philip E.; Clark, Hilary; Gonzalez, Lino C.

    2016-01-01

    Viruses encode secreted and cell-surface expressed proteins essential to modulate host immune defenses and establish productive infections. However, to date there has been no systematic study of the extracellular interactome of any human virus. Here we utilize the E3 proteins, diverse and rapidly evolving transmembrane-containing proteins encoded by human adenoviruses, as a model system to survey the extracellular immunomodulatory landscape. From a large-scale protein interaction screen against a microarray of more than 1,500 human proteins, we find and validate 51 previously unidentified virus–host interactions. Our results uncover conserved strategies as well as substantial diversity and multifunctionality in host targeting within and between viral species. Prominent modulation of the leukocyte immunoglobulin-like and signalling lymphocyte activation molecule families and a number of inhibitory receptors were identified as hubs for viral perturbation, suggesting unrecognized immunoregulatory strategies. We describe a virus–host extracellular interaction map of unprecedented scale that provides new insights into viral immunomodulation. PMID:27145901

  16. Expanding the Interactome of the Noncanonical NF-κB Signaling Pathway.

    PubMed

    Willmann, Katharina L; Sacco, Roberto; Martins, Rui; Garncarz, Wojciech; Krolo, Ana; Knapp, Sylvia; Bennett, Keiryn L; Boztug, Kaan

    2016-09-01

    NF-κB signaling is a central pathway of immunity and integrates signal transduction upon a wide array of inflammatory stimuli. Noncanonical NF-κB signaling is activated by a small subset of TNF family receptors and characterized by NF-κB2/p52 transcriptional activity. The medical relevance of this pathway has recently re-emerged from the discovery of primary immunodeficiency patients that have loss-of-function mutations in the MAP3K14 gene encoding NIK. Nevertheless, knowledge of protein interactions that regulate noncanonical NF-κB signaling is sparse. Here we report a detailed state-of-the-art mass spectrometry-based protein-protein interaction network including the noncanonical NF-κB signaling nodes TRAF2, TRAF3, IKKα, NIK, and NF-κB2/p100. The value of the data set was confirmed by the identification of interactions already known to regulate this pathway. In addition, a remarkable number of novel interactors were identified. We provide validation of the novel NIK and IKKα interactor FKBP8, which may regulate processes downstream of noncanonical NF-κB signaling. To understand perturbed noncanonical NF-κB signaling in the context of misregulated NIK in disease, we also provide a differential interactome of NIK mutants that cause immunodeficiency. Altogether, this data set not only provides critical insight into how protein-protein interactions can regulate immune signaling but also offers a novel resource on noncanonical NF-κB signaling.

  17. What model organisms and interactomics can reveal about the genetics of human obesity.

    PubMed

    Williams, Michael J; Almén, Markus S; Fredriksson, Robert; Schiöth, Helgi B

    2012-11-01

    Genome-wide association studies have identified a number of genes associated with human body weight. While some of these genes are large fields within obesity research, such as MC4R, POMC, FTO and BDNF, the majority do not have a clearly defined functional role explaining why they may affect body weight. Here, we searched biological databases and discovered 33 additional genes associated with human obesity (CADM2, GIPR, GPCR5B, LRP1B, NEGR1, NRXN3, SH2B1, FANCL, GNPDA2, HMGCR, MAP2K5, NUDT3, PRKD1, QPCTL, TNNI3K, MTCH2, DNAJC27, SLC39A8, MTIF3, RPL27A, SEC16B, ETV5, HMGA1, TFAP2B, TUB, ZNF608, FAIM2, KCTD15, LINGO2, POC5, PTBP2, TMEM18, TMEM160). We find that the majority have orthologues in distant species, such as D. melanogaster and C. elegans, suggesting that they are important for the biology of most bilateral species. Intriguingly, signalling cascade genes and transcription factors are enriched among these obesity genes, and several of the genes show properties that could be useful for potential drug discovery. In this review, we demonstrate how information from several distant model species, interactomics and signalling pathway analysis represents an important way to better understand the functional diversity of the surprisingly high number of molecules that seem to be important for human obesity.

  18. Inhibitory activities of short linear motifs underlie Hox interactome specificity in vivo

    PubMed Central

    Baëza, Manon; Viala, Séverine; Heim, Marjorie; Dard, Amélie; Hudry, Bruno; Duffraisse, Marilyne; Rogulja-Ortmann, Ana; Brun, Christine; Merabet, Samir

    2015-01-01

    Hox proteins are well-established developmental regulators that coordinate cell fate and morphogenesis throughout embryogenesis. In contrast, our knowledge of their specific molecular modes of action is limited to the interaction with few cofactors. Here, we show that Hox proteins are able to interact with a wide range of transcription factors in the live Drosophila embryo. In this context, specificity relies on a versatile usage of conserved short linear motifs (SLiMs), which, surprisingly, often restrains the interaction potential of Hox proteins. This novel buffering activity of SLiMs was observed in different tissues and found in Hox proteins from cnidarian to mouse species. Although these interactions remain to be analysed in the context of endogenous Hox regulatory activities, our observations challenge the traditional role assigned to SLiMs and provide an alternative concept to explain how Hox interactome specificity could be achieved during the embryonic development. DOI: http://dx.doi.org/10.7554/eLife.06034.001 PMID:25869471

  19. The molecular basis for ANE syndrome revealed by the large ribosomal subunit processome interactome

    PubMed Central

    McCann, Kathleen L; Teramoto, Takamasa; Zhang, Jun; Tanaka Hall, Traci M; Baserga, Susan J

    2016-01-01

    ANE syndrome is a ribosomopathy caused by a mutation in an RNA recognition motif of RBM28, a nucleolar protein conserved to yeast (Nop4). While patients with ANE syndrome have fewer mature ribosomes, it is unclear how this mutation disrupts ribosome assembly. Here we use yeast as a model system and show that the mutation confers growth and pre-rRNA processing defects. Recently, we found that Nop4 is a hub protein in the nucleolar large subunit (LSU) processome interactome. Here we demonstrate that the ANE syndrome mutation disrupts Nop4’s hub function by abrogating several of Nop4’s protein-protein interactions. Circular dichroism and NMR demonstrate that the ANE syndrome mutation in RRM3 of human RBM28 disrupts domain folding. We conclude that the ANE syndrome mutation generates defective protein folding which abrogates protein-protein interactions and causes faulty pre-LSU rRNA processing, thus revealing one aspect of the molecular basis of this human disease. DOI: http://dx.doi.org/10.7554/eLife.16381.001 PMID:27077951

  20. Copy number variation of genes involved in the hepatitis C virus-human interactome

    PubMed Central

    Budzko, Lucyna; Marcinkowska-Swojak, Malgorzata; Jackowiak, Paulina; Kozlowski, Piotr; Figlerowicz, Marek

    2016-01-01

    Copy number variation (CNV) is a newly discovered form of intra-species genetic polymorphism that is defined as deletions or duplications of genome segments ranging from 1 kbp to several Mbp. CNV accounts for the majority of the genetic variation observed in humans (CNV regions cover more than 10% of the human genome); therefore, it may significantly influence both the phenotype and susceptibility to various diseases. Unfortunately, the impact of CNV on a number of diseases, including hepatitis C virus (HCV) infection, remains largely unexplored. Here, we analyzed 421 human genes encoding proteins that have been shown to interact with HCV proteins or genomic RNA (proteins from the HCV-human interactome). We found that 19 of the 421 candidate genes are located in putative CNV regions. For all of these genes, copy numbers were determined for European, Asiatic and African populations using the multiplex ligation-dependent amplification (MLPA) method. As a result, we identified 4 genes, IGLL1, MLLT4, PDPK1, PPP1R13L, for which the CN-genotype ranged from 1 to 6. All of these genes are involved in host-virus interaction; thus, their polymorphism has a potential impact on the development of HCV infection and/or therapy outcome. PMID:27510840

  1. Locus-specific targeting to the X-chromosome revealed by the RNA interactome of CTCF

    PubMed Central

    Kung, Johnny T.; Kesner, Barry; An, Jee Young; Ahn, Janice Y.; Cifuentes-Rojas, Catherine; Colognori, David; Jeon, Yesu; Szanto, Attila; del Rosario, Brian C.; Pinter, Stefan F.; Erwin, Jennifer A.; Lee, Jeannie T.

    2015-01-01

    CTCF is a master regulator that plays important roles in genome architecture and gene expression. How CTCF is recruited in a locus-specific manner is not fully understood. Evidence from epigenetic processes, such as X-chromosome inactivation (XCI), indicates that CTCF associates functionally with RNA. Using genome-wide approaches to investigate the relationship between its RNA interactome and epigenomic landscape, here we report that CTCF binds thousands of transcripts in mouse embryonic stem cells, many in close proximity to CTCF’s genomic binding sites. CTCF is a specific and high-affinity RNA-binding protein (Kd <1 nM). During XCI, CTCF differentially binds the active and inactive X-chromosomes and interacts directly with Tsix, Xite, and Xist RNAs. Tsix and Xite RNAs target CTCF to the X-inactivation center, thereby inducing homologous X-chromosome pairing. Our work elucidates one mechanism by which CTCF is recruited in a locus-specific manner and implicates CTCF-RNA interactions in long-range chromosomal interactions. PMID:25578877

  2. Dynamics of Turing Patterns under Spatiotemporal Forcing

    NASA Astrophysics Data System (ADS)

    Rüdiger, S.; Míguez, D. G.; Muñuzuri, A. P.; Sagués, F.; Casademunt, J.

    2003-03-01

    We study, both theoretically and experimentally, the dynamical response of Turing patterns to a spatiotemporal forcing in the form of a traveling-wave modulation of a control parameter. We show that from strictly spatial resonance, it is possible to induce new, generic dynamical behaviors, including temporally modulated traveling waves and localized traveling solitonlike solutions. The latter make contact with the soliton solutions of Coullet [

    Phys. Rev. Lett.PRLTAO0031-9007 56, 724 (1986)
    ] and generalize them. The stability diagram for the different propagating modes in the Lengyel-Epstein model is determined numerically. Direct observations of the predicted solutions in experiments carried out with light modulations in the photosensitive chlorine dioxide-iodine-malonic acid reaction are also reported.

  3. Spatiotemporally varying visual hallucinations: II. Spectral classification and comparison with theory.

    PubMed

    Henke, H; Robinson, P A; Drysdale, P M

    2014-09-21

    In order to better understand the nature of visual hallucinations, and to test predictions of spatiotemporally oscillating hallucinations from a recent corticothalamic model of visual dynamics, clinical descriptions of hallucinations are used to establish boundaries on the spatiotemporal frequencies observed in various disorders. Detailed comparisons with hallucinations during migraine aura demonstrate that key features are consistent with corticothalamic origin and specific abnormalities, but underline the need for more detailed quantitative data to be obtained on temporally oscillating hallucinations more generally.

  4. Identification and functional analysis of the BIM interactome; new clues on its possible involvement in Epstein-Barr Virus-associated diseases.

    PubMed

    Rouka, Erasmia; Kyriakou, Despoina

    2015-12-01

    Epigenetic deregulation is a common feature in the pathogenesis of Epstein-Barr Virus (EBV)-related lymphomas and carcinomas. Previous studies have demonstrated a strong association between EBV latency in B-cells and epigenetic silencing of the tumor suppressor gene BIM. This study aimed to the construction and functional analysis of the BIM interactome in order to identify novel host genes that may be targeted by EBV. Fifty-nine unique interactors were found to compose the BIM gene network. Ontological analysis at the pathway level highlighted infectious diseases along with neuropathologies. These results underline the possible interplay between the BIM interactome and EBV-associated disorders.

  5. An integrative in silico approach for discovering candidates for drug-targetable protein-protein interactions in interactome data

    PubMed Central

    Sugaya, Nobuyoshi; Ikeda, Kazuyoshi; Tashiro, Toshiyuki; Takeda, Shizu; Otomo, Jun; Ishida, Yoshiko; Shiratori, Akiko; Toyoda, Atsushi; Noguchi, Hideki; Takeda, Tadayuki; Kuhara, Satoru; Sakaki, Yoshiyuki; Iwayanagi, Takao

    2007-01-01

    Background Protein-protein interactions (PPIs) are challenging but attractive targets for small chemical drugs. Whole PPIs, called the 'interactome', have been emerged in several organisms, including human, based on the recent development of high-throughput screening (HTS) technologies. Individual PPIs have been targeted by small drug-like chemicals (SDCs), however, interactome data have not been fully utilized for exploring drug targets due to the lack of comprehensive methodology for utilizing these data. Here we propose an integrative in silico approach for discovering candidates for drug-targetable PPIs in interactome data. Results Our novel in silico screening system comprises three independent assessment procedures: i) detection of protein domains responsible for PPIs, ii) finding SDC-binding pockets on protein surfaces, and iii) evaluating similarities in the assignment of Gene Ontology (GO) terms between specific partner proteins. We discovered six candidates for drug-targetable PPIs by applying our in silico approach to original human PPI data composed of 770 binary interactions produced by our HTS yeast two-hybrid (HTS-Y2H) assays. Among them, we further examined two candidates, RXRA/NRIP1 and CDK2/CDKN1A, with respect to their biological roles, PPI network around each candidate, and tertiary structures of the interacting domains. Conclusion An integrative in silico approach for discovering candidates for drug-targetable PPIs was applied to original human PPIs data. The system excludes false positive interactions and selects reliable PPIs as drug targets. Its effectiveness was demonstrated by the discovery of the six promising candidate target PPIs. Inhibition or stabilization of the two interactions may have potential therapeutic effects against human diseases. PMID:17705877

  6. Spatiotemporal Interpolation for Environmental Modelling.

    PubMed

    Susanto, Ferry; de Souza, Paulo; He, Jing

    2016-01-01

    A variation of the reduction-based approach to spatiotemporal interpolation (STI), in which time is treated independently from the spatial dimensions, is proposed in this paper. We reviewed and compared three widely-used spatial interpolation techniques: ordinary kriging, inverse distance weighting and the triangular irregular network. We also proposed a new distribution-based distance weighting (DDW) spatial interpolation method. In this study, we utilised one year of Tasmania's South Esk Hydrology model developed by CSIRO. Root mean squared error statistical methods were performed for performance evaluations. Our results show that the proposed reduction approach is superior to the extension approach to STI. However, the proposed DDW provides little benefit compared to the conventional inverse distance weighting (IDW) method. We suggest that the improved IDW technique, with the reduction approach used for the temporal dimension, is the optimal combination for large-scale spatiotemporal interpolation within environmental modelling applications. PMID:27509497

  7. Spatiotemporal Interpolation for Environmental Modelling

    PubMed Central

    Susanto, Ferry; de Souza, Paulo; He, Jing

    2016-01-01

    A variation of the reduction-based approach to spatiotemporal interpolation (STI), in which time is treated independently from the spatial dimensions, is proposed in this paper. We reviewed and compared three widely-used spatial interpolation techniques: ordinary kriging, inverse distance weighting and the triangular irregular network. We also proposed a new distribution-based distance weighting (DDW) spatial interpolation method. In this study, we utilised one year of Tasmania’s South Esk Hydrology model developed by CSIRO. Root mean squared error statistical methods were performed for performance evaluations. Our results show that the proposed reduction approach is superior to the extension approach to STI. However, the proposed DDW provides little benefit compared to the conventional inverse distance weighting (IDW) method. We suggest that the improved IDW technique, with the reduction approach used for the temporal dimension, is the optimal combination for large-scale spatiotemporal interpolation within environmental modelling applications. PMID:27509497

  8. Interactomes to Biological Phase Space: a call to begin thinking at a new level in computational biology.

    SciTech Connect

    Davidson, George S.; Brown, William Michael

    2007-09-01

    Techniques for high throughput determinations of interactomes, together with high resolution protein collocalizations maps within organelles and through membranes will soon create a vast resource. With these data, biological descriptions, akin to the high dimensional phase spaces familiar to physicists, will become possible. These descriptions will capture sufficient information to make possible realistic, system-level models of cells. The descriptions and the computational models they enable will require powerful computing techniques. This report is offered as a call to the computational biology community to begin thinking at this scale and as a challenge to develop the required algorithms and codes to make use of the new data.3

  9. Expanding the Interactome of the Noncanonical NF-κB Signaling Pathway.

    PubMed

    Willmann, Katharina L; Sacco, Roberto; Martins, Rui; Garncarz, Wojciech; Krolo, Ana; Knapp, Sylvia; Bennett, Keiryn L; Boztug, Kaan

    2016-09-01

    NF-κB signaling is a central pathway of immunity and integrates signal transduction upon a wide array of inflammatory stimuli. Noncanonical NF-κB signaling is activated by a small subset of TNF family receptors and characterized by NF-κB2/p52 transcriptional activity. The medical relevance of this pathway has recently re-emerged from the discovery of primary immunodeficiency patients that have loss-of-function mutations in the MAP3K14 gene encoding NIK. Nevertheless, knowledge of protein interactions that regulate noncanonical NF-κB signaling is sparse. Here we report a detailed state-of-the-art mass spectrometry-based protein-protein interaction network including the noncanonical NF-κB signaling nodes TRAF2, TRAF3, IKKα, NIK, and NF-κB2/p100. The value of the data set was confirmed by the identification of interactions already known to regulate this pathway. In addition, a remarkable number of novel interactors were identified. We provide validation of the novel NIK and IKKα interactor FKBP8, which may regulate processes downstream of noncanonical NF-κB signaling. To understand perturbed noncanonical NF-κB signaling in the context of misregulated NIK in disease, we also provide a differential interactome of NIK mutants that cause immunodeficiency. Altogether, this data set not only provides critical insight into how protein-protein interactions can regulate immune signaling but also offers a novel resource on noncanonical NF-κB signaling. PMID:27416764

  10. Long-term potentiation modulates synaptic phosphorylation networks and reshapes the structure of the postsynaptic interactome.

    PubMed

    Li, Jing; Wilkinson, Brent; Clementel, Veronica A; Hou, Junjie; O'Dell, Thomas J; Coba, Marcelo P

    2016-01-01

    The postsynaptic site of neurons is composed of more than 1500 proteins arranged in protein-protein interaction complexes, the composition of which is modulated by protein phosphorylation through the actions of complex signaling networks. Components of these networks function as key regulators of synaptic plasticity, in particular hippocampal long-term potentiation (LTP). The postsynaptic density (PSD) is a complex multicomponent structure that includes receptors, enzymes, scaffold proteins, and structural proteins. We triggered LTP in the mouse hippocampus CA1 region and then performed large-scale analyses to identify phosphorylation-mediated events in the PSD and changes in the protein-protein interactome of the PSD that were associated with LTP induction. Our data indicated LTP-induced reorganization of the PSD. The dynamic reorganization of the PSD links glutamate receptor signaling to kinases (writers) and phosphatases (erasers), as well as the target proteins that are modulated by protein phosphorylation and the proteins that recognize the phosphorylation status of their binding partners (readers). Protein phosphorylation and protein interaction networks converged at highly connected nodes within the PSD network. Furthermore, the LTP-regulated phosphoproteins, which included the scaffold proteins Shank3, Syngap1, Dlgap1, and Dlg4, represented the "PSD risk" for schizophrenia and autism spectrum disorder, such that without these proteins in the analysis, the association with the PSD and these two psychiatric diseases was not present. These data are a rich resource for future studies of LTP and suggest that the PSD holds the keys to understanding the molecular events that contribute to complex neurological disorders that affect synaptic plasticity. PMID:27507650

  11. Bayesian spatio-temporal modeling of particulate matter concentrations in Peninsular Malaysia

    NASA Astrophysics Data System (ADS)

    Manga, Edna; Awang, Norhashidah

    2016-06-01

    This article presents an application of a Bayesian spatio-temporal Gaussian process (GP) model on particulate matter concentrations from Peninsular Malaysia. We analyze daily PM10 concentration levels from 35 monitoring sites in June and July 2011. The spatiotemporal model set in a Bayesian hierarchical framework allows for inclusion of informative covariates, meteorological variables and spatiotemporal interactions. Posterior density estimates of the model parameters are obtained by Markov chain Monte Carlo methods. Preliminary data analysis indicate information on PM10 levels at sites classified as industrial locations could explain part of the space time variations. We include the site-type indicator in our modeling efforts. Results of the parameter estimates for the fitted GP model show significant spatio-temporal structure and positive effect of the location-type explanatory variable. We also compute some validation criteria for the out of sample sites that show the adequacy of the model for predicting PM10 at unmonitored sites.

  12. Bacterial interactomes: Interacting protein partners share similar function and are validated in independent assays more frequently than previously reported.

    DOE PAGES

    Shatsky, Maxim; Allen, Simon; Gold, Barbara; Liu, Nancy L.; Juba, Thomas R.; Elias, Dwayne A; Reveco, Sonia A.; Prathapam, Ramadevi; He, Jennifer; Yang, Wenhong; et al

    2016-05-01

    Numerous affinity purification – mass-spectrometry (AP-MS) and yeast two hybrid (Y2H) screens have each defined thousands of pairwise protein-protein interactions (PPIs), most between functionally unrelated proteins. The accuracy of these networks, however, is under debate. Here we present an AP-MS survey of the bacterium Desulfovibrio vulgaris together with a critical reanalysis of nine published bacterial Y2H and AP-MS screens. We have identified 459 high confidence PPIs from D. vulgaris and 391 from Escherichia coli. Compared to the nine published interactomes, our two networks are smaller; are much less highly connected; have significantly lower false discovery rates; and are much moremore » enriched in protein pairs that are encoded in the same operon, have similar functions, and are reproducibly detected in other physical interaction assays. Lastly, our work establishes more stringent benchmarks for the properties of protein interactomes and suggests that bona fide PPIs much more frequently involve protein partners that are annotated with similar functions or that can be validated in independent assays than earlier studies suggested.« less

  13. Mapping the H(+) (V)-ATPase interactome: identification of proteins involved in trafficking, folding, assembly and phosphorylation.

    PubMed

    Merkulova, Maria; Păunescu, Teodor G; Azroyan, Anie; Marshansky, Vladimir; Breton, Sylvie; Brown, Dennis

    2015-01-01

    V-ATPases (H(+) ATPases) are multisubunit, ATP-dependent proton pumps that regulate pH homeostasis in virtually all eukaryotes. They are involved in key cell biological processes including vesicle trafficking, endosomal pH sensing, membrane fusion and intracellular signaling. They also have critical systemic roles in renal acid excretion and blood pH balance, male fertility, bone remodeling, synaptic transmission, olfaction and hearing. Furthermore, V-ATPase dysfunction either results in or aggravates various other diseases, but little is known about the complex protein interactions that regulate these varied V-ATPase functions. Therefore, we performed a proteomic analysis to identify V-ATPase associated proteins and construct a V-ATPase interactome. Our analysis using kidney tissue revealed V-ATPase-associated protein clusters involved in protein quality control, complex assembly and intracellular trafficking. ARHGEF7, DMXL1, EZR, NCOA7, OXR1, RPS6KA3, SNX27 and 9 subunits of the chaperonin containing TCP1 complex (CCT) were found to interact with V-ATPase for the first time in this study. Knockdown of two interacting proteins, DMXL1 and WDR7, inhibited V-ATPase-mediated intracellular vesicle acidification in a kidney cell line, providing validation for the utility of our interactome as a screen for functionally important novel V-ATPase-regulating proteins. Our data, therefore, provide new insights and directions for the analysis of V-ATPase cell biology and (patho)physiology. PMID:26442671

  14. Exhaustive search of the SNP-SNP interactome identifies epistatic effects on brain volume in two cohorts

    PubMed Central

    Hibar, Derrek P.; Stein, Jason L.; Jahanshad, Neda; Kohannim, Omid; Toga, Arthur W.; McMahon, Katie L.; de Zubicaray, Greig I.; Montgomery, Grant W.; Martin, Nicholas G.; Wright, Margaret J.; Weiner, Michael W.; Thompson, Paul M.

    2014-01-01

    The SNP-SNP interactome has rarely been explored in the context of neuroimaging genetics mainly due to the complexity of conducting ∼1011 pairwise statistical tests. However, recent advances in machine learning, specifically the iterative sure independence screening (SIS) method, have enabled the analysis of datasets where the number of predictors is much larger than the number of observations. Using an implementation of the SIS algorithm (called EPISIS), we used exhaustive search of the genome-wide, SNP-SNP interactome to identify and prioritize SNPs for interaction analysis. We identified a significant SNP pair, rs1345203 and rs1213205, associated with temporal lobe volume. We further examined the full-brain, voxelwise effects of the interaction in the ADNI dataset and separately in an independent dataset of healthy twins (QTIM). We found that each additional loading in the epistatic effect was associated with ∼5% greater brain regional brain volume (a protective effect) in both the ADNI and QTIM samples. PMID:24505811

  15. Quantitative network mapping of the human kinome interactome reveals new clues for rational kinase inhibitor discovery and individualized cancer therapy.

    PubMed

    Cheng, Feixiong; Jia, Peilin; Wang, Quan; Zhao, Zhongming

    2014-06-15

    The human kinome is gaining importance through its promising cancer therapeutic targets, yet no general model to address the kinase inhibitor resistance has emerged. Here, we constructed a systems biology-based framework to catalogue the human kinome, including 538 kinase genes, in the broader context of the human interactome. Specifically, we constructed three networks: a kinase-substrate interaction network containing 7,346 pairs connecting 379 kinases to 36,576 phosphorylation sites in 1,961 substrates, a protein-protein interaction network (PPIN) containing 92,699 pairs, and an atomic resolution PPIN containing 4,278 pairs. We identified the conserved regulatory phosphorylation motifs (e.g., Ser/Thr-Pro) using a sequence logo analysis. We found the typical anticancer target selection strategy that uses network hubs as drug targets, might lead to a high adverse drug reaction risk. Furthermore, we found the distinct network centrality of kinases creates a high anticancer drug resistance risk by feedback or crosstalk mechanisms within cellular networks. This notion is supported by the systematic network and pathway analyses that anticancer drug resistance genes are significantly enriched as hubs and heavily participate in multiple signaling pathways. Collectively, this comprehensive human kinome interactome map sheds light on anticancer drug resistance mechanisms and provides an innovative resource for rational kinase inhibitor design.

  16. Comprehensively Characterizing the Thioredoxin Interactome In Vivo Highlights the Central Role Played by This Ubiquitous Oxidoreductase in Redox Control.

    PubMed

    Arts, Isabelle S; Vertommen, Didier; Baldin, Francesca; Laloux, Géraldine; Collet, Jean-François

    2016-06-01

    Thioredoxin (Trx) is a ubiquitous oxidoreductase maintaining protein-bound cysteine residues in the reduced thiol state. Here, we combined a well-established method to trap Trx substrates with the power of bacterial genetics to comprehensively characterize the in vivo Trx redox interactome in the model bacterium Escherichia coli Using strains engineered to optimize trapping, we report the identification of a total 268 Trx substrates, including 201 that had never been reported to depend on Trx for reduction. The newly identified Trx substrates are involved in a variety of cellular processes, ranging from energy metabolism to amino acid synthesis and transcription. The interaction between Trx and two of its newly identified substrates, a protein required for the import of most carbohydrates, PtsI, and the bacterial actin homolog MreB was studied in detail. We provide direct evidence that PtsI and MreB contain cysteine residues that are susceptible to oxidation and that participate in the formation of an intermolecular disulfide with Trx. By considerably expanding the number of Trx targets, our work highlights the role played by this major oxidoreductase in a variety of cellular processes. Moreover, as the dependence on Trx for reduction is often conserved across species, it also provides insightful information on the interactome of Trx in organisms other than E. coli. PMID:27081212

  17. Mapping the H+ (V)-ATPase interactome: identification of proteins involved in trafficking, folding, assembly and phosphorylation

    PubMed Central

    Merkulova, Maria; Păunescu, Teodor G.; Azroyan, Anie; Marshansky, Vladimir; Breton, Sylvie; Brown, Dennis

    2015-01-01

    V-ATPases (H+ ATPases) are multisubunit, ATP-dependent proton pumps that regulate pH homeostasis in virtually all eukaryotes. They are involved in key cell biological processes including vesicle trafficking, endosomal pH sensing, membrane fusion and intracellular signaling. They also have critical systemic roles in renal acid excretion and blood pH balance, male fertility, bone remodeling, synaptic transmission, olfaction and hearing. Furthermore, V-ATPase dysfunction either results in or aggravates various other diseases, but little is known about the complex protein interactions that regulate these varied V-ATPase functions. Therefore, we performed a proteomic analysis to identify V-ATPase associated proteins and construct a V-ATPase interactome. Our analysis using kidney tissue revealed V-ATPase-associated protein clusters involved in protein quality control, complex assembly and intracellular trafficking. ARHGEF7, DMXL1, EZR, NCOA7, OXR1, RPS6KA3, SNX27 and 9 subunits of the chaperonin containing TCP1 complex (CCT) were found to interact with V-ATPase for the first time in this study. Knockdown of two interacting proteins, DMXL1 and WDR7, inhibited V-ATPase-mediated intracellular vesicle acidification in a kidney cell line, providing validation for the utility of our interactome as a screen for functionally important novel V-ATPase-regulating proteins. Our data, therefore, provide new insights and directions for the analysis of V-ATPase cell biology and (patho)physiology. PMID:26442671

  18. Toxoplasmosis and Polygenic Disease Susceptibility Genes: Extensive Toxoplasma gondii Host/Pathogen Interactome Enrichment in Nine Psychiatric or Neurological Disorders

    PubMed Central

    Carter, C. J.

    2013-01-01

    Toxoplasma gondii is not only implicated in schizophrenia and related disorders, but also in Alzheimer's or Parkinson's disease, cancer, cardiac myopathies, and autoimmune disorders. During its life cycle, the pathogen interacts with ~3000 host genes or proteins. Susceptibility genes for multiple sclerosis, Alzheimer's disease, schizophrenia, bipolar disorder, depression, childhood obesity, Parkinson's disease, attention deficit hyperactivity disorder (P  from  8.01E − 05  (ADHD)  to  1.22E − 71) (multiple sclerosis), and autism (P = 0.013), but not anorexia or chronic fatigue are highly enriched in the human arm of this interactome and 18 (ADHD) to 33% (MS) of the susceptibility genes relate to it. The signalling pathways involved in the susceptibility gene/interactome overlaps are relatively specific and relevant to each disease suggesting a means whereby susceptibility genes could orient the attentions of a single pathogen towards disruption of the specific pathways that together contribute (positively or negatively) to the endophenotypes of different diseases. Conditional protein knockdown, orchestrated by T. gondii proteins or antibodies binding to those of the host (pathogen derived autoimmunity) and metabolite exchange, may contribute to this disruption. Susceptibility genes may thus be related to the causes and influencers of disease, rather than (and as well as) to the disease itself. PMID:23533776

  19. Division protein interaction web: identification of a phylogenetically conserved common interactome between Streptococcus pneumoniae and Escherichia coli.

    PubMed

    Maggi, Silvia; Massidda, Orietta; Luzi, Giuseppe; Fadda, Daniela; Paolozzi, Luciano; Ghelardini, Patrizia

    2008-10-01

    The ability of each of the 11 Streptococcus pneumoniae division proteins to interact with itself and with each of the remaining proteins was studied in 66 combinations of protein pairs, using a bacterial two-hybrid system. Interactions (homo- or hetero-dimerizations) were detected between 37 protein pairs, whereas 29 protein pairs did not interact. In some cases, positive interactions of the S. pneumoniae proteins were confirmed by co-immunoprecipitation experiments in Escherichia coli. Comparison between the S. pneumoniae division protein interaction web and that of E. coli, the only micro-organisms for which the whole division interactome has been described systematically, was also performed. At least nine division proteins, ZapA, FtsZ, FtsA, FtsK, FtsQ/DivIB, FtsB/DivIC, FtsL, FtsI and FtsW, are believed to have a conserved function between these bacteria and thus we may say that a significant part of the interactions are conserved. Out of 45 protein pairs tested in both bacteria, 30 showed the same behaviour: 23 interacted while seven did not. In agreement with these results, cross-interactions between S. pneumoniae proteins and the corresponding E. coli orthologues were observed. Taken together, these results suggest a phylogenetically conserved minimal common interactome of the division proteins.

  20. Neural mechanisms of spatiotemporal signal processing

    NASA Astrophysics Data System (ADS)

    Khanbabaie Shoub, Shaban (Reza)

    We have studied the synaptic, dendritic, and network mechanisms of spatiotemporal signal processing underlying the computation of visual motion in the avian tectum. Such mechanisms are critical for information processing in all vertebrates, but have been difficult to elucidate in mammals because of anatomical limitations. We have therefore developed a chick tectal slice preparation, which has features that help us circumvent these limitations. Using single-electrode multi-pulse synaptic stimulation experiments we found that the SGC-I cell responds to synaptic stimulation in a binary manner and its response is phasic in a time dependent probabilistic manner over large time scales. Synaptic inputs at two locations typically interact in a mutually exclusive manner when delivered within the "interaction time" of approximately 30 ms. Then we constructed a model of SGC-I cell and the retinal inputs to examine the role of the observed non-linear cellular properties in shaping the response of SGC-I neurons to assumed retinal representations of dynamic spatiotemporal visual stimuli. We found that by these properties, SGC-I cells can classify different stimuli. Especially without the phasic synaptic signal transfer the model SGC-I cell fails to distinguish between the static stationary stimuli and dynamic spatiotemporal stimuli. Based on one-site synaptic response probability and the assumption of independent neighboring dendritic endings we predicted the response probability of SGC-I cells to multiple synaptic inputs. We tested this independence-based model prediction and found that the independency assumption is not valid. The measured SGC-I response probability to multiple synaptic inputs does not increase with the number of synaptic inputs. The presence of GABAergic horizontal cells in layer 5 suggest an inhibitory effect of these cells on the SGC-I retino-tectal synaptic responses. In our experiment we found that the measured SGC-I response probability to multiple

  1. Precursor of transition to turbulence: spatiotemporal wave front.

    PubMed

    Bhaumik, S; Sengupta, T K

    2014-04-01

    To understand transition to turbulence via 3D disturbance growth, we report here results obtained from the solution of Navier-Stokes equation (NSE) to reproduce experimental results obtained by minimizing background disturbances and imposing deterministic excitation inside the shear layer. A similar approach was adopted in Sengupta and Bhaumik [Phys. Rev. Lett. 107, 154501 (2011)], where a route of transition from receptivity to fully developed turbulent stage was explained for 2D flow in terms of the spatio-temporal wave-front (STWF). The STWF was identified as the unit process of 2D turbulence creation for low amplitude wall excitation. Theoretical prediction of STWF for boundary layer was established earlier in Sengupta, Rao, and Venkatasubbaiah [Phys. Rev. Lett. 96, 224504 (2006)] from the Orr-Sommerfeld equation as due to spatiotemporal instability. Here, the same unit process of the STWF during transition is shown to be present for 3D disturbance field from the solution of governing NSE.

  2. A semiparametric spatio-temporal model for solar irradiance data

    DOE PAGES

    Patrick, Joshua D.; Harvill, Jane L.; Hansen, Clifford W.

    2016-03-01

    Here, we evaluate semiparametric spatio-temporal models for global horizontal irradiance at high spatial and temporal resolution. These models represent the spatial domain as a lattice and are capable of predicting irradiance at lattice points, given data measured at other lattice points. Using data from a 1.2 MW PV plant located in Lanai, Hawaii, we show that a semiparametric model can be more accurate than simple interpolation between sensor locations. We investigate spatio-temporal models with separable and nonseparable covariance structures and find no evidence to support assuming a separable covariance structure. These results indicate a promising approach for modeling irradiance atmore » high spatial resolution consistent with available ground-based measurements. Moreover, this kind of modeling may find application in design, valuation, and operation of fleets of utility-scale photovoltaic power systems.« less

  3. Noise tolerant spatiotemporal chaos computing

    SciTech Connect

    Kia, Behnam; Kia, Sarvenaz; Ditto, William L.; Lindner, John F.; Sinha, Sudeshna

    2014-12-01

    We introduce and design a noise tolerant chaos computing system based on a coupled map lattice (CML) and the noise reduction capabilities inherent in coupled dynamical systems. The resulting spatiotemporal chaos computing system is more robust to noise than a single map chaos computing system. In this CML based approach to computing, under the coupled dynamics, the local noise from different nodes of the lattice diffuses across the lattice, and it attenuates each other's effects, resulting in a system with less noise content and a more robust chaos computing architecture.

  4. Comprehensive Protein Interactome Analysis of a Key RNA Helicase: Detection of Novel Stress Granule Proteins

    PubMed Central

    Bish, Rebecca; Cuevas-Polo, Nerea; Cheng, Zhe; Hambardzumyan, Dolores; Munschauer, Mathias; Landthaler, Markus; Vogel, Christine

    2015-01-01

    DDX6 (p54/RCK) is a human RNA helicase with central roles in mRNA decay and translation repression. To help our understanding of how DDX6 performs these multiple functions, we conducted the first unbiased, large-scale study to map the DDX6-centric protein-protein interactome using immunoprecipitation and mass spectrometry. Using DDX6 as bait, we identify a high-confidence and high-quality set of protein interaction partners which are enriched for functions in RNA metabolism and ribosomal proteins. The screen is highly specific, maximizing the number of true positives, as demonstrated by the validation of 81% (47/58) of the RNA-independent interactors through known functions and interactions. Importantly, we minimize the number of indirect interaction partners through use of a nuclease-based digestion to eliminate RNA. We describe eleven new interactors, including proteins involved in splicing which is an as-yet unknown role for DDX6. We validated and characterized in more detail the interaction of DDX6 with Nuclear fragile X mental retardation-interacting protein 2 (NUFIP2) and with two previously uncharacterized proteins, FAM195A and FAM195B (here referred to as granulin-1 and granulin-2, or GRAN1 and GRAN2). We show that NUFIP2, GRAN1, and GRAN2 are not P-body components, but re-localize to stress granules upon exposure to stress, suggesting a function in translation repression in the cellular stress response. Using a complementary analysis that resolved DDX6’s multiple complex memberships, we further validated these interaction partners and the presence of splicing factors. As DDX6 also interacts with the E3 SUMO ligase TIF1β, we tested for and observed a significant enrichment of sumoylation amongst DDX6’s interaction partners. Our results represent the most comprehensive screen for direct interaction partners of a key regulator of RNA life cycle and localization, highlighting new stress granule components and possible DDX6 functions—many of which are

  5. A weighted and integrated drug-target interactome: drug repurposing for schizophrenia as a use case

    PubMed Central

    2015-01-01

    Background Computational pharmacology can uniquely address some issues in the process of drug development by providing a macroscopic view and a deeper understanding of drug action. Specifically, network-assisted approach is promising for the inference of drug repurposing. However, the drug-target associations coming from different sources and various assays have much noise, leading to an inflation of the inference errors. To reduce the inference errors, it is necessary and critical to create a comprehensive and weighted data set of drug-target associations. Results In this study, we created a weighted and integrated drug-target interactome (WinDTome) to provide a comprehensive resource of drug-target associations for computational pharmacology. We first collected drug-target interactions from six commonly used drug-target centered data sources including DrugBank, KEGG, TTD, MATADOR, PDSP Ki Database, and BindingDB. Then, we employed the record linkage method to normalize drugs and targets to the unique identifiers by utilizing the public data sources including PubChem, Entrez Gene, and UniProt. To assess the reliability of the drug-target associations, we assigned two scores (Score_S and Score_R) to each drug-target association based on their data sources and publication references. Consequently, the WinDTome contains 546,196 drug-target associations among 303,018 compounds and 4,113 genes. To assess the application of the WinDTome, we designed a network-based approach for drug repurposing using mental disorder schizophrenia (SCZ) as a case. Starting from 41 known SCZ drugs and their targets, we inferred a total of 264 potential SCZ drugs through the associations of drug-target with Score_S higher than two in WinDTome and human protein-protein interactions. Among the 264 SCZ-related drugs, 39 drugs have been investigated in clinical trials for SCZ treatment and 74 drugs for the treatment of other mental disorders, respectively. Compared with the results using other

  6. Improving the yeast two-hybrid system with permutated fusions proteins: the Varicella Zoster Virus interactome

    PubMed Central

    2010-01-01

    Background Yeast two-hybrid (Y2H) screens have been among the most powerful methods to detect and analyze protein-protein interactions. However, they suffer from a significant degree of false negatives, i.e. true interactions that are not detected, and to a certain degree from false positives, i.e. interactions that appear to take place only in the context of the Y2H assay. While the fraction of false positives remains difficult to estimate, the fraction of false negatives in typical Y2H screens is on the order of 70-90%. Here we present novel Y2H vectors that significantly decrease the number of false negatives and help to mitigate the false positive problem. Results We have constructed two new vectors (pGBKCg and pGADCg) that allow us to make both C-terminal fusion proteins of DNA-binding and activation domains. Both vectors can be combined with existing vectors for N-terminal fusions and thus allow four different bait-prey combinations: NN, CC, NC, and CN. We have tested all ~4,900 pairwise combinations of the 70 Varicella-Zoster-Virus (VZV) proteins for interactions, using all possible combinations. About ~20,000 individual Y2H tests resulted in 182 NN, 89 NC, 149 CN, and 144 CC interactions. Overlap between screens ranged from 17% (NC-CN) to 43% (CN-CC). Performing four screens (i.e. permutations) instead of one resulted in about twice as many interactions and thus much fewer false negatives. In addition, interactions that are found in multiple combinations confirm each other and thus provide a quality score. This study is the first systematic analysis of such N- and C-terminal Y2H vectors. Conclusions Permutations of C- and N-terminal Y2H vectors dramatically increase the coverage of interactome studies and thus significantly reduce the number of false negatives. We suggest that future interaction screens should use such vector combinations on a routine basis, not the least because they provide a built-in quality score for Y2H interactions that can provide a

  7. Comprehensive Protein Interactome Analysis of a Key RNA Helicase: Detection of Novel Stress Granule Proteins.

    PubMed

    Bish, Rebecca; Cuevas-Polo, Nerea; Cheng, Zhe; Hambardzumyan, Dolores; Munschauer, Mathias; Landthaler, Markus; Vogel, Christine

    2015-01-01

    DDX6 (p54/RCK) is a human RNA helicase with central roles in mRNA decay and translation repression. To help our understanding of how DDX6 performs these multiple functions, we conducted the first unbiased, large-scale study to map the DDX6-centric protein-protein interactome using immunoprecipitation and mass spectrometry. Using DDX6 as bait, we identify a high-confidence and high-quality set of protein interaction partners which are enriched for functions in RNA metabolism and ribosomal proteins. The screen is highly specific, maximizing the number of true positives, as demonstrated by the validation of 81% (47/58) of the RNA-independent interactors through known functions and interactions. Importantly, we minimize the number of indirect interaction partners through use of a nuclease-based digestion to eliminate RNA. We describe eleven new interactors, including proteins involved in splicing which is an as-yet unknown role for DDX6. We validated and characterized in more detail the interaction of DDX6 with Nuclear fragile X mental retardation-interacting protein 2 (NUFIP2) and with two previously uncharacterized proteins, FAM195A and FAM195B (here referred to as granulin-1 and granulin-2, or GRAN1 and GRAN2). We show that NUFIP2, GRAN1, and GRAN2 are not P-body components, but re-localize to stress granules upon exposure to stress, suggesting a function in translation repression in the cellular stress response. Using a complementary analysis that resolved DDX6's multiple complex memberships, we further validated these interaction partners and the presence of splicing factors. As DDX6 also interacts with the E3 SUMO ligase TIF1β, we tested for and observed a significant enrichment of sumoylation amongst DDX6's interaction partners. Our results represent the most comprehensive screen for direct interaction partners of a key regulator of RNA life cycle and localization, highlighting new stress granule components and possible DDX6 functions-many of which are likely

  8. Spatiotemporal evolution of ventricular fibrillation

    NASA Astrophysics Data System (ADS)

    Witkowski, Francis X.; Leon, L. Joshua; Penkoske, Patricia A.; Giles, Wayne R.; Spano, Mark L.; Ditto, William L.; Winfree, Arthur T.

    1998-03-01

    Sudden cardiac death is the leading cause of death in the industrialized world, with the majority of such tragedies being due to ventricular fibrillation. Ventricular fibrillation is a frenzied and irregular disturbance of the heart rhythm that quickly renders the heart incapable of sustaining life. Rotors, electrophysiological structures that emit rotating spiral waves, occur in several systems that all share with the heart the functional properties of excitability and refractoriness. These re-entrant waves, seen in numerical solutions of simplified models of cardiac tissue, may occur during ventricular tachycardias,. It has been difficult to detect such forms of re-entry in fibrillating mammalian ventricles. Here we show that, in isolated perfused dog hearts, high spatial and temporal resolution mapping of optical transmembrane potentials can easily detect transiently erupting rotors during the early phase of ventricular fibrillation. This activity is characterized by a relatively high spatiotemporal cross-correlation. During this early fibrillatory interval, frequent wavefront collisions and wavebreak generation are also dominant features. Interestingly, this spatiotemporal pattern undergoes an evolution to a less highly spatially correlated mechanism that lacks the epicardial manifestations of rotors despite continued myocardial perfusion.

  9. Spatiotemporal Thinking in the Geosciences

    NASA Astrophysics Data System (ADS)

    Shipley, T. F.; Manduca, C. A.; Ormand, C. J.; Tikoff, B.

    2011-12-01

    Reasoning about spatial relations is a critical skill for geoscientists. Within the geosciences different disciplines may reason about different sorts of relationships. These relationships may span vastly different spatial and temporal scales (from the spatial alignment in atoms in crystals to the changes in the shape of plates). As part of work in a research center on spatial thinking in STEM education, we have been working to classify the spatial skills required in geology, develop tests for each spatial skill, and develop the cognitive science tools to promote the critical spatial reasoning skills. Research in psychology, neurology and linguistics supports a broad classification of spatial skills along two dimensions: one versus many objects (which roughly translates to object- focused and navigation focused skills) and static versus dynamic spatial relations. The talk will focus on the interaction of space and time in spatial cognition in the geosciences. We are working to develop measures of skill in visualizing spatiotemporal changes. A new test developed to measure visualization of brittle deformations will be presented. This is a skill that has not been clearly recognized in the cognitive science research domain and thus illustrates the value of interdisciplinary work that combines geosciences with cognitive sciences. Teaching spatiotemporal concepts can be challenging. Recent theoretical work suggests analogical reasoning can be a powerful tool to aid student learning to reason about temporal relations using spatial skills. Recent work in our lab has found that progressive alignment of spatial and temporal scales promotes accurate reasoning about temporal relations at geological time scales.

  10. Large-scale de novo prediction of physical protein-protein association.

    PubMed

    Elefsinioti, Antigoni; Saraç, Ömer Sinan; Hegele, Anna; Plake, Conrad; Hubner, Nina C; Poser, Ina; Sarov, Mihail; Hyman, Anthony; Mann, Matthias; Schroeder, Michael; Stelzl, Ulrich; Beyer, Andreas

    2011-11-01

    Information about the physical association of proteins is extensively used for studying cellular processes and disease mechanisms. However, complete experimental mapping of the human interactome will remain prohibitively difficult in the near future. Here we present a map of predicted human protein interactions that distinguishes functional association from physical binding. Our network classifies more than 5 million protein pairs predicting 94,009 new interactions with high confidence. We experimentally tested a subset of these predictions using yeast two-hybrid analysis and affinity purification followed by quantitative mass spectrometry. Thus we identified 462 new protein-protein interactions and confirmed the predictive power of the network. These independent experiments address potential issues of circular reasoning and are a distinctive feature of this work. Analysis of the physical interactome unravels subnetworks mediating between different functional and physical subunits of the cell. Finally, we demonstrate the utility of the network for the analysis of molecular mechanisms of complex diseases by applying it to genome-wide association studies of neurodegenerative diseases. This analysis provides new evidence implying TOMM40 as a factor involved in Alzheimer's disease. The network provides a high-quality resource for the analysis of genomic data sets and genetic association studies in particular. Our interactome is available via the hPRINT web server at: www.print-db.org.

  11. Spatiotemporal behavior and nonlinear dynamics in a phase conjugate resonator

    NASA Technical Reports Server (NTRS)

    Liu, Siuying Raymond

    1993-01-01

    The work described can be divided into two parts. The first part is an investigation of the transient behavior and stability property of a phase conjugate resonator (PCR) below threshold. The second part is an experimental and theoretical study of the PCR's spatiotemporal dynamics above threshold. The time-dependent coupled wave equations for four-wave mixing (FWM) in a photorefractive crystal, with two distinct interaction regions caused by feedback from an ordinary mirror, was used to model the transient dynamics of a PCR below threshold. The conditions for self-oscillation were determined and the solutions were used to define the PCR's transfer function and analyze its stability. Experimental results for the buildup and decay times confirmed qualitatively the predicted behavior. Experiments were carried out above threshold to study the spatiotemporal dynamics of the PCR as a function of Pragg detuning and the resonator's Fresnel number. The existence of optical vortices in the wavefront were identified by optical interferometry. It was possible to describe the transverse dynamics and the spatiotemporal instabilities by modeling the three-dimensional-coupled wave equations in photorefractive FWM using a truncated modal expansion approach.

  12. A centrosome interactome provides insight into organelle assembly and reveals a non-duplication role for Plk4

    PubMed Central

    Galletta, Brian J.; Fagerstrom, Carey J.; Schoborg, Todd A.; McLamarrah, Tiffany A.; Ryniawec, John M.; Buster, Daniel W.; Slep, Kevin C.; Rogers, Gregory C.; Rusan, Nasser M.

    2016-01-01

    The centrosome is the major microtubule-organizing centre of many cells, best known for its role in mitotic spindle organization. How the proteins of the centrosome are accurately assembled to carry out its many functions remains poorly understood. The non-membrane-bound nature of the centrosome dictates that protein–protein interactions drive its assembly and functions. To investigate this massive macromolecular organelle, we generated a ‘domain-level' centrosome interactome using direct protein–protein interaction data from a focused yeast two-hybrid screen. We then used biochemistry, cell biology and the model organism Drosophila to provide insight into the protein organization and kinase regulatory machinery required for centrosome assembly. Finally, we identified a novel role for Plk4, the master regulator of centriole duplication. We show that Plk4 phosphorylates Cep135 to properly position the essential centriole component Asterless. This interaction landscape affords a critical framework for research of normal and aberrant centrosomes. PMID:27558293

  13. Characterization of the Human NEK7 Interactome Suggests Catalytic and Regulatory Properties Distinct from Those of NEK6

    PubMed Central

    2015-01-01

    Human NEK7 is a regulator of cell division and plays an important role in growth and survival of mammalian cells. Human NEK6 and NEK7 are closely related, consisting of a conserved C-terminal catalytic domain and a nonconserved and disordered N-terminal regulatory domain, crucial to mediate the interactions with their respective proteins. Here, in order to better understand NEK7 cellular functions, we characterize the NEK7 interactome by two screening approaches: one using a yeast two-hybrid system and the other based on immunoprecipitation followed by mass spectrometry analysis. These approaches led to the identification of 61 NEK7 interactors that contribute to a variety of biological processes, including cell division. Combining additional interaction and phosphorylation assays from yeast two-hybrid screens, we validated CC2D1A, TUBB2B, MNAT1, and NEK9 proteins as potential NEK7 interactors and substrates. Notably, endogenous RGS2, TUBB, MNAT1, NEK9, and PLEKHA8 localized with NEK7 at key sites throughout the cell cycle, especially during mitosis and cytokinesis. Furthermore, we obtained evidence that the closely related kinases NEK6 and NEK7 do not share common interactors, with the exception of NEK9, and display different modes of protein interaction, depending on their N- and C-terminal regions, in distinct fashions. In summary, our work shows for the first time a comprehensive NEK7 interactome that, combined with functional in vitro and in vivo assays, suggests that NEK7 is a multifunctional kinase acting in different cellular processes in concert with cell division signaling and independently of NEK6. PMID:25093993

  14. Spatio-Temporal Clustering of Monitoring Network

    NASA Astrophysics Data System (ADS)

    Hussain, I.; Pilz, J.

    2009-04-01

    Pakistan has much diversity in seasonal variation of different locations. Some areas are in desserts and remain very hot and waterless, for example coastal areas are situated along the Arabian Sea and have very warm season and a little rainfall. Some areas are covered with mountains, have very low temperature and heavy rainfall; for instance Karakoram ranges. The most important variables that have an impact on the climate are temperature, precipitation, humidity, wind speed and elevation. Furthermore, it is hard to find homogeneous regions in Pakistan with respect to climate variation. Identification of homogeneous regions in Pakistan can be useful in many aspects. It can be helpful for prediction of the climate in the sub-regions and for optimizing the number of monitoring sites. In the earlier literature no one tried to identify homogeneous regions of Pakistan with respect to climate variation. There are only a few papers about spatio-temporal clustering of monitoring network. Steinhaus (1956) presented the well-known K-means clustering method. It can identify a predefined number of clusters by iteratively assigning centriods to clusters based. Castro et al. (1997) developed a genetic heuristic algorithm to solve medoids based clustering. Their method is based on genetic recombination upon random assorting recombination. The suggested method is appropriate for clustering the attributes which have genetic characteristics. Sap and Awan (2005) presented a robust weighted kernel K-means algorithm incorporating spatial constraints for clustering climate data. The proposed algorithm can effectively handle noise, outliers and auto-correlation in the spatial data, for effective and efficient data analysis by exploring patterns and structures in the data. Soltani and Modarres (2006) used hierarchical and divisive cluster analysis to categorize patterns of rainfall in Iran. They only considered rainfall at twenty-eight monitoring sites and concluded that eight clusters

  15. Front dynamics in the presence of spatiotemporal structured noises.

    PubMed

    Santos, M A; Sancho, J M

    2001-07-01

    Front dynamics modeled by a reaction-diffusion equation are studied under the influence of spatiotemporal structured noises. An effective deterministic model is analytical derived where the noise parameters, intensity, correlation time, and correlation length appear explicitly. The different effects of these parameters are discussed for the Ginzburg-Landau and Schlögl models. We obtain an analytical expression for the front velocity as a function of the noise parameters. Numerical simulation results are in a good agreement with the theoretical predictions.

  16. Host-Mycobacterium avium subsp. paratuberculosis interactome reveals a novel iron assimilation mechanism linked to nitric oxide stress during early infection

    PubMed Central

    2013-01-01

    Background The initial interaction between host cell and pathogen sets the stage for the ensuing infection and ultimately determine the course of disease. However, there is limited knowledge of the transcripts utilized by host and pathogen and how they may impact one another during this critical step. The purpose of this study was to create a host-Mycobacterium avium subsp. paratuberculosis (MAP) interactome for early infection in an epithelium-macrophage co-culture system using RNA-seq. Results Establishment of the host-MAP interactome revealed a novel iron assimilation system for carboxymycobactin. Iron assimilation is linked to nitric oxide synthase-2 production by the host and subsequent nitric oxide buildup. Iron limitation as well as nitric oxide is a prompt for MAP to enter into an iron sequestration program. This new iron sequestration program provides an explanation for mycobactin independence in some MAP strains grown in vitro as well as during infection within the host cell. Utilization of such a pathway is likely to aid MAP establishment and long-term survival within the host. Conclusions The host-MAP interactome identified a number of metabolic, DNA repair and virulence genes worthy for consideration as novel drug targets as well as future pathogenesis studies. Reported interactome data may also be utilized to conduct focused, hypothesis-driven research. Co-culture of uninfected bovine epithelial cells (MAC-T) and primary bovine macrophages creates a tolerant genotype as demonstrated by downregulation of inflammatory pathways. This co-culture system may serve as a model to investigate other bovine enteric pathogens. PMID:24112552

  17. Evolutionary diversification of the BetaM interactome acquired through co-option of the ATP1B4 gene in placental mammals

    PubMed Central

    Korneenko, Tatyana V.; Pestov, Nikolay B.; Ahmad, Nisar; Okkelman, Irina A.; Dmitriev, Ruslan I.; Shakhparonov, Mikhail I.; Modyanov, Nikolai N.

    2016-01-01

    ATP1B4 genes represent a rare instance of orthologous vertebrate gene co-option that radically changed properties of the encoded BetaM proteins, which function as Na,K-ATPase subunits in lower vertebrates and birds. Eutherian BetaM has lost its ancestral function and became a muscle-specific resident of the inner nuclear membrane. Our earlier work implicated BetaM in regulation of gene expression through direct interaction with the transcriptional co-regulator SKIP. To gain insight into evolution of BetaM interactome we performed expanded screening of eutherian and avian cDNA libraries using yeast-two-hybrid and split-ubiquitin systems. The inventory of identified BetaM interactors includes lamina-associated protein LAP-1, myocyte nuclear envelope protein Syne1, BetaM itself, heme oxidases HMOX1 and HMOX2; transcription factor LZIP/CREB3, ERGIC3, PHF3, reticulocalbin-3, and β-sarcoglycan. No new interactions were found for chicken BetaM and human Na,K-ATPase β1, β2 and β3 isoforms, indicating the uniqueness of eutherian BetaM interactome. Analysis of truncated forms of BetaM indicates that residues 72-98 adjacent to the membrane in nucleoplasmic domain are important for the interaction with SKIP. These findings demonstrate that evolutionary alterations in structural and functional properties of eutherian BetaM proteins are associated with the increase in its interactome complexity. PMID:26939788

  18. Interactome analysis reveals that FAM161A, deficient in recessive retinitis pigmentosa, is a component of the Golgi-centrosomal network.

    PubMed

    Di Gioia, Silvio Alessandro; Farinelli, Pietro; Letteboer, Stef J F; Arsenijevic, Yvan; Sharon, Dror; Roepman, Ronald; Rivolta, Carlo

    2015-06-15

    Defects in FAM161A, a protein of unknown function localized at the cilium of retinal photoreceptor cells, cause retinitis pigmentosa, a form of hereditary blindness. By using different fragments of this protein as baits to screen cDNA libraries of human and bovine retinas, we defined a yeast two-hybrid-based FAM161A interactome, identifying 53 bona fide partners. In addition to statistically significant enrichment in ciliary proteins, as expected, this interactome revealed a substantial bias towards proteins from the Golgi apparatus, the centrosome and the microtubule network. Validation of interaction with key partners by co-immunoprecipitation and proximity ligation assay confirmed that FAM161A is a member of the recently recognized Golgi-centrosomal interactome, a network of proteins interconnecting Golgi maintenance, intracellular transport and centrosome organization. Notable FAM161A interactors included AKAP9, FIP3, GOLGA3, KIFC3, KLC2, PDE4DIP, NIN and TRIP11. Furthermore, analysis of FAM161A localization during the cell cycle revealed that this protein followed the centrosome during all stages of mitosis, likely reflecting a specific compartmentalization related to its role at the ciliary basal body during the G0 phase. Altogether, these findings suggest that FAM161A's activities are probably not limited to ciliary tasks but also extend to more general cellular functions, highlighting possible novel mechanisms for the molecular pathology of retinal disease. PMID:25749990

  19. Spatiotemporally controlled single cell sonoporation

    PubMed Central

    Fan, Zhenzhen; Liu, Haiyan; Mayer, Michael; Deng, Cheri X.

    2012-01-01

    This paper presents unique approaches to enable control and quantification of ultrasound-mediated cell membrane disruption, or sonoporation, at the single-cell level. Ultrasound excitation of microbubbles that were targeted to the plasma membrane of HEK-293 cells generated spatially and temporally controlled membrane disruption with high repeatability. Using whole-cell patch clamp recording combined with fluorescence microscopy, we obtained time-resolved measurements of single-cell sonoporation and quantified the size and resealing rate of pores. We measured the intracellular diffusion coefficient of cytoplasmic RNA/DNA from sonoporation-induced transport of an intercalating fluorescent dye into and within single cells. We achieved spatiotemporally controlled delivery with subcellular precision and calcium signaling in targeted cells by selective excitation of microbubbles. Finally, we utilized sonoporation to deliver calcein, a membrane-impermeant substrate of multidrug resistance protein-1 (MRP1), into HEK-MRP1 cells, which overexpress MRP1, and monitored the calcein efflux by MRP1. This approach made it possible to measure the efflux rate in individual cells and to compare it directly to the efflux rate in parental control cells that do not express MRP1. PMID:23012425

  20. Modeling microbial communities: current, developing, and future technologies for predicting microbial community interaction.

    PubMed

    Larsen, Peter; Hamada, Yuki; Gilbert, Jack

    2012-07-31

    Never has there been a greater opportunity for investigating microbial communities. Not only are the profound effects of microbial ecology on every aspect of Earth's geochemical cycles beginning to be understood, but also the analytical and computational tools for investigating microbial Earth are undergoing a rapid revolution. This environmental microbial interactome, the system of interactions between the microbiome and the environment, has shaped the planet's past and will undoubtedly continue to do so in the future. We review recent approaches for modeling microbial community structures and the interactions of microbial populations with their environments. Different modeling approaches consider the environmental microbial interactome from different aspects, and each provides insights to different facets of microbial ecology. We discuss the challenges and opportunities for the future of microbial modeling and describe recent advances in microbial community modeling that are extending current descriptive technologies into a predictive science.

  1. Modeling microbial communities: current, developing, and future technologies for predicting microbial community interaction.

    PubMed

    Larsen, Peter; Hamada, Yuki; Gilbert, Jack

    2012-07-31

    Never has there been a greater opportunity for investigating microbial communities. Not only are the profound effects of microbial ecology on every aspect of Earth's geochemical cycles beginning to be understood, but also the analytical and computational tools for investigating microbial Earth are undergoing a rapid revolution. This environmental microbial interactome, the system of interactions between the microbiome and the environment, has shaped the planet's past and will undoubtedly continue to do so in the future. We review recent approaches for modeling microbial community structures and the interactions of microbial populations with their environments. Different modeling approaches consider the environmental microbial interactome from different aspects, and each provides insights to different facets of microbial ecology. We discuss the challenges and opportunities for the future of microbial modeling and describe recent advances in microbial community modeling that are extending current descriptive technologies into a predictive science. PMID:22465599

  2. Mercury Toolset for Spatiotemporal Metadata

    NASA Technical Reports Server (NTRS)

    Wilson, Bruce E.; Palanisamy, Giri; Devarakonda, Ranjeet; Rhyne, B. Timothy; Lindsley, Chris; Green, James

    2010-01-01

    Mercury (http://mercury.ornl.gov) is a set of tools for federated harvesting, searching, and retrieving metadata, particularly spatiotemporal metadata. Version 3.0 of the Mercury toolset provides orders of magnitude improvements in search speed, support for additional metadata formats, integration with Google Maps for spatial queries, facetted type search, support for RSS (Really Simple Syndication) delivery of search results, and enhanced customization to meet the needs of the multiple projects that use Mercury. It provides a single portal to very quickly search for data and information contained in disparate data management systems, each of which may use different metadata formats. Mercury harvests metadata and key data from contributing project servers distributed around the world and builds a centralized index. The search interfaces then allow the users to perform a variety of fielded, spatial, and temporal searches across these metadata sources. This centralized repository of metadata with distributed data sources provides extremely fast search results to the user, while allowing data providers to advertise the availability of their data and maintain complete control and ownership of that data. Mercury periodically (typically daily) harvests metadata sources through a collection of interfaces and re-indexes these metadata to provide extremely rapid search capabilities, even over collections with tens of millions of metadata records. A number of both graphical and application interfaces have been constructed within Mercury, to enable both human users and other computer programs to perform queries. Mercury was also designed to support multiple different projects, so that the particular fields that can be queried and used with search filters are easy to configure for each different project.

  3. Mercury Toolset for Spatiotemporal Metadata

    NASA Astrophysics Data System (ADS)

    Devarakonda, Ranjeet; Palanisamy, Giri; Green, James; Wilson, Bruce; Rhyne, B. Timothy; Lindsley, Chris

    2010-06-01

    Mercury (http://mercury.ornl.gov) is a set of tools for federated harvesting, searching, and retrieving metadata, particularly spatiotemporal metadata. Version 3.0 of the Mercury toolset provides orders of magnitude improvements in search speed, support for additional metadata formats, integration with Google Maps for spatial queries, facetted type search, support for RSS (Really Simple Syndication) delivery of search results, and enhanced customization to meet the needs of the multiple projects that use Mercury. It provides a single portal to very quickly search for data and information contained in disparate data management systems, each of which may use different metadata formats. Mercury harvests metadata and key data from contributing project servers distributed around the world and builds a centralized index. The search interfaces then allow the users to perform a variety of fielded, spatial, and temporal searches across these metadata sources. This centralized repository of metadata with distributed data sources provides extremely fast search results to the user, while allowing data providers to advertise the availability of their data and maintain complete control and ownership of that data. Mercury periodically (typically daily)harvests metadata sources through a collection of interfaces and re-indexes these metadata to provide extremely rapid search capabilities, even over collections with tens of millions of metadata records. A number of both graphical and application interfaces have been constructed within Mercury, to enable both human users and other computer programs to perform queries. Mercury was also designed to support multiple different projects, so that the particular fields that can be queried and used with search filters are easy to configure for each different project.

  4. Dynamic proximity of spatio-temporal sequences.

    PubMed

    Horn, David; Dror, Gideon; Quenet, Brigitte

    2004-09-01

    Recurrent networks can generate spatio-temporal neural sequences of very large cycles, having an apparent random behavior. Nonetheless a proximity measure between these sequences may be defined through comparison of the synaptic weight matrices that generate them. Following the dynamic neural filter (DNF) formalism we demonstrate this concept by comparing teacher and student recurrent networks of binary neurons. We show that large sequences, providing a training set well exceeding the Cover limit, allow for good determination of the synaptic matrices. Alternatively, assuming the matrices to be known, very fast determination of the biases can be achieved. Thus, a spatio-temporal sequence may be regarded as spatio-temporal encoding of the bias vector. We introduce a linear support vector machine (SVM) variant of the DNF in order to specify an optimal weight matrix. This approach allows us to deal with noise. Spatio-temporal sequences generated by different DNFs with the same number of neurons may be compared by calculating correlations of the synaptic matrices of the reconstructed DNFs. Other types of spatio-temporal sequences need the introduction of hidden neurons, and/or the use of a kernel variant of the SVM approach. The latter is being defined as a recurrent support vector network (RSVN).

  5. Spatiotemporal testing and modeling of catfish retinal neurons.

    PubMed Central

    Krausz, H I; Naka, K

    1980-01-01

    The responses of retinal neurons depend on the interaction of both temporal and spatial aspects of a light stimulus. We developed a linear spatiotemporal model of receptor and horizontal cell layers in the catfish retina based on reciprocal interactions between both layers and coupling within each. Horizontal cell transfer properties were measured experimentally using white-noise intensity modulated light spots of different diameters and were compared with analytical predictions based on the model. Good agreement was obtained with a reasonable choice of model space-constants and feedback parameters. Furthermore, the same set of parameter values determined from spot experiments enabled accurate prediction of experimental horizontal cell responses to traveling gratings. The proposed feedback connections from horizontal cells to receptors quicken the time-course of responses in both layers and sharpen receptive fields. PMID:7260243

  6. Hierarchical Bayesian space-time interpolation versus spatio-temporal BME approach

    NASA Astrophysics Data System (ADS)

    Hussain, I.; Pilz, J.; Spoeck, G.

    2010-03-01

    The restrictions of the analysis of natural processes which are observed at any point in space or time to a purely spatial or purely temporal domain may cause loss of information and larger prediction errors. Moreover, the arbitrary combinations of purely spatial and purely temporal models may not yield valid models for the space-time domain. For such processes the variation can be characterized by sophisticated spatio-temporal modeling. In the present study the composite spatio-temporal Bayesian maximum entropy (BME) method and transformed hierarchical Bayesian space-time interpolation are used in order to predict precipitation in Pakistan during the monsoon period. Monthly average precipitation data whose time domain is the monsoon period for the years 1974-2000 and whose spatial domain are various regions in Pakistan are considered. The prediction of space-time precipitation is applicable in many sectors of industry and economy in Pakistan especially; the agricultural sector. Mean field maps and prediction error maps for both methods are estimated and compared. In this paper it is shown that the transformed hierarchical Bayesian model is providing more accuracy and lower prediction error compared to the spatio-temporal Bayesian maximum entropy method; additionally, the transformed hierarchical Bayesian model also provides predictive distributions.

  7. BME analysis of spatiotemporal particulate matter distributions in North Carolina

    NASA Astrophysics Data System (ADS)

    Christakos, George; Serre, Marc L.

    Spatiotemporal maps of particulate matter (PM) concentrations contribute considerably to the understanding of the underlying natural processes and the adequate assessment of the PM health effects. These maps should be derived using an approach that combines rigorous mathematical formulation with sound science. To achieve such a task, the PM 10 distribution in the state of North Carolina is studied using the Bayesian maximum entropy (BME) mapping method. This method is based on a realistic representation of the spatiotemporal domain, which can integrate rigorously and efficiently various forms of physical knowledge and sources of uncertainty. BME offers a complete characterization of PM 10 concentration patterns in terms of multi-point probability distributions and allows considerable flexibility regarding the choice of the appropriate concentration estimates. The PM 10 maps show significant variability both spatially and temporally, a finding that may be associated with geographical characteristics, climatic changes, seasonal patterns, and random fluctuations. The inherently spatiotemporal nature of PM 10 variation is demonstrated by means of theoretical considerations as well as in terms of the more accurate PM 10 predictions of composite space/time analysis compared to spatial estimation. It is shown that the study of PM 10 distributions in North Carolina can be improved by properly incorporating uncertain data into the mapping process, whereas more informative estimates are generated by considering soft data at the estimation points. Uncertainty maps illustrate the significance of stochastic PM 10 characterization in space/time, and identify limitations associated with inadequate interpolation techniques. Stochastic PM 10 analysis has important applications in the optimization of monitoring networks in space and time, environmental risk assessment, health management and administration, etc.

  8. Intracellular interactome of secreted antibody Fab fragment in Pichia pastoris reveals its routes of secretion and degradation.

    PubMed

    Pfeffer, Martin; Maurer, Michael; Stadlmann, Johannes; Grass, Josephine; Delic, Marizela; Altmann, Friedrich; Mattanovich, Diethard

    2012-03-01

    Protein translation, translocation, folding, processing, and secretion in eukaryotic cells are complex and not always straightforward processes, e.g., different routes of secretion and degradation exist. Formation of malfolded proteins in the endoplasmic reticulum (ER) can be one of the major bottlenecks for recombinant protein production. In this regard, an in-depth analysis of the interactions of a secreted protein during its pathway through the cell may be beneficial, as realized in this study for the methylotrophic yeast Pichia pastoris. The antibody fragment Fab3H6 used here is the anti-idiotype to the HIV neutralizing antibody 2F5 and is known to be intracellularly degraded in significant amounts when expressed in P. pastoris. The interactome of Fab3H6 was analyzed by using a pull-down mass spectrometry approach, and 23 proteins were found to bind specifically to the antibody fragment. Those allowed concluding that Fab3H6 is post-translationally translocated into the ER and degraded via the proteasome as well as the vacuole. In line with this, the expression of Fab3H6 increased the proteasomal activities by over 20%. Partial inhibition of the proteasome resulted in a significant increase of extracellular Fab3H6. Thus, it seems that ER quality control overshoots its requirements for the recombinant protein expressed and that more than just terminally malfolded protein is degraded by ER-associated degradation. This work will further facilitate our understanding how recombinant proteins behave in the secretory pathway. PMID:22350260

  9. The interactome of Streptococcus pneumoniae and its bacteriophages show highly specific patterns of interactions among bacteria and their phages.

    PubMed

    Mariano, Rachelle; Wuchty, Stefan; Vizoso-Pinto, Maria G; Häuser, Roman; Uetz, Peter

    2016-01-01

    Although an abundance of bacteriophages exists, little is known about interactions between their proteins and those of their bacterial hosts. Here, we experimentally determined the phage-host interactomes of the phages Dp-1 and Cp-1 and their underlying protein interaction network in the host Streptococcus pneumoniae. We compared our results to the interaction patterns of E. coli phages lambda and T7. Dp-1 and Cp-1 target highly connected host proteins, occupy central network positions, and reach many protein clusters through the interactions of their targets. In turn, lambda and T7 targets cluster to conserved and essential proteins in E. coli, while such patterns were largely absent in S. pneumoniae. Furthermore, targets in E. coli were mutually strongly intertwined, while targets of Dp-1 and Cp-1 were strongly connected through essential and orthologous proteins in their immediate network vicinity. In both phage-host systems, the impact of phages on their protein targets appears to extend from their network neighbors, since proteins that interact with phage targets were located in central network positions, have a strong topologically disruptive effect and touch complexes with high functional heterogeneity. Such observations suggest that the phages, biological impact is accomplished through a surprisingly limited topological reach of their targets. PMID:27103053

  10. AF4 and AF4N protein complexes: recruitment of P-TEFb kinase, their interactome and potential functions

    PubMed Central

    Scholz, Bastian; Kowarz, Eric; Rössler, Tanja; Ahmad, Khalil; Steinhilber, Dieter; Marschalek, Rolf

    2015-01-01

    AF4/AFF1 and AF5/AFF4 are the molecular backbone to assemble “super-elongation complexes” (SECs) that have two main functions: (1) control of transcriptional elongation by recruiting the positive transcription elongation factor b (P-TEFb = CyclinT1/CDK9) that is usually stored in inhibitory 7SK RNPs; (2) binding of different histone methyltransferases, like DOT1L, NSD1 and CARM1. This way, transcribed genes obtain specific histone signatures (e.g. H3K79me2/3, H3K36me2) to generate a transcriptional memory system. Here we addressed several questions: how is P-TEFb recruited into SEC, how is the AF4 interactome composed, and what is the function of the naturally occuring AF4N protein variant which exhibits only the first 360 amino acids of the AF4 full-length protein. Noteworthy, shorter protein variants are a specific feature of all AFF protein family members. Here, we demonstrate that full-length AF4 and AF4N are both catalyzing the transition of P-TEFb from 7SK RNP to their N-terminal domain. We have also mapped the protein-protein interaction network within both complexes. In addition, we have first evidence that the AF4N protein also recruits TFIIH and the tumor suppressor MEN1. This indicate that AF4N may have additional functions in transcriptional initiation and in MEN1-dependend transcriptional processes. PMID:26171280

  11. Topological characteristics of target genes regulated by abiotic-stress-responsible miRNAs in a rice interactome network.

    PubMed

    Zhang, Linzhong; Xuan, Hongdong; Zuo, Yongchun; Xu, Gaojian; Wang, Ping; Song, Youhong; Zhang, Shihua

    2016-05-01

    A great number of microRNAs (miRNAs) have been identified in responding and acting in gene regulatory networks associated with plant tolerance to abiotic stress conditions, such as drought, salinity, and high temperature. The topological exploration of target genes regulated by abiotic-stress-responsible miRNAs (ASRmiRs) in a network facilitates to discover the molecular basis of plant abiotic stress response. This study was based on the staple food rice (Oryza sativa) in which ASRmiRs were manually curated. After having compared the topological properties of target genes (stress-miR-targets) with those (non-stress-miR-targets) not regulated by ASRmiRs in a rice interactome network, we found that stress-miR-targets exhibited distinguishable topological properties. The interaction probability analysis and k-core decomposition showed that stress-miR-targets preferentially interacted with non-stress-miR-targets and located at the peripheral positions in the network. Our results indicated an obvious topological distinction between the two types of genes, reflecting the specific mechanisms of action of stress-miR-targets in rice abiotic stress response. Also, the results may provide valuable clues to elucidate molecular mechanisms of crop response to abiotic stress.

  12. In Vivo Mapping of Eukaryotic RNA Interactomes Reveals Principles of Higher-Order Organization and Regulation.

    PubMed

    Aw, Jong Ghut Ashley; Shen, Yang; Wilm, Andreas; Sun, Miao; Lim, Xin Ni; Boon, Kum-Loong; Tapsin, Sidika; Chan, Yun-Shen; Tan, Cheng-Peow; Sim, Adelene Y L; Zhang, Tong; Susanto, Teodorus Theo; Fu, Zhiyan; Nagarajan, Niranjan; Wan, Yue

    2016-05-19

    Identifying pairwise RNA-RNA interactions is key to understanding how RNAs fold and interact with other RNAs inside the cell. We present a high-throughput approach, sequencing of psoralen crosslinked, ligated, and selected hybrids (SPLASH), that maps pairwise RNA interactions in vivo with high sensitivity and specificity, genome-wide. Applying SPLASH to human and yeast transcriptomes revealed the diversity and dynamics of thousands of long-range intra- and intermolecular RNA-RNA interactions. Our analysis highlighted key structural features of RNA classes, including the modular organization of mRNAs, its impact on translation and decay, and the enrichment of long-range interactions in noncoding RNAs. Additionally, intermolecular mRNA interactions were organized into network clusters and were remodeled during cellular differentiation. We also identified hundreds of known and new snoRNA-rRNA binding sites, expanding our knowledge of rRNA biogenesis. These results highlight the underexplored complexity of RNA interactomes and pave the way to better understanding how RNA organization impacts biology. PMID:27184079

  13. “Stop Ne(c)king around”: How interactomics contributes to functionally characterize Nek family kinases

    PubMed Central

    Meirelles, Gabriela Vaz; Perez, Arina Marina; de Souza, Edmárcia Elisa; Basei, Fernanda Luisa; Papa, Priscila Ferreira; Melo Hanchuk, Talita Diniz; Cardoso, Vanessa Bomfim; Kobarg, Jörg

    2014-01-01

    Aside from Polo and Aurora, a third but less studied kinase family involved in mitosis regulation is the never in mitosis-gene A (NIMA)-related kinases (Neks). The founding member of this family is the sole member NIMA of Aspergillus nidulans, which is crucial for the initiation of mitosis in that organism. All 11 human Neks have been functionally assigned to one of the three core functions established for this family in mammals: (1) centrioles/mitosis; (2) primary ciliary function/ciliopathies; and (3) DNA damage response (DDR). Recent findings, especially on Nek 1 and 8, showed however, that several Neks participate in parallel in at least two of these contexts: primary ciliary function and DDR. In the core section of this in-depth review, we report the current detailed functional knowledge on each of the 11 Neks. In the discussion, we return to the cross-connections among Neks and point out how our and other groups’ functional and interactomics studies revealed that most Neks interact with protein partners associated with two if not all three of the functional contexts. We then raise the hypothesis that Neks may be the connecting regulatory elements that allow the cell to fine tune and synchronize the cellular events associated with these three core functions. The new and exciting findings on the Nek family open new perspectives and should allow the Neks to finally claim the attention they deserve in the field of kinases and cell cycle biology. PMID:24921005

  14. TCTEX1D4 Interactome in Human Testis: Unraveling the Function of Dynein Light Chain in Spermatozoa

    PubMed Central

    Freitas, Maria João; Korrodi-Gregório, Luís; Morais-Santos, Filipa; da Cruz e Silva, Edgar

    2014-01-01

    Abstract Studies were designed to identify the TCTEX1D4 interactome in human testis, with the purpose of unraveling putative protein complexes essential to male reproduction and thus novel TCTEX1D4 functions. TCTEX1D4 is a dynein light chain that belongs to the DYNT1/TCTEX1 family. In spermatozoa, it appears to be important to sperm motility, intraflagellar transport, and acrosome reaction. To contribute to the knowledge on TCTEX1D4 function in testis and spermatozoa, a yeast two-hybrid assay was performed in testis, which allowed the identification of 40 novel TCTEX1D4 interactors. Curiously, another dynein light chain, TCTEX1D2, was identified and its existence demonstrated for the first time in human spermatozoa. Immunofluorescence studies proved that TCTEX1D2 is an intra-acrosomal protein also present in the midpiece, suggesting a role in cargo movement in human spermatozoa. Further, an in silico profile of TCTEX1D4 revealed that most TCTEX1D4 interacting proteins were not previously characterized and the ones described present a very broad nature. This reinforces TCTEX1D4 as a dynein light chain that is capable of interacting with a variety of functionally different proteins. These observations collectively contribute to a deeper molecular understanding of the human spermatozoa function. PMID:24606217

  15. Quantitative model of R-loop forming structures reveals a novel level of RNA-DNA interactome complexity.

    PubMed

    Wongsurawat, Thidathip; Jenjaroenpun, Piroon; Kwoh, Chee Keong; Kuznetsov, Vladimir

    2012-01-01

    R-loop is the structure co-transcriptionally formed between nascent RNA transcript and DNA template, leaving the non-transcribed DNA strand unpaired. This structure can be involved in the hyper-mutation and dsDNA breaks in mammalian immunoglobulin (Ig) genes, oncogenes and neurodegenerative disease related genes. R-loops have not been studied at the genome scale yet. To identify the R-loops, we developed a computational algorithm and mapped R-loop forming sequences (RLFS) onto 66,803 sequences defined by UCSC as 'known' genes. We found that ∼59% of these transcribed sequences contain at least one RLFS. We created R-loopDB (http://rloop.bii.a-star.edu.sg/), the database that collects all RLFS identified within over half of the human genes and links to the UCSC Genome Browser for information integration and visualisation across a variety of bioinformatics sources. We found that many oncogenes and tumour suppressors (e.g. Tp53, BRCA1, BRCA2, Kras and Ptprd) and neurodegenerative diseases related genes (e.g. ATM, Park2, Ptprd and GLDC) could be prone to significant R-loop formation. Our findings suggest that R-loops provide a novel level of RNA-DNA interactome complexity, playing key roles in gene expression controls, mutagenesis, recombination process, chromosomal rearrangement, alternative splicing, DNA-editing and epigenetic modifications. RLFSs could be used as a novel source of prospective therapeutic targets.

  16. Comparative Analysis of Human Tissue Interactomes Reveals Factors Leading to Tissue-Specific Manifestation of Hereditary Diseases

    PubMed Central

    Barshir, Ruth; Shwartz, Omer; Smoly, Ilan Y.; Yeger-Lotem, Esti

    2014-01-01

    An open question in human genetics is what underlies the tissue-specific manifestation of hereditary diseases, which are caused by genomic aberrations that are present in cells across the human body. Here we analyzed this phenomenon for over 300 hereditary diseases by using comparative network analysis. We created an extensive resource of protein expression and interactions in 16 main human tissues, by integrating recent data of gene and protein expression across tissues with data of protein-protein interactions (PPIs). The resulting tissue interaction networks (interactomes) shared a large fraction of their proteins and PPIs, and only a small fraction of them were tissue-specific. Applying this resource to hereditary diseases, we first show that most of the disease-causing genes are widely expressed across tissues, yet, enigmatically, cause disease phenotypes in few tissues only. Upon testing for factors that could lead to tissue-specific vulnerability, we find that disease-causing genes tend to have elevated transcript levels and increased number of tissue-specific PPIs in their disease tissues compared to unaffected tissues. We demonstrate through several examples that these tissue-specific PPIs can highlight disease mechanisms, and thus, owing to their small number, provide a powerful filter for interrogating disease etiologies. As two thirds of the hereditary diseases are associated with these factors, comparative tissue analysis offers a meaningful and efficient framework for enhancing the understanding of the molecular basis of hereditary diseases. PMID:24921629

  17. The interactome of Streptococcus pneumoniae and its bacteriophages show highly specific patterns of interactions among bacteria and their phages

    PubMed Central

    Mariano, Rachelle; Wuchty, Stefan; Vizoso-Pinto, Maria G.; Häuser, Roman; Uetz, Peter

    2016-01-01

    Although an abundance of bacteriophages exists, little is known about interactions between their proteins and those of their bacterial hosts. Here, we experimentally determined the phage-host interactomes of the phages Dp-1 and Cp-1 and their underlying protein interaction network in the host Streptococcus pneumoniae. We compared our results to the interaction patterns of E. coli phages lambda and T7. Dp-1 and Cp-1 target highly connected host proteins, occupy central network positions, and reach many protein clusters through the interactions of their targets. In turn, lambda and T7 targets cluster to conserved and essential proteins in E. coli, while such patterns were largely absent in S. pneumoniae. Furthermore, targets in E. coli were mutually strongly intertwined, while targets of Dp-1 and Cp-1 were strongly connected through essential and orthologous proteins in their immediate network vicinity. In both phage-host systems, the impact of phages on their protein targets appears to extend from their network neighbors, since proteins that interact with phage targets were located in central network positions, have a strong topologically disruptive effect and touch complexes with high functional heterogeneity. Such observations suggest that the phages, biological impact is accomplished through a surprisingly limited topological reach of their targets. PMID:27103053

  18. The interactome of Streptococcus pneumoniae and its bacteriophages show highly specific patterns of interactions among bacteria and their phages.

    PubMed

    Mariano, Rachelle; Wuchty, Stefan; Vizoso-Pinto, Maria G; Häuser, Roman; Uetz, Peter

    2016-04-22

    Although an abundance of bacteriophages exists, little is known about interactions between their proteins and those of their bacterial hosts. Here, we experimentally determined the phage-host interactomes of the phages Dp-1 and Cp-1 and their underlying protein interaction network in the host Streptococcus pneumoniae. We compared our results to the interaction patterns of E. coli phages lambda and T7. Dp-1 and Cp-1 target highly connected host proteins, occupy central network positions, and reach many protein clusters through the interactions of their targets. In turn, lambda and T7 targets cluster to conserved and essential proteins in E. coli, while such patterns were largely absent in S. pneumoniae. Furthermore, targets in E. coli were mutually strongly intertwined, while targets of Dp-1 and Cp-1 were strongly connected through essential and orthologous proteins in their immediate network vicinity. In both phage-host systems, the impact of phages on their protein targets appears to extend from their network neighbors, since proteins that interact with phage targets were located in central network positions, have a strong topologically disruptive effect and touch complexes with high functional heterogeneity. Such observations suggest that the phages, biological impact is accomplished through a surprisingly limited topological reach of their targets.

  19. The Two-pore channel (TPC) interactome unmasks isoform-specific roles for TPCs in endolysosomal morphology and cell pigmentation.

    PubMed

    Lin-Moshier, Yaping; Keebler, Michael V; Hooper, Robert; Boulware, Michael J; Liu, Xiaolong; Churamani, Dev; Abood, Mary E; Walseth, Timothy F; Brailoiu, Eugen; Patel, Sandip; Marchant, Jonathan S

    2014-09-01

    The two-pore channels (TPC1 and TPC2) belong to an ancient family of intracellular ion channels expressed in the endolysosomal system. Little is known about how regulatory inputs converge to modulate TPC activity, and proposed activation mechanisms are controversial. Here, we compiled a proteomic characterization of the human TPC interactome, which revealed that TPCs complex with many proteins involved in Ca(2+) homeostasis, trafficking, and membrane organization. Among these interactors, TPCs were resolved to scaffold Rab GTPases and regulate endomembrane dynamics in an isoform-specific manner. TPC2, but not TPC1, caused a proliferation of endolysosomal structures, dysregulating intracellular trafficking, and cellular pigmentation. These outcomes required both TPC2 and Rab activity, as well as their interactivity, because TPC2 mutants that were inactive, or rerouted away from their endogenous expression locale, or deficient in Rab binding, failed to replicate these outcomes. Nicotinic acid adenine dinucleotide phosphate (NAADP)-evoked Ca(2+) release was also impaired using either a Rab binding-defective TPC2 mutant or a Rab inhibitor. These data suggest a fundamental role for the ancient TPC complex in trafficking that holds relevance for lysosomal proliferative scenarios observed in disease.

  20. Mutant p53 interactome identifies nardilysin as a p53R273H-specific binding partner that promotes invasion.

    PubMed

    Coffill, Cynthia R; Muller, Patricia A J; Oh, Hue Kian; Neo, Suat Peng; Hogue, Kelly A; Cheok, Chit Fang; Vousden, Karen H; Lane, David P; Blackstock, Walter P; Gunaratne, Jayantha

    2012-07-01

    The invasiveness of tumour cells depends on changes in cell shape, polarity and migration. Mutant p53 induces enhanced tumour metastasis in mice, and human cells overexpressing p53R273H have aberrant polarity and increased invasiveness, demonstrating the 'gain of function' of mutant p53 in carcinogenesis. We hypothesize that p53R273H interacts with mutant p53-specific binding partners that control polarity, migration or invasion. Here we analyze the p53R273H interactome using stable isotope labelling by amino acids in cell culture and quantitative mass spectrometry, and identify at least 15 new potential mutant p53-specific binding partners. The interaction of p53R273H with one of them--nardilysin (NRD1)--promotes an invasive response to heparin binding-epidermal growth factor-like growth factor that is p53R273H-dependant but does not require Rab coupling protein or p63. Advanced proteomics has thus allowed the detection of a new mechanism of p53-driven invasion.

  1. Proteome Based Construction of the Lymphocyte Function-Associated Antigen 1 (LFA-1) Interactome in Human Dendritic Cells

    PubMed Central

    Eich, Christina; Lasonder, Edwin; Cruz, Luis J.; Reinieren-Beeren, Inge; Cambi, Alessandra; Figdor, Carl G.; Buschow, Sonja I.

    2016-01-01

    The β2-integrin lymphocyte function-associated antigen 1 (LFA-1) plays an important role in the migration, adhesion and intercellular communication of dendritic cells (DCs). During the differentiation of human DCs from monocyte precursors, LFA-1 ligand binding capacity is completely lost, even though its expression levels were remained constant. Yet LFA-1-mediated adhesive capacity on DCs can be regained by exposing DCs to the chemokine CCL21, suggesting a high degree of regulation of LFA-1 activity during the course of DC differentiation. The molecular mechanisms underlying this regulation of LFA-1 function in DCs, however, remain elusive. To get more insight we attempted to identify specific LFA-1 binding partners that may play a role in regulating LFA-1 activity in DCs. We used highly sensitive label free quantitative mass-spectrometry to identify proteins co-immunoprecipitated (co-IP) with LFA-1 from ex vivo generated DCs. Among the potential binding partners we identified not only established components of integrin signalling pathways and cytoskeletal proteins, but also several novel LFA-1 binding partners including CD13, galectin-3, thrombospondin-1 and CD44. Further comparison to the LFA-1 interaction partners in monocytes indicated that DC differentiation was accompanied by an overall increase in LFA-1 associated proteins, in particular cytoskeletal, signalling and plasma membrane (PM) proteins. The here presented LFA-1 interactome composed of 78 proteins thus represents a valuable resource of potential regulators of LFA-1 function during the DC lifecycle. PMID:26889827

  2. TCTEX1D4 interactome in human testis: unraveling the function of dynein light chain in spermatozoa.

    PubMed

    Freitas, Maria João; Korrodi-Gregório, Luís; Morais-Santos, Filipa; Cruz e Silva, Edgar da; Fardilha, Margarida

    2014-04-01

    Studies were designed to identify the TCTEX1D4 interactome in human testis, with the purpose of unraveling putative protein complexes essential to male reproduction and thus novel TCTEX1D4 functions. TCTEX1D4 is a dynein light chain that belongs to the DYNT1/TCTEX1 family. In spermatozoa, it appears to be important to sperm motility, intraflagellar transport, and acrosome reaction. To contribute to the knowledge on TCTEX1D4 function in testis and spermatozoa, a yeast two-hybrid assay was performed in testis, which allowed the identification of 40 novel TCTEX1D4 interactors. Curiously, another dynein light chain, TCTEX1D2, was identified and its existence demonstrated for the first time in human spermatozoa. Immunofluorescence studies proved that TCTEX1D2 is an intra-acrosomal protein also present in the midpiece, suggesting a role in cargo movement in human spermatozoa. Further, an in silico profile of TCTEX1D4 revealed that most TCTEX1D4 interacting proteins were not previously characterized and the ones described present a very broad nature. This reinforces TCTEX1D4 as a dynein light chain that is capable of interacting with a variety of functionally different proteins. These observations collectively contribute to a deeper molecular understanding of the human spermatozoa function.

  3. Magnetic nanoparticles to recover cellular organelles and study the time resolved nanoparticle-cell interactome throughout uptake.

    PubMed

    Bertoli, Filippo; Davies, Gemma-Louise; Monopoli, Marco P; Moloney, Micheal; Gun'ko, Yurii K; Salvati, Anna; Dawson, Kenneth A

    2014-08-27

    Nanoparticles in contact with cells and living organisms generate quite novel interactions at the interface between the nanoparticle surface and the surrounding biological environment. However, a detailed time resolved molecular level description of the evolving interactions as nanoparticles are internalized and trafficked within the cellular environment is still missing and will certainly be required for the emerging arena of nanoparticle-cell interactions to mature. In this paper promising methodologies to map out the time resolved nanoparticle-cell interactome for nanoparticle uptake are discussed. Thus silica coated magnetite nanoparticles are presented to cells and their magnetic properties used to isolate, in a time resolved manner, the organelles containing the nanoparticles. Characterization of the recovered fractions shows that different cell compartments are isolated at different times, in agreement with imaging results on nanoparticle intracellular location. Subsequently the internalized nanoparticles can be further isolated from the recovered organelles, allowing the study of the most tightly nanoparticle-bound biomolecules, analogous to the 'hard corona' that so far has mostly been characterized in extracellular environments. Preliminary data on the recovered nanoparticles suggest that significant portion of the original corona (derived from the serum in which particles are presented to the cells) is preserved as nanoparticles are trafficked through the cells.

  4. Comparative analysis of human tissue interactomes reveals factors leading to tissue-specific manifestation of hereditary diseases.

    PubMed

    Barshir, Ruth; Shwartz, Omer; Smoly, Ilan Y; Yeger-Lotem, Esti

    2014-06-01

    An open question in human genetics is what underlies the tissue-specific manifestation of hereditary diseases, which are caused by genomic aberrations that are present in cells across the human body. Here we analyzed this phenomenon for over 300 hereditary diseases by using comparative network analysis. We created an extensive resource of protein expression and interactions in 16 main human tissues, by integrating recent data of gene and protein expression across tissues with data of protein-protein interactions (PPIs). The resulting tissue interaction networks (interactomes) shared a large fraction of their proteins and PPIs, and only a small fraction of them were tissue-specific. Applying this resource to hereditary diseases, we first show that most of the disease-causing genes are widely expressed across tissues, yet, enigmatically, cause disease phenotypes in few tissues only. Upon testing for factors that could lead to tissue-specific vulnerability, we find that disease-causing genes tend to have elevated transcript levels and increased number of tissue-specific PPIs in their disease tissues compared to unaffected tissues. We demonstrate through several examples that these tissue-specific PPIs can highlight disease mechanisms, and thus, owing to their small number, provide a powerful filter for interrogating disease etiologies. As two thirds of the hereditary diseases are associated with these factors, comparative tissue analysis offers a meaningful and efficient framework for enhancing the understanding of the molecular basis of hereditary diseases. PMID:24921629

  5. Proteome Based Construction of the Lymphocyte Function-Associated Antigen 1 (LFA-1) Interactome in Human Dendritic Cells.

    PubMed

    Eich, Christina; Lasonder, Edwin; Cruz, Luis J; Reinieren-Beeren, Inge; Cambi, Alessandra; Figdor, Carl G; Buschow, Sonja I

    2016-01-01

    The β2-integrin lymphocyte function-associated antigen 1 (LFA-1) plays an important role in the migration, adhesion and intercellular communication of dendritic cells (DCs). During the differentiation of human DCs from monocyte precursors, LFA-1 ligand binding capacity is completely lost, even though its expression levels were remained constant. Yet LFA-1-mediated adhesive capacity on DCs can be regained by exposing DCs to the chemokine CCL21, suggesting a high degree of regulation of LFA-1 activity during the course of DC differentiation. The molecular mechanisms underlying this regulation of LFA-1 function in DCs, however, remain elusive. To get more insight we attempted to identify specific LFA-1 binding partners that may play a role in regulating LFA-1 activity in DCs. We used highly sensitive label free quantitative mass-spectrometry to identify proteins co-immunoprecipitated (co-IP) with LFA-1 from ex vivo generated DCs. Among the potential binding partners we identified not only established components of integrin signalling pathways and cytoskeletal proteins, but also several novel LFA-1 binding partners including CD13, galectin-3, thrombospondin-1 and CD44. Further comparison to the LFA-1 interaction partners in monocytes indicated that DC differentiation was accompanied by an overall increase in LFA-1 associated proteins, in particular cytoskeletal, signalling and plasma membrane (PM) proteins. The here presented LFA-1 interactome composed of 78 proteins thus represents a valuable resource of potential regulators of LFA-1 function during the DC lifecycle. PMID:26889827

  6. An Approach for the Identification of Targets Specific to Bone Metastasis Using Cancer Genes Interactome and Gene Ontology Analysis

    PubMed Central

    Vashisht, Shikha; Bagler, Ganesh

    2012-01-01

    Metastasis is one of the most enigmatic aspects of cancer pathogenesis and is a major cause of cancer-associated mortality. Secondary bone cancer (SBC) is a complex disease caused by metastasis of tumor cells from their primary site and is characterized by intricate interplay of molecular interactions. Identification of targets for multifactorial diseases such as SBC, the most frequent complication of breast and prostate cancers, is a challenge. Towards achieving our aim of identification of targets specific to SBC, we constructed a ‘Cancer Genes Network’, a representative protein interactome of cancer genes. Using graph theoretical methods, we obtained a set of key genes that are relevant for generic mechanisms of cancers and have a role in biological essentiality. We also compiled a curated dataset of 391 SBC genes from published literature which serves as a basis of ontological correlates of secondary bone cancer. Building on these results, we implement a strategy based on generic cancer genes, SBC genes and gene ontology enrichment method, to obtain a set of targets that are specific to bone metastasis. Through this study, we present an approach for probing one of the major complications in cancers, namely, metastasis. The results on genes that play generic roles in cancer phenotype, obtained by network analysis of ‘Cancer Genes Network’, have broader implications in understanding the role of molecular regulators in mechanisms of cancers. Specifically, our study provides a set of potential targets that are of ontological and regulatory relevance to secondary bone cancer. PMID:23166660

  7. Systems biology approaches and tools for analysis of interactomes and multi-target drugs.

    PubMed

    Schrattenholz, André; Groebe, Karlfried; Soskic, Vukic

    2010-01-01

    Systems biology is essentially a proteomic and epigenetic exercise because the relatively condensed information of genomes unfolds on the level of proteins. The flexibility of cellular architectures is not only mediated by a dazzling number of proteinaceous species but moreover by the kinetics of their molecular changes: The time scales of posttranslational modifications range from milliseconds to years. The genetic framework of an organism only provides the blue print of protein embodiments which are constantly shaped by external input. Indeed, posttranslational modifications of proteins represent the scope and velocity of these inputs and fulfil the requirements of integration of external spatiotemporal signal transduction inside an organism. The optimization of biochemical networks for this type of information processing and storage results in chemically extremely fine tuned molecular entities. The huge dynamic range of concentrations, the chemical diversity and the necessity of synchronisation of complex protein expression patterns pose the major challenge of systemic analysis of biological models. One further message is that many of the key reactions in living systems are essentially based on interactions of moderate affinities and moderate selectivities. This principle is responsible for the enormous flexibility and redundancy of cellular circuitries. In complex disorders such as cancer or neurodegenerative diseases, which initially appear to be rooted in relatively subtle dysfunctions of multimodal physiologic pathways, drug discovery programs based on the concept of high affinity/high specificity compounds ("one-target, one-disease"), which has been dominating the pharmaceutical industry for a long time, increasingly turn out to be unsuccessful. Despite improvements in rational drug design and high throughput screening methods, the number of novel, single-target drugs fell much behind expectations during the past decade, and the treatment of "complex

  8. A modified consumer inkjet for spatiotemporal control of gene expression.

    PubMed

    Cohen, Daniel J; Morfino, Roberto C; Maharbiz, Michel M

    2009-01-01

    This paper presents a low-cost inkjet dosing system capable of continuous, two-dimensional spatiotemporal regulation of gene expression via delivery of diffusible regulators to a custom-mounted gel culture of E. coli. A consumer-grade, inkjet printer was adapted for chemical printing; E. coli cultures were grown on 750 microm thick agar embedded in micro-wells machined into commercial compact discs. Spatio-temporal regulation of the lac operon was demonstrated via the printing of patterns of lactose and glucose directly into the cultures; X-Gal blue patterns were used for visual feedback. We demonstrate how the bistable nature of the lac operon's feedback, when perturbed by patterning lactose (inducer) and glucose (inhibitor), can lead to coordination of cell expression patterns across a field in ways that mimic motifs seen in developmental biology. Examples of this include sharp boundaries and the generation of traveling waves of mRNA expression. To our knowledge, this is the first demonstration of reaction-diffusion effects in the well-studied lac operon. A finite element reaction-diffusion model of the lac operon is also presented which predicts pattern formation with good fidelity. PMID:19763256

  9. Spatio-temporal statistical models with applications to atmospheric processes

    SciTech Connect

    Wikle, C.K.

    1996-12-31

    This doctoral dissertation is presented as three self-contained papers. An introductory chapter considers traditional spatio-temporal statistical methods used in the atmospheric sciences from a statistical perspective. Although this section is primarily a review, many of the statistical issues considered have not been considered in the context of these methods and several open questions are posed. The first paper attempts to determine a means of characterizing the semiannual oscillation (SAO) spatial variation in the northern hemisphere extratropical height field. It was discovered that the midlatitude SAO in 500hPa geopotential height could be explained almost entirely as a result of spatial and temporal asymmetries in the annual variation of stationary eddies. It was concluded that the mechanism for the SAO in the northern hemisphere is a result of land-sea contrasts. The second paper examines the seasonal variability of mixed Rossby-gravity waves (MRGW) in lower stratospheric over the equatorial Pacific. Advanced cyclostationary time series techniques were used for analysis. It was found that there are significant twice-yearly peaks in MRGW activity. Analyses also suggested a convergence of horizontal momentum flux associated with these waves. In the third paper, a new spatio-temporal statistical model is proposed that attempts to consider the influence of both temporal and spatial variability. This method is mainly concerned with prediction in space and time, and provides a spatially descriptive and temporally dynamic model.

  10. Spatiotemporal electromagnetic soliton and spatial ring formation in nonlinear metamaterials

    SciTech Connect

    Zhang Jinggui; Wen Shuangchun; Xiang Yuanjiang; Wang Youwen; Luo Hailu

    2010-02-15

    We present a systematic investigation of ultrashort electromagnetic pulse propagation in metamaterials (MMs) with simultaneous cubic electric and magnetic nonlinearity. We predict that spatiotemporal electromagnetic solitons may exist in the positive-index region of a MM with focusing nonlinearity and anomalous group velocity dispersion (GVD), as well as in the negative-index region of the MM with defocusing nonlinearity and normal GVD. The experimental circumstances for generating and manipulating spatiotemporal electromagnetic solitons can be created by elaborating appropriate MMs. In addition, we find that, in the negative-index region of a MM, a spatial ring may be formed as the electromagnetic pulse propagates for focusing nonlinearity and anomalous GVD; while the phenomenon of temporal splitting of the electromagnetic pulse may appear for the same case except for the defocusing nonlinearity. Finally, we demonstrate that the nonlinear magnetization makes the sign of effective electric nonlinear effect switchable due to the combined action of electric and magnetic nonlinearity, exerting a significant influence on the propagation of electromagnetic pulses.

  11. A modified consumer inkjet for spatiotemporal control of gene expression.

    PubMed

    Cohen, Daniel J; Morfino, Roberto C; Maharbiz, Michel M

    2009-09-18

    This paper presents a low-cost inkjet dosing system capable of continuous, two-dimensional spatiotemporal regulation of gene expression via delivery of diffusible regulators to a custom-mounted gel culture of E. coli. A consumer-grade, inkjet printer was adapted for chemical printing; E. coli cultures were grown on 750 microm thick agar embedded in micro-wells machined into commercial compact discs. Spatio-temporal regulation of the lac operon was demonstrated via the printing of patterns of lactose and glucose directly into the cultures; X-Gal blue patterns were used for visual feedback. We demonstrate how the bistable nature of the lac operon's feedback, when perturbed by patterning lactose (inducer) and glucose (inhibitor), can lead to coordination of cell expression patterns across a field in ways that mimic motifs seen in developmental biology. Examples of this include sharp boundaries and the generation of traveling waves of mRNA expression. To our knowledge, this is the first demonstration of reaction-diffusion effects in the well-studied lac operon. A finite element reaction-diffusion model of the lac operon is also presented which predicts pattern formation with good fidelity.

  12. Spatiotemporal resource distribution and foraging strategies of ants (Hymenoptera: Formicidae)

    PubMed Central

    Lanan, Michele

    2014-01-01

    The distribution of food resources in space and time is likely to be an important factor governing the type of foraging strategy used by ants. However, no previous systematic attempt has been made to determine whether spatiotemporal resource distribution is in fact correlated with foraging strategy across the ants. In this analysis, I present data compiled from the literature on the foraging strategy and food resource use of 402 species of ants from across the phylogenetic tree. By categorizing the distribution of resources reported in these studies in terms of size relative to colony size, spatial distribution relative to colony foraging range, frequency of occurrence in time relative to worker life span, and depletability (i.e., whether the colony can cause a change in resource frequency), I demonstrate that different foraging strategies are indeed associated with specific spatiotemporal resource attributes. The general patterns I describe here can therefore be used as a framework to inform predictions in future studies of ant foraging behavior. No differences were found between resources collected via short-term recruitment strategies (group recruitment, short-term trails, and volatile recruitment), whereas different resource distributions were associated with solitary foraging, trunk trails, long-term trail networks, group raiding, and raiding. In many cases, ant species use a combination of different foraging strategies to collect diverse resources. It is useful to consider these foraging strategies not as separate options but as modular parts of the total foraging effort of a colony. PMID:25525497

  13. Using spatiotemporal statistical models to estimate animal abundance and infer ecological dynamics from survey counts

    USGS Publications Warehouse

    Conn, Paul B.; Johnson, Devin S.; Ver Hoef, Jay M.; Hooten, Mevin B.; London, Joshua M.; Boveng, Peter L.

    2015-01-01

    Ecologists often fit models to survey data to estimate and explain variation in animal abundance. Such models typically require that animal density remains constant across the landscape where sampling is being conducted, a potentially problematic assumption for animals inhabiting dynamic landscapes or otherwise exhibiting considerable spatiotemporal variation in density. We review several concepts from the burgeoning literature on spatiotemporal statistical models, including the nature of the temporal structure (i.e., descriptive or dynamical) and strategies for dimension reduction to promote computational tractability. We also review several features as they specifically relate to abundance estimation, including boundary conditions, population closure, choice of link function, and extrapolation of predicted relationships to unsampled areas. We then compare a suite of novel and existing spatiotemporal hierarchical models for animal count data that permit animal density to vary over space and time, including formulations motivated by resource selection and allowing for closed populations. We gauge the relative performance (bias, precision, computational demands) of alternative spatiotemporal models when confronted with simulated and real data sets from dynamic animal populations. For the latter, we analyze spotted seal (Phoca largha) counts from an aerial survey of the Bering Sea where the quantity and quality of suitable habitat (sea ice) changed dramatically while surveys were being conducted. Simulation analyses suggested that multiple types of spatiotemporal models provide reasonable inference (low positive bias, high precision) about animal abundance, but have potential for overestimating precision. Analysis of spotted seal data indicated that several model formulations, including those based on a log-Gaussian Cox process, had a tendency to overestimate abundance. By contrast, a model that included a population closure assumption and a scale prior on total

  14. A Spatio-temporal Model of African Animal Trypanosomosis Risk

    PubMed Central

    Dicko, Ahmadou H.; Percoma, Lassane; Sow, Adama; Adam, Yahaya; Mahama, Charles; Sidibé, Issa; Dayo, Guiguigbaza-Kossigan; Thévenon, Sophie; Fonta, William; Sanfo, Safietou; Djiteye, Aligui; Salou, Ernest; Djohan, Vincent; Cecchi, Giuliano; Bouyer, Jérémy

    2015-01-01

    Background African animal trypanosomosis (AAT) is a major constraint to sustainable development of cattle farming in sub-Saharan Africa. The habitat of the tsetse fly vector is increasingly fragmented owing to demographic pressure and shifts in climate, which leads to heterogeneous risk of cyclical transmission both in space and time. In Burkina Faso and Ghana, the most important vectors are riverine species, namely Glossina palpalis gambiensis and G. tachinoides, which are more resilient to human-induced changes than the savannah and forest species. Although many authors studied the distribution of AAT risk both in space and time, spatio-temporal models allowing predictions of it are lacking. Methodology/Principal Findings We used datasets generated by various projects, including two baseline surveys conducted in Burkina Faso and Ghana within PATTEC (Pan African Tsetse and Trypanosomosis Eradication Campaign) national initiatives. We computed the entomological inoculation rate (EIR) or tsetse challenge using a range of environmental data. The tsetse apparent density and their infection rate were separately estimated and subsequently combined to derive the EIR using a “one layer-one model” approach. The estimated EIR was then projected into suitable habitat. This risk index was finally validated against data on bovine trypanosomosis. It allowed a good prediction of the parasitological status (r2 = 67%), showed a positive correlation but less predictive power with serological status (r2 = 22%) aggregated at the village level but was not related to the illness status (r2 = 2%). Conclusions/Significance The presented spatio-temporal model provides a fine-scale picture of the dynamics of AAT risk in sub-humid areas of West Africa. The estimated EIR was high in the proximity of rivers during the dry season and more widespread during the rainy season. The present analysis is a first step in a broader framework for an efficient risk management of climate

  15. Changes in spatiotemporal patterns of hydrological response after partial deforestation

    NASA Astrophysics Data System (ADS)

    Wiekenkamp, Inge; Huisman, Johan Alexander; Reemt Bogena, Heye; Lin, Henry; Drüe, Clemens; Vereecken, Harry

    2016-04-01

    Predicting the effects of land use change on hydrology can be extremely challenging. It requires looking beyond the current structure and functioning of hydrological systems to predict how the system is influenced in a changed setting. Although the hydrological effects of land use change have been studied extensively, only few high resolution datasets are available to accurately describe, model and predict detailed changes in spatiotemporal patterns of hydrological fluxes and states due to land use change. The TERENO test site Wüstebach provides a unique monitoring setup to measure the major components of the water balance (evapotranspiration, discharge, precipitation) and the spatiotemporal distribution of soil moisture before and after a partial deforestation. Here, we present 5 years of measured hydrological data, including soil moisture and water budget component data 3 years before and 2 years after the partial deforestation. A data-driven investigation was used to understand changes and related feedback mechanisms in spatiotemporal hydrological response patterns. The effects of deforestation on soil moisture and evapotranspiration were analyzed by comparing states and fluxes for the control and the deforested area. The effects on discharge characteristics were analyzed using discharge metrics, including baseflow separation, peakflow rates and time to peak. Changes in preferential flow occurrence were identified using a sensor response time analysis of soil moisture measurements before and after the deforestation where preferential flow was identified as a non-sequential sequence of sensor response times within the soil. As expected from earlier studies, the partial deforestation caused a decrease in evapotranspiration and an increase in discharge. A closer look at the high resolution datasets however reveals new insights in the intra-annual variability of the water balance components. The overall decrease in evapotranspiration caused a large increase in soil

  16. Spatiotemporal chaos in Easter Island ecology.

    PubMed

    Sprott, J C

    2012-10-01

    This paper demonstrates that a recently proposed spatiotemporal model for the ecology of Easter Island admits periodic and chaotic attractors, not previously reported. Such behavior may more realistically depict the population dynamics of general ecosystems and illustrates the power of simple models to produce the kind of complex behavior that is ubiquitous in such systems.

  17. The Voronoi spatio-temporal data structure

    NASA Astrophysics Data System (ADS)

    Mioc, Darka

    2002-04-01

    Current GIS models cannot integrate the temporal dimension of spatial data easily. Indeed, current GISs do not support incremental (local) addition and deletion of spatial objects, and they can not support the temporal evolution of spatial data. Spatio-temporal facilities would be very useful in many GIS applications: harvesting and forest planning, cadastre, urban and regional planning, and emergency planning. The spatio-temporal model that can overcome these problems is based on a topological model---the Voronoi data structure. Voronoi diagrams are irregular tessellations of space, that adapt to spatial objects and therefore they are a synthesis of raster and vector spatial data models. The main advantage of the Voronoi data structure is its local and sequential map updates, which allows us to automatically record each event and performed map updates within the system. These map updates are executed through map construction commands that are composed of atomic actions (geometric algorithms for addition, deletion, and motion of spatial objects) on the dynamic Voronoi data structure. The formalization of map commands led to the development of a spatial language comprising a set of atomic operations or constructs on spatial primitives (points and lines), powerful enough to define the complex operations. This resulted in a new formal model for spatio-temporal change representation, where each update is uniquely characterized by the numbers of newly created and inactivated Voronoi regions. This is used for the extension of the model towards the hierarchical Voronoi data structure. In this model, spatio-temporal changes induced by map updates are preserved in a hierarchical data structure that combines events and corresponding changes in topology. This hierarchical Voronoi data structure has an implicit time ordering of events visible through changes in topology, and it is equivalent to an event structure that can support temporal data without precise temporal

  18. Characterization of the Cardiac Overexpression of HSPB2 Reveals Mitochondrial and Myogenic Roles Supported by a Cardiac HspB2 Interactome.

    PubMed

    Grose, Julianne H; Langston, Kelsey; Wang, Xiaohui; Squires, Shayne; Mustafi, Soumyajit Banerjee; Hayes, Whitney; Neubert, Jonathan; Fischer, Susan K; Fasano, Matthew; Saunders, Gina Moore; Dai, Qiang; Christians, Elisabeth; Lewandowski, E Douglas; Ping, Peipei; Benjamin, Ivor J

    2015-01-01

    Small Heat Shock Proteins (sHSPs) are molecular chaperones that transiently interact with other proteins, thereby assisting with quality control of proper protein folding and/or degradation. They are also recruited to protect cells from a variety of stresses in response to extreme heat, heavy metals, and oxidative-reductive stress. Although ten human sHSPs have been identified, their likely diverse biological functions remain an enigma in health and disease, and much less is known about non-redundant roles in selective cells and tissues. Herein, we set out to comprehensively characterize the cardiac-restricted Heat Shock Protein B-2 (HspB2), which exhibited ischemic cardioprotection in transgenic overexpressing mice including reduced infarct size and maintenance of ATP levels. Global yeast two-hybrid analysis using HspB2 (bait) and a human cardiac library (prey) coupled with co-immunoprecipitation studies for mitochondrial target validation revealed the first HspB2 "cardiac interactome" to contain many myofibril and mitochondrial-binding partners consistent with the overexpression phenotype. This interactome has been submitted to the Biological General Repository for Interaction Datasets (BioGRID). A related sHSP chaperone HspB5 had only partially overlapping binding partners, supporting specificity of the interactome as well as non-redundant roles reported for these sHSPs. Evidence that the cardiac yeast two-hybrid HspB2 interactome targets resident mitochondrial client proteins is consistent with the role of HspB2 in maintaining ATP levels and suggests new chaperone-dependent functions for metabolic homeostasis. One of the HspB2 targets, glyceraldehyde 3-phosphate dehydrogenase (GAPDH), has reported roles in HspB2 associated phenotypes including cardiac ATP production, mitochondrial function, and apoptosis, and was validated as a potential client protein of HspB2 through chaperone assays. From the clientele and phenotypes identified herein, it is tempting to

  19. Annotating spatio-temporal datasets for meaningful analysis in the Web

    NASA Astrophysics Data System (ADS)

    Stasch, Christoph; Pebesma, Edzer; Scheider, Simon

    2014-05-01

    More and more environmental datasets that vary in space and time are available in the Web. This comes along with an advantage of using the data for other purposes than originally foreseen, but also with the danger that users may apply inappropriate analysis procedures due to lack of important assumptions made during the data collection process. In order to guide towards a meaningful (statistical) analysis of spatio-temporal datasets available in the Web, we have developed a Higher-Order-Logic formalism that captures some relevant assumptions in our previous work [1]. It allows to proof on meaningful spatial prediction and aggregation in a semi-automated fashion. In this poster presentation, we will present a concept for annotating spatio-temporal datasets available in the Web with concepts defined in our formalism. Therefore, we have defined a subset of the formalism as a Web Ontology Language (OWL) pattern. It allows capturing the distinction between the different spatio-temporal variable types, i.e. point patterns, fields, lattices and trajectories, that in turn determine whether a particular dataset can be interpolated or aggregated in a meaningful way using a certain procedure. The actual annotations that link spatio-temporal datasets with the concepts in the ontology pattern are provided as Linked Data. In order to allow data producers to add the annotations to their datasets, we have implemented a Web portal that uses a triple store at the backend to store the annotations and to make them available in the Linked Data cloud. Furthermore, we have implemented functions in the statistical environment R to retrieve the RDF annotations and, based on these annotations, to support a stronger typing of spatio-temporal datatypes guiding towards a meaningful analysis in R. [1] Stasch, C., Scheider, S., Pebesma, E., Kuhn, W. (2014): "Meaningful spatial prediction and aggregation", Environmental Modelling & Software, 51, 149-165.

  20. Non-reciprocal elastic wave propagation in spatiotemporal periodic structures

    NASA Astrophysics Data System (ADS)

    Trainiti, G.; Ruzzene, M.

    2016-08-01

    We study longitudinal and transverse wave propagation in beams with elastic properties that are periodically varying in space and time. Spatiotemporal modulation of the elastic properties breaks mechanical reciprocity and induces one-way propagation. We follow an analytic approach to characterize the non-reciprocal behavior of the structures by analyzing the symmetry breaking of the dispersion spectrum, which results in the formation of directional band gaps and produces shifts of the first Brillouin zone limits. This approach allows us to relate position and width of the directional band gaps to the modulation parameters. Moreover, we identify the critical values of the modulation speed to maximize the non-reciprocal effect. We numerically verify the theoretical predictions by using a finite element model of the modulated beams to compute the transient response of the structure. We compute the two-dimensional Fourier transform of the collected displacement fields to calculate numerical band diagrams, showing excellent agreement between theoretical and numerical dispersion diagrams.

  1. An integrated framework of spatiotemporal dynamics of binocular rivalry.

    PubMed

    Kang, Min-Suk; Blake, Randolph

    2011-01-01

    Fluctuations in perceptual dominance during binocular rivalry exhibit several hallmark characteristics. First, dominance switches are not periodic but, instead, stochastic: perception changes unpredictably. Second, despite being stochastic, average durations of rivalry dominance vary dependent on the strength of the rival stimuli: variations in contrast, luminance, or spatial frequency produce predictable changes in average dominance durations and, hence, in alternation rate. Third, perceptual switches originate locally and spread globally over time, sometimes as traveling waves of dominance: rivalry transitions are spatiotemporal events. This essay (1) reviews recent advances in our understanding of the bases of these three hallmark characteristics of binocular rivalry dynamics and (2) provides an integrated framework to account for those dynamics using cooperative and competitive spatial interactions among local neural circuits distributed over the visual field's retinotopic map. We close with speculations about how that framework might incorporate top-down influences on rivalry dynamics.

  2. A SILAC-based proteomics elicits the molecular interactome of alisertib (MLN8237) in human erythroleukemia K562 cells

    PubMed Central

    Shu, Li-Ping; Zhou, Zhi-Wei; Zi, Dan; He, Zhi-Xu; Zhou, Shu-Feng

    2015-01-01

    Alisertib (MLN8237, ALS), an Aurora kinase A (AURKA) inhibitor, exerts potent anti-tumor effects in the treatment of solid tumor and hematologic malignancies in preclinical and clinical studies. However, the fully spectrum of molecular targets of ALS and its anticancer effect in the treatment of chronic myeloid leukemia (CML) are not clear. This study aimed to examine the proteomic responses to ALS treatment and unveil the molecular interactome and possible mechanisms for its anticancer effect in K562 cells using stable-isotope labeling by amino acids in cell culture (SILAC) approach. The proteomic data identified that ALS treatment modulated the expression of 1541 protein molecules (570 up; 971 down). The pathway analysis showed that 299 signaling pathways and 459 cellular functional proteins directly responded to ALS treatment in K562 cells. These targeted molecules and signaling pathways were mainly involved in cell growth and proliferation, cell metabolism, and cell survival and death. Subsequently, the effects of ALS on cell cycle distribution, apoptosis, and autophagy were verified. The flow cytometric analysis showed that ALS significantly induced G2/M phase arrest and the Western blotting assays showed that ALS induced apoptosis via mitochondria-dependent pathway and promoted autophagy with the involvement of PI3K/Akt/mTOR, p38 MAPK, and AMPK signaling pathways in K562 cells. Collectively, this study provides a clue to quantitatively evaluate the proteomic responses to ALS and assists in globally identifying the potential molecular targets and elucidating the underlying mechanisms of ALS for CML treatment, which may help develop new efficacious and safe therapies for CML treatment. PMID:26807190

  3. Spatiotemporal Symmetry in Rings of Coupled Biological Oscillators of Physarum Plasmodial Slime Mold

    NASA Astrophysics Data System (ADS)

    Takamatsu, Atsuko; Tanaka, Reiko; Yamada, Hiroyasu; Nakagaki, Toshiyuki; Fujii, Teruo; Endo, Isao

    2001-08-01

    Spatiotemporal patterns in rings of coupled biological oscillators of the plasmodial slime mold, Physarum polycephalum, were investigated by comparing with results analyzed by the symmetric Hopf bifurcation theory based on group theory. In three-, four-, and five-oscillator systems, all types of oscillation modes predicted by the theory were observed including a novel oscillation mode, a half period oscillation, which has not been reported anywhere in practical systems. Our results support the effectiveness of the symmetric Hopf bifurcation theory in practical systems.

  4. Spatiotemporal dynamics and optical vortices in a photorefractive phase-conjugate resonator

    NASA Technical Reports Server (NTRS)

    Liu, Siuying Raymond; Indebetouw, Guy

    1992-01-01

    A truncated modal expansion approach is used to study the spatiotemporal dynamics of a phase-conjugate resonator as a function of Bragg detuning. The numerical results reveal a rich variety of behaviors. Emphasis is given to the spatial distribution of optical vortices, their trajectories and their relationship to the beam's spatial coherence. The limitations of the model are discussed and experimental results are presented for comparison with the model's predictions and assessment of its soundness.

  5. Spatiotemporal Symmetry in Rings of Coupled Biological Oscillators of Physarum Plasmodial Slime Mold

    SciTech Connect

    Takamatsu, Atsuko; Tanaka, Reiko; Yamada, Hiroyasu; Nakagaki, Toshiyuki; Fujii, Teruo; Endo, Isao

    2001-08-13

    Spatiotemporal patterns in rings of coupled biological oscillators of the plasmodial slime mold, Physarum polycephalum, were investigated by comparing with results analyzed by the symmetric Hopf bifurcation theory based on group theory. In three-, four-, and five-oscillator systems, all types of oscillation modes predicted by the theory were observed including a novel oscillation mode, a half period oscillation, which has not been reported anywhere in practical systems. Our results support the effectiveness of the symmetric Hopf bifurcation theory in practical systems.

  6. Spatiotemporally varying visual hallucinations: I. Corticothalamic theory.

    PubMed

    Henke, H; Robinson, P A; Drysdale, P M; Loxley, P N

    2014-09-21

    The thalamus is introduced to a recent model of the visual cortex to examine its effect on pattern formation in general and the generation of temporally oscillating patterns in particular. By successively adding more physiological details to a basic corticothalamic model, it is determined which features are responsible for which effects. In particular, with the addition of a thalamic population, several changes occur in the spatiotemporal power spectrum: power increases at resonances of the corticothalamic loop, while the loop acts as a spatiotemporal low-pass filter, and synaptic and dendritic dynamics temporally low-pass filter the activity more generally. Investigation of the effect of altering parameters and gains reveals new parameter regimes where activity that corresponds to hallucinations is induced by both spatially homogeneous and inhomogeneous temporally oscillating modes. This suggests that the thalamus and corticothalamic loops are essential components of a model of oscillating visual hallucinations.

  7. A comprehensive protein-protein interactome for yeast PAS kinase 1 reveals direct inhibition of respiration through the phosphorylation of Cbf1.

    PubMed

    DeMille, Desiree; Bikman, Benjamin T; Mathis, Andrew D; Prince, John T; Mackay, Jordan T; Sowa, Steven W; Hall, Tacie D; Grose, Julianne H

    2014-07-15

    Per-Arnt-Sim (PAS) kinase is a sensory protein kinase required for glucose homeostasis in yeast, mice, and humans, yet little is known about the molecular mechanisms of its function. Using both yeast two-hybrid and copurification approaches, we identified the protein-protein interactome for yeast PAS kinase 1 (Psk1), revealing 93 novel putative protein binding partners. Several of the Psk1 binding partners expand the role of PAS kinase in glucose homeostasis, including new pathways involved in mitochondrial metabolism. In addition, the interactome suggests novel roles for PAS kinase in cell growth (gene/protein expression, replication/cell division, and protein modification and degradation), vacuole function, and stress tolerance. In vitro kinase studies using a subset of 25 of these binding partners identified Mot3, Zds1, Utr1, and Cbf1 as substrates. Further evidence is provided for the in vivo phosphorylation of Cbf1 at T211/T212 and for the subsequent inhibition of respiration. This respiratory role of PAS kinase is consistent with the reported hypermetabolism of PAS kinase-deficient mice, identifying a possible molecular mechanism and solidifying the evolutionary importance of PAS kinase in the regulation of glucose homeostasis.

  8. A comprehensive protein–protein interactome for yeast PAS kinase 1 reveals direct inhibition of respiration through the phosphorylation of Cbf1

    PubMed Central

    DeMille, Desiree; Bikman, Benjamin T.; Mathis, Andrew D.; Prince, John T.; Mackay, Jordan T.; Sowa, Steven W.; Hall, Tacie D.; Grose, Julianne H.

    2014-01-01

    Per-Arnt-Sim (PAS) kinase is a sensory protein kinase required for glucose homeostasis in yeast, mice, and humans, yet little is known about the molecular mechanisms of its function. Using both yeast two-hybrid and copurification approaches, we identified the protein–protein interactome for yeast PAS kinase 1 (Psk1), revealing 93 novel putative protein binding partners. Several of the Psk1 binding partners expand the role of PAS kinase in glucose homeostasis, including new pathways involved in mitochondrial metabolism. In addition, the interactome suggests novel roles for PAS kinase in cell growth (gene/protein expression, replication/cell division, and protein modification and degradation), vacuole function, and stress tolerance. In vitro kinase studies using a subset of 25 of these binding partners identified Mot3, Zds1, Utr1, and Cbf1 as substrates. Further evidence is provided for the in vivo phosphorylation of Cbf1 at T211/T212 and for the subsequent inhibition of respiration. This respiratory role of PAS kinase is consistent with the reported hypermetabolism of PAS kinase–deficient mice, identifying a possible molecular mechanism and solidifying the evolutionary importance of PAS kinase in the regulation of glucose homeostasis. PMID:24850888

  9. Spatiotemporal dynamics of continuum neural fields

    NASA Astrophysics Data System (ADS)

    Bressloff, Paul C.

    2012-01-01

    We survey recent analytical approaches to studying the spatiotemporal dynamics of continuum neural fields. Neural fields model the large-scale dynamics of spatially structured biological neural networks in terms of nonlinear integrodifferential equations whose associated integral kernels represent the spatial distribution of neuronal synaptic connections. They provide an important example of spatially extended excitable systems with nonlocal interactions and exhibit a wide range of spatially coherent dynamics including traveling waves oscillations and Turing-like patterns.

  10. Spatiotemporal Floral Scent Variation of Penstemon digitalis.

    PubMed

    Burdon, Rosalie C F; Raguso, Robert A; Kessler, André; Parachnowitsch, Amy L

    2015-07-01

    Variability in floral volatile emissions can occur temporally through floral development, during diel cycles, as well as spatially within a flower. These spatiotemporal patterns are hypothesized to provide additional information to floral visitors, but they are rarely measured, and their attendant hypotheses are even more rarely tested. In Penstemon digitalis, a plant whose floral scent has been shown to be under strong phenotypic selection for seed fitness, we investigated spatiotemporal variation in floral scent by using dynamic headspace collection, respectively solid-phase microextraction, and analyzed the volatile samples by combined gas chromatography-mass spectrometry. Total volatile emission was greatest during flowering and peak pollinator activity hours, suggesting its importance in mediating ecological interactions. We also detected tissue and reward-specific compounds, consistent with the hypothesis that complexity in floral scent composition reflects several ecological functions. In particular, we found tissue-specific scents for the stigma, stamens, and staminode (a modified sterile stamen common to all Penstemons). Our findings emphasize the dynamic nature of floral scents and highlight a need for greater understanding of ecological and physiological mechanisms driving spatiotemporal patterns in scent production.

  11. Nearest matched filter classification of spatiotemporal patterns.

    PubMed

    Hecht-Nielsen, R

    1987-05-15

    Recent advances in massively parallel optical and electronic neural network processing technology have made it plausible to consider the use of matched filter banks containing large numbers of individual filters as pattern classifiers for complex spatiotemporal pattern environments such as speech, sonar, radar, and advanced communications. This paper begins with an overview of how neural networks can be used to approximately implement such multidimensional matched filter banks. The nearest matched filter classifier is then formally defined. This definition is then reformulated to show that the classifier is equivalent to a nearest neighbor classifier in a separable infinite-dimensional metric space that specifies the local-in-time behavior of spatiotemporal patterns. The result of Cover and Hart is then applied to show that, given a statistically comprehensive set of filter templates, the nearest matched filter classifier will have near-Bayesian performance for spatiotemporal patterns. The combination of near-Bayesian classifier performance with the excellent performance of matched filtering in noise yields a powerful new classification technique. This result adds additional interest to Grossberg's hypothesis that the mammalian cerebral cortex carries out local-in-time nearest matched filter classification of both auditory and visual sensory inputs as an initial step in sensory pattern recognition-which may help explain the almost instantaneous pattern recognition capabilities of animals.

  12. Normative Spatiotemporal Gait Parameters in Older Adults

    PubMed Central

    Hollman, John H.; McDade, Eric M.; Petersen, Ronald C.

    2011-01-01

    While factor analyses have characterized pace, rhythm and variability as factors that explain variance in gait performance in older adults, comprehensive analyses incorporating many gait parameters have not been undertaken and normative data for many of those parameters are lacking. The purposes of this study were to conduct a factor analysis on nearly two dozen spatiotemporal gait parameters and to contribute to the normative database of gait parameters from healthy, able-bodied men and women over the age of 70. Data were extracted from 294 participants enrolled in the Mayo Clinic Study of Aging. Spatiotemporal gait data were obtained as participants completed two walks across a 5.6-m electronic walkway (GAITRite®). Five primary domains of spatiotemporal gait performance were identified: a “rhythm” domain was characterized by cadence and temporal parameters such as stride time; a “phase” domain was characterized by temporophasic parameters that constitute distinct divisions of the gait cycle; a “variability” domain encompassed gait cycle and step variability parameters; a “pace” domain was characterized by parameters that included gait speed, step length and stride length; and a “base of support” domain was characterized by step width and step width variability. Several domains differed between men and women and differed across age groups. Reference values of 23 gait parameters are presented which researchers or clinicians can use for assessing and interpreting gait dysfunction in aging persons. PMID:21531139

  13. A network medicine approach to quantify distance between hereditary disease modules on the interactome

    NASA Astrophysics Data System (ADS)

    Caniza, Horacio; Romero, Alfonso E.; Paccanaro, Alberto

    2015-12-01

    We introduce a MeSH-based method that accurately quantifies similarity between heritable diseases at molecular level. This method effectively brings together the existing information about diseases that is scattered across the vast corpus of biomedical literature. We prove that sets of MeSH terms provide a highly descriptive representation of heritable disease and that the structure of MeSH provides a natural way of combining individual MeSH vocabularies. We show that our measure can be used effectively in the prediction of candidate disease genes. We developed a web application to query more than 28.5 million relationships between 7,574 hereditary diseases (96% of OMIM) based on our similarity measure.

  14. Tomographic reconstruction of the pulse-echo spatiotemporal impulse response

    NASA Astrophysics Data System (ADS)

    Nguyen, Nghia Q.; Abbey, Craig K.; Yapp, Rebecca D.; Insana, Michael F.

    2010-03-01

    Virtually every area of ultrasonic imaging research requires accurate estimation of the spatiotemporal impulse response of the instrument, and yet accurate measurements are difficult to achieve. The impulse response can also be difficult to predict numerically for a specific device because small unknown perturbations in array properties can generate significant changes in predicted pulse-echo field patterns. A typical measurement for a 1-D array transducer employs a line scatterer oriented perpendicular to the scan plane. Echoes from line scatterers located throughout the field of view constitute estimates of shift-varying line response functions. We propose an inverse-problem approach to the reconstruction of point-spread functions from line-spread functions. A collection of echoes recorded for a range of line-scatterer rotation angles are treated as projections of sound pressure onto the transducer array surface. Although the reconstruction is mathematically equivalent to filtered backprojection, it provides significant advantages with respect to interpolation that confound straightforward implementations. Field II predictions used to model measurements made on commercial systems suggest the reconstruction accuracy is with 0.32% for noiseless echo data. Application of the method to data acquired from a commercial system are evaluated from the perspective of deconvolution.

  15. A Hierarchical Bayesian Approach for Learning Sparse Spatio-Temporal Decomposition of Multichannel EEG

    PubMed Central

    Wu, Wei; Chen, Zhe; Gao, Shangkai; Brown, Emery N.

    2011-01-01

    Multichannel electroencephalography (EEG) offers a non-invasive tool to explore spatio-temporal dynamics of brain activity. With EEG recordings consisting of multiple trials, traditional signal processing approaches that ignore inter-trial variability in the data may fail to accurately estimate the underlying spatio-temporal brain patterns. Moreover, precise characterization of such inter-trial variability per se can be of high scientific value in establishing the relationship between brain activity and behavior. In this paper, a statistical modeling framework is introduced for learning spatiotemporal decomposition of multiple-trial EEG data recorded under two contrasting experimental conditions. By modeling the variance of source signals as random variables varying across trials, the proposed two-stage hierarchical Bayesian model is able to capture inter-trial amplitude variability in the data in a sparse way where a parsimonious representation of the data can be obtained. A variational Bayesian (VB) algorithm is developed for statistical inference of the hierarchical model. The efficacy of the proposed modeling framework is validated with the analysis of both synthetic and real EEG data. In the simulation study we show that even at low signal-to-noise ratios our approach is able to recover with high precision the underlying spatiotemporal patterns and the evolution of source amplitude across trials; on two brain-computer interface (BCI) data sets we show that our VB algorithm can extract physiologically meaningful spatio-temporal patterns and make more accurate predictions than other two widely used algorithms: the common spatial patterns (CSP) algorithm and the Infomax algorithm for independent component analysis (ICA). The results demonstrate that our statistical modeling framework can serve as a powerful tool for extracting brain patterns, characterizing trial-to-trial brain dynamics, and decoding brain states by exploiting useful structures in the data. PMID

  16. Integrated interactions database: tissue-specific view of the human and model organism interactomes.

    PubMed

    Kotlyar, Max; Pastrello, Chiara; Sheahan, Nicholas; Jurisica, Igor

    2016-01-01

    IID (Integrated Interactions Database) is the first database providing tissue-specific protein-protein interactions (PPIs) for model organisms and human. IID covers six species (S. cerevisiae (yeast), C. elegans (worm), D. melonogaster (fly), R. norvegicus (rat), M. musculus (mouse) and H. sapiens (human)) and up to 30 tissues per species. Users query IID by providing a set of proteins or PPIs from any of these organisms, and specifying species and tissues where IID should search for interactions. If query proteins are not from the selected species, IID enables searches across species and tissues automatically by using their orthologs; for example, retrieving interactions in a given tissue, conserved in human and mouse. Interaction data in IID comprises three types of PPI networks: experimentally detected PPIs from major databases, orthologous PPIs and high-confidence computationally predicted PPIs. Interactions are assigned to tissues where their proteins pairs or encoding genes are expressed. IID is a major replacement of the I2D interaction database, with larger PPI networks (a total of 1,566,043 PPIs among 68,831 proteins), tissue annotations for interactions, and new query, analysis and data visualization capabilities. IID is available at http://ophid.utoronto.ca/iid.

  17. cytoHubba: identifying hub objects and sub-networks from complex interactome

    PubMed Central

    2014-01-01

    Background Network is a useful way for presenting many types of biological data including protein-protein interactions, gene regulations, cellular pathways, and signal transductions. We can measure nodes by their network features to infer their importance in the network, and it can help us identify central elements of biological networks. Results We introduce a novel Cytoscape plugin cytoHubba for ranking nodes in a network by their network features. CytoHubba provides 11 topological analysis methods including Degree, Edge Percolated Component, Maximum Neighborhood Component, Density of Maximum Neighborhood Component, Maximal Clique Centrality and six centralities (Bottleneck, EcCentricity, Closeness, Radiality, Betweenness, and Stress) based on shortest paths. Among the eleven methods, the new proposed method, MCC, has a better performance on the precision of predicting essential proteins from the yeast PPI network. Conclusions CytoHubba provide a user-friendly interface to explore important nodes in biological networks. It computes all eleven methods in one stop shopping way. Besides, researchers are able to combine cytoHubba with and other plugins into a novel analysis scheme. The network and sub-networks caught by this topological analysis strategy will lead to new insights on essential regulatory networks and protein drug targets for experimental biologists. According to cytoscape plugin download statistics, the accumulated number of cytoHubba is around 6,700 times since 2010. PMID:25521941

  18. Looking at Cerebellar Malformations through Text-Mined Interactomes of Mice and Humans

    PubMed Central

    Iossifov, Ivan; Rodriguez-Esteban, Raul; Mayzus, Ilya; Millen, Kathleen J.; Rzhetsky, Andrey

    2009-01-01

    We have generated and made publicly available two very large networks of molecular interactions: 49,493 mouse-specific and 52,518 human-specific interactions. These networks were generated through automated analysis of 368,331 full-text research articles and 8,039,972 article abstracts from the PubMed database, using the GeneWays system. Our networks cover a wide spectrum of molecular interactions, such as bind, phosphorylate, glycosylate, and activate; 207 of these interaction types occur more than 1,000 times in our unfiltered, multi-species data set. Because mouse and human genes are linked through an orthological relationship, human and mouse networks are amenable to straightforward, joint computational analysis. Using our newly generated networks and known associations between mouse genes and cerebellar malformation phenotypes, we predicted a number of new associations between genes and five cerebellar phenotypes (small cerebellum, absent cerebellum, cerebellar degeneration, abnormal foliation, and abnormal vermis). Using a battery of statistical tests, we showed that genes that are associated with cerebellar phenotypes tend to form compact network clusters. Further, we observed that cerebellar malformation phenotypes tend to be associated with highly connected genes. This tendency was stronger for developmental phenotypes and weaker for cerebellar degeneration. PMID:19893633

  19. Spatiotemporal patterns of terrestrial gross primary production: A review

    NASA Astrophysics Data System (ADS)

    Anav, Alessandro; Friedlingstein, Pierre; Beer, Christian; Ciais, Philippe; Harper, Anna; Jones, Chris; Murray-Tortarolo, Guillermo; Papale, Dario; Parazoo, Nicholas C.; Peylin, Philippe; Piao, Shilong; Sitch, Stephen; Viovy, Nicolas; Wiltshire, Andy; Zhao, Maosheng

    2015-09-01

    Great advances have been made in the last decade in quantifying and understanding the spatiotemporal patterns of terrestrial gross primary production (GPP) with ground, atmospheric, and space observations. However, although global GPP estimates exist, each data set relies upon assumptions and none of the available data are based only on measurements. Consequently, there is no consensus on the global total GPP and large uncertainties exist in its benchmarking. The objective of this review is to assess how the different available data sets predict the spatiotemporal patterns of GPP, identify the differences among data sets, and highlight the main advantages/disadvantages of each data set. We compare GPP estimates for the historical period (1990-2009) from two observation-based data sets (Model Tree Ensemble and Moderate Resolution Imaging Spectroradiometer) to coupled carbon-climate models and terrestrial carbon cycle models from the Fifth Climate Model Intercomparison Project and TRENDY projects and to a new hybrid data set (CARBONES). Results show a large range in the mean global GPP estimates. The different data sets broadly agree on GPP seasonal cycle in terms of phasing, while there is still discrepancy on the amplitude. For interannual variability (IAV) and trends, there is a clear separation between the observation-based data that show little IAV and trend, while the process-based models have large GPP variability and significant trends. These results suggest that there is an urgent need to improve observation-based data sets and develop carbon cycle modeling with processes that are currently treated either very simplistically to correctly estimate present GPP and better quantify the future uptake of carbon dioxide by the world's vegetation.

  20. Spatio-Temporal Patterns of Schistosomiasis Japonica in Lake and Marshland Areas in China: The Effect of Snail Habitats

    PubMed Central

    Hu, Yi; Gao, Jie; Chi, Meina; Luo, Can; Lynn, Henry; Sun, Liqian; Tao, Bo; Wang, Decheng; Zhang, Zhijie; Jiang, Qingwu

    2014-01-01

    The progress of the integrated control policy for schistosomiasis implemented since 2005 in China, which is aiming at reducing the roles of bovines and humans as infection sources, may be challenged by persistent presence of infected snails in lake and marshland areas. Based on annual parasitologic data for schistosomiasis during 2004–2011 in Xingzi County, a spatio-temporal kriging model was used to investigate the spatio-temporal pattern of schistosomiasis risk. Results showed that environmental factors related to snail habitats can explain the spatio-temporal variation of schistosomiasis. Predictive maps of schistosomiasis risk illustrated that clusters of the disease fluctuated during 2004–2008; there was an extensive outbreak in 2008 and attenuated disease occurrences afterwards. An area with an annually constant cluster of schistosomiasis was identified. Our study suggests that targeting snail habitats located within high-risk areas for schistosomiasis would be an economic and sustainable way of schistosomiasis control in the future. PMID:24980498

  1. Spatio-temporal patterns of schistosomiasis japonica in lake and marshland areas in China: the effect of snail habitats.

    PubMed

    Hu, Yi; Gao, Jie; Chi, Meina; Luo, Can; Lynn, Henry; Sun, Liqian; Tao, Bo; Wang, Decheng; Zhang, Zhijie; Jiang, Qingwu

    2014-09-01

    The progress of the integrated control policy for schistosomiasis implemented since 2005 in China, which is aiming at reducing the roles of bovines and humans as infection sources, may be challenged by persistent presence of infected snails in lake and marshland areas. Based on annual parasitologic data for schistosomiasis during 2004-2011 in Xingzi County, a spatio-temporal kriging model was used to investigate the spatio-temporal pattern of schistosomiasis risk. Results showed that environmental factors related to snail habitats can explain the spatio-temporal variation of schistosomiasis. Predictive maps of schistosomiasis risk illustrated that clusters of the disease fluctuated during 2004-2008; there was an extensive outbreak in 2008 and attenuated disease occurrences afterwards. An area with an annually constant cluster of schistosomiasis was identified. Our study suggests that targeting snail habitats located within high-risk areas for schistosomiasis would be an economic and sustainable way of schistosomiasis control in the future.

  2. Size-dependent diffusion promotes the emergence of spatiotemporal patterns.

    PubMed

    Zhang, Lai; Thygesen, Uffe Høgsbro; Banerjee, Malay

    2014-07-01

    Spatiotemporal patterns, indicating the spatiotemporal variability of individual abundance, are a pronounced scenario in ecological interactions. Most of the existing models for spatiotemporal patterns treat species as homogeneous groups of individuals with average characteristics by ignoring intraspecific physiological variations at the individual level. Here we explore the impacts of size variation within species resulting from individual ontogeny, on the emergence of spatiotemporal patterns in a fully size-structured population model. We found that size dependency of animal's diffusivity greatly promotes the formation of spatiotemporal patterns, by creating regular spatiotemporal patterns out of temporal chaos. We also found that size-dependent diffusion can substitute large-amplitude base harmonics with spatiotemporal patterns with lower amplitude oscillations but with enriched harmonics. Finally, we found that the single-generation cycle is more likely to drive spatiotemporal patterns compared to predator-prey cycles, meaning that the mechanism of Hopf bifurcation might be more common than hitherto appreciated since the former cycle is more widespread than the latter in case of interacting populations. Due to the ubiquity of individual ontogeny in natural ecosystems we conclude that diffusion variability within populations is a significant driving force for the emergence of spatiotemporal patterns. Our results offer a perspective on self-organized phenomena, and pave a way to understand such phenomena in systems organized as complex ecological networks. PMID:25122357

  3. Characterization of the Cardiac Overexpression of HSPB2 Reveals Mitochondrial and Myogenic Roles Supported by a Cardiac HspB2 Interactome

    PubMed Central

    Grose, Julianne H.; Langston, Kelsey; Wang, Xiaohui; Squires, Shayne; Mustafi, Soumyajit Banerjee; Hayes, Whitney; Neubert, Jonathan; Fischer, Susan K.; Fasano, Matthew; Saunders, Gina Moore; Dai, Qiang; Christians, Elisabeth; Lewandowski, E. Douglas; Ping, Peipei; Benjamin, Ivor J.

    2015-01-01

    Small Heat Shock Proteins (sHSPs) are molecular chaperones that transiently interact with other proteins, thereby assisting with quality control of proper protein folding and/or degradation. They are also recruited to protect cells from a variety of stresses in response to extreme heat, heavy metals, and oxidative-reductive stress. Although ten human sHSPs have been identified, their likely diverse biological functions remain an enigma in health and disease, and much less is known about non-redundant roles in selective cells and tissues. Herein, we set out to comprehensively characterize the cardiac-restricted Heat Shock Protein B-2 (HspB2), which exhibited ischemic cardioprotection in transgenic overexpressing mice including reduced infarct size and maintenance of ATP levels. Global yeast two-hybrid analysis using HspB2 (bait) and a human cardiac library (prey) coupled with co-immunoprecipitation studies for mitochondrial target validation revealed the first HspB2 “cardiac interactome” to contain many myofibril and mitochondrial-binding partners consistent with the overexpression phenotype. This interactome has been submitted to the Biological General Repository for Interaction Datasets (BioGRID). A related sHSP chaperone HspB5 had only partially overlapping binding partners, supporting specificity of the interactome as well as non-redundant roles reported for these sHSPs. Evidence that the cardiac yeast two-hybrid HspB2 interactome targets resident mitochondrial client proteins is consistent with the role of HspB2 in maintaining ATP levels and suggests new chaperone-dependent functions for metabolic homeostasis. One of the HspB2 targets, glyceraldehyde 3-phosphate dehydrogenase (GAPDH), has reported roles in HspB2 associated phenotypes including cardiac ATP production, mitochondrial function, and apoptosis, and was validated as a potential client protein of HspB2 through chaperone assays. From the clientele and phenotypes identified herein, it is tempting to

  4. Spatiotemporal dynamics of random stimuli account for trial-to-trial variability in perceptual decision making

    PubMed Central

    Park, Hame; Lueckmann, Jan-Matthis; von Kriegstein, Katharina; Bitzer, Sebastian; Kiebel, Stefan J.

    2016-01-01

    Decisions in everyday life are prone to error. Standard models typically assume that errors during perceptual decisions are due to noise. However, it is unclear how noise in the sensory input affects the decision. Here we show that there are experimental tasks for which one can analyse the exact spatio-temporal details of a dynamic sensory noise and better understand variability in human perceptual decisions. Using a new experimental visual tracking task and a novel Bayesian decision making model, we found that the spatio-temporal noise fluctuations in the input of single trials explain a significant part of the observed responses. Our results show that modelling the precise internal representations of human participants helps predict when perceptual decisions go wrong. Furthermore, by modelling precisely the stimuli at the single-trial level, we were able to identify the underlying mechanism of perceptual decision making in more detail than standard models. PMID:26752272

  5. Spatio-temporal correlation-based fast coding unit depth decision for high efficiency video coding

    NASA Astrophysics Data System (ADS)

    Zhou, Chengtao; Zhou, Fan; Chen, Yaowu

    2013-10-01

    The exhaustive block partition search process in high efficiency video coding (HEVC) imposes a very high computational complexity on test module of HEVC encoder (HM). A fast coding unit (CU) depth algorithm using the spatio-temporal correlation of the depth information to fasten the search process is proposed. The depth of the coding tree unit (CTU) is predicted first by using the depth information of the spatio-temporal neighbor CTUs. Then, the depth information of the adjacent CU is incorporated to skip some specific depths when encoding the sub-CTU. As compared with the original HM encoder, experimental results show that the proposed algorithm can save more than 20% encoding time on average for intra-only, low-delay, low-delay P slices, and random access cases with almost the same rate-distortion performance.

  6. Asymmetric spatiotemporal evolution of prebiotic homochirality.

    PubMed

    Gleiser, Marcelo

    2007-06-01

    The role of asymmetry on the evolution of prebiotic homochirality is investigated in the context of autocatalytic polymerization reaction networks. A model featuring enantiometric cross-inhibition and chiral bias is used to study the diffusion equations controlling the spatiotemporal development of left and right-handed domains. Bounds on the chiral bias are obtained based on present-day constraints on the emergence of life on early Earth. The viability of biasing mechanisms such as weak neutral currents and circularly polarized UV light is discussed. The results can be applied to any hypothetical planetary platform. PMID:17131085

  7. Spatiotemporal pulse shaping using resonant diffraction gratings.

    PubMed

    Golovastikov, Nikita V; Bykov, Dmitry A; Doskolovich, Leonid L

    2015-08-01

    We propose a new theoretical model describing spatiotemporal transformations of two-dimensional optical pulses by resonant diffraction gratings. The diffraction of the pulse is described in terms of a linear system. Simple analytical approximations for the transfer function and the impulse response of the system are derived. The derived approximations contain five independent parameters, which can be estimated using the rigorous coupled-wave analysis. The presented numerical simulation results demonstrate that the resonant grating can perform complex pulse transformations, such as the simultaneous spatial and temporal differentiation of the optical pulse envelope.

  8. Spatiotemporal evolution of bacterial biofilm colonies

    NASA Astrophysics Data System (ADS)

    Wilking, James; Koehler, Stephan; Sinha, Naveen; Seminara, Agnese; Brenner, Michael; Weitz, David

    2014-03-01

    Many bacteria on earth live in surface-attached communities known as biofilms. Gene expression in a biofilm is typically varied, resulting in a variety of phenotypes within a single film. These phenotypes play a critical role in biofilm physiology and development. We use time-resolved, wide-field fluorescence microscopy to image triple-labeled fluorescent Bacillus Subtilis colonies grown on agar to determine in a non-invasive fashion the evolving phenotypes. We infer their transition rates from the resulting spatiotemporal maps of gene expression. Moreover, we correlate these transition rates with local measurements of nutrient concentration to determine the influence of extracellular signals on gene expression.

  9. Workload induced spatio-temporal distortions and safety of flight

    SciTech Connect

    Barrett, C.L.; Weisgerber, S.A.; Naval Weapons Center, China Lake, CA )

    1989-01-01

    A theoretical analysis of the relationship between cognitive complexity and the perception of time and distance is presented and experimentally verified. Complex tasks produce high rates of mental representation which affect the subjective sense of duration and, through the subjective time scale, the percept of distance derived from dynamic visual cues (i.e., visual cues requiring rate integration). The analysis of the interrelationship of subjective time and subjective distance yields the prediction that, as a function of cognitive complexity, distance estimates derived from dynamic visual cues will be longer than the actual distance whereas estimates based on perceived temporal duration will be shorter than the actual distance. This prediction was confirmed in an experiment in which subjects (both pilots and non-pilots) estimated distances using either temporal cues or dynamic visual cues. The distance estimation task was also combined with secondary loading tasks in order to vary the overall task complexity. The results indicated that distance estimates based on temporal cues were underestimated while estimates based on visual cues were overestimated. This spatio-temporal distortion effect increased with increases in overall task complexity. 30 refs., 6 figs., 1 tab.

  10. Spatiotemporal modeling of monthly soil temperature using artificial neural networks

    NASA Astrophysics Data System (ADS)

    Wu, Wei; Tang, Xiao-Ping; Guo, Nai-Jia; Yang, Chao; Liu, Hong-Bin; Shang, Yue-Feng

    2013-08-01

    Soil temperature data are critical for understanding land-atmosphere interactions. However, in many cases, they are limited at both spatial and temporal scales. In the current study, an attempt was made to predict monthly mean soil temperature at a depth of 10 cm using artificial neural networks (ANNs) over a large region with complex terrain. Gridded independent variables, including latitude, longitude, elevation, topographic wetness index, and normalized difference vegetation index, were derived from a digital elevation model and remote sensing images with a resolution of 1 km. The good performance and robustness of the proposed ANNs were demonstrated by comparisons with multiple linear regressions. On average, the developed ANNs presented a relative improvement of about 44 % in root mean square error, 70 % in mean absolute percentage error, and 18 % in coefficient of determination over classical linear models. The proposed ANN models were then applied to predict soil temperatures at unsampled locations across the study area. Spatiotemporal variability of soil temperature was investigated based on the obtained database. Future work will be needed to test the applicability of ANNs for estimating soil temperature at finer scales.

  11. Searching for cellular partners of hantaviral nonstructural protein NSs: Y2H screening of mouse cDNA library and analysis of cellular interactome.

    PubMed

    Rönnberg, Tuomas; Jääskeläinen, Kirsi; Blot, Guillaume; Parviainen, Ville; Vaheri, Antti; Renkonen, Risto; Bouloy, Michele; Plyusnin, Alexander

    2012-01-01

    Hantaviruses (Bunyaviridae) are negative-strand RNA viruses with a tripartite genome. The small (S) segment encodes the nucleocapsid protein and, in some hantaviruses, also the nonstructural protein (NSs). The aim of this study was to find potential cellular partners for the hantaviral NSs protein. Toward this aim, yeast two-hybrid (Y2H) screening of mouse cDNA library was performed followed by a search for potential NSs protein counterparts via analyzing a cellular interactome. The resulting interaction network was shown to form logical, clustered structures. Furthermore, several potential binding partners for the NSs protein, for instance ACBD3, were identified and, to prove the principle, interaction between NSs and ACBD3 proteins was demonstrated biochemically.

  12. Searching for Cellular Partners of Hantaviral Nonstructural Protein NSs: Y2H Screening of Mouse cDNA Library and Analysis of Cellular Interactome

    PubMed Central

    Parviainen, Ville; Vaheri, Antti; Renkonen, Risto; Bouloy, Michele; Plyusnin, Alexander

    2012-01-01

    Hantaviruses (Bunyaviridae) are negative-strand RNA viruses with a tripartite genome. The small (S) segment encodes the nucleocapsid protein and, in some hantaviruses, also the nonstructural protein (NSs). The aim of this study was to find potential cellular partners for the hantaviral NSs protein. Toward this aim, yeast two-hybrid (Y2H) screening of mouse cDNA library was performed followed by a search for potential NSs protein counterparts via analyzing a cellular interactome. The resulting interaction network was shown to form logical, clustered structures. Furthermore, several potential binding partners for the NSs protein, for instance ACBD3, were identified and, to prove the principle, interaction between NSs and ACBD3 proteins was demonstrated biochemically. PMID:22506017

  13. Asynchronous Visualization of Spatiotemporal Information for Multiple Moving Targets

    ERIC Educational Resources Information Center

    Wang, Huadong

    2013-01-01

    In the modern information age, the quantity and complexity of spatiotemporal data is increasing both rapidly and continuously. Sensor systems with multiple feeds that gather multidimensional spatiotemporal data will result in information clusters and overload, as well as a high cognitive load for users of these systems. To meet future…

  14. Spatiotemporal Data Mining, Analysis, and Visualization of Human Activity Data

    ERIC Educational Resources Information Center

    Li, Xun

    2012-01-01

    This dissertation addresses the research challenge of developing efficient new methods for discovering useful patterns and knowledge in large volumes of electronically collected spatiotemporal activity data. I propose to analyze three types of such spatiotemporal activity data in a methodological framework that integrates spatial analysis, data…

  15. Spatiotemporal pattern recognition using hidden Markov models

    NASA Astrophysics Data System (ADS)

    Fielding, Kenneth H.; Ruck, Dennis W.; Rogers, Steven K.; Welsh, Byron M.; Oxley, Mark E.

    1993-10-01

    A spatio-temporal method for identifying objects contained in an image sequence is presented. The Hidden Markov Model (HMM) technique is used as the classification algorithm, making classification decisions based on a spatio-temporal sequence of observed object features. A five class problem is considered. Classification accuracies of 100% and 99.7% are obtained for sequences of images generated over two separate regions of viewing positions. HMMs trained on image sequences of the objects moving in opposite directions showed a 98.1% successful classification rate by class and direction of movement. The HMM technique proved robust to image corruption with additive correlated noise and had a higher accuracy than a single look nearest neighbor method. A real image sequence of one of the objects used was successfully recognized with the HMMs trained on synthetic data. This study shows the temporal changes that observed feature vectors undergo due to object motion hold information that can yield superior classification accuracy when compared to single frame techniques.

  16. Integrating environmental isoscapes for spatiotemporal assignment

    NASA Astrophysics Data System (ADS)

    Bowen, G.; Bataille, C.; Kennedy, C.; Zhang, T.; West, J.

    2012-04-01

    Numerous case studies in the ecological and forensic fields have illustrated the potential utility of light stable isotopes as tracers of the geographic origin of biological materials. However, a number of critical challenges continue to limit the application of these tools, among them (1) limitations to our knowledge of isotopic values expected for materials formed at particular locations and times, (2) uncertainty in our understanding of the interplay between temporal and spatial variation in the isotope 'signature' transferred to isotopic materials, and (3) lack of robust, widely used models for quantitative statistical assessment of spatiotemporal origin and associated uncertainty. In order to acknowledge and address each of these limitations, we present new models and analysis of spatiotemporal variation in the stable isotope ratios of hydrogen, oxygen, and strontium in the environment, representing three isotope systems with strong and complementary potential for provenancing applications. We demonstrate a statistical framework for the integration of these isoscapes in assignment problems and describe how this toolkit has been made broadly accessible through the IsoMAP web-GIS portal.

  17. Spatiotemporal control of opioid signaling and behavior

    PubMed Central

    Siuda, Edward R.; Copits, Bryan A.; Schmidt, Martin J.; Baird, Madison A.; Al-Hasani, Ream; Planer, William J.; Funderburk, Samuel C.; McCall, Jordan G.; Gereau, Robert W.; Bruchas, Michael R.

    2015-01-01

    Summary Optogenetics is now a widely accepted tool for spatiotemporal manipulation of neuronal activity. However, a majority of optogenetic approaches use binary on/off control schemes. Here we extend the optogenetic toolset by developing a neuromodulatory approach using a rationale-based design to generate a Gi-coupled, optically-sensitive, mu-opioid-like receptor, we term opto-MOR. We demonstrate that opto-MOR engages canonical mu-opioid signaling through inhibition of adenylyl cyclase, activation of MAPK and G protein-gated inward rectifying potassium (GIRK) channels, and internalizes with similar kinetics as the mu-opioid receptor. To assess in vivo utility we expressed a Cre-dependent viral opto-MOR in RMTg/VTA GABAergic neurons, which led to a real-time place preference. In contrast, expression of opto-MOR in GABAergic neurons of the ventral pallidum hedonic cold spot, led to real-time place aversion. This tool has generalizable application for spatiotemporal control of opioid signaling and, furthermore, can be used broadly for mimicking endogenous neuronal inhibition pathways. PMID:25937173

  18. Bayesian spatiotemporal modelling for the assessment of short-term exposure to particle pollution in urban areas

    PubMed Central

    Pirani, Monica; Gulliver, John; Fuller, Gary W; Blangiardo, Marta

    2014-01-01

    This paper describes a Bayesian hierarchical approach to predict short-term concentrations of particle pollution in an urban environment, with application to inhalable particulate matter (PM10) in Greater London. We developed and compared several spatiotemporal models that differently accounted for factors affecting the spatiotemporal properties of particle concentrations. We considered two main source contributions to ambient measurements: (i) the long-range transport of the secondary fraction of particles, which temporal variability was described by a latent variable derived from rural concentrations; and (ii) the local primary component of particles (traffic- and non-traffic-related) captured by the output of the dispersion model ADMS-Urban, which site-specific effect was described by a Bayesian kriging. We also assessed the effect of spatiotemporal covariates, including type of site, daily temperature to describe the seasonal changes in chemical processes affecting local PM10 concentrations that are not considered in local-scale dispersion models and day of the week to account for time-varying emission rates not available in emissions inventories. The evaluation of the predictive ability of the models, obtained via a cross-validation approach, revealed that concentration estimates in urban areas benefit from combining the city-scale particle component and the long-range transport component with covariates that account for the residual spatiotemporal variation in the pollution process. PMID:24280683

  19. Bayesian spatiotemporal interpolation of rainfall in the Central Chilean Andes

    NASA Astrophysics Data System (ADS)

    Ossa-Moreno, Juan; Keir, Greg; McIntyre, Neil

    2016-04-01

    Water availability in the populous and economically significant Central Chilean region is governed by complex interactions between precipitation, temperature, snow and glacier melt, and streamflow. Streamflow prediction at daily time scales depends strongly on accurate estimations of precipitation in this predominantly dry region, particularly during the winter period. This can be difficult as gauged rainfall records are scarce, especially in the higher elevation regions of the Chilean Andes, and topographic influences on rainfall are not well understood. Remotely sensed precipitation and topographic products can be used to construct spatiotemporal multivariate regression models to estimate rainfall at ungauged locations. However, classical estimation methods such as kriging cannot easily accommodate the complicated statistical features of the data, including many 'no rainfall' observations, as well as non-normality, non-stationarity, and temporal autocorrelation. We use a separable space-time model to predict rainfall using the R-INLA package for computationally efficient Bayesian inference, using the gridded CHIRPS satellite-based rainfall dataset and digital elevation models as covariates. We jointly model both the probability of rainfall occurrence on a given day (using a binomial likelihood) as well as amount (using a gamma likelihood or similar). Correlation in space and time is modelled using a Gaussian Markov Random Field (GMRF) with a Matérn spatial covariance function which can evolve over time according to an autoregressive model if desired. It is possible to evaluate the GMRF at relatively coarse temporal resolution to speed up computations, but still produce daily rainfall predictions. We describe the process of model selection and inference using an information criterion approach, which we use to objectively select from competing models with various combinations of temporal smoothing, likelihoods, and autoregressive model orders.

  20. Spatio-Temporal Change Modeling of Lulc: a Semantic Kriging Approach

    NASA Astrophysics Data System (ADS)

    Bhattacharjee, S.; Ghosh, S. K.

    2015-07-01

    Spatio-temporal land-use/ land-cover (LULC) change modeling is important to forecast the future LULC distribution, which may facilitate natural resource management, urban planning, etc. The spatio-temporal change in LULC trend often exhibits non-linear behavior, due to various dynamic factors, such as, human intervention (e.g., urbanization), environmental factors, etc. Hence, proper forecasting of LULC distribution should involve the study and trend modeling of historical data. Existing literatures have reported that the meteorological attributes (e.g., NDVI, LST, MSI), are semantically related to the terrain. Being influenced by the terrestrial dynamics, the temporal changes of these attributes depend on the LULC properties. Hence, incorporating meteorological knowledge into the temporal prediction process may help in developing an accurate forecasting model. This work attempts to study the change in inter-annual LULC pattern and the distribution of different meteorological attributes of a region in Kolkata (a metropolitan city in India) during the years 2000-2010 and forecast the future spread of LULC using semantic kriging (SemK) approach. A new variant of time-series SemK is proposed, namely Rev-SemKts to capture the multivariate semantic associations between different attributes. From empirical analysis, it may be observed that the augmentation of semantic knowledge in spatio-temporal modeling of meteorological attributes facilitate more precise forecasting of LULC pattern.

  1. A method to estimate spatiotemporal air quality in an urban traffic corridor.

    PubMed

    Singh, Nongthombam Premananda; Gokhale, Sharad

    2015-12-15

    Air quality exposure assessment using personal exposure sampling or direct measurement of spatiotemporal air pollutant concentrations has difficulty and limitations. Most statistical methods used for estimating spatiotemporal air quality do not account for the source characteristics (e.g. emissions). In this study, a prediction method, based on the lognormal probability distribution of hourly-average-spatial concentrations of carbon monoxide (CO) obtained by a CALINE4 model, has been developed and validated in an urban traffic corridor. The data on CO concentrations were collected at three locations and traffic and meteorology within the urban traffic corridor.(1) The method has been developed with the data of one location and validated at other two locations. The method estimated the CO concentrations reasonably well (correlation coefficient, r≥0.96). Later, the method has been applied to estimate the probability of occurrence [P(C≥Cstd] of the spatial CO concentrations in the corridor. The results have been promising and, therefore, may be useful to quantifying spatiotemporal air quality within an urban area. PMID:26318683

  2. A method to estimate spatiotemporal air quality in an urban traffic corridor.

    PubMed

    Singh, Nongthombam Premananda; Gokhale, Sharad

    2015-12-15

    Air quality exposure assessment using personal exposure sampling or direct measurement of spatiotemporal air pollutant concentrations has difficulty and limitations. Most statistical methods used for estimating spatiotemporal air quality do not account for the source characteristics (e.g. emissions). In this study, a prediction method, based on the lognormal probability distribution of hourly-average-spatial concentrations of carbon monoxide (CO) obtained by a CALINE4 model, has been developed and validated in an urban traffic corridor. The data on CO concentrations were collected at three locations and traffic and meteorology within the urban traffic corridor.(1) The method has been developed with the data of one location and validated at other two locations. The method estimated the CO concentrations reasonably well (correlation coefficient, r≥0.96). Later, the method has been applied to estimate the probability of occurrence [P(C≥Cstd] of the spatial CO concentrations in the corridor. The results have been promising and, therefore, may be useful to quantifying spatiotemporal air quality within an urban area.

  3. A Metascalable Computing Framework for Large Spatiotemporal-Scale Atomistic Simulations

    SciTech Connect

    Nomura, K; Seymour, R; Wang, W; Kalia, R; Nakano, A; Vashishta, P; Shimojo, F; Yang, L H

    2009-02-17

    A metascalable (or 'design once, scale on new architectures') parallel computing framework has been developed for large spatiotemporal-scale atomistic simulations of materials based on spatiotemporal data locality principles, which is expected to scale on emerging multipetaflops architectures. The framework consists of: (1) an embedded divide-and-conquer (EDC) algorithmic framework based on spatial locality to design linear-scaling algorithms for high complexity problems; (2) a space-time-ensemble parallel (STEP) approach based on temporal locality to predict long-time dynamics, while introducing multiple parallelization axes; and (3) a tunable hierarchical cellular decomposition (HCD) parallelization framework to map these O(N) algorithms onto a multicore cluster based on hybrid implementation combining message passing and critical section-free multithreading. The EDC-STEP-HCD framework exposes maximal concurrency and data locality, thereby achieving: (1) inter-node parallel efficiency well over 0.95 for 218 billion-atom molecular-dynamics and 1.68 trillion electronic-degrees-of-freedom quantum-mechanical simulations on 212,992 IBM BlueGene/L processors (superscalability); (2) high intra-node, multithreading parallel efficiency (nanoscalability); and (3) nearly perfect time/ensemble parallel efficiency (eon-scalability). The spatiotemporal scale covered by MD simulation on a sustained petaflops computer per day (i.e. petaflops {center_dot} day of computing) is estimated as NT = 2.14 (e.g. N = 2.14 million atoms for T = 1 microseconds).

  4. Spatiotemporal Co-existence of Female Thyroid and Breast Cancers in Hangzhou, China

    PubMed Central

    Fei, Xufeng; Christakos, George; Lou, Zhaohan; Ren, Yanjun; Liu, Qingmin; Wu, Jiaping

    2016-01-01

    Thyroid and breast cancers (TC, BC) are common female malignant tumors worldwide. Studies suggest that TC patients have a higher BC risk, and vice versa. However, it has not been investigated quantitatively if there is an association between the space-time TC and BC incidence distributions at the population level. This work aims to answer this question. 5358 TC and 8784 BC (female) cases were diagnosed in Hangzhou (China, 2008–2012). Pearson and Spearman rank correlation coefficients of the TC and BC incidences were high, and their patterns were geographically similar. The spatiotemporal co-existence of TC and BC distributions was investigated using the integrative disease predictability (IDP) criterion: if TC-BC association is part of the disease mapping knowledge bases, it should yield improved space-time incidence predictions. Improved TC (BC) incidence predictions were generated when integrating both TC and BC data than when using only TC (BC) data. IDP consistently demonstrated the spatiotemporal co-existence of TC and BC distributions throughout Hangzhou (2008–2012), which means that when the population experiences high incidences of one kind of cancer attention should be paid to the other kind of cancer too. The strength of TC-BC association was measured by the IDP coefficients and incidence prediction accuracy. PMID:27341638

  5. Spatiotemporal Co-existence of Female Thyroid and Breast Cancers in Hangzhou, China

    NASA Astrophysics Data System (ADS)

    Fei, Xufeng; Christakos, George; Lou, Zhaohan; Ren, Yanjun; Liu, Qingmin; Wu, Jiaping

    2016-06-01

    Thyroid and breast cancers (TC, BC) are common female malignant tumors worldwide. Studies suggest that TC patients have a higher BC risk, and vice versa. However, it has not been investigated quantitatively if there is an association between the space-time TC and BC incidence distributions at the population level. This work aims to answer this question. 5358 TC and 8784 BC (female) cases were diagnosed in Hangzhou (China, 2008–2012). Pearson and Spearman rank correlation coefficients of the TC and BC incidences were high, and their patterns were geographically similar. The spatiotemporal co-existence of TC and BC distributions was investigated using the integrative disease predictability (IDP) criterion: if TC-BC association is part of the disease mapping knowledge bases, it should yield improved space-time incidence predictions. Improved TC (BC) incidence predictions were generated when integrating both TC and BC data than when using only TC (BC) data. IDP consistently demonstrated the spatiotemporal co-existence of TC and BC distributions throughout Hangzhou (2008–2012), which means that when the population experiences high incidences of one kind of cancer attention should be paid to the other kind of cancer too. The strength of TC-BC association was measured by the IDP coefficients and incidence prediction accuracy.

  6. Associative memory with spatiotemporal chaos control

    NASA Astrophysics Data System (ADS)

    Kushibe, Masanori; Liu, Yun; Ohtsubo, Junji

    1996-05-01

    Control of spatiotemporal chaos in a neural network with discrete time and continuous state variables is investigated. The chaos control is performed with the knowledge of only a part of the target information in the memory patterns. The success rate for the pattern associations and the dependence of the search time on the sampling number in the proposed chaos neural network are studied. By the introduction of the reinforcement factor in the learning process, the recognition rate of the network can be much enhanced. Random and regular samplings of the pattern for the control are tested and the successful results of the associations are demonstrated. The chaotic behavior and recalling ability of the system are evaluated based on the analysis of the Lyapunov spectrum of the network.

  7. Cortical spatiotemporal dimensionality reduction for visual grouping.

    PubMed

    Cocci, Giacomo; Barbieri, Davide; Citti, Giovanna; Sarti, Alessandro

    2015-06-01

    The visual systems of many mammals, including humans, are able to integrate the geometric information of visual stimuli and perform cognitive tasks at the first stages of the cortical processing. This is thought to be the result of a combination of mechanisms, which include feature extraction at the single cell level and geometric processing by means of cell connectivity. We present a geometric model of such connectivities in the space of detected features associated with spatiotemporal visual stimuli and show how they can be used to obtain low-level object segmentation. The main idea is to define a spectral clustering procedure with anisotropic affinities over data sets consisting of embeddings of the visual stimuli into higher-dimensional spaces. Neural plausibility of the proposed arguments will be discussed. PMID:25826020

  8. Spatio-temporal synchronization of recurrent epidemics.

    PubMed Central

    He, Daihai; Stone, Lewi

    2003-01-01

    Long-term spatio-temporal datasets of disease incidences have made it clear that many recurring epidemics, especially childhood infections, tend to synchronize in-phase across suburbs. In some special cases, epidemics between suburbs have been found to oscillate in an out-of-phase ('antiphase') relationship for lengthy periods. Here, we use modelling techniques to help explain the presence of in-phase and antiphase synchronization. The nonlinearity of the epidemic dynamics is often such that the intensity of the outbreak influences the phase of the oscillation thereby introducing 'shear', a factor that is found to be important for generating antiphase synchronization. By contrast, the coupling between suburbs via the immigration of infectives tends to enhance in-phase synchronization. The emerging synchronization depends delicately on these opposite factors. We use theoretical results from continuous time models to provide a framework for understanding the relationship between synchronization patterns for different model structures. PMID:12965019

  9. Spatiotemporal dynamics of counterpropagating Airy beams

    NASA Astrophysics Data System (ADS)

    Wiersma, Noémi; Marsal, Nicolas; Sciamanna, Marc; Wolfersberger, Delphine

    2015-08-01

    We analyse theoretically the spatiotemporal dynamics of two incoherent counterpropagating Airy beams interacting in a photorefractive crystal under focusing conditions. For a large enough nonlinearity strength the interaction between the two Airy beams leads to light-induced waveguiding. The stability of the waveguide is determined by the crystal length, the nonlinearity strength and the beam’s intensities and is improved when comparing to the situation using Gaussian beams. We further identify the threshold above which the waveguide is no longer static but evolves dynamically either time-periodically or even chaotically. Above the stability threshold, each Airy-soliton moves erratically between privileged output positions that correspond to the spatial positions of the lobes of the counterpropagating Airy beam. These results suggest new ways of creating dynamically varying waveguides, optical logic gates and chaos-based computing.

  10. Spatiotemporal dynamics of counterpropagating Airy beams

    PubMed Central

    Wiersma, Noémi; Marsal, Nicolas; Sciamanna, Marc; Wolfersberger, Delphine

    2015-01-01

    We analyse theoretically the spatiotemporal dynamics of two incoherent counterpropagating Airy beams interacting in a photorefractive crystal under focusing conditions. For a large enough nonlinearity strength the interaction between the two Airy beams leads to light-induced waveguiding. The stability of the waveguide is determined by the crystal length, the nonlinearity strength and the beam’s intensities and is improved when comparing to the situation using Gaussian beams. We further identify the threshold above which the waveguide is no longer static but evolves dynamically either time-periodically or even chaotically. Above the stability threshold, each Airy-soliton moves erratically between privileged output positions that correspond to the spatial positions of the lobes of the counterpropagating Airy beam. These results suggest new ways of creating dynamically varying waveguides, optical logic gates and chaos-based computing. PMID:26315530

  11. Concerning immune synapses: a spatiotemporal timeline

    PubMed Central

    Ortega-Carrion, Alvaro; Vicente-Manzanares, Miguel

    2016-01-01

    The term “immune synapse” was originally coined to highlight the similarities between the synaptic contacts between neurons in the central nervous system and the cognate, antigen-dependent interactions between T cells and antigen-presenting cells. Here, instead of offering a comprehensive molecular catalogue of molecules involved in the establishment, stabilization, function, and resolution of the immune synapse, we follow a spatiotemporal timeline that begins at the initiation of exploratory contacts between the T cell and the antigen-presenting cell and ends with the termination of the contact. We focus on specific aspects that distinguish synapses established by cytotoxic and T helper cells as well as unresolved issues and controversies regarding the formation of this intercellular structure. PMID:27092248

  12. Assessment of groundwater utilization for irrigating park trees under the spatiotemporal uncertainty condition of water quality

    NASA Astrophysics Data System (ADS)

    Jang, Cheng-Shin; Kuo, Yi-Ming

    2013-04-01

    Parks have a variety of functions for residents and are important for urban landscape planning. The healthy growth of urban park trees requires regular irrigation. To reduce the pressure of high groundwater levels and to avoid wasting groundwater resources, proper groundwater extraction for irrigating park trees in the Taipei Basin is regarded as a reciprocal solution of sustainable groundwater management and preserving excellent urban landscapes. Therefore, this study determines pristine groundwater use for irrigating park trees in the metropolitan Taipei Basin under the spatiotemporal uncertainty condition of water quality. First, six hydrochemical parameters in groundwater associated with an irrigation water quality standard were collected from a 12-year survey. Upper, median and lower quartiles of the six hydrochemical parameters were obtained to establish three thresholds. According to the irrigation water quality standard, multivariate indicator kriging (MVIK) was adopted to probabilistically evaluate the integration of the six hydrochemical parameters. Entropy was then applied to quantify the spatiotemporal uncertainty of the hydrochemical parameters. Finally, locations, which have high estimated probabilities for the median-quartile threshold and low local uncertainty, are suitable for pumping groundwater for irrigating park trees. The study results demonstrate that MVIK and entropy are capable of characterizing the spatiotemporal uncertainty of groundwater quality parameters and determining suitable parks of groundwater utilization for irrigation. Moreover, the upper, median and lower quartiles of hydrochemical parameters are served as three estimated thresholds in MVIK, which is robust to assessment predictions. Therefore, this study significantly improves the methodological application and limitation of MVIK for spatiotemporally analyzing environmental quality compared with the previous related works. Furthermore, the analyzed results indicate that 64

  13. Spatio-temporal Transmission and Environmental Determinants of Schistosomiasis Japonica in Anhui Province, China

    PubMed Central

    Hu, Yi; Li, Rui; Bergquist, Robert; Lynn, Henry; Gao, Fenghua; Wang, Qizhi; Zhang, Shiqing; Sun, Liqian; Zhang, Zhijie; Jiang, Qingwu

    2015-01-01

    Background Schistosomiasis japonica still remains of public health and economic significance in China, especially in the lake and marshland areas along the Yangtze River Basin, where the control of transmission has proven difficult. In the study, we investigated spatio-temporal variations of S. japonicum infection risk in Anhui Province and assessed the associations of the disease with key environmental factors with the aim of understanding the mechanism of the disease and seeking clues to effective and sustainable schistosomiasis control. Methodology/Principal Findings Infection data of schistosomiasis from annual conventional surveys were obtained at the village level in Anhui Province, China, from 2000 to 2010 and used in combination with environmental data. The spatio-temporal kriging model was used to assess how these environmental factors affected the spatio-temporal pattern of schistosomiasis risk. Our results suggested that seasonal variation of the normalized difference vegetation index (NDVI), seasonal variation of land surface temperature at daytime (LSTD), and distance to the Yangtze River were negatively significantly associated with risk of schistosomiasis. Predictive maps showed that schistosomiasis prevalence remained at a low level and schistosomiasis risk mainly evolved along the Yangtze River. Schistosomiasis risk also followed a focal spatial pattern, fluctuating temporally with a peak (the largest spatial extent) in 2005 and then contracting gradually but with a scattered distribution until 2010. Conclusion The fitted spatio-temporal kriging model can capture variations of schistosomiasis risk over space and time. Combined with techniques of geographic information system (GIS) and remote sensing (RS), this approach facilitates and enriches risk modeling of schistosomiasis, which in turn helps to identify prior areas for effective and sustainable control of schistosomiasis in Anhui Province and perhaps elsewhere in China. PMID:25659112

  14. Characterizing configurations of fire ignition points through spatiotemporal point processes

    NASA Astrophysics Data System (ADS)

    Comas, C.; Costafreda-Aumedes, S.; Vega-Garcia, C.

    2014-04-01

    Human-caused forest fires are usually regarded as unpredictable but often exhibit trends towards clustering in certain locations and periods. Characterizing such configurations is crucial for understanding spatiotemporal fire dynamics and implementing preventive actions. Our objectives were to analyse the spatiotemporal point configuration and to test for spatiotemporal interaction. We characterized the spatiotemporal structure of 984 fire ignition points in a study area of Galicia, Spain, during 2007-2011 by the K-Ripley's function. Our results suggest the presence of spatiotemporal structures for time lags of less than two years and ignition point distances in the range 0-12 km. Ignition centre points at time lags of less than 100 days are aggregated for any inter-event distance. This cluster structure loses strength as the time lag increases, and at time lags of more than 365 days this cluster structure is not significant for any lag distance. Our results also suggest spatiotemporal interdependencies at time lags of less than 100 days and inter-event distances of less than 10 km. At time lags of up to 365 days spatiotemporal components are independent for any point distance. These results suggest that risk conditions occur locally and are short-lived in this study area.

  15. Bayesian Modeling and Analysis for Gradients in Spatiotemporal Processes

    PubMed Central

    Quick, Harrison; Banerjee, Sudipto; Carlin, Bradley P.

    2015-01-01

    Summary Stochastic process models are widely employed for analyzing spatiotemporal datasets in various scientific disciplines including, but not limited to, environmental monitoring, ecological systems, forestry, hydrology, meteorology and public health. After inferring on a spatiotemporal process for a given dataset, inferential interest may turn to estimating rates of change, or gradients, over space and time. This manuscript develops fully model-based inference on spatiotemporal gradients under continuous space, continuous time settings. Our contribution is to offer, within a exible spatiotemporal process model setting, a framework to estimate arbitrary directional gradients over space at any given timepoint, temporal derivatives at any given spatial location and, finally, mixed spatiotemporal gradients that reflect rapid change in spatial gradients over time and vice-versa. We achieve such inference without compromising on rich and exible spatiotemporal process models and use nonseparable covariance structures. We illustrate our methodology using a simulated data example and subsequently apply it to a dataset of daily PM2.5 concentrations in California, where the spatiotemporal gradient process reveals the effects of California’s unique topography on pollution and detects the aftermath of a devastating series of wildfires. PMID:25898989

  16. Bayesian modeling and analysis for gradients in spatiotemporal processes.

    PubMed

    Quick, Harrison; Banerjee, Sudipto; Carlin, Bradley P

    2015-09-01

    Stochastic process models are widely employed for analyzing spatiotemporal datasets in various scientific disciplines including, but not limited to, environmental monitoring, ecological systems, forestry, hydrology, meteorology, and public health. After inferring on a spatiotemporal process for a given dataset, inferential interest may turn to estimating rates of change, or gradients, over space and time. This manuscript develops fully model-based inference on spatiotemporal gradients under continuous space, continuous time settings. Our contribution is to offer, within a flexible spatiotemporal process model setting, a framework to estimate arbitrary directional gradients over space at any given timepoint, temporal derivatives at any given spatial location and, finally, mixed spatiotemporal gradients that reflect rapid change in spatial gradients over time and vice-versa. We achieve such inference without compromising on rich and flexible spatiotemporal process models and use nonseparable covariance structures. We illustrate our methodology using a simulated data example and subsequently apply it to a dataset of daily PM2.5 concentrations in California, where the spatiotemporal gradient process reveals the effects of California's unique topography on pollution and detects the aftermath of a devastating series of wildfires. PMID:25898989

  17. Spatiotemporal complexity of the aortic sinus vortex

    NASA Astrophysics Data System (ADS)

    Moore, Brandon; Dasi, Lakshmi Prasad

    2014-07-01

    The aortic sinus vortex is a classical flow structure of significant importance to aortic valve dynamics and the initiation and progression of calcific aortic valve disease. We characterize the spatiotemporal characteristics of aortic sinus vortex dynamics in relation to the viscosity of blood analog solution as well as heart rate. High-resolution time-resolved (2 kHz) particle image velocimetry was conducted to capture 2D particle streak videos and 2D instantaneous velocity and streamlines along the sinus midplane using a physiological but rigid aorta model fitted with a porcine bioprosthetic heart valve. Blood analog fluids used include a water-glycerin mixture and saline to elucidate the sensitivity of vortex dynamics to viscosity. Experiments were conducted to record 10 heart beats for each combination of blood analog and heart rate condition. Results show that the topological characteristics of the velocity field vary in timescales as revealed using time bin-averaged vectors and corresponding instantaneous streamlines. There exist small timescale vortices and a large timescale main vortex. A key flow structure observed is the counter vortex at the upstream end of the sinus adjacent to the base (lower half) of the leaflet. The spatiotemporal complexity of vortex dynamics is shown to be profoundly influenced by strong leaflet flutter during systole with a peak frequency of 200 Hz and peak amplitude of 4 mm observed in the saline case. While fluid viscosity influences the length and timescales as well as the introduction of leaflet flutter, heart rate influences the formation of counter vortex at the upstream end of the sinus. Higher heart rates are shown to reduce the strength of the counter vortex that can greatly influence the directionality and strength of shear stresses along the base of the leaflet. This study demonstrates the impact of heart rate and blood analog viscosity on aortic sinus hemodynamics.

  18. Spatio-temporal properties of letter crowding

    PubMed Central

    Chung, Susana T. L.

    2016-01-01

    Crowding between adjacent letters has been investigated primarily as a spatial effect. The purpose of this study was to investigate the spatio-temporal properties of letter crowding. Specifically, we examined the systematic changes in the degradation effects in letter identification performance when adjacent letters were presented with a temporal asynchrony, as a function of letter separation and between the fovea and the periphery. We measured proportion-correct performance for identifying the middle target letter in strings of three lowercase letters at the fovea and 10° in the inferior visual field, for a range of center-to-center letter separations and a range of stimulus onset asynchronies (SOA) between the target and flanking letters (positive SOAs: target preceded flankers). As expected, the accuracy for identifying the target letters reduces with decreases in letter separation. This crowding effect shows a strong dependency on SOAs, such that crowding is maximal between 0 and ∼100 ms (depending on conditions) and diminishes for larger SOAs (positive or negative). Maximal crowding does not require the target and flanking letters to physically coexist for the entire presentation duration. Most importantly, crowding can be minimized even for closely spaced letters if there is a large temporal asynchrony between the target and flankers. The reliance of letter identification performance on SOAs and how it changes with letter separations imply that the crowding effect can be traded between space and time. Our findings are consistent with the notion that crowding should be considered as a spatio-temporal, and not simply a spatial, effect. PMID:27088895

  19. Spatio-temporal properties of letter crowding.

    PubMed

    Chung, Susana T L

    2016-01-01

    Crowding between adjacent letters has been investigated primarily as a spatial effect. The purpose of this study was to investigate the spatio-temporal properties of letter crowding. Specifically, we examined the systematic changes in the degradation effects in letter identification performance when adjacent letters were presented with a temporal asynchrony, as a function of letter separation and between the fovea and the periphery. We measured proportion-correct performance for identifying the middle target letter in strings of three lowercase letters at the fovea and 10° in the inferior visual field, for a range of center-to-center letter separations and a range of stimulus onset asynchronies (SOA) between the target and flanking letters (positive SOAs: target preceded flankers). As expected, the accuracy for identifying the target letters reduces with decreases in letter separation. This crowding effect shows a strong dependency on SOAs, such that crowding is maximal between 0 and ∼100 ms (depending on conditions) and diminishes for larger SOAs (positive or negative). Maximal crowding does not require the target and flanking letters to physically coexist for the entire presentation duration. Most importantly, crowding can be minimized even for closely spaced letters if there is a large temporal asynchrony between the target and flankers. The reliance of letter identification performance on SOAs and how it changes with letter separations imply that the crowding effect can be traded between space and time. Our findings are consistent with the notion that crowding should be considered as a spatio-temporal, and not simply a spatial, effect.

  20. Research of spatio-temporal analysis of agricultural pest

    NASA Astrophysics Data System (ADS)

    Wang, Changwei; Li, Deren; Hu, Yueming; Wu, Xiaofang; Qi, Yu

    2009-10-01

    The increase of agricultural pest disasters in recent years has become one of major problems in agriculture harvest; how to predict and control the disasters of agricultural pest has thus attracted great research interest. Although a series of works have been done and some achievements have been attained, the knowledge in this area remains limited. The migration of agricultural pest is not only related to the time variation, but also the space; consequently, the population of agricultural pest has complex spatio-temporal characteristics. The space factor and the temporal factor must be considered at the same time in the research of dynamics changes of the pest population. Using plant hoppers as an object of study, this study employed the biological analogy deviation model to study the distribution of pest population in different periods of time in Guangdong Province. It is demonstrated that the population distribution of plant hoppers is not only related to the space location, but also has a certain direction. The result reported here offers help to the monitor, prevention and control of plant hoppers in Guangdong Provinces.

  1. Spatiotemporal dynamics of auditory attention synchronize with speech

    PubMed Central

    Wöstmann, Malte; Herrmann, Björn; Maess, Burkhard

    2016-01-01

    Attention plays a fundamental role in selectively processing stimuli in our environment despite distraction. Spatial attention induces increasing and decreasing power of neural alpha oscillations (8–12 Hz) in brain regions ipsilateral and contralateral to the locus of attention, respectively. This study tested whether the hemispheric lateralization of alpha power codes not just the spatial location but also the temporal structure of the stimulus. Participants attended to spoken digits presented to one ear and ignored tightly synchronized distracting digits presented to the other ear. In the magnetoencephalogram, spatial attention induced lateralization of alpha power in parietal, but notably also in auditory cortical regions. This alpha power lateralization was not maintained steadily but fluctuated in synchrony with the speech rate and lagged the time course of low-frequency (1–5 Hz) sensory synchronization. Higher amplitude of alpha power modulation at the speech rate was predictive of a listener’s enhanced performance of stream-specific speech comprehension. Our findings demonstrate that alpha power lateralization is modulated in tune with the sensory input and acts as a spatiotemporal filter controlling the read-out of sensory content. PMID:27001861

  2. Spatiotemporal dynamics of auditory attention synchronize with speech.

    PubMed

    Wöstmann, Malte; Herrmann, Björn; Maess, Burkhard; Obleser, Jonas

    2016-04-01

    Attention plays a fundamental role in selectively processing stimuli in our environment despite distraction. Spatial attention induces increasing and decreasing power of neural alpha oscillations (8-12 Hz) in brain regions ipsilateral and contralateral to the locus of attention, respectively. This study tested whether the hemispheric lateralization of alpha power codes not just the spatial location but also the temporal structure of the stimulus. Participants attended to spoken digits presented to one ear and ignored tightly synchronized distracting digits presented to the other ear. In the magnetoencephalogram, spatial attention induced lateralization of alpha power in parietal, but notably also in auditory cortical regions. This alpha power lateralization was not maintained steadily but fluctuated in synchrony with the speech rate and lagged the time course of low-frequency (1-5 Hz) sensory synchronization. Higher amplitude of alpha power modulation at the speech rate was predictive of a listener's enhanced performance of stream-specific speech comprehension. Our findings demonstrate that alpha power lateralization is modulated in tune with the sensory input and acts as a spatiotemporal filter controlling the read-out of sensory content. PMID:27001861

  3. Systemic risk and spatiotemporal dynamics of the US housing market.

    PubMed

    Meng, Hao; Xie, Wen-Jie; Jiang, Zhi-Qiang; Podobnik, Boris; Zhou, Wei-Xing; Stanley, H Eugene

    2014-01-13

    Housing markets play a crucial role in economies and the collapse of a real-estate bubble usually destabilizes the financial system and causes economic recessions. We investigate the systemic risk and spatiotemporal dynamics of the US housing market (1975-2011) at the state level based on the Random Matrix Theory (RMT). We identify richer economic information in the largest eigenvalues deviating from RMT predictions for the housing market than for stock markets and find that the component signs of the eigenvectors contain either geographical information or the extent of differences in house price growth rates or both. By looking at the evolution of different quantities such as eigenvalues and eigenvectors, we find that the US housing market experienced six different regimes, which is consistent with the evolution of state clusters identified by the box clustering algorithm and the consensus clustering algorithm on the partial correlation matrices. We find that dramatic increases in the systemic risk are usually accompanied by regime shifts, which provide a means of early detection of housing bubbles.

  4. Systemic risk and spatiotemporal dynamics of the US housing market

    NASA Astrophysics Data System (ADS)

    Meng, Hao; Xie, Wen-Jie; Jiang, Zhi-Qiang; Podobnik, Boris; Zhou, Wei-Xing; Stanley, H. Eugene

    2014-01-01

    Housing markets play a crucial role in economies and the collapse of a real-estate bubble usually destabilizes the financial system and causes economic recessions. We investigate the systemic risk and spatiotemporal dynamics of the US housing market (1975-2011) at the state level based on the Random Matrix Theory (RMT). We identify richer economic information in the largest eigenvalues deviating from RMT predictions for the housing market than for stock markets and find that the component signs of the eigenvectors contain either geographical information or the extent of differences in house price growth rates or both. By looking at the evolution of different quantities such as eigenvalues and eigenvectors, we find that the US housing market experienced six different regimes, which is consistent with the evolution of state clusters identified by the box clustering algorithm and the consensus clustering algorithm on the partial correlation matrices. We find that dramatic increases in the systemic risk are usually accompanied by regime shifts, which provide a means of early detection of housing bubbles.

  5. Systemic risk and spatiotemporal dynamics of the US housing market

    PubMed Central

    Meng, Hao; Xie, Wen-Jie; Jiang, Zhi-Qiang; Podobnik, Boris; Zhou, Wei-Xing; Stanley, H. Eugene

    2014-01-01

    Housing markets play a crucial role in economies and the collapse of a real-estate bubble usually destabilizes the financial system and causes economic recessions. We investigate the systemic risk and spatiotemporal dynamics of the US housing market (1975–2011) at the state level based on the Random Matrix Theory (RMT). We identify richer economic information in the largest eigenvalues deviating from RMT predictions for the housing market than for stock markets and find that the component signs of the eigenvectors contain either geographical information or the extent of differences in house price growth rates or both. By looking at the evolution of different quantities such as eigenvalues and eigenvectors, we find that the US housing market experienced six different regimes, which is consistent with the evolution of state clusters identified by the box clustering algorithm and the consensus clustering algorithm on the partial correlation matrices. We find that dramatic increases in the systemic risk are usually accompanied by regime shifts, which provide a means of early detection of housing bubbles. PMID:24413626

  6. Key frame extraction based on spatiotemporal motion trajectory

    NASA Astrophysics Data System (ADS)

    Zhang, Yunzuo; Tao, Ran; Zhang, Feng

    2015-05-01

    Spatiotemporal motion trajectory can accurately reflect the changes of motion state. Motivated by this observation, this letter proposes a method for key frame extraction based on motion trajectory on the spatiotemporal slice. Different from the well-known motion related methods, the proposed method utilizes the inflexions of the motion trajectory on the spatiotemporal slice of all the moving objects. Experimental results show that although a similar performance is achieved in the single-objective screen, by comparing the proposed method to that achieved with the state-of-the-art methods based on motion energy or acceleration, the proposed method shows a better performance in a multiobjective video.

  7. Ambient Air Pollution and Preeclampsia: A Spatiotemporal Analysis

    PubMed Central

    Figueras, Francesc; Basagaña, Xavier; Beelen, Rob; Martinez, David; Cirach, Marta; Schembari, Anna; Hoek, Gerard; Brunekreef, Bert; Nieuwenhuijsen, Mark J

    2013-01-01

    Background: Available evidence concerning the association between air pollution and preeclampsia is limited, and specific associations with early- and late-onset preeclampsia have not been assessed. Objectives: We investigated the association, if any, between preeclampsia (all, early-, and late-onset) and exposure to nitrogen dioxide, nitrogen oxides, particulate matter with aerodynamic diameter ≤ 2.5 μm (PM2.5; fine particles), ≤ 10 μm, and 2.5–10 μm, and PM2.5 light absorption (a proxy for elemental carbon) during the entire pregnancy and during the first, second, and third trimesters. Methods: This study was based on 8,398 pregnancies (including 103 cases of preeclampsia) among women residing in Barcelona, Spain (2000–2005). We applied a spatiotemporal exposure assessment framework using land use regression models to predict ambient pollutant levels during each week of pregnancy at the geocoded residence address of each woman at the time of birth. Logistic and conditional logistic regression models were used to estimate unadjusted and adjusted associations. Results: We found positive associations for most of our evaluated outcome–exposure pairs, with the strongest associations observed for preeclampsia and late-onset preeclampsia in relation to the third-trimester exposure to fine particulate pollutants, and for early-onset preeclampsia in relation to the first-trimester exposure to fine particulate pollutants. Among our investigated associations, those of first- and third-trimester exposures to PM2.5 and third-trimester exposure to PM2.5 absorbance and all preeclampsia, and third-trimester PM2.5 exposure and late-onset preeclampsia attained statistical significance. Conclusion: We observed increased risk of preeclampsia associated with exposure to fine particulate air pollution. Our findings, in combination with previous evidence suggesting distinct pathogenic mechanisms for early- and late-onset preeclampsia, support additional research on this

  8. The spatiotemporal structure of control variables during catching.

    PubMed

    Polman, R C; Whiting, H T; Savelsbergh, G J

    1996-06-01

    The discrepancy between traditional (force scaling models) and the more recently conceived dynamic explanations of load compensation (lambda model) was the departure point for the present study. By using the complex "open" motor skill of catching a ball--rather than the traditional "closed" skills--under "normal" (baseline) conditions and under conditions where a spring load was applied to the catching hand (thereby changing the dynamics of the skeletomuscular system) it was hoped to provide further clarification of this issue. Traditional force scaling models, in this respect, would predict that maximal closing velocity of the grasp action, and movement time would not be significantly different between a control and a spring-load condition. In contrast, a dynamic system perspective would maintain that spring loading would be compensated for by a change in the rate of shift of the reciprocal command (R-command). The obtained results showed a significant difference for conditions with regard to the maximal closing velocity of the grasp action, the baseline condition being higher than the two spring-load conditions. Furthermore, a significant difference was found for the aperture at moment of catch, the aperture at moment of catch being smaller in the baseline condition than that under the two spring-load conditions. With regard to the temporal variables, no significant differences were obtained. A comprehensive overall explanation of the obtained data in terms of the force scaling models was not realisable. It may be that findings supporting such theories are task specific and that for constrained tasks--such as catching a ball--different underlying organisational principles apply. The lambda model, however, could explain adequately the obtained results. It was concluded that, except for the preparatory phase associated with load compensation before the onset of the movement of the ball, the spatiotemporal structure of the control pattern underlying catching remains

  9. Assessing the impact of a movement network on the spatiotemporal spread of infectious diseases.

    PubMed

    Schrödle, Birgit; Held, Leonhard; Rue, Håvard

    2012-09-01

    Linking information on a movement network with space-time data on disease incidence is one of the key challenges in infectious disease epidemiology. In this article, we propose and compare two statistical frameworks for this purpose, namely, parameter-driven (PD) and observation-driven (OD) models. Bayesian inference in PD models is done using integrated nested Laplace approximations, while OD models can be easily fitted with existing software using maximum likelihood. The predictive performance of both formulations is assessed using proper scoring rules. As a case study, the impact of cattle trade on the spatiotemporal spread of Coxiellosis in Swiss cows, 2004-2009, is finally investigated.

  10. Spatiotemporal Gait Parameters as Predictors of Lower-Limb Overuse Injuries in Military Training

    PubMed Central

    Gottlieb, Uri; Lozin, Mariya

    2016-01-01

    The study objective was to determine whether spatiotemporal gait parameters could predict lower-limb overuse injuries in cohort of combat soldiers during first year of military service. Newly recruited infantry soldiers walked on a treadmill at a 15° incline with a fixed speed of 1.67 m/sec while wearing a standard military vest with a 10 kg load. Stride time variability, stride length variability, step length asymmetry, and the duration of the loading response phase of the gait cycle were measured. Injury data on 76 soldiers who did not report musculoskeletal complaints at initial screening were collected one year after recruitment. Multiple logistic regression analyses were conducted to determine the predictive effect of the gait parameters on lower-limb injuries. Twenty-four soldiers (31.6%) had overuse injuries during the first year after recruitment. Duration of the loading response was a significant predictor of general lower-limb injury (p < 0.05), as well as of foot/ankle and knee injuries (p < 0.05, p < 0.01, resp.). A cutoff value of less than 12.15% for loading response duration predicted knee injuries with 83% sensitivity and 67% specificity. This study demonstrates the utility of spatiotemporal gait evaluation, a simple screening tool before military training, which may help to identify individuals at risk of lower-limb overuse injuries. PMID:27478864

  11. Spatiotemporal Gait Parameters as Predictors of Lower-Limb Overuse Injuries in Military Training.

    PubMed

    Springer, Shmuel; Gottlieb, Uri; Lozin, Mariya

    2016-01-01

    The study objective was to determine whether spatiotemporal gait parameters could predict lower-limb overuse injuries in cohort of combat soldiers during first year of military service. Newly recruited infantry soldiers walked on a treadmill at a 15° incline with a fixed speed of 1.67 m/sec while wearing a standard military vest with a 10 kg load. Stride time variability, stride length variability, step length asymmetry, and the duration of the loading response phase of the gait cycle were measured. Injury data on 76 soldiers who did not report musculoskeletal complaints at initial screening were collected one year after recruitment. Multiple logistic regression analyses were conducted to determine the predictive effect of the gait parameters on lower-limb injuries. Twenty-four soldiers (31.6%) had overuse injuries during the first year after recruitment. Duration of the loading response was a significant predictor of general lower-limb injury (p < 0.05), as well as of foot/ankle and knee injuries (p < 0.05, p < 0.01, resp.). A cutoff value of less than 12.15% for loading response duration predicted knee injuries with 83% sensitivity and 67% specificity. This study demonstrates the utility of spatiotemporal gait evaluation, a simple screening tool before military training, which may help to identify individuals at risk of lower-limb overuse injuries. PMID:27478864

  12. A LANGUAGE FOR MODULAR SPATIO-TEMPORAL SIMULATION (R824766)

    EPA Science Inventory

    Creating an effective environment for collaborative spatio-temporal model development will require computational systems that provide support for the user in three key areas: (1) Support for modular, hierarchical model construction and archiving/linking of simulation modules; (2)...

  13. Transition of spatiotemporal patterns in neuronal networks with chemical synapses

    NASA Astrophysics Data System (ADS)

    Wang, Rong; Li, Jiajia; Du, Mengmeng; Lei, Jinzhi; Wu, Ying

    2016-11-01

    In mammalian neocortex plane waves, spiral and irregular waves appear alternately. In this paper, we study the transition of spatiotemporal patterns in neuronal networks in which neurons are coupled via two types of chemical synapses: fast excitatory synapse and fast inhibitory synapse. Our results indicate that the fast excitatory synapse connection is easier to induce regular spatiotemporal patterns than fast inhibitory synapse connection, and the mechanism is discussed through bifurcation analysis of a single neuron. We introduce the permutation entropy as a measure of network firing complexity to study the mechanisms of formation and transition of spatiotemporal patterns. Our calculations show that the spatiotemporal pattern transitions are closely connected to a sudden decrease in the firing complexity of neuronal networks, and the neuronal networks with fast excitatory synapses have higher firing complexity than those with fast inhibitory synapses.

  14. The Activation-Induced Assembly of an RNA/Protein Interactome Centered on the Splicing Factor U2AF2 Regulates Gene Expression in Human CD4 T Cells.

    PubMed

    Whisenant, Thomas C; Peralta, Eigen R; Aarreberg, Lauren D; Gao, Nina J; Head, Steven R; Ordoukhanian, Phillip; Williamson, Jamie R; Salomon, Daniel R

    2015-01-01

    Activation of CD4 T cells is a reaction to challenges such as microbial pathogens, cancer and toxins that defines adaptive immune responses. The roles of T cell receptor crosslinking, intracellular signaling, and transcription factor activation are well described, but the importance of post-transcriptional regulation by RNA-binding proteins (RBPs) has not been considered in depth. We describe a new model expanding and activating primary human CD4 T cells and applied this to characterizing activation-induced assembly of splicing factors centered on U2AF2. We immunoprecipitated U2AF2 to identify what mRNA transcripts were bound as a function of activation by TCR crosslinking and costimulation. In parallel, mass spectrometry revealed the proteins incorporated into the U2AF2-centered RNA/protein interactome. Molecules that retained interaction with the U2AF2 complex after RNAse treatment were designated as "central" interactome members (CIMs). Mass spectrometry also identified a second class of activation-induced proteins, "peripheral" interactome members (PIMs), that bound to the same transcripts but were not in physical association with U2AF2 or its partners. siRNA knockdown of two CIMs and two PIMs caused changes in activation marker expression, cytokine secretion, and gene expression that were unique to each protein and mapped to pathways associated with key aspects of T cell activation. While knocking down the PIM, SYNCRIP, impacts a limited but immunologically important set of U2AF2-bound transcripts, knockdown of U2AF1 significantly impairs assembly of the majority of protein and mRNA components in the activation-induced interactome. These results demonstrated that CIMs and PIMs, either directly or indirectly through RNA, assembled into activation-induced U2AF2 complexes and play roles in post-transcriptional regulation of genes related to cytokine secretion. These data suggest an additional layer of regulation mediated by the activation-induced assembly of RNA

  15. The Activation-Induced Assembly of an RNA/Protein Interactome Centered on the Splicing Factor U2AF2 Regulates Gene Expression in Human CD4 T Cells

    PubMed Central

    Aarreberg, Lauren D.; Gao, Nina J.; Head, Steven R.; Ordoukhanian, Phillip; Williamson, Jamie R.; Salomon, Daniel R.

    2015-01-01

    Activation of CD4 T cells is a reaction to challenges such as microbial pathogens, cancer and toxins that defines adaptive immune responses. The roles of T cell receptor crosslinking, intracellular signaling, and transcription factor activation are well described, but the importance of post-transcriptional regulation by RNA-binding proteins (RBPs) has not been considered in depth. We describe a new model expanding and activating primary human CD4 T cells and applied this to characterizing activation-induced assembly of splicing factors centered on U2AF2. We immunoprecipitated U2AF2 to identify what mRNA transcripts were bound as a function of activation by TCR crosslinking and costimulation. In parallel, mass spectrometry revealed the proteins incorporated into the U2AF2-centered RNA/protein interactome. Molecules that retained interaction with the U2AF2 complex after RNAse treatment were designated as “central” interactome members (CIMs). Mass spectrometry also identified a second class of activation-induced proteins, “peripheral” interactome members (PIMs), that bound to the same transcripts but were not in physical association with U2AF2 or its partners. siRNA knockdown of two CIMs and two PIMs caused changes in activation marker expression, cytokine secretion, and gene expression that were unique to each protein and mapped to pathways associated with key aspects of T cell activation. While knocking down the PIM, SYNCRIP, impacts a limited but immunologically important set of U2AF2-bound transcripts, knockdown of U2AF1 significantly impairs assembly of the majority of protein and mRNA components in the activation-induced interactome. These results demonstrated that CIMs and PIMs, either directly or indirectly through RNA, assembled into activation-induced U2AF2 complexes and play roles in post-transcriptional regulation of genes related to cytokine secretion. These data suggest an additional layer of regulation mediated by the activation-induced assembly

  16. Spatiotemporal stochastic resonance and its consequences in neural model systems.

    PubMed

    Balazsi, Gabor; Kish, Laszlo B.; Moss, Frank E.

    2001-09-01

    The realization of spatiotemporal stochastic resonance is studied in a two-dimensional FitzHugh-Nagumo system, and in a one-dimensional system of integrate-and-fire neurons. We show that spatiotemporal stochastic resonance occurs in these neural model systems, independent of the method of modeling. Moreover, the ways of realization are analogous in the two model systems. The biological implications and open questions are discussed. (c) 2001 American Institute of Physics. PMID:12779493

  17. Propagation of partially coherent pulsed beams in the spatiotemporal domain.

    PubMed

    Wang, Li-gang; Lin, Qiang; Chen, Hong; Zhu, Shi-yao

    2003-05-01

    A generalized model to describe the spatiotemporal partially coherent pulsed beams is presented. The corresponding propagation formula is derived by using the partially coherent light theory. Based on this formula, we obtain a nonstationary generalized ABCD law (which illustrates the transformation of optical beams or pulses passing through media) to describe the spatiotemporal behavior of partially coherent Gaussian pulsed beams. The physical meaning of such generalized pulsed beams is discussed. An example to illustrate the application of this law is given. PMID:12786302

  18. Different routes from a matter wavepacket to spatiotemporal chaos

    SciTech Connect

    Rong Shiguang; Hai Wenhua; Xie Qiongtao; Zhong Honghua

    2012-09-15

    We investigate the dynamics of a quasi-one-dimensional Bose-Einstein condensate confined in a double-well potential with spatiotemporally modulated interaction. A variety of phenomena is identified in different frequency regimes, including the self-compression, splitting, breathing-like, and near-fidelity of the matter wavepacket, which are associated with different routes for the onset of spatiotemporal chaos. The results also reveal that chaos can retain space-inversion symmetry of the system.

  19. Spatiotemporal characteristics of flood protection level

    NASA Astrophysics Data System (ADS)

    Tanoue, M.; Ikeuchi, H.; Hirabayashi, Y.

    2015-12-01

    Flooding is the most frequent natural hazard and its global impacts will be rising associated with climate change and socioeconomic growth. So, the understanding of the physical and spatial-temporal patterns of risk drivers (exposure, damage, and flood protection level) are required to conduct effective adaptation and reduce the negative impacts of flooding. Although the understanding of exposure and damage has greatly improved using a combination of numerical model simulation and spatiotemporal distributions of population and asset, that of flood protection level is still lacking in particular spatial patterns. Previous research clarifies its temporal variation and relationship with per-capita income, however they do not consider its spatial variation. Flood protection level was associated with geographical characteristics (e.g., soil type and tectonic zone etc). This study tried to estimate spatiotemporal of flood protection level at country level and discuss about relationship between its spatial patterns and geographical characteristics. Mortality rate (percentage of fatalities in modeled exposed population) and loss rate (percentage of losses in modeled exposed GDP) to fluvial river flooding across the world suggested by Jongmann et al. (2015) were estimated from modeled flood exposure and damage statistics taken from the International Emergency Disasters Database. The result indicated that mortality rate reduced across the world from 1990 to 2005. The degree of its reduction decreased with increasing per-capita income level. On the other hand, loss rate at high income and middle low income levels reduced, while that at middle high income and low income levels drastically increased between 1995 and 2000 due to growth economic and occurrence of serious fluvial river flooding. Spatial distribution of mortality and loss rates were high in East Asia, the western part of South America, and the eastern part of Europe. These regions seem to be corresponded to the

  20. Parallel indexing technique for spatio-temporal data

    NASA Astrophysics Data System (ADS)

    He, Zhenwen; Kraak, Menno-Jan; Huisman, Otto; Ma, Xiaogang; Xiao, Jing

    2013-04-01

    The requirements for efficient access and management of massive multi-dimensional spatio-temporal data in geographical information system and its applications are well recognized and researched. The most popular spatio-temporal access method is the R-Tree and its variants. However, it is difficult to use them for parallel access to multi-dimensional spatio-temporal data because R-Trees, and variants thereof, are in hierarchical structures which have severe overlapping problems in high dimensional space. We extended a two-dimensional interval space representation of intervals to a multi-dimensional parallel space, and present a set of formulae to transform spatio-temporal queries into parallel interval set operations. This transformation reduces problems of multi-dimensional object relationships to simpler two-dimensional spatial intersection problems. Experimental results show that the new parallel approach presented in this paper has superior range query performance than R*-trees for handling multi-dimensional spatio-temporal data and multi-dimensional interval data. When the number of CPU cores is larger than that of the space dimensions, the insertion performance of this new approach is also superior to R*-trees. The proposed approach provides a potential parallel indexing solution for fast data retrieval of massive four-dimensional or higher dimensional spatio-temporal data.

  1. MaxiK channel interactome reveals its interaction with GABA transporter 3 and heat shock protein 60 in the mammalian brain.

    PubMed

    Singh, H; Li, M; Hall, L; Chen, S; Sukur, S; Lu, R; Caputo, A; Meredith, A L; Stefani, E; Toro, L

    2016-03-11

    Large conductance voltage and calcium-activated potassium (MaxiK) channels are activated by membrane depolarization and elevated cytosolic Ca(2+). In the brain, they localize to neurons and astrocytes, where they play roles such as resetting the membrane potential during an action potential, neurotransmitter release, and neurovascular coupling. MaxiK channels are known to associate with several modulatory proteins and accessory subunits, and each of these interactions can have distinct physiological consequences. To uncover new players in MaxiK channel brain physiology, we applied a directed proteomic approach and obtained MaxiK channel pore-forming α subunit brain interactome using specific antibodies. Controls included immunoprecipitations with rabbit immunoglobulin G (IgG) and with anti-MaxiK antibodies in wild type and MaxiK channel knockout mice (Kcnma1(-/-)), respectively. We have found known and unreported interactive partners that localize to the plasma membrane, extracellular space, cytosol and intracellular organelles including mitochondria, nucleus, endoplasmic reticulum and Golgi apparatus. Localization of MaxiK channel to mitochondria was further confirmed using purified brain mitochondria colabeled with MitoTracker. Independent proof of MaxiK channel interaction with previously unidentified partners is given for GABA transporter 3 (GAT3) and heat shock protein 60 (HSP60). In human embryonic kidney 293 cells containing SV40 T-antigen (HEK293T) cells, both GAT3 and HSP60 coimmunoprecipitated and colocalized with MaxiK channel; colabeling was observed mainly at the cell periphery with GAT3 and intracellularly with HSP60 with protein proximity indices of ∼ 0.6 and ∼ 0.4, respectively. In rat primary hippocampal neurons, colocalization index was identical for GAT3 (∼ 0.6) and slightly higher for HSP60 (∼ 0.5) association with MaxiK channel. The results of this study provide a complete interactome of MaxiK channel the mouse brain, further establish

  2. Identification of the Hypoxia-inducible Factor 2α Nuclear Interactome in Melanoma Cells Reveals Master Proteins Involved in Melanoma Development*

    PubMed Central

    Steunou, Anne-Lise; Ducoux-Petit, Manuelle; Lazar, Ikrame; Monsarrat, Bernard; Erard, Monique; Muller, Catherine; Clottes, Eric; Burlet-Schiltz, Odile; Nieto, Laurence

    2013-01-01

    Hypoxia-inducible factors (HIFs) are heterodimeric transcription factors that play a key role in cellular adaptation to hypoxia. HIF proteins are composed of an α subunit regulated by oxygen pressure (essentially HIF1α or HIF2α) and a constitutively expressed β subunit. These proteins are often overexpressed in cancer cells, and HIF overexpression frequently correlates with poor prognosis, making HIF proteins promising therapeutic targets. HIF proteins are involved in melanoma initiation and progression; however, the specific function of HIF2 in melanoma has not yet been studied comprehensively. Identifying protein complexes is a valuable way to uncover protein function, and affinity purification coupled with mass spectrometry and label-free quantification is a reliable method for this approach. We therefore applied quantitative interaction proteomics to identify exhaustively the nuclear complexes containing HIF2α in a human melanoma cell line, 501mel. We report, for the first time, a high-throughput analysis of the interactome of an HIF subunit. Seventy proteins were identified that interact with HIF2α, including some well-known HIF partners and some new interactors. The new HIF2α partners microphthalmia-associated transcription factor, SOX10, and AP2α, which are master actors of melanoma development, were confirmed via co-immunoprecipitation experiments. Their ability to bind to HIF1α was also tested: microphthalmia-associated transcription factor and SOX10 were confirmed as HIF1α partners, but the transcription factor AP2α was not. AP2α expression correlates with low invasive capacities. Interestingly, we demonstrated that when HIF2α was overexpressed, only cells expressing large amounts of AP2α exhibited decreased invasive capacities in hypoxia relative to normoxia. The simultaneous presence of both transcription factors therefore reduces cells' invasive properties. Knowledge of the HIF2α interactome is thus a useful resource for investigating

  3. Transient dynamics and rhythm coordination of inferior olive spatio-temporal patterns.

    PubMed

    Latorre, Roberto; Aguirre, Carlos; Rabinovich, Mikhail I; Varona, Pablo

    2013-01-01

    The inferior olive (IO) is a neural network belonging to the olivo-cerebellar system whose neurons are coupled with electrical synapses and display subthreshold oscillations and spiking activity. The IO is frequently proposed as the generator of timing signals to the cerebellum. Electrophysiological and imaging recordings show that the IO network generates complex spatio-temporal patterns. The generation and modulation of coherent spiking activity in the IO is one key issue in cerebellar research. In this work, we build a large scale IO network model of electrically coupled conductance-based neurons to study the emerging spatio-temporal patterns of its transient neuronal activity. Our modeling reproduces and helps to understand important phenomena observed in IO in vitro and in vivo experiments, and draws new predictions regarding the computational properties of this network and the associated cerebellar circuits. The main factors studied governing the collective dynamics of the IO network were: the degree of electrical coupling, the extent of the electrotonic connections, the presence of stimuli or regions with different excitability levels and the modulatory effect of an inhibitory loop (IL). The spatio-temporal patterns were analyzed using a discrete wavelet transform to provide a quantitative characterization. Our results show that the electrotonic coupling produces quasi-synchronized subthreshold oscillations over a wide dynamical range. The synchronized oscillatory activity plays the role of a timer for a coordinated representation of spiking rhythms with different frequencies. The encoding and coexistence of several coordinated rhythms is related to the different clusterization and coherence of transient spatio-temporal patterns in the network, where the spiking activity is commensurate with the quasi-synchronized subthreshold oscillations. In the presence of stimuli, different rhythms are encoded in the spiking activity of the IO neurons that nevertheless

  4. Spatiotemporal Temperature Distribution and Cancer Cell Death in Response to Extracellular Hyperthermia Induced by Gold Nanorods

    PubMed Central

    Huang, Huang-Chiao; Rege, Kaushal; Heys, Jeffrey J.

    2010-01-01

    Plasmonic nanoparticles have shown promise in hyperthermic cancer therapy, both in vitro and in vivo. Previous reports have described hyperthermic ablation using targeted and non-targeted nanoparticles internalized by cancer cells, but most reports do not describe a theoretical analysis for determining optimal parameters. The focus of the current research was first to evaluate the spatiotemporal temperature distribution and cell death induced by extracellular hyperthermia in which gold nanorods (GNRs) were maintained in the dispersion outside human prostate cancer cells. The nanorod dispersion was irradiated with near infrared (NIR) laser and the spatiotemporal distribution of temperature was determined experimentally. This information was employed to develop and validate theoretical models of spatiotemporal temperature profiles for gold nanorod dispersions undergoing laser irradiation, and the impact of the resulting heat generation on the viability of human prostate cancer cells. A cell injury/death model was then coupled to the heat transfer model to predict spatial and temporal variations in cell death and injury. The model predictions agreed well with experimental measurements of both, temperature and cell death profiles. Finally, the model was extended to examine the impact of selective binding of gold nanorods to cancer cells compared to non-malignant cells, coupled with a small change in cell injury activation energy. The impact of these relatively minor changes results in a dramatic change in the overall cell death rate. Taken together, extracellular hyperthermia using gold nanorods is a promising strategy and tailoring the cellular binding efficacy of nanorods can result in varying therapeutic efficacies using this approach. PMID:20387828

  5. Spatio-temporal availability of soft mast in clearcuts in the Southern Appalachians

    USGS Publications Warehouse

    Reynolds-Hogland, M. J.; Mitchell, M.S.; Powell, R.A.

    2006-01-01

    Soft mast is an important resource for many wild populations in the Southern Appalachians, yet the way clear-cutting affects availability of soft mast though time is not fully understood. We tested a theoretical model of temporal availability of soft mast in clearcuts using empirical data on percent cover and berry production of Gaylussacia, Vaccinium, and Rubus spp. plants in 100 stands that were clearcut (0-122 years old) in the Southern Appalachian Mountains. We modeled the relationship between soft mast availability and stand age, evaluated the effects of topography and forest type on soft mast, developed statistical models for predicting the spatio-temporal distribution of soft mast, and tested the hypothesis that percent cover of berry plants and berry production provided similar information about soft mast availability. We found temporal dynamics explained berry production better than it predicted percent plant cover, whereas topographic variables influenced percent plant cover more than they influenced berry production. Berry production and percent plant cover were highest in ???2-9-year-old stands. Percent plant cover was lowest in 10-69-year-old stands and intermediate in 70+-year-old stands. Three of our spatio-temporal models performed well during model testing and they were not biased by the training data, indicating the inferences about spatio-temporal availability of soft mast extended beyond our sample data. The methods we used to estimate the distribution of soft mast may be useful for modeling distributions of other resources. ?? 2006 Elsevier B.V. All rights reserved.

  6. Spatiotemporal gait parameters and recurrent falls in community-dwelling elderly women: a prospective study

    PubMed Central

    Moreira, Bruno S.; Sampaio, Rosana F.; Kirkwood, Renata N.

    2015-01-01

    BACKGROUND: Falling is a common but devastating and costly problem of aging. There is no consensus in the literature on whether the spatial and temporal gait parameters could identify elderly people at risk of recurrent falls. OBJECTIVE: To determine whether spatiotemporal gait parameters could predict recurrent falls in elderly women. METHOD: One hundred and forty-eight elderly women (65-85 years) participated in this study. Seven spatiotemporal gait parameters were collected with the GAITRite(r) system. Falls were recorded prospectively during 12 months through biweekly phone contacts. Elderly women who reported two or more falls throughout the follow-up period were considered as recurrent fallers. Principal component analysis (PCA) and discriminant analysis followed by biplot graph interpretation were applied to the gait parameters. RESULTS: After 12 months, 23 elderly women fell twice or more and comprised the recurrent fallers group and 110 with one or no falls comprised the non-recurrent fallers group. PCA resulted in three components that explained 88.3% of data variance. Discriminant analysis showed that none of the components could significantly discriminate the groups. However, visual inspection of the biplot showed a trend towards group separation in relation to gait velocity and stance time. PC1 represented gait rhythm and showed that recurrent fallers tend to walk with lower velocity and cadence and increased stance time in relation to non-recurrent fallers. CONCLUSIONS: The analyzed spatiotemporal gait parameters failed to predict recurrent falls in this sample. The PCA-biplot technique highlighted important trends or red flags that should be considered when evaluating recurrent falls in elderly females. PMID:25714603

  7. Spatio-temporal correlations in Coulomb clusters

    NASA Astrophysics Data System (ADS)

    Ghosal, Amit; Ash, Biswarup; Chakrabarti, Jaydeb

    Dynamical response of Coulomb-particles in nanoclusters are investigated at different temperatures characterizing their solid-like (Wigner molecule) and liquid-like behavior. The density correlations probe spatio-temporal relaxation, uncovering distinct behavior at multiple time scales in these systems. They show a stretched-Gaussian or stretched-exponential spatial decay at long times in circular and irregular traps. Interplay of confinement and long-range nature of interactions yields spatially correlated motion of the particles in string-like paths, leaving the system heterogeneous even at long times. While particles in a `solid' flow producing dynamic heterogeneities, their random motion in `liquid' defies central limit theorem. Distinguishing the two confinements, temperature dependent motional signatures serve as a criterion for the crossover between `solid' and `liquid'. The irregular Wigner molecule turns into a nearly homogeneous liquid over a much wider temperature window compared to the circular case. The temperature dependence of different relaxation time scales builds crucial insights. A phenomenological model, relating the unusual dynamics to the heterogeneous nature of the diffusivities in the system, captures much of the subtleties of our numerical simulations.

  8. Spatiotemporal video deinterlacing using control grid interpolation

    NASA Astrophysics Data System (ADS)

    Venkatesan, Ragav; Zwart, Christine M.; Frakes, David H.; Li, Baoxin

    2015-03-01

    With the advent of progressive format display and broadcast technologies, video deinterlacing has become an important video-processing technique. Numerous approaches exist in the literature to accomplish deinterlacing. While most earlier methods were simple linear filtering-based approaches, the emergence of faster computing technologies and even dedicated video-processing hardware in display units has allowed higher quality but also more computationally intense deinterlacing algorithms to become practical. Most modern approaches analyze motion and content in video to select different deinterlacing methods for various spatiotemporal regions. We introduce a family of deinterlacers that employs spectral residue to choose between and weight control grid interpolation based spatial and temporal deinterlacing methods. The proposed approaches perform better than the prior state-of-the-art based on peak signal-to-noise ratio, other visual quality metrics, and simple perception-based subjective evaluations conducted by human viewers. We further study the advantages of using soft and hard decision thresholds on the visual performance.

  9. Spatiotemporal Patterns in Excitable and Self - Media

    NASA Astrophysics Data System (ADS)

    Zou, Xiaoqin

    The formation of spatiotemporal patterns is studied in excitable and self-oscillatory media. Two systems are considered in detail: oxidation of CO over catalyst surfaces and propagation of cardiac action potentials. In the first case, several wave patterns are investigated, including traveling waves and spiral waves on a polycrystalline substrate at atmospheric pressure, and standing waves on a single crystal surface at low pressure. Specifically, the dispersion relation and linear stability are analyzed for traveling waves, and selection rules of frequency and wavelength are obtained for spirals. A possible mechanism for the formation of standing waves is also proposed, that of a self-induced parametric driving. In the cardiac case, reentrant spiral waves are examined from two different perspectives. First, the interaction between a drifting spiral and defects is studied numerically by modeling the myocardium as a simple excitable medium. Here, trapping by defects will sustain a permanent reentrant spiral. Second, the instability of spiral waves is analyzed indirectly by investigating electrical wave propagation along a ring. A coupled discrete map reduced from a electrophyiological model shows that a 1D (almost) period-doubling instability is closely related to 2D spiral breakup.

  10. Spatiotemporal SERT expression in cortical map development.

    PubMed

    Chen, Xiaoning; Petit, Emilie I; Dobrenis, Kostantin; Sze, Ji Ying

    2016-09-01

    The cerebral cortex is organized into morphologically distinct areas that provide biological frameworks underlying perception, cognition, and behavior. Profiling mouse and human cortical transcriptomes have revealed temporal-specific differential gene expression modules in distinct neocortical areas during cortical map establishment. However, the biological roles of spatiotemporal gene expression in cortical patterning and how cortical topographic gene expression is regulated are largely unknown. Here, we characterize temporal- and spatial-defined expression of serotonin (5-HT) transporter (SERT) in glutamatergic neurons during sensory map development in mice. SERT is transiently expressed in glutamatergic thalamic neurons projecting to sensory cortices and in pyramidal neurons in the prefrontal cortex (PFC) and hippocampus (HPC) during the period that lays down the basic functional neural circuits. We previously identified that knockout of SERT in the thalamic neurons blocks 5-HT uptake by their thalamocortical axons, resulting in excessive 5-HT signaling that impairs sensory map architecture. In contrast, here we show that selective SERT knockout in the PFC and HPC neurons does not perturb sensory map patterning. These data suggest that transient SERT expression in specific glutamatergic neurons provides area-specific instructions for cortical map patterning. Hence, genetic and pharmacological manipulations of this SERT function could illuminate the fundamental genetic programming of cortex-specific maps and biological roles of temporal-specific cortical topographic gene expression in normal development and mental disorders. PMID:27282696

  11. Network Analysis Using Spatio-Temporal Patterns

    NASA Astrophysics Data System (ADS)

    Miranda, Gisele H. B.; Machicao, Jeaneth; Bruno, Odemir M.

    2016-08-01

    Different network models have been proposed along the last years inspired by real-world topologies. The characterization of these models implies the understanding of the underlying network phenomena, which accounts structural and dynamic properties. Several mathematical tools can be employed to characterize such properties as Cellular Automata (CA), which can be defined as dynamical systems of discrete nature composed by spatially distributed units governed by deterministic rules. In this paper, we proposed a method based on the modeling of one specific CA over distinct network topologies in order to perform the classification of the network model. The proposed methodology consists in the modeling of a binary totalistic CA over a network. The transition function that governs each CA cell is based on the density of living neighbors. Secondly, the distribution of the Shannon entropy is obtained from the evolved spatio-temporal pattern of the referred CA and used as a network descriptor. The experiments were performed using a dataset composed of four different types of networks: random, small-world, scale-free and geographical. We also used cross-validation for training purposes. We evaluated the accuracy of classification as a function of the initial number of living neighbors, and, also, as a function of a threshold parameter related to the density of living neighbors. The results show high accuracy values in distinguishing among the network models which demonstrates the feasibility of the proposed method.

  12. Automatic spatiotemporal matching of detected pleural thickenings

    NASA Astrophysics Data System (ADS)

    Chaisaowong, Kraisorn; Keller, Simon Kai; Kraus, Thomas

    2014-01-01

    Pleural thickenings can be found in asbestos exposed patient's lung. Non-invasive diagnosis including CT imaging can detect aggressive malignant pleural mesothelioma in its early stage. In order to create a quantitative documentation of automatic detected pleural thickenings over time, the differences in volume and thickness of the detected thickenings have to be calculated. Physicians usually estimate the change of each thickening via visual comparison which provides neither quantitative nor qualitative measures. In this work, automatic spatiotemporal matching techniques of the detected pleural thickenings at two points of time based on the semi-automatic registration have been developed, implemented, and tested so that the same thickening can be compared fully automatically. As result, the application of the mapping technique using the principal components analysis turns out to be advantageous than the feature-based mapping using centroid and mean Hounsfield Units of each thickening, since the resulting sensitivity was improved to 98.46% from 42.19%, while the accuracy of feature-based mapping is only slightly higher (84.38% to 76.19%).

  13. Role of lateral and feedback connections in primary visual cortex in the processing of spatiotemporal regularity - a TMS study.

    PubMed

    Roebuck, H; Bourke, P; Guo, K

    2014-03-28

    Our human visual system exploits spatiotemporal regularity to interpret incoming visual signals. With a dynamic stimulus sequence of four collinear bars (predictors) appearing consecutively toward the fovea, followed by a target bar with varying contrasts, we have previously found that this predictable spatiotemporal stimulus structure enhances target detection performance and its underlying neural process starts in the primary visual cortex (area V1). However, the relative contribution of V1 lateral and feedback connections in the processing of spatiotemporal regularity remains unclear. In this study we measured human contrast detection of a briefly presented foveal target that was embedded in a dynamic collinear predictor-target sequence. Transcranial magnetic stimulation (TMS) was used to selectively disrupt V1 horizontal and feedback connections in the processing of predictors. The coil was positioned over a cortical location corresponding to the location of the last predictor prior to target onset. Single-pulse TMS at an intensity of 10% below phosphene thresholdwas delivered at 20 or 90ms after the predictor onset. Our analysis revealed that the delivery of TMS at both time windows equally reduced, but did not abolish, the facilitation effect of the predictors on target detection. Furthermore, if the predictors' ordination was randomized to suppress V1 lateral connections, the TMS disruption was significantly more evident at 20ms than at 90-ms time window. We suggest that both lateral and feedback connections contribute to the encoding of spatiotemporal regularity in V1. These findings develop understanding of how our visual system exploits spatiotemporal regularity to facilitate the efficiency of visual perception. PMID:24462610

  14. Quantitative proteomics of the yeast Hsp70/Hsp90 interactomes during DNA damage reveals chaperone-dependent regulation of ribonucleotide reductase

    PubMed Central

    Truman, Andrew W.; Kristjansdottir, Kolbrun; Wolfgeher, Donald; Ricco, Natalia; Mayampurath, Anoop; Volchenboum, Samuel L.; Clotet, Josep; Kron, Stephen J.

    2015-01-01

    The highly conserved molecular chaperones Hsp90 and Hsp70 are indispensible for folding and maturation of a significant fraction of the proteome, including many proteins involved in signal transduction and stress response. To examine the dynamics of chaperone-client interactions after DNA damage, we applied quantitative affinity-purification mass spectrometry (AP-MS) proteomics to characterize interactomes of the yeast Hsp70 isoform Ssa1 and Hsp90 isoform Hsp82 before and after exposure to methyl methanesulfonate. Of 256 proteins identified and quantified via 16O/18O labeling and LC-MS/MS, 142 are novel Hsp70/90 interactors. Nearly all interactions remained unchanged or decreased after DNA damage, but 5 proteins increased interactions with Ssa1 and/or Hsp82, including the ribonucleotide reductase (RNR) subunit Rnr4. Inhibiting Hsp70 or 90 chaperone activity destabilized Rnr4 in yeast and its vertebrate homolog hRMM2 in breast cancer cells. In turn, pre-treatment of cancer cells with chaperone inhibitors sensitized cells to the RNR inhibitor gemcitabine, suggesting a novel chemotherapy strategy. All MS data have been deposited in the ProteomeXchange with identifier PXD001284. PMID:25452130

  15. The nuclear F-actin interactome of Xenopus oocytes reveals an actin-bundling kinesin that is essential for meiotic cytokinesis.

    PubMed

    Samwer, Matthias; Dehne, Heinz-Jürgen; Spira, Felix; Kollmar, Martin; Gerlich, Daniel W; Urlaub, Henning; Görlich, Dirk

    2013-07-01

    Nuclei of Xenopus laevis oocytes grow 100 000-fold larger in volume than a typical somatic nucleus and require an unusual intranuclear F-actin scaffold for mechanical stability. We now developed a method for mapping F-actin interactomes and identified a comprehensive set of F-actin binders from the oocyte nuclei. Unexpectedly, the most prominent interactor was a novel kinesin termed NabKin (Nuclear and meiotic actin-bundling Kinesin). NabKin not only binds microtubules but also F-actin structures, such as the intranuclear actin bundles in prophase and the contractile actomyosin ring during cytokinesis. The interaction between NabKin and F-actin is negatively regulated by Importin-β and is responsive to spatial information provided by RanGTP. Disconnecting NabKin from F-actin during meiosis caused cytokinesis failure and egg polyploidy. We also found actin-bundling activity in Nabkin's somatic paralogue KIF14, which was previously shown to be essential for somatic cell division. Our data are consistent with the notion that NabKin/KIF14 directly link microtubules with F-actin and that such link is essential for cytokinesis. PMID:23727888

  16. Interactome Analyses Identify Ties of PrPC and Its Mammalian Paralogs to Oligomannosidic N-Glycans and Endoplasmic Reticulum-Derived Chaperones

    PubMed Central

    Won, Amy Hye; Shi, Tujin; Daude, Nathalie; Lau, Agnes; Young, Rebecca; Xu, Lei; Carlson, George A.; Williams, David; Westaway, David; Schmitt-Ulms, Gerold

    2009-01-01

    The physiological environment which hosts the conformational conversion of the cellular prion protein (PrPC) to disease-associated isoforms has remained enigmatic. A quantitative investigation of the PrPC interactome was conducted in a cell culture model permissive to prion replication. To facilitate recognition of relevant interactors, the study was extended to Doppel (Prnd) and Shadoo (Sprn), two mammalian PrPC paralogs. Interestingly, this work not only established a similar physiological environment for the three prion protein family members in neuroblastoma cells, but also suggested direct interactions amongst them. Furthermore, multiple interactions between PrPC and the neural cell adhesion molecule, the laminin receptor precursor, Na/K ATPases and protein disulfide isomerases (PDI) were confirmed, thereby reconciling previously separate findings. Subsequent validation experiments established that interactions of PrPC with PDIs may extend beyond the endoplasmic reticulum and may play a hitherto unrecognized role in the accumulation of PrPSc. A simple hypothesis is presented which accounts for the majority of interactions observed in uninfected cells and suggests that PrPC organizes its molecular environment on account of its ability to bind to adhesion molecules harboring immunoglobulin-like domains, which in turn recognize oligomannose-bearing membrane proteins. PMID:19798432

  17. Identification of the Low Density Lipoprotein (LDL) Receptor-related Protein-1 Interactome in Central Nervous System Myelin Suggests a Role in the Clearance of Necrotic Cell Debris*

    PubMed Central

    Fernandez-Castaneda, Anthony; Arandjelovic, Sanja; Stiles, Travis L.; Schlobach, Ryan K.; Mowen, Kerri A.; Gonias, Steven L.; Gaultier, Alban

    2013-01-01

    In the central nervous system (CNS), fast neuronal signals are facilitated by the oligodendrocyte-produced myelin sheath. Oligodendrocyte turnover or injury generates myelin debris that is usually promptly cleared by phagocytic cells. Failure to remove dying oligodendrocytes leads to accumulation of degraded myelin, which, if recognized by the immune system, may contribute to the development of autoimmunity in diseases such as multiple sclerosis. We recently identified low density lipoprotein receptor-related protein-1 (LRP1) as a novel phagocytic receptor for myelin debris. Here, we report characterization of the LRP1 interactome in CNS myelin. Fusion proteins were designed corresponding to the extracellular ligand-binding domains of LRP1. LRP1 partners were isolated by affinity purification and characterized by mass spectrometry. We report that LRP1 binds intracellular proteins via its extracellular domain and functions as a receptor for necrotic cells. Peptidyl arginine deiminase-2 and cyclic nucleotide phosphodiesterase are novel LRP1 ligands identified in our screen, which interact with full-length LRP1. Furthermore, the extracellular domain of LRP1 is a target of peptidyl arginine deiminase-2-mediated deimination in vitro. We propose that LRP1 functions as a receptor for endocytosis of intracellular components released during cellular damage and necrosis. PMID:23264627

  18. Proteomic Analysis of the EWS-Fli-1 Interactome Reveals the Role of the Lysosome in EWS-Fli-1 Turnover

    PubMed Central

    2015-01-01

    Ewing sarcoma is a cancer of bone and soft tissue in children that is characterized by a chromosomal translocation involving EWS and an Ets family transcription factor, most commonly Fli-1. EWS-Fli-1 fusion accounts for 85% of cases. The growth and survival of Ewing sarcoma cells are critically dependent on EWS-Fli-1. A large body of evidence has established that EWS-Fli-1 functions as a DNA-binding transcription factor that regulates the expression of a number of genes important for cell proliferation and transformation. However, little is known about the biochemical properties of the EWS-Fli-1 protein. We undertook a series of proteomic analyses to dissect the EWS-Fli-1 interactome. Employing a proximity-dependent biotinylation technique, BioID, we identified cation-independent mannose 6-phosphate receptor (CIMPR) as a protein located in the vicinity of EWS-Fli-1 within a cell. CIMPR is a cargo that mediates the delivery of lysosomal hydrolases from the trans-Golgi network to the endosome, which are subsequently transferred to the lysosomes. Further molecular cell biological analyses uncovered a role for lysosomes in the turnover of the EWS-Fli-1 protein. We demonstrate that an mTORC1 active-site inhibitor, torin 1, which stimulates the TFEB-lysosome pathway, can induce the degradation of EWS-Fli-1, suggesting a potential therapeutic approach to target EWS-Fli-1 for degradation. PMID:24999758

  19. SRC Homology 2 Domain Binding Sites in Insulin, IGF-1 and FGF receptor mediated signaling networks reveal an extensive potential interactome

    PubMed Central

    2012-01-01

    Specific peptide ligand recognition by modular interaction domains is essential for the fidelity of information flow through the signal transduction networks that control cell behavior in response to extrinsic and intrinsic stimuli. Src homology 2 (SH2) domains recognize distinct phosphotyrosine peptide motifs, but the specific sites that are phosphorylated and the complement of available SH2 domains varies considerably in individual cell types. Such differences are the basis for a wide range of available protein interaction microstates from which signaling can evolve in highly divergent ways. This underlying complexity suggests the need to broadly map the signaling potential of systems as a prerequisite for understanding signaling in specific cell types as well as various pathologies that involve signal transduction such as cancer, developmental defects and metabolic disorders. This report describes interactions between SH2 domains and potential binding partners that comprise initial signaling downstream of activated fibroblast growth factor (FGF), insulin (Ins), and insulin-like growth factor-1 (IGF-1) receptors. A panel of 50 SH2 domains screened against a set of 192 phosphotyrosine peptides defines an extensive potential interactome while demonstrating the selectivity of individual SH2 domains. The interactions described confirm virtually all previously reported associations while describing a large set of potential novel interactions that imply additional complexity in the signaling networks initiated from activated receptors. This study of pTyr ligand binding by SH2 domains provides valuable insight into the selectivity that underpins complex signaling networks that are assembled using modular protein interaction domains. PMID:22974441

  20. A study of the spatiotemporal health impacts of ozone exposure.

    PubMed

    Christakos, G; Kolovos, A

    1999-01-01

    Exposure analysis and mapping of spatiotemporal pollutants in relation to their health effects are important challenges facing environmental health scientists and integrated assessment modellers. In this work, a methodological framework is discussed to study the impact of spatiotemporal ozone (O3) exposure distributions on the health of human populations. The framework, however, is very general and can be used to study various other pollutants. The spatiotemporal analysis starts with exposure distributions producing the input to pollutokinetic (or toxicokinetic) laws which are linked to effect models which, in turn, are integrated with relationships that describe how effects are distributed across populations. Important characteristics of the environmental health framework are holisticity and stochasticity. Holisticity emphasizes the functional relationships between composite space/time O3 maps, pollutokinetic models of burden on target organs and tissues, and health effects. These relationships offer a meaningful physical interpretation of the exposure and biological processes that affect human exposure. Stochasticity involves the rigorous representation of natural uncertainties and biological variations in terms of spatiotemporal random fields. The stochastic perspective introduces a deeper epistemological understanding in the development of improved models of spatiotemporal human exposure analysis and mapping. Also, it explicitly determines the knowledge bases available and develops logically plausible rules and standards for data processing and human exposure map construction. The proposed approach allows the horizontal integration among sciences related to the human exposure problem that leads to accurate and informative spatiotemporal maps of O3 exposure and effect distributions and an integrative analysis of the whole risk case. By processing a variety of knowledge bases, the spatiotemporal analysis can bring together several sciences which are all relevant

  1. Tracking pedestrians using local spatio-temporal motion patterns in extremely crowded scenes.

    PubMed

    Kratz, Louis; Nishino, Ko

    2012-05-01

    Tracking pedestrians is a vital component of many computer vision applications, including surveillance, scene understanding, and behavior analysis. Videos of crowded scenes present significant challenges to tracking due to the large number of pedestrians and the frequent partial occlusions that they produce. The movement of each pedestrian, however, contributes to the overall crowd motion (i.e., the collective motions of the scene's constituents over the entire video) that exhibits an underlying spatially and temporally varying structured pattern. In this paper, we present a novel Bayesian framework for tracking pedestrians in videos of crowded scenes using a space-time model of the crowd motion. We represent the crowd motion with a collection of hidden Markov models trained on local spatio-temporal motion patterns, i.e., the motion patterns exhibited by pedestrians as they move through local space-time regions of the video. Using this unique representation, we predict the next local spatio-temporal motion pattern a tracked pedestrian will exhibit based on the observed frames of the video. We then use this prediction as a prior for tracking the movement of an individual in videos of extremely crowded scenes. We show that our approach of leveraging the crowd motion enables tracking in videos of complex scenes that present unique difficulty to other approaches. PMID:21844618

  2. The evolution of meaning: spatio-temporal dynamics of visual object recognition.

    PubMed

    Clarke, Alex; Taylor, Kirsten I; Tyler, Lorraine K

    2011-08-01

    Research on the spatio-temporal dynamics of visual object recognition suggests a recurrent, interactive model whereby an initial feedforward sweep through the ventral stream to prefrontal cortex is followed by recurrent interactions. However, critical questions remain regarding the factors that mediate the degree of recurrent interactions necessary for meaningful object recognition. The novel prediction we test here is that recurrent interactivity is driven by increasing semantic integration demands as defined by the complexity of semantic information required by the task and driven by the stimuli. To test this prediction, we recorded magnetoencephalography data while participants named living and nonliving objects during two naming tasks. We found that the spatio-temporal dynamics of neural activity were modulated by the level of semantic integration required. Specifically, source reconstructed time courses and phase synchronization measures showed increased recurrent interactions as a function of semantic integration demands. These findings demonstrate that the cortical dynamics of object processing are modulated by the complexity of semantic information required from the visual input. PMID:20617883

  3. Predicting the fission yeast protein interaction network.

    PubMed

    Pancaldi, Vera; Saraç, Omer S; Rallis, Charalampos; McLean, Janel R; Převorovský, Martin; Gould, Kathleen; Beyer, Andreas; Bähler, Jürg

    2012-04-01

    A systems-level understanding of biological processes and information flow requires the mapping of cellular component interactions, among which protein-protein interactions are particularly important. Fission yeast (Schizosaccharomyces pombe) is a valuable model organism for which no systematic protein-interaction data are available. We exploited gene and protein properties, global genome regulation datasets, and conservation of interactions between budding and fission yeast to predict fission yeast protein interactions in silico. We have extensively tested our method in three ways: first, by predicting with 70-80% accuracy a selected high-confidence test set; second, by recapitulating interactions between members of the well-characterized SAGA co-activator complex; and third, by verifying predicted interactions of the Cbf11 transcription factor using mass spectrometry of TAP-purified protein complexes. Given the importance of the pathway in cell physiology and human disease, we explore the predicted sub-networks centered on the Tor1/2 kinases. Moreover, we predict the histidine kinases Mak1/2/3 to be vital hubs in the fission yeast stress response network, and we suggest interactors of argonaute 1, the principal component of the siRNA-mediated gene silencing pathway, lost in budding yeast but preserved in S. pombe. Of the new high-quality interactions that were discovered after we started this work, 73% were found in our predictions. Even though any predicted interactome is imperfect, the protein network presented here can provide a valuable basis to explore biological processes and to guide wet-lab experiments in fission yeast and beyond. Our predicted protein interactions are freely available through PInt, an online resource on our website (www.bahlerlab.info/PInt).

  4. Resonant spatiotemporal learning in large random recurrent networks.

    PubMed

    Daucé, Emmanuel; Quoy, Mathias; Doyon, Bernard

    2002-09-01

    Taking a global analogy with the structure of perceptual biological systems, we present a system composed of two layers of real-valued sigmoidal neurons. The primary layer receives stimulating spatiotemporal signals, and the secondary layer is a fully connected random recurrent network. This secondary layer spontaneously displays complex chaotic dynamics. All connections have a constant time delay. We use for our experiments a Hebbian (covariance) learning rule. This rule slowly modifies the weights under the influence of a periodic stimulus. The effect of learning is twofold: (i) it simplifies the secondary-layer dynamics, which eventually stabilizes to a periodic orbit; and (ii) it connects the secondary layer to the primary layer, and realizes a feedback from the secondary to the primary layer. This feedback signal is added to the incoming signal, and matches it (i.e., the secondary layer performs a one-step prediction of the forthcoming stimulus). After learning, a resonant behavior can be observed: the system resonates with familiar stimuli, which activates a feedback signal. In particular, this resonance allows the recognition and retrieval of partial signals, and dynamic maintenance of the memory of past stimuli. This resonance is highly sensitive to the temporal relationships and to the periodicity of the presented stimuli. When we present stimuli which do not match in time or space, the feedback remains silent. The number of different stimuli for which resonant behavior can be learned is analyzed. As with Hopfield networks, the capacity is proportional to the size of the second, recurrent layer. Moreover, the high capacity displayed allows the implementation of our model on real-time systems interacting with their environment. Such an implementation is reported in the case of a simple behavior-based recognition task on a mobile robot. Finally, we present some functional analogies with biological systems in terms of autonomy and dynamic binding, and present

  5. Spatio-Temporal Dynamics of Hypoxia during Radiotherapy

    PubMed Central

    Kempf, Harald; Bleicher, Marcus; Meyer-Hermann, Michael

    2015-01-01

    Tumour hypoxia plays a pivotal role in cancer therapy for most therapeutic approaches from radiotherapy to immunotherapy. The detailed and accurate knowledge of the oxygen distribution in a tumour is necessary in order to determine the right treatment strategy. Still, due to the limited spatial and temporal resolution of imaging methods as well as lacking fundamental understanding of internal oxygenation dynamics in tumours, the precise oxygen distribution map is rarely available for treatment planing. We employ an agent-based in silico tumour spheroid model in order to study the complex, localized and fast oxygen dynamics in tumour micro-regions which are induced by radiotherapy. A lattice-free, 3D, agent-based approach for cell representation is coupled with a high-resolution diffusion solver that includes a tissue density-dependent diffusion coefficient. This allows us to assess the space- and time-resolved reoxygenation response of a small subvolume of tumour tissue in response to radiotherapy. In response to irradiation the tumour nodule exhibits characteristic reoxygenation and re-depletion dynamics which we resolve with high spatio-temporal resolution. The reoxygenation follows specific timings, which should be respected in treatment in order to maximise the use of the oxygen enhancement effects. Oxygen dynamics within the tumour create windows of opportunity for the use of adjuvant chemotherapeutica and hypoxia-activated drugs. Overall, we show that by using modelling it is possible to follow the oxygenation dynamics beyond common resolution limits and predict beneficial strategies for therapy and in vitro verification. Models of cell cycle and oxygen dynamics in tumours should in the future be combined with imaging techniques, to allow for a systematic experimental study of possible improved schedules and to ultimately extend the reach of oxygenation monitoring available in clinical treatment. PMID:26273841

  6. Combining Land-Use Regression and Chemical Transport Modeling in a Spatiotemporal Geostatistical Model for Ozone and PM2.5.

    PubMed

    Wang, Meng; Sampson, Paul D; Hu, Jianlin; Kleeman, Michael; Keller, Joshua P; Olives, Casey; Szpiro, Adam A; Vedal, Sverre; Kaufman, Joel D

    2016-05-17

    Assessments of long-term air pollution exposure in population studies have commonly employed land-use regression (LUR) or chemical transport modeling (CTM) techniques. Attempts to incorporate both approaches in one modeling framework are challenging. We present a novel geostatistical modeling framework, incorporating CTM predictions into a spatiotemporal LUR model with spatial smoothing to estimate spatiotemporal variability of ozone (O3) and particulate matter with diameter less than 2.5 μm (PM2.5) from 2000 to 2008 in the Los Angeles Basin. The observations include over 9 years' data from more than 20 routine monitoring sites and specific monitoring data at over 100 locations to provide more comprehensive spatial coverage of air pollutants. Our composite modeling approach outperforms separate CTM and LUR models in terms of root-mean-square error (RMSE) assessed by 10-fold cross-validation in both temporal and spatial dimensions, with larger improvement in the accuracy of predictions for O3 (RMSE [ppb] for CTM, 6.6; LUR, 4.6; composite, 3.6) than for PM2.5 (RMSE [μg/m(3)] CTM: 13.7, LUR: 3.2, composite: 3.1). Our study highlights the opportunity for future exposure assessment to make use of readily available spatiotemporal modeling methods and auxiliary gridded data that takes chemical reaction processes into account to improve the accuracy of predictions in a single spatiotemporal modeling framework.

  7. Combining Land-Use Regression and Chemical Transport Modeling in a Spatiotemporal Geostatistical Model for Ozone and PM2.5.

    PubMed

    Wang, Meng; Sampson, Paul D; Hu, Jianlin; Kleeman, Michael; Keller, Joshua P; Olives, Casey; Szpiro, Adam A; Vedal, Sverre; Kaufman, Joel D

    2016-05-17

    Assessments of long-term air pollution exposure in population studies have commonly employed land-use regression (LUR) or chemical transport modeling (CTM) techniques. Attempts to incorporate both approaches in one modeling framework are challenging. We present a novel geostatistical modeling framework, incorporating CTM predictions into a spatiotemporal LUR model with spatial smoothing to estimate spatiotemporal variability of ozone (O3) and particulate matter with diameter less than 2.5 μm (PM2.5) from 2000 to 2008 in the Los Angeles Basin. The observations include over 9 years' data from more than 20 routine monitoring sites and specific monitoring data at over 100 locations to provide more comprehensive spatial coverage of air pollutants. Our composite modeling approach outperforms separate CTM and LUR models in terms of root-mean-square error (RMSE) assessed by 10-fold cross-validation in both temporal and spatial dimensions, with larger improvement in the accuracy of predictions for O3 (RMSE [ppb] for CTM, 6.6; LUR, 4.6; composite, 3.6) than for PM2.5 (RMSE [μg/m(3)] CTM: 13.7, LUR: 3.2, composite: 3.1). Our study highlights the opportunity for future exposure assessment to make use of readily available spatiotemporal modeling methods and auxiliary gridded data that takes chemical reaction processes into account to improve the accuracy of predictions in a single spatiotemporal modeling framework. PMID:27074524

  8. Spatiotemporal modeling of node temperatures in supercomputers

    DOE PAGES

    Storlie, Curtis Byron; Reich, Brian James; Rust, William Newton; Ticknor, Lawrence O.; Bonnie, Amanda Marie; Montoya, Andrew J.; Michalak, Sarah E.

    2016-06-10

    Los Alamos National Laboratory (LANL) is home to many large supercomputing clusters. These clusters require an enormous amount of power (~500-2000 kW each), and most of this energy is converted into heat. Thus, cooling the components of the supercomputer becomes a critical and expensive endeavor. Recently a project was initiated to investigate the effect that changes to the cooling system in a machine room had on three large machines that were housed there. Coupled with this goal was the aim to develop a general good-practice for characterizing the effect of cooling changes and monitoring machine node temperatures in this andmore » other machine rooms. This paper focuses on the statistical approach used to quantify the effect that several cooling changes to the room had on the temperatures of the individual nodes of the computers. The largest cluster in the room has 1,600 nodes that run a variety of jobs during general use. Since extremes temperatures are important, a Normal distribution plus generalized Pareto distribution for the upper tail is used to model the marginal distribution, along with a Gaussian process copula to account for spatio-temporal dependence. A Gaussian Markov random field (GMRF) model is used to model the spatial effects on the node temperatures as the cooling changes take place. This model is then used to assess the condition of the node temperatures after each change to the room. The analysis approach was used to uncover the cause of a problematic episode of overheating nodes on one of the supercomputing clusters. Lastly, this same approach can easily be applied to monitor and investigate cooling systems at other data centers, as well.« less

  9. Fluorescence advantages with microscopic spatiotemporal control

    NASA Astrophysics Data System (ADS)

    Goswami, Debabrata; Roy, Debjit; De, Arijit K.

    2013-03-01

    We present a clever design concept of using femtosecond laser pulses in microscopy by selective excitation or de-excitation of one fluorophore over the other overlapping one. Using either a simple pair of femtosecond pulses with variable delay or using a train of laser pulses at 20-50 Giga-Hertz excitation, we show controlled fluorescence excitation or suppression of one of the fluorophores with respect to the other through wave-packet interference, an effect that prevails even after the fluorophore coherence timescale. Such an approach can be used both under the single-photon excitation as well as in the multi-photon excitation conditions resulting in effective higher spatial resolution. Such high spatial resolution advantage with broadband-pulsed excitation is of immense benefit to multi-photon microscopy and can also be an effective detection scheme for trapped nanoparticles with near-infrared light. Such sub-diffraction limit trapping of nanoparticles is challenging and a two-photon fluorescence diagnostics allows a direct observation of a single nanoparticle in a femtosecond high-repetition rate laser trap, which promises new directions to spectroscopy at the single molecule level in solution. The gigantic peak power of femtosecond laser pulses at high repetition rate, even at low average powers, provide huge instantaneous gradient force that most effectively result in a stable optical trap for spatial control at sub-diffraction limit. Such studies have also enabled us to explore simultaneous control of internal and external degrees of freedom that require coupling of various control parameters to result in spatiotemporal control, which promises to be a versatile tool for the microscopic world.

  10. Predictability of Conversation Partners

    NASA Astrophysics Data System (ADS)

    Takaguchi, Taro; Nakamura, Mitsuhiro; Sato, Nobuo; Yano, Kazuo; Masuda, Naoki

    2011-08-01

    Recent developments in sensing technologies have enabled us to examine the nature of human social behavior in greater detail. By applying an information-theoretic method to the spatiotemporal data of cell-phone locations, [C. Song , ScienceSCIEAS0036-8075 327, 1018 (2010)] found that human mobility patterns are remarkably predictable. Inspired by their work, we address a similar predictability question in a different kind of human social activity: conversation events. The predictability in the sequence of one’s conversation partners is defined as the degree to which one’s next conversation partner can be predicted given the current partner. We quantify this predictability by using the mutual information. We examine the predictability of conversation events for each individual using the longitudinal data of face-to-face interactions collected from two company offices in Japan. Each subject wears a name tag equipped with an infrared sensor node, and conversation events are marked when signals are exchanged between sensor nodes in close proximity. We find that the conversation events are predictable to a certain extent; knowing the current partner decreases the uncertainty about the next partner by 28.4% on average. Much of the predictability is explained by long-tailed distributions of interevent intervals. However, a predictability also exists in the data, apart from the contribution of their long-tailed nature. In addition, an individual’s predictability is correlated with the position of the individual in the static social network derived from the data. Individuals confined in a community—in the sense of an abundance of surrounding triangles—tend to have low predictability, and those bridging different communities tend to have high predictability.

  11. Spatio-temporal networks: reachability, centrality and robustness

    PubMed Central

    Musolesi, Mirco

    2016-01-01

    Recent advances in spatial and temporal networks have enabled researchers to more-accurately describe many real-world systems such as urban transport networks. In this paper, we study the response of real-world spatio-temporal networks to random error and systematic attack, taking a unified view of their spatial and temporal performance. We propose a model of spatio-temporal paths in time-varying spatially embedded networks which captures the property that, as in many real-world systems, interaction between nodes is non-instantaneous and governed by the space in which they are embedded. Through numerical experiments on three real-world urban transport systems, we study the effect of node failure on a network's topological, temporal and spatial structure. We also demonstrate the broader applicability of this framework to three other classes of network. To identify weaknesses specific to the behaviour of a spatio-temporal system, we introduce centrality measures that evaluate the importance of a node as a structural bridge and its role in supporting spatio-temporally efficient flows through the network. This exposes the complex nature of fragility in a spatio-temporal system, showing that there is a variety of failure modes when a network is subject to systematic attacks. PMID:27429776

  12. An evaluation of space time cube representation of spatiotemporal patterns.

    PubMed

    Kristensson, Per Ola; Dahlbäck, Nils; Anundi, Daniel; Björnstad, Marius; Gillberg, Hanna; Haraldsson, Jonas; Mårtensson, Ingrid; Nordvall, Mathias; Ståhl, Josefine

    2009-01-01

    Space time cube representation is an information visualization technique where spatiotemporal data points are mapped into a cube. Information visualization researchers have previously argued that space time cube representation is beneficial in revealing complex spatiotemporal patterns in a data set to users. The argument is based on the fact that both time and spatial information are displayed simultaneously to users, an effect difficult to achieve in other representations. However, to our knowledge the actual usefulness of space time cube representation in conveying complex spatiotemporal patterns to users has not been empirically validated. To fill this gap, we report on a between-subjects experiment comparing novice users' error rates and response times when answering a set of questions using either space time cube or a baseline 2D representation. For some simple questions, the error rates were lower when using the baseline representation. For complex questions where the participants needed an overall understanding of the spatiotemporal structure of the data set, the space time cube representation resulted in on average twice as fast response times with no difference in error rates compared to the baseline. These results provide an empirical foundation for the hypothesis that space time cube representation benefits users analyzing complex spatiotemporal patterns. PMID:19423892

  13. Spatio-temporal networks: reachability, centrality and robustness.

    PubMed

    Williams, Matthew J; Musolesi, Mirco

    2016-06-01

    Recent advances in spatial and temporal networks have enabled researchers to more-accurately describe many real-world systems such as urban transport networks. In this paper, we study the response of real-world spatio-temporal networks to random error and systematic attack, taking a unified view of their spatial and temporal performance. We propose a model of spatio-temporal paths in time-varying spatially embedded networks which captures the property that, as in many real-world systems, interaction between nodes is non-instantaneous and governed by the space in which they are embedded. Through numerical experiments on three real-world urban transport systems, we study the effect of node failure on a network's topological, temporal and spatial structure. We also demonstrate the broader applicability of this framework to three other classes of network. To identify weaknesses specific to the behaviour of a spatio-temporal system, we introduce centrality measures that evaluate the importance of a node as a structural bridge and its role in supporting spatio-temporally efficient flows through the network. This exposes the complex nature of fragility in a spatio-temporal system, showing that there is a variety of failure modes when a network is subject to systematic attacks.

  14. Spatio-temporal networks: reachability, centrality and robustness.

    PubMed

    Williams, Matthew J; Musolesi, Mirco

    2016-06-01

    Recent advances in spatial and temporal networks have enabled researchers to more-accurately describe many real-world systems such as urban transport networks. In this paper, we study the response of real-world spatio-temporal networks to random error and systematic attack, taking a unified view of their spatial and temporal performance. We propose a model of spatio-temporal paths in time-varying spatially embedded networks which captures the property that, as in many real-world systems, interaction between nodes is non-instantaneous and governed by the space in which they are embedded. Through numerical experiments on three real-world urban transport systems, we study the effect of node failure on a network's topological, temporal and spatial structure. We also demonstrate the broader applicability of this framework to three other classes of network. To identify weaknesses specific to the behaviour of a spatio-temporal system, we introduce centrality measures that evaluate the importance of a node as a structural bridge and its role in supporting spatio-temporally efficient flows through the network. This exposes the complex nature of fragility in a spatio-temporal system, showing that there is a variety of failure modes when a network is subject to systematic attacks. PMID:27429776

  15. Assessment of soil organic carbon distribution in Europe scale by spatio-temporal data and geostatistics

    NASA Astrophysics Data System (ADS)

    Aksoy, Ece; Panagos, Panos; Montanarella, Luca

    2013-04-01

    Accuracy in assessing the distribution of soil organic carbon (SOC) is an important issue because SOC is an important soil component that plays key roles in the functions of both natural ecosystems and agricultural systems. The SOC content varies from place to place and it is strongly related with climate variables (temperature and rainfall), terrain features, soil texture, parent material, vegetation, land-use types, and human management (management and degradation) at different spatial scales. Geostatistical techniques allow for the prediction of soil properties using soil information and environmental covariates. In this study, assessment of SOC distribution has been predicted using combination of LUCAS soil samples with local soil data and ten spatio-temporal predictors (slope, aspect, elevation, CTI, CORINE land-cover classification, parent material, texture, WRB soil classification, average temperature and precipitation) with Regression-Kriging method in Europe scale. Significant correlation between the covariates and the organic carbon dependent variable was found.

  16. Spatio-temporal propagation of cascading overload failures in spatially embedded networks.

    PubMed

    Zhao, Jichang; Li, Daqing; Sanhedrai, Hillel; Cohen, Reuven; Havlin, Shlomo

    2016-01-01

    Different from the direct contact in epidemics spread, overload failures propagate through hidden functional dependencies. Many studies focused on the critical conditions and catastrophic consequences of cascading failures. However, to understand the network vulnerability and mitigate the cascading overload failures, the knowledge of how the failures propagate in time and space is essential but still missing. Here we study the spatio-temporal propagation behaviour of cascading overload failures analytically and numerically on spatially embedded networks. The cascading overload failures are found to spread radially from the centre of the initial failure with an approximately constant velocity. The propagation velocity decreases with increasing tolerance, and can be well predicted by our theoretical framework with one single correction for all the tolerance values. This propagation velocity is found similar in various model networks and real network structures. Our findings may help to predict the dynamics of cascading overload failures in realistic systems.

  17. Spatio-temporal propagation of cascading overload failures in spatially embedded networks

    PubMed Central

    Zhao, Jichang; Li, Daqing; Sanhedrai, Hillel; Cohen, Reuven; Havlin, Shlomo

    2016-01-01

    Different from the direct contact in epidemics spread, overload failures propagate through hidden functional dependencies. Many studies focused on the critical conditions and catastrophic consequences of cascading failures. However, to understand the network vulnerability and mitigate the cascading overload failures, the knowledge of how the failures propagate in time and space is essential but still missing. Here we study the spatio-temporal propagation behaviour of cascading overload failures analytically and numerically on spatially embedded networks. The cascading overload failures are found to spread radially from the centre of the initial failure with an approximately constant velocity. The propagation velocity decreases with increasing tolerance, and can be well predicted by our theoretical framework with one single correction for all the tolerance values. This propagation velocity is found similar in various model networks and real network structures. Our findings may help to predict the dynamics of cascading overload failures in realistic systems. PMID:26754065

  18. Field scale spatio-temporal soil moisture variability for trafficability and crop water availability

    NASA Astrophysics Data System (ADS)

    Carranza, Coleen; van der Ploeg, Martine; Ritsema, Coen

    2016-04-01

    Spatio-temporal patterns of soil moisture have been studied mostly for inputs in land surface models for weather and climate predictions. Remote sensing techniques for estimation of soil moisture have been explored because of the good spatial coverage at different scales. Current available satellite data provide surface soil moisture as microwave systems only measure soil moisture content up to 5cm soil depth. The OWAS1S project will focus on estimation of soil moisture from freely available Sentinel-1 datasets for operational water management in agricultural areas. As part of the project, it is essential to develop spatio-temporal methods to estimate root zone soil moisture from surface soil moisture. This will be used for crop water availability and trafficability in selected agricultural fields in the Netherlands. A network of single capacitance sensors installed per field will provide continuous measurements of soil moisture in the study area. Ground penetrating radar will be used to measure soil moisture variability within a single field for different time periods. During wetter months, optimal conditions for traffic will be assessed using simultaneous soil strength and soil moisture measurements. Towards water deficit periods, focus is on the relation (or the lack thereof) between surface soil moisture and root zone soil moisture to determine the amount of water for crops. Spatio-temporal distribution will determine important physical controls for surface and root zone soil moisture and provide insights for root-zone soil moisture. Existing models for field scale soil-water balance and data assimilation methods (e.g. Kalman filter) will be combined to estimate root zone soil moisture. Furthermore, effects of root development on soil structure and soil hydraulic properties and subsequent effects on trafficability and crop water availability will be investigated. This research project has recently started, therefore we want to present methods and framework of

  19. Spatiotemporal dynamics of optogenetically induced and spontaneous seizure transitions in primary generalized epilepsy

    PubMed Central

    Truccolo, Wilson; Wang, Jing; Nurmikko, Arto V.

    2014-01-01

    Transitions into primary generalized epileptic seizures occur abruptly and synchronously across the brain. Their potential triggers remain unknown. We used optogenetics to causally test the hypothesis that rhythmic population bursting of excitatory neurons in a local neocortical region can rapidly trigger absence seizures. Most previous studies have been purely correlational, and it remains unclear whether epileptiform events induced by rhythmic stimulation (e.g., sensory/electrical) mimic actual spontaneous seizures, especially regarding their spatiotemporal dynamics. In this study, we used a novel combination of intracortical optogenetic stimulation and microelectrode array recordings in freely moving WAG/Rij rats, a model of absence epilepsy with a cortical focus in the somatosensory cortex (SI). We report three main findings: 1) Brief rhythmic bursting, evoked by optical stimulation of neocortical excitatory neurons at frequencies around 10 Hz, induced seizures consisting of self-sustained spike-wave discharges (SWDs) for about 10% of stimulation trials. The probability of inducing seizures was frequency-dependent, reaching a maximum at 10 Hz. 2) Local field potential power before stimulation and response amplitudes during stimulation both predicted seizure induction, demonstrating a modulatory effect of brain states and neural excitation levels. 3) Evoked responses during stimulation propagated as cortical waves, likely reaching the cortical focus, which in turn generated self-sustained SWDs after stimulation was terminated. Importantly, SWDs during induced and spontaneous seizures propagated with the same spatiotemporal dynamics. Our findings demonstrate that local rhythmic bursting of excitatory neurons in neocortex at particular frequencies, under susceptible ongoing brain states, is sufficient to trigger primary generalized seizures with stereotypical spatiotemporal dynamics. PMID:25552645

  20. Reaction diffusion equation with spatio-temporal delay

    NASA Astrophysics Data System (ADS)

    Zhao, Zhihong; Rong, Erhua

    2014-07-01

    We investigate reaction-diffusion equation with spatio-temporal delays, the global existence, uniqueness and asymptotic behavior of solutions for which in relation to constant steady-state solution, included in the region of attraction of a stable steady solution. It is shown that if the delay reaction function satisfies some conditions and the system possesses a pair of upper and lower solutions then there exists a unique global solution. In terms of the maximal and minimal constant solutions of the corresponding steady-state problem, we get the asymptotic stability of reaction-diffusion equation with spatio-temporal delay. Applying this theory to Lotka-Volterra model with spatio-temporal delay, we get the global solution asymptotically tend to the steady-state problem's steady-state solution.

  1. Experimental study of spatiotemporally localized surface gravity water waves.

    PubMed

    Chabchoub, A; Akhmediev, N; Hoffmann, N P

    2012-07-01

    We present experimental results on the study of spatiotemporally localized surface wave events on deep water that can be modeled using the Peregrine breather solution of the nonlinear Schrödinger equation. These are often considered as prototypes of oceanic rogue waves that can focus wave energy into a single wave packet. For small steepness values of the carrier gravity waves the Peregrine breathers are relatively wide, thus providing an excellent agreement between the theory and experimental results. For larger steepnesses the focusing leads to temporally and spatially shorter events. Nevertheless, agreement between measurements and the Peregrine breather theory remains reasonably good, with discrepancies of modulation gradients and spatiotemporal symmetries being tolerable. Lifetimes and travel distances of the spatiotemporally localized wave events determined from the experiment are in good agreement with the theory.

  2. Dynamical topology and statistical properties of spatiotemporal chaos.

    PubMed

    Zhuang, Quntao; Gao, Xun; Ouyang, Qi; Wang, Hongli

    2012-12-01

    For spatiotemporal chaos described by partial differential equations, there are generally locations where the dynamical variable achieves its local extremum or where the time partial derivative of the variable vanishes instantaneously. To a large extent, the location and movement of these topologically special points determine the qualitative structure of the disordered states. We analyze numerically statistical properties of the topologically special points in one-dimensional spatiotemporal chaos. The probability distribution functions for the number of point, the lifespan, and the distance covered during their lifetime are obtained from numerical simulations. Mathematically, we establish a probabilistic model to describe the dynamics of these topologically special points. In spite of the different definitions in different spatiotemporal chaos, the dynamics of these special points can be described in a uniform approach.

  3. Spiking neural network for recognizing spatiotemporal sequences of spikes

    NASA Astrophysics Data System (ADS)

    Jin, Dezhe Z.

    2004-02-01

    Sensory neurons in many brain areas spike with precise timing to stimuli with temporal structures, and encode temporally complex stimuli into spatiotemporal spikes. How the downstream neurons read out such neural code is an important unsolved problem. In this paper, we describe a decoding scheme using a spiking recurrent neural network. The network consists of excitatory neurons that form a synfire chain, and two globally inhibitory interneurons of different types that provide delayed feedforward and fast feedback inhibition, respectively. The network signals recognition of a specific spatiotemporal sequence when the last excitatory neuron down the synfire chain spikes, which happens if and only if that sequence was present in the input spike stream. The recognition scheme is invariant to variations in the intervals between input spikes within some range. The computation of the network can be mapped into that of a finite state machine. Our network provides a simple way to decode spatiotemporal spikes with diverse types of neurons.

  4. Spatiotemporal observation of transport in fractured rocks

    NASA Astrophysics Data System (ADS)

    Kulenkampff, Johannes; Enzmann, Frieder; Gründig, Marion; Mittmann, Hellmuth; Wolf, Martin

    2010-05-01

    A number of injection experiments in different rocks types have been conducted with positron emission-process-tomography using a high-resolution "small-animal" PET-scanner (ClearPET by Raytest, Straubenhardt) for the monitoring of transport processes. The fluids are labelled with positron-emitting isotopes like e.g. 18F-, 124I- or dissolvable complexes like K3[58Co(CN)6], without affecting their physico-chemical properties. The annihilation radiation from individual decaying tracer atoms is detected with high sensitivity, and the tomographic reconstruction of the recorded events yields quantitative 3D-images of the tracer distribution. Sequential tomograms during and after tracer injection are used for the spatiotemporal observation of the fluid transport. Raw data is corrected with respect to background radiation (randoms) and Compton scattering, which turns out to be much more significant in rocks than in common biomedical applications. Although in principle these effects are exactly known, we developed and apply simplified and fast correction methods. Deficiencies of these correction algorithms generate some artefacts, that cause the lower limit of the tracer concentration in the order of 1 kBq/?l or about 107 atoms/?l, still outranging other methods (e.g. NMR or resistivity tomography) by many orders of magnitude. New 3D-visualizations of the process-tomograms in fractured rocks show strongly localized and complex flow paths and in parts unexpected deviations from the fracture structures as deduced from ?CT-images. Such results demonstrate the potential of large discrepancies between ?CT-derived parameters like pore volume and specific surface area and the hydraulic effective parameters as derived by means of the PET-process-tomography. We conclude that such discrepancies and the complexity of the transport process in natural heterogeneous porous media illustrates the limits of parameter determination methods from model simulations based on structural pore

  5. Spatiotemporal modelling of viral infection dynamics

    NASA Astrophysics Data System (ADS)

    Beauchemin, Catherine

    Viral kinetics have been studied extensively in the past through the use of ordinary differential equations describing the time evolution of the diseased state in a spatially well-mixed medium. However, emerging spatial structures such as localized populations of dead cells might affect the spread of infection, similar to the manner in which a counter-fire can stop a forest fire from spreading. In the first phase of the project, a simple two-dimensional cellular automaton model of viral infections was developed. It was validated against clinical immunological data for uncomplicated influenza A infections and shown to be accurate enough to adequately model them. In the second phase of the project, the simple two-dimensional cellular automaton model was used to investigate the effects of relaxing the well-mixed assumption on viral infection dynamics. It was shown that grouping the initially infected cells into patches rather than distributing them uniformly on the grid reduced the infection rate as only cells on the perimeter of the patch have healthy neighbours to infect. Use of a local epithelial cell regeneration rule where dead cells are replaced by healthy cells when an immediate neighbour divides was found to result in more extensive damage of the epithelium and yielded a better fit to experimental influenza A infection data than a global regeneration rule based on division rate of healthy cell. Finally, the addition of immune cell at the site of infection was found to be a better strategy at low infection levels, while addition at random locations on the grid was the better strategy at high infection level. In the last project, the movement of T cells within lymph nodes in the absence of antigen, was investigated. Based on individual T cell track data captured by two-photon microscopy experiments in vivo, a simple model was proposed for the motion of T cells. This is the first step towards the implementation of a more realistic spatiotemporal model of HIV than

  6. Male reproductive strategy explains spatiotemporal segregation in brown bears.

    PubMed

    Steyaert, Sam M J G; Kindberg, Jonas; Swenson, Jon E; Zedrosser, Andreas

    2013-07-01

    Spatiotemporal segregation is often explained by the risk for offspring predation or by differences in physiology, predation risk vulnerability or competitive abilities related to size dimorphism. Most large carnivores are size dimorphic and offspring predation is often intraspecific and related to nonparental infanticide (NPI). NPI can be a foraging strategy, a strategy to reduce competition, or a male reproductive strategy. Spatiotemporal segregation is widespread among large carnivores, but its nature remains poorly understood. We evaluated three hypotheses to explain spatiotemporal segregation in the brown bear, a size-dimorphic large carnivore in which NPI is common; the 'NPI - foraging/competition hypothesis', i.e. NPI as a foraging strategy or a strategy to reduce competition, the 'NPI - sexual selection hypothesis', i.e. infanticide as a male reproductive strategy and the 'body size hypothesis', i.e. body-size-related differences in physiology, predation risk vulnerability or competitive ability causes spatiotemporal segregation. To test these hypotheses, we quantified spatiotemporal segregation among adult males, lone adult females and females with cubs-of-the-year, based on GPS-relocation data (2006-2010) and resource selection functions in a Scandinavian population. We found that spatiotemporal segregation was strongest between females with cubs-of-the-year and adult males during the mating season. During the mating season, females with cubs-of-the-year selected their resources, in contrast to adult males, in less rugged landscapes in relative close proximity to certain human-related variables, and in more open habitat types. After the mating season, females with cubs-of-the-year markedly shifted their resource selection towards a pattern more similar to that of their conspecifics. No strong spatiotemporal segregation was apparent between females with cubs-of-the-year and conspecifics during the mating and the postmating season. The 'NPI - sexual

  7. Male reproductive strategy explains spatiotemporal segregation in brown bears

    PubMed Central

    Steyaert, Sam MJG; Kindberg, Jonas; Swenson, Jon E; Zedrosser, Andreas

    2013-01-01

    1. Spatiotemporal segregation is often explained by the risk for offspring predation or by differences in physiology, predation risk vulnerability or competitive abilities related to size dimorphism. 2. Most large carnivores are size dimorphic and offspring predation is often intraspecific and related to nonparental infanticide (NPI). NPI can be a foraging strategy, a strategy to reduce competition, or a male reproductive strategy. Spatiotemporal segregation is widespread among large carnivores, but its nature remains poorly understood. 3. We evaluated three hypotheses to explain spatiotemporal segregation in the brown bear, a size-dimorphic large carnivore in which NPI is common; the ‘NPI – foraging/competition hypothesis', i.e. NPI as a foraging strategy or a strategy to reduce competition, the ‘NPI – sexual selection hypothesis’, i.e. infanticide as a male reproductive strategy and the ‘body size hypothesis’, i.e. body-size-related differences in physiology, predation risk vulnerability or competitive ability causes spatiotemporal segregation. To test these hypotheses, we quantified spatiotemporal segregation among adult males, lone adult females and females with cubs-of-the-year, based on GPS-relocation data (2006–2010) and resource selection functions in a Scandinavian population. 4. We found that spatiotemporal segregation was strongest between females with cubs-of-the-year and adult males during the mating season. During the mating season, females with cubs-of-the-year selected their resources, in contrast to adult males, in less rugged landscapes in relative close proximity to certain human-related variables, and in more open habitat types. After the mating season, females with cubs-of-the-year markedly shifted their resource selection towards a pattern more similar to that of their conspecifics. No strong spatiotemporal segregation was apparent between females with cubs-of-the-year and conspecifics during the mating and the postmating

  8. Routes to spatiotemporal chaos in Kerr optical frequency combs

    SciTech Connect

    Coillet, Aurélien; Chembo, Yanne K.

    2014-03-15

    We investigate the various routes to spatiotemporal chaos in Kerr optical frequency combs, obtained through pumping an ultra-high Q-factor whispering-gallery mode resonator with a continuous-wave laser. The Lugiato–Lefever model is used to build bifurcation diagrams with regards to the parameters that are externally controllable, namely, the frequency and the power of the pumping laser. We show that the spatiotemporal chaos emerging from Turing patterns and solitons display distinctive dynamical features. Experimental spectra of chaotic Kerr combs are also presented for both cases, in excellent agreement with theoretical spectra.

  9. Spatiotemporal focusing dynamics in plasmas at X-ray wavelength

    SciTech Connect

    Sharma, A. Tibai, Z.; Hebling, J.; Mishra, S. K.

    2014-03-15

    Using a finite curvature beam, we investigate here the spatiotemporal focusing dynamics of a laser pulse in plasmas at X-ray wavelength. We trace the dependence of curvature parameter on the focusing of laser pulse and recognize that the self-focusing in plasma is more intense for the X-ray laser pulse with curved wavefront than with flat wavefront. The simulation results demonstrate that spatiotemporal focusing dynamics in plasmas can be controlled with the appropriate choice of beam-plasma parameters to explore the high intensity effects in X-ray regime.

  10. Tensor analysis methods for activity characterization in spatiotemporal data

    SciTech Connect

    Haass, Michael Joseph; Van Benthem, Mark Hilary; Ochoa, Edward M.

    2014-03-01

    Tensor (multiway array) factorization and decomposition offers unique advantages for activity characterization in spatio-temporal datasets because these methods are compatible with sparse matrices and maintain multiway structure that is otherwise lost in collapsing for regular matrix factorization. This report describes our research as part of the PANTHER LDRD Grand Challenge to develop a foundational basis of mathematical techniques and visualizations that enable unsophisticated users (e.g. users who are not steeped in the mathematical details of matrix algebra and mulitway computations) to discover hidden patterns in large spatiotemporal data sets.

  11. Time reversal and the spatio-temporal matched filter

    SciTech Connect

    Lehman, S K; Poggio, A J; Kallman, J S; Meyer, A W; Candy, J V

    2004-03-08

    It is known that focusing of an acoustic field by a time-reversal mirror (TRM) is equivalent to a spatio-temporal matched filter under conditions where the Green's function of the field satisfies reciprocity and is time invariant, i.e. the Green's function is independent of the choice of time origin. In this letter, it is shown that both reciprocity and time invariance can be replaced by a more general constraint on the Green's function that allows a TRM to implement the spatio-temporal matched filter even when conditions are time varying.

  12. Improving transverse resolution of confocal microscopy through spatiotemporal modulation

    NASA Astrophysics Data System (ADS)

    Wang, Baokai; Zou, Limin; Zhang, Su; Tan, Jiubin

    2015-11-01

    A new method is proposed in this paper to improve transverse resolution of a confocal microscope. By setting up the model of a confocal microscope system through spatiotemporal modulation with moving gratings or acousto-optical modulation without defocus distance under coherent light illumination and deducing two-dimensional coherent image formula and transfer function, simulation tests are run with or without spatiotemporal modulation to prove the effectiveness of the proposed method. Simulation results indicate the proposed method can be used to improve the transverse resolution of a confocal microscope system.

  13. A general science-based framework for dynamical spatio-temporal models

    USGS Publications Warehouse

    Wikle, C.K.; Hooten, M.B.

    2010-01-01

    Spatio-temporal statistical models are increasingly being used across a wide variety of scientific disciplines to describe and predict spatially-explicit processes that evolve over time. Correspondingly, in recent years there has been a significant amount of research on new statistical methodology for such models. Although descriptive models that approach the problem from the second-order (covariance) perspective are important, and innovative work is being done in this regard, many real-world processes are dynamic, and it can be more efficient in some cases to characterize the associated spatio-temporal dependence by the use of dynamical models. The chief challenge with the specification of such dynamical models has been related to the curse of dimensionality. Even in fairly simple linear, first-order Markovian, Gaussian error settings, statistical models are often over parameterized. Hierarchical models have proven invaluable in their ability to deal to some extent with this issue by allowing dependency among groups of parameters. In addition, this framework has allowed for the specification of science based parameterizations (and associated prior distributions) in which classes of deterministic dynamical models (e. g., partial differential equations (PDEs), integro-difference equations (IDEs), matrix models, and agent-based models) are used to guide specific parameterizations. Most of the focus for the application of such models in statistics has been in the linear case. The problems mentioned above with linear dynamic models are compounded in the case of nonlinear models. In this sense, the need for coherent and sensible model parameterizations is not only helpful, it is essential. Here, we present an overview of a framework for incorporating scientific information to motivate dynamical spatio-temporal models. First, we illustrate the methodology with the linear case. We then develop a general nonlinear spatio-temporal framework that we call general quadratic

  14. Forecasting Hotspots-A Predictive Analytics Approach.

    PubMed

    Maciejewski, R; Hafen, R; Rudolph, S; Larew, S G; Mitchell, M A; Cleveland, W S; Ebert, D S

    2011-04-01

    Current visual analytics systems provide users with the means to explore trends in their data. Linked views and interactive displays provide insight into correlations among people, events, and places in space and time. Analysts search for events of interest through statistical tools linked to visual displays, drill down into the data, and form hypotheses based upon the available information. However, current systems stop short of predicting events. In spatiotemporal data, analysts are searching for regions of space and time with unusually high incidences of events (hotspots). In the cases where hotspots are found, analysts would like to predict how these regions may grow in order to plan resource allocation and preventative measures. Furthermore, analysts would also like to predict where future hotspots may occur. To facilitate such forecasting, we have created a predictive visual analytics toolkit that provides analysts with linked spatiotemporal and statistical analytic views. Our system models spatiotemporal events through the combination of kernel density estimation for event distribution and seasonal trend decomposition by loess smoothing for temporal predictions. We provide analysts with estimates of error in our modeling, along with spatial and temporal alerts to indicate the occurrence of statistically significant hotspots. Spatial data are distributed based on a modeling of previous event locations, thereby maintaining a temporal coherence with past events. Such tools allow analysts to perform real-time hypothesis testing, plan intervention strategies, and allocate resources to correspond to perceived threats.

  15. Functional Principal Component Analysis of Spatio-Temporal Point Processes with Applications in Disease Surveillance

    PubMed Central

    Li, Yehua; Guan, Yongtao

    2014-01-01

    In disease surveillance applications, the disease events are modeled by spatio-temporal point processes. We propose a new class of semiparametric generalized linear mixed model for such data, where the event rate is related to some known risk factors and some unknown latent random effects. We model the latent spatio-temporal process as spatially correlated functional data, and propose Poisson maximum likelihood and composite likelihood methods based on spline approximations to estimate the mean and covariance functions of the latent process. By performing functional principal component analysis to the latent process, we can better understand the correlation structure in the point process. We also propose an empirical Bayes method to predict the latent spatial random effects, which can help highlight hot areas with unusually high event rates. Under an increasing domain and increasing knots asymptotic framework, we establish the asymptotic distribution for the parametric components in the model and the asymptotic convergence rates for the functional principal component estimators. We illustrate the methodology through a simulation study and an application to the Connecticut Tumor Registry data. PMID:25368436

  16. Plastic response of fearful prey to the spatiotemporal dynamics of predator distribution.

    PubMed

    Basille, Mathieu; Fortin, Daniel; Dussault, Christian; Bastille-Rousseau, Guillaume; Ouellet, Jean-pierre; Courtois, Rthaume

    2015-10-01

    Ecological theory predicts that the intensity of antipredator responses is dependent upon the spatiotemporal context of predation risk (the risk allocation hypothesis). However, most studies to date have been conducted over small spatial extents, and did not fully take into account gradual responses to predator proximity. We simultaneously collected spatially explicit data on predator and prey to investigate acute responses of a threatened forest ungulate, the boreal caribou (Rangifer tarandus), to the spatiotemporal dynamics of wolf (Canis lupus) distribution during spring. Movement analysis of GPS-collared individuals from both species revealed high plasticity in habitat-selection decisions of caribou. Female caribou avoided open areas and deciduous forests and moved relatively fast and toward foraging areas when wolves were closer than 2.5 km. Caribou also avoided food-rich areas only when wolves were within 1 km. Our results bridge the gap between long-term perceived risk and immediate flight responses by revealing dynamic antipredator tactics in response to predator proximity. PMID:26649384

  17. The role of climate and socioeconomic factors on the spatiotemporal variability of cholera in Nigeria

    NASA Astrophysics Data System (ADS)

    Abdussalam, Auwal; Thornes, John; Leckebusch, Gregor

    2015-04-01

    Nigeria has a number of climate-sensitive infectious diseases; one of the most important of these diseases that remains a threat to public health is cholera. This study investigates the influences of both meteorological and socioeconomic factors on the spatiotemporal variability of cholera in Nigeria. A stepwise multiple regression models are used to estimate the influence of the year-to-year variations of cholera cases and deaths for individual states in the country and as well for three groups of states that are classified based on annual rainfall amount. Specifically, seasonal mean maximum and minimum temperatures and annual rainfall totals were analysed with annual aggregate count of cholera cases and deaths, taking into account of the socioeconomic factors that are potentially enhancing vulnerability such as: absolute poverty, adult literacy, access to pipe borne water and population density. Result reveals that the most important explanatory meteorological and socioeconomic variables in explaining the spatiotemporal variability of the disease are rainfall totals, seasonal mean maximum temperature, absolute poverty, and accessibility to pipe borne water. The influences of socioeconomic factors appeared to be more pronounced in the northern part of the country, and vice-versa in the case of meteorological factors. Also, cross validated models output suggests a strong possibility of disease prediction, which will help authorities to put effective control measures in place which depend on prevention, and or efficient response.

  18. Plastic response of fearful prey to the spatiotemporal dynamics of predator distribution.

    PubMed

    Basille, Mathieu; Fortin, Daniel; Dussault, Christian; Bastille-Rousseau, Guillaume; Ouellet, Jean-pierre; Courtois, Rthaume

    2015-10-01

    Ecological theory predicts that the intensity of antipredator responses is dependent upon the spatiotemporal context of predation risk (the risk allocation hypothesis). However, most studies to date have been conducted over small spatial extents, and did not fully take into account gradual responses to predator proximity. We simultaneously collected spatially explicit data on predator and prey to investigate acute responses of a threatened forest ungulate, the boreal caribou (Rangifer tarandus), to the spatiotemporal dynamics of wolf (Canis lupus) distribution during spring. Movement analysis of GPS-collared individuals from both species revealed high plasticity in habitat-selection decisions of caribou. Female caribou avoided open areas and deciduous forests and moved relatively fast and toward foraging areas when wolves were closer than 2.5 km. Caribou also avoided food-rich areas only when wolves were within 1 km. Our results bridge the gap between long-term perceived risk and immediate flight responses by revealing dynamic antipredator tactics in response to predator proximity.

  19. Value-at-Risk forecasts by a spatiotemporal model in Chinese stock market

    NASA Astrophysics Data System (ADS)

    Gong, Pu; Weng, Yingliang

    2016-01-01

    This paper generalizes a recently proposed spatial autoregressive model and introduces a spatiotemporal model for forecasting stock returns. We support the view that stock returns are affected not only by the absolute values of factors such as firm size, book-to-market ratio and momentum but also by the relative values of factors like trading volume ranking and market capitalization ranking in each period. This article studies a new method for constructing stocks' reference groups; the method is called quartile method. Applying the method empirically to the Shanghai Stock Exchange 50 Index, we compare the daily volatility forecasting performance and the out-of-sample forecasting performance of Value-at-Risk (VaR) estimated by different models. The empirical results show that the spatiotemporal model performs surprisingly well in terms of capturing spatial dependences among individual stocks, and it produces more accurate VaR forecasts than the other three models introduced in the previous literature. Moreover, the findings indicate that both allowing for serial correlation in the disturbances and using time-varying spatial weight matrices can greatly improve the predictive accuracy of a spatial autoregressive model.

  20. Spatiotemporal Spike Coding of Behavioral Adaptation in the Dorsal Anterior Cingulate Cortex.

    PubMed

    Logiaco, Laureline; Quilodran, René; Procyk, Emmanuel; Arleo, Angelo

    2015-08-01

    The frontal cortex controls behavioral adaptation in environments governed by complex rules. Many studies have established the relevance of firing rate modulation after informative events signaling whether and how to update the behavioral policy. However, whether the spatiotemporal features of these neuronal activities contribute to encoding imminent behavioral updates remains unclear. We investigated this issue in the dorsal anterior cingulate cortex (dACC) of monkeys while they adapted their behavior based on their memory of feedback from past choices. We analyzed spike trains of both single units and pairs of simultaneously recorded neurons using an algorithm that emulates different biologically plausible decoding circuits. This method permits the assessment of the performance of both spike-count and spike-timing sensitive decoders. In response to the feedback, single neurons emitted stereotypical spike trains whose temporal structure identified informative events with higher accuracy than mere spike count. The optimal decoding time scale was in the range of 70-200 ms, which is significantly shorter than the memory time scale required by the behavioral task. Importantly, the temporal spiking patterns of single units were predictive of the monkeys' behavioral response time. Furthermore, some features of these spiking patterns often varied between jointly recorded neurons. All together, our results suggest that dACC drives behavioral adaptation through complex spatiotemporal spike coding. They also indicate that downstream networks, which decode dACC feedback signals, are unlikely to act as mere neural integrators. PMID:26266537

  1. Spatio-temporal evolution of biogeochemical processes at a landfill site

    NASA Astrophysics Data System (ADS)

    Arora, B.; Mohanty, B. P.; McGuire, J. T.

    2011-12-01

    Predictions of fate and transport of contaminants are strongly dependent on spatio-temporal variability of soil hydraulic and geochemical properties. This study focuses on time-series signatures of hydrological and geochemical properties at different locations within the Norman landfill site. Norman Landfill is a closed municipal landfill site with prevalent organic contamination. Monthly data at the site include specific conductance, δ18O, δ2H, dissolved organic carbon (DOC) and anions (chloride, sulfate, nitrate) from 1998-2006. Column scale data on chemical concentrations, redox gradients, and flow parameters are also available on daily and hydrological event (infiltration, drainage, etc.) scales. Since high-resolution datasets of contaminant concentrations are usually unavailable, Wavelet and Fourier analyses were used to infer the dominance of different biogeochemical processes at different spatio-temporal scales and to extract linkages between transport and reaction processes. Results indicate that time variability controls the progression of reactions affecting biodegradation of contaminants. Wavelet analysis suggests that iron-sulfide reduction reactions had high seasonal variability at the site, while fermentation processes dominated at the annual time scale. Findings also suggest the dominance of small spatial features such as layered interfaces and clay lenses in driving biogeochemical reactions at both column and landfill scales. A conceptual model that caters to increased understanding and remediating structurally heterogeneous variably-saturated media is developed from the study.

  2. Estimating spatio-temporal dynamics of stream total phosphate concentration by soft computing techniques.

    PubMed

    Chang, Fi-John; Chen, Pin-An; Chang, Li-Chiu; Tsai, Yu-Hsuan

    2016-08-15

    This study attempts to model the spatio-temporal dynamics of total phosphate (TP) concentrations along a river for effective hydro-environmental management. We propose a systematical modeling scheme (SMS), which is an ingenious modeling process equipped with a dynamic neural network and three refined statistical methods, for reliably predicting the TP concentrations along a river simultaneously. Two different types of artificial neural network (BPNN-static neural network; NARX network-dynamic neural network) are constructed in modeling the dynamic system. The Dahan River in Taiwan is used as a study case, where ten-year seasonal water quality data collected at seven monitoring stations along the river are used for model training and validation. Results demonstrate that the NARX network can suitably capture the important dynamic features and remarkably outperforms the BPNN model, and the SMS can effectively identify key input factors, suitably overcome data scarcity, significantly increase model reliability, satisfactorily estimate site-specific TP concentration at seven monitoring stations simultaneously, and adequately reconstruct seasonal TP data into a monthly scale. The proposed SMS can reliably model the dynamic spatio-temporal water pollution variation in a river system for missing, hazardous or costly data of interest. PMID:27100003

  3. Intrinsic Islet Heterogeneity and Gap Junction Coupling Determine Spatiotemporal Ca2+ Wave Dynamics

    PubMed Central

    Benninger, Richard K.P.; Hutchens, Troy; Head, W. Steven; McCaughey, Michael J.; Zhang, Min; Le Marchand, Sylvain J.; Satin, Leslie S.; Piston, David W.

    2014-01-01

    Insulin is released from the islets of Langerhans in discrete pulses that are linked to synchronized oscillations of intracellular free calcium ([Ca2+]i). Associated with each synchronized oscillation is a propagating calcium wave mediated by Connexin36 (Cx36) gap junctions. A computational islet model predicted that waves emerge due to heterogeneity in β-cell function throughout the islet. To test this, we applied defined patterns of glucose stimulation across the islet using a microfluidic device and measured how these perturbations affect calcium wave propagation. We further investigated how gap junction coupling regulates spatiotemporal [Ca2+]i dynamics in the face of heterogeneous glucose stimulation. Calcium waves were found to originate in regions of the islet having elevated excitability, and this heterogeneity is an intrinsic property of islet β-cells. The extent of [Ca2+]i elevation across the islet in the presence of heterogeneity is gap-junction dependent, which reveals a glucose dependence of gap junction coupling. To better describe these observations, we had to modify the computational islet model to consider the electrochemical gradient between neighboring β-cells. These results reveal how the spatiotemporal [Ca2+]i dynamics of the islet depend on β-cell heterogeneity and cell-cell coupling, and are important for understanding the regulation of coordinated insulin release across the islet. PMID:25468351

  4. Prediction model of potential hepatocarcinogenicity of rat hepatocarcinogens using a large-scale toxicogenomics database

    SciTech Connect

    Uehara, Takeki; Minowa, Yohsuke; Morikawa, Yuji; Kondo, Chiaki; Maruyama, Toshiyuki; Kato, Ikuo; Nakatsu, Noriyuki; Igarashi, Yoshinobu; Ono, Atsushi; Hayashi, Hitomi; Mitsumori, Kunitoshi; Yamada, Hiroshi; Ohno, Yasuo; Urushidani, Tetsuro

    2011-09-15

    The present study was performed to develop a robust gene-based prediction model for early assessment of potential hepatocarcinogenicity of chemicals in rats by using our toxicogenomics database, TG-GATEs (Genomics-Assisted Toxicity Evaluation System developed by the Toxicogenomics Project in Japan). The positive training set consisted of high- or middle-dose groups that received 6 different non-genotoxic hepatocarcinogens during a 28-day period. The negative training set consisted of high- or middle-dose groups of 54 non-carcinogens. Support vector machine combined with wrapper-type gene selection algorithms was used for modeling. Consequently, our best classifier yielded prediction accuracies for hepatocarcinogenicity of 99% sensitivity and 97% specificity in the training data set, and false positive prediction was almost completely eliminated. Pathway analysis of feature genes revealed that the mitogen-activated protein kinase p38- and phosphatidylinositol-3-kinase-centered interactome and the v-myc myelocytomatosis viral oncogene homolog-centered interactome were the 2 most significant networks. The usefulness and robustness of our predictor were further confirmed in an independent validation data set obtained from the public database. Interestingly, similar positive predictions were obtained in several genotoxic hepatocarcinogens as well as non-genotoxic hepatocarcinogens. These results indicate that the expression profiles of our newly selected candidate biomarker genes might be common characteristics in the early stage of carcinogenesis for both genotoxic and non-genotoxic carcinogens in the rat liver. Our toxicogenomic model might be useful for the prospective screening of hepatocarcinogenicity of compounds and prioritization of compounds for carcinogenicity testing. - Highlights: >We developed a toxicogenomic model to predict hepatocarcinogenicity of chemicals. >The optimized model consisting of 9 probes had 99% sensitivity and 97% specificity. >This model

  5. Transfer of Predictive Signals Across Saccades

    PubMed Central

    Vetter, Petra; Edwards, Grace; Muckli, Lars

    2012-01-01

    Predicting visual information facilitates efficient processing of visual signals. Higher visual areas can support the processing of incoming visual information by generating predictive models that are fed back to lower visual areas. Functional brain imaging has previously shown that predictions interact with visual input already at the level of the primary visual cortex (V1; Harrison et al., 2007; Alink et al., 2010). Given that fixation changes up to four times a second in natural viewing conditions, cortical predictions are effective in V1 only if they are fed back in time for the processing of the next stimulus and at the corresponding new retinotopic position. Here, we tested whether spatio-temporal predictions are updated before, during, or shortly after an inter-hemifield saccade is executed, and thus, whether the predictive signal is transferred swiftly across hemifields. Using an apparent motion illusion, we induced an internal motion model that is known to produce a spatio-temporal prediction signal along the apparent motion trace in V1 (Muckli et al., 2005; Alink et al., 2010). We presented participants with both visually predictable and unpredictable targets on the apparent motion trace. During the task, participants saccaded across the illusion whilst detecting the target. As found previously, predictable stimuli were detected more frequently than unpredictable stimuli. Furthermore, we found that the detection advantage of predictable targets is detectable as early as 50–100 ms after saccade offset. This result demonstrates the rapid nature of the transfer of a spatio-temporally precise predictive signal across hemifields, in a paradigm previously shown to modulate V1. PMID:22701107

  6. Spatiotemporal Variation in Distance Dependent Animal Movement Contacts: One Size Doesn’t Fit All

    PubMed Central

    Brommesson, Peter; Wennergren, Uno; Lindström, Tom

    2016-01-01

    The structure of contacts that mediate transmission has a pronounced effect on the outbreak dynamics of infectious disease and simulation models are powerful tools to inform policy decisions. Most simulation models of livestock disease spread rely to some degree on predictions of animal movement between holdings. Typically, movements are more common between nearby farms than between those located far away from each other. Here, we assessed spatiotemporal variation in such distance dependence of animal movement contacts from an epidemiological perspective. We evaluated and compared nine statistical models, applied to Swedish movement data from 2008. The models differed in at what level (if at all), they accounted for regional and/or seasonal heterogeneities in the distance dependence of the contacts. Using a kernel approach to describe how probability of contacts between farms changes with distance, we developed a hierarchical Bayesian framework and estimated parameters by using Markov Chain Monte Carlo techniques. We evaluated models by three different approaches of model selection. First, we used Deviance Information Criterion to evaluate their performance relative to each other. Secondly, we estimated the log predictive posterior distribution, this was also used to evaluate their relative performance. Thirdly, we performed posterior predictive checks by simulating movements with each of the parameterized models and evaluated their ability to recapture relevant summary statistics. Independent of selection criteria, we found that accounting for regional heterogeneity improved model accuracy. We also found that accounting for seasonal heterogeneity was beneficial, in terms of model accuracy, according to two of three methods used for model selection. Our results have important implications for livestock disease spread models where movement is an important risk factor for between farm transmission. We argue that modelers should refrain from using methods to simulate

  7. Spatio-temporal analysis of environmental radiation in Korea

    SciTech Connect

    Kim, J.Y.; Lee, B.C.; Shin, H.K.

    2007-07-01

    Geostatistical visualization of environmental radiation is a very powerful approach to explore and understand spatio-temporal variabilities of environmental radiation data. Spatial patterns of environmental radiation can be described quantitatively in terms of variogram and kriging, which are based on the idea that statistical variation of data are functions of distance. (authors)

  8. Spatiotemporal characterization of Sclerotinia crown rot epidemics in pyrethrum

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Sclerotinia crown rot, caused by Sclerotinia minor and S. sclerotiorum is a disease of pyrethrum in Australia that may cause substantial decline in plant density. The spatiotemporal characteristics of the disease were quantified in 14 fields spread across three growing seasons. Fitting the binary ...

  9. Spatio-temporal Laplacian pyramid coding for action recognition.

    PubMed

    Shao, Ling; Zhen, Xiantong; Tao, Dacheng; Li, Xuelong

    2014-06-01

    We present a novel descriptor, called spatio-temporal Laplacian pyramid coding (STLPC), for holistic representation of human actions. In contrast to sparse representations based on detected local interest points, STLPC regards a video sequence as a whole with spatio-temporal features directly extracted from it, which prevents the loss of information in sparse representations. Through decomposing each sequence into a set of band-pass-filtered components, the proposed pyramid model localizes features residing at different scales, and therefore is able to effectively encode the motion information of actions. To make features further invariant and resistant to distortions as well as noise, a bank of 3-D Gabor filters is applied to each level of the Laplacian pyramid, followed by max pooling within filter bands and over spatio-temporal neighborhoods. Since the convolving and pooling are performed spatio-temporally, the coding model can capture structural and motion information simultaneously and provide an informative representation of actions. The proposed method achieves superb recognition rates on the KTH, the multiview IXMAS, the challenging UCF Sports, and the newly released HMDB51 datasets. It outperforms state of the art methods showing its great potential on action recognition.

  10. Location, Location, Location: Development of Spatiotemporal Sequence Learning in Infancy

    ERIC Educational Resources Information Center

    Kirkham, Natasha Z.; Slemmer, Jonathan A.; Richardson, Daniel C.; Johnson, Scott P.

    2007-01-01

    We investigated infants' sensitivity to spatiotemporal structure. In Experiment 1, circles appeared in a statistically defined spatial pattern. At test 11-month-olds, but not 8-month-olds, looked longer at a novel spatial sequence. Experiment 2 presented different color/shape stimuli, but only the location sequence was violated during test;…

  11. Robust visual tracking with dual spatio-temporal context trackers

    NASA Astrophysics Data System (ADS)

    Sun, Shiyan; Zhang, Hong; Yuan, Ding

    2015-12-01

    Visual tracking is a challenging problem in computer vision. Recent years, significant numbers of trackers have been proposed. Among these trackers, tracking with dense spatio-temporal context has been proved to be an efficient and accurate method. Other than trackers with online trained classifier that struggle to meet the requirement of real-time tracking task, a tracker with spatio-temporal context can run at hundreds of frames per second with Fast Fourier Transform (FFT). Nevertheless, the performance of the tracker with Spatio-temporal context relies heavily on the learning rate of the context, which restricts the robustness of the tracker. In this paper, we proposed a tracking method with dual spatio-temporal context trackers that hold different learning rate during tracking. The tracker with high learning rate could track the target smoothly when the appearance of target changes, while the tracker with low learning rate could percepts the occlusion occurring and continues to track when the target starts to emerge again. To find the target among the candidates from these two trackers, we adopt Normalized Correlation Coefficient (NCC) to evaluate the confidence of each sample. Experimental results show that the proposed algorithm performs robustly against several state-of-the-art tracking methods.

  12. Complex spatio-temporal features in meg data.

    PubMed

    Sapuppo, Francesca; Umana, Elena; Frasca, Mattia; Rosa, Manuela La; Shannahoff-Khalsa, David; Fortuna, Luigi; Bucolo, Maide

    2006-10-01

    Magnetoencephalography (MEG) brain signals are studied using a method for characterizing complex nonlinear dynamics. This approach uses the value of d(infinity) (d-infinite) to characterize the system's asymptotic chaotic behavior. A novel procedure has been developed to extract this parameter from time series when the system's structure and laws are unknown. The implementation of the algorithm was proven to be general and computationally efficient. The information characterized by this parameter is furthermore independent and complementary to the signal power since it considers signals normalized with respect to their amplitude. The algorithm implemented here is applied to whole-head 148 channel MEG data during two highly structured yogic breathing meditation techniques. Results are presented for the spatio-temporal distributions of the calculated d(infinity) on the MEG channels, and they are compared for the dirrerent phases of the yogic protocol. The algorithm was applied to six MEG data sets recorded over a three-month period. This provides the opportunity of verifying the consistency of unique spatio-temporal features found in specific protocol phases and the chance to investigate the potential long term effects of these yogic techniques. Differences among the spatio-temporal patterns related to each phase were found, and they were independent of the power spatio-temporal distributions that are based on conventional analysis. This approach also provides an opportunity to compare both methods and possibly gain complementary information.

  13. Mapping and spatiotemporal analysis tool for hydrological data: Spellmap

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Lack of data management and analyses tools is one of the major limitations to effectively evaluate and use large datasets of high-resolution atmospheric, surface, and subsurface observations. High spatial and temporal resolution datasets better represent the spatiotemporal variability of hydrologica...

  14. Finding Spatio-Temporal Patterns in Large Sensor Datasets

    ERIC Educational Resources Information Center

    McGuire, Michael Patrick

    2010-01-01

    Spatial or temporal data mining tasks are performed in the context of the relevant space, defined by a spatial neighborhood, and the relevant time period, defined by a specific time interval. Furthermore, when mining large spatio-temporal datasets, interesting patterns typically emerge where the dataset is most dynamic. This dissertation is…

  15. Spatiotemporal information during unsupervised learning enhances viewpoint invariant object recognition.

    PubMed

    Tian, Moqian; Grill-Spector, Kalanit

    2015-01-01

    Recognizing objects is difficult because it requires both linking views of an object that can be different and distinguishing objects with similar appearance. Interestingly, people can learn to recognize objects across views in an unsupervised way, without feedback, just from the natural viewing statistics. However, there is intense debate regarding what information during unsupervised learning is used to link among object views. Specifically, researchers argue whether temporal proximity, motion, or spatiotemporal continuity among object views during unsupervised learning is beneficial. Here, we untangled the role of each of these factors in unsupervised learning of novel three-dimensional (3-D) objects. We found that after unsupervised training with 24 object views spanning a 180° view space, participants showed significant improvement in their ability to recognize 3-D objects across rotation. Surprisingly, there was no advantage to unsupervised learning with spatiotemporal continuity or motion information than training with temporal proximity. However, we discovered that when participants were trained with just a third of the views spanning the same view space, unsupervised learning via spatiotemporal continuity yielded significantly better recognition performance on novel views than learning via temporal proximity. These results suggest that while it is possible to obtain view-invariant recognition just from observing many views of an object presented in temporal proximity, spatiotemporal information enhances performance by producing representations with broader view tuning than learning via temporal association. Our findings have important implications for theories of object recognition and for the development of computational algorithms that learn from examples.

  16. Cubic map algebra functions for spatio-temporal analysis

    USGS Publications Warehouse

    Mennis, J.; Viger, R.; Tomlin, C.D.

    2005-01-01

    We propose an extension of map algebra to three dimensions for spatio-temporal data handling. This approach yields a new class of map algebra functions that we call "cube functions." Whereas conventional map algebra functions operate on data layers representing two-dimensional space, cube functions operate on data cubes representing two-dimensional space over a third-dimensional period of time. We describe the prototype implementation of a spatio-temporal data structure and selected cube function versions of conventional local, focal, and zonal map algebra functions. The utility of cube functions is demonstrated through a case study analyzing the spatio-temporal variability of remotely sensed, southeastern U.S. vegetation character over various land covers and during different El Nin??o/Southern Oscillation (ENSO) phases. Like conventional map algebra, the application of cube functions may demand significant data preprocessing when integrating diverse data sets, and are subject to limitations related to data storage and algorithm performance. Solutions to these issues include extending data compression and computing strategies for calculations on very large data volumes to spatio-temporal data handling.

  17. Spatiotemporal Coupling of the Tongue in Amyotrophic Lateral Sclerosis

    ERIC Educational Resources Information Center

    Kuruvilla, Mili S.; Green, Jordan R.; Yunusova, Yana; Hanford, Kathy

    2012-01-01

    Purpose: The primary aim of the investigation was to identify deficits in spatiotemporal coupling between tongue regions in amyotrophic lateral sclerosis (ALS). The relations between disease-related changes in tongue movement patterns and speech intelligibility were also determined. Methods: The authors recorded word productions from 11…

  18. Spatio-Temporal Dynamics of Cross Polarized Wave Generation

    NASA Astrophysics Data System (ADS)

    Adams, Daniel; Squier, Jeff; Durfee, Charles

    2009-10-01

    We use time-domain Spatially and Spectrally Resolved Interferometry (SSRI) to investigate cross-polarized wave (XPW) generation in barium fluoride. We find that the XPW pulse is √3 smaller than the input in the spatiotemporal domain regardless of the input chirp. Additionally, we calculate a temporally dependent focal length resulting from the nonlinear interaction, and discuss its implications.

  19. Spatio-temporal evaluation matrices for geospatial data

    NASA Astrophysics Data System (ADS)

    Triglav, Joc; Petrovič, Dušan; Stopar, Bojan

    2011-02-01

    The global geospatial community is investing substantial effort in providing tools for geospatial data-quality information analysis and systematizing the criteria for geospatial data quality. The importance of these activities is increasing, especially in the last decade, which has witnessed an enormous expansion of geospatial data use in general and especially among mass users. Although geospatial data producers are striving to define and present data-quality standards to users and users increasingly need to assess the fitness for use of the data, the success of these activities is still far from what is expected or required. As a consequence, neglect or misunderstanding of data quality among users results in misuse or risks. This paper presents an aid in spatio-temporal quality evaluation through the use of spatio-temporal evaluation matrices (STEM) and the index of spatio-temporal anticipations (INSTANT) matrices. With the help of these two simple tools, geospatial data producers can systematically categorize and visualize the granularity of their spatio-temporal data, and users can present their requirements in the same way using business intelligence principles and a Web 2.0 approach. The basic principles and some examples are presented in the paper, and potential further applied research activities are briefly described.

  20. A spatiotemporal dynamic distributed solution to the MEG inverse problem

    PubMed Central

    Lamus, Camilo; Hämäläinen, Matti S.; Temereanca, Simona; Brown, Emery N.; Purdon, Patrick L.

    2012-01-01

    MEG/EEG are non-invasive imaging techniques that record brain activity with high temporal resolution. However, estimation of brain source currents from surface recordings requires solving an ill-conditioned inverse problem. Converging lines of evidence in neuroscience, from neuronal network models to resting-state imaging and neurophysiology, suggest that cortical activation is a distributed spatiotemporal dynamic process, supported by both local and long-distance neuroanatomic connections. Because spatiotemporal dynamics of this kind are central to brain physiology, inverse solutions could be improved by incorporating models of these dynamics. In this article, we present a model for cortical activity based on nearest-neighbor autoregression that incorporates local spatiotemporal interactions between distributed sources in a manner consistent with neurophysiology and neuroanatomy. We develop a dynamic Maximum a Posteriori Expectation-Maximization (dMAP-EM) source localization algorithm for estimation of cortical sources and model parameters based on the Kalman Filter, the Fixed Interval Smoother, and the EM algorithms. We apply the dMAP-EM algorithm to simulated experiments as well as to human experimental data. Furthermore, we derive expressions to relate our dynamic estimation formulas to those of standard static models, and show how dynamic methods optimally assimilate past and future data. Our results establish the feasibility of spatiotemporal dynamic estimation in large-scale distributed source spaces with several thousand source locations and hundreds of sensors, with resulting inverse solutions that provide substantial performance improvements over static methods. PMID:22155043

  1. The dynamic neural filter: a binary model of spatiotemporal coding.

    PubMed

    Quenet, Brigitte; Horn, David

    2003-02-01

    We describe and discuss the properties of a binary neural network that can serve as a dynamic neural filter (DNF), which maps regions of input space into spatiotemporal sequences of neuronal activity. Both deterministic and stochastic dynamics are studied, allowing the investigation of the stability of spatiotemporal sequences under noisy conditions. We define a measure of the coding capacity of a DNF and develop an algorithm for constructing a DNF that can serve as a source of given codes. On the basis of this algorithm, we suggest using a minimal DNF capable of generating observed sequences as a measure of complexity of spatiotemporal data. This measure is applied to experimental observations in the locust olfactory system, whose reverberating local field potential provides a natural temporal scale allowing the use of a binary DNF. For random synaptic matrices, a DNF can generate very large cycles, thus becoming an efficient tool for producing spatiotemporal codes. The latter can be stabilized by applying to the parameters of the DNF a learning algorithm with suitable margins.

  2. Spatio-Temporal Saliency Perception via Hypercomplex Frequency Spectral Contrast

    PubMed Central

    Li, Ce; Xue, Jianru; Zheng, Nanning; Lan, Xuguang; Tian, Zhiqiang

    2013-01-01

    Salient object perception is the process of sensing the salient information from the spatio-temporal visual scenes, which is a rapid pre-attention mechanism for the target location in a visual smart sensor. In recent decades, many successful models of visual saliency perception have been proposed to simulate the pre-attention behavior. Since most of the methods usually need some ad hoc parameters or high-cost preprocessing, they are difficult to rapidly detect salient object or be implemented by computing parallelism in a smart sensor. In this paper, we propose a novel spatio-temporal saliency perception method based on spatio-temporal hypercomplex spectral contrast (HSC). Firstly, the proposed HSC algorithm represent the features in the HSV (hue, saturation and value) color space and features of motion by a hypercomplex number. Secondly, the spatio-temporal salient objects are efficiently detected by hypercomplex Fourier spectral contrast in parallel. Finally, our saliency perception model also incorporates with the non-uniform sampling, which is a common phenomenon of human vision that directs visual attention to the logarithmic center of the image/video in natural scenes. The experimental results on the public saliency perception datasets demonstrate the effectiveness of the proposed approach compared to eleven state-of-the-art approaches. In addition, we extend the proposed model to moving object extraction in dynamic scenes, and the proposed algorithm is superior to the traditional algorithms. PMID:23482090

  3. Visual Experience Modulates Spatio-Temporal Dynamics of Circuit Activation

    PubMed Central

    Wang, Lang; Fontanini, Alfredo; Maffei, Arianna

    2011-01-01

    Persistent reduction in sensory drive in early development results in multiple plastic changes of different cortical synapses. How these experience-dependent modifications affect the spatio-temporal dynamics of signal propagation in neocortical circuits is poorly understood. Here we demonstrate that brief visual deprivation significantly affects the propagation of electrical signals in the primary visual cortex. The spatio-temporal spread of circuit activation upon direct stimulation of its input layer (Layer 4) is reduced, as is the activation of L2/3 – the main recipient of the output from L4. Our data suggest that the decrease in spatio-temporal activation of L2/3 depends on reduced L4 output, and is not intrinsically generated within L2/3. The data shown here suggest that changes in the synaptic components of the visual cortical circuit result not only in alteration of local integration of excitatory and inhibitory inputs, but also in a significant decrease in overall circuit activation. Furthermore, our data indicate a differential effect of visual deprivation on L4 and L2/3, suggesting that while feedforward activation of L2/3 is reduced, its activation by long range, within layer inputs is unaltered. Thus, brief visual deprivation induces experience-dependent circuit re-organization by modulating not only circuit excitability, but also the spatio-temporal patterns of cortical activation within and between layers. PMID:21743804

  4. Kernel Averaged Predictors for Spatio-Temporal Regression Models.

    PubMed

    Heaton, Matthew J; Gelfand, Alan E

    2012-12-01

    In applications where covariates and responses are observed across space and time, a common goal is to quantify the effect of a change in the covariates on the response while adequately accounting for the spatio-temporal structure of the observations. The most common approach for building such a model is to confine the relationship between a covariate and response variable to a single spatio-temporal location. However, oftentimes the relationship between the response and predictors may extend across space and time. In other words, the response may be affected by levels of predictors in spatio-temporal proximity to the response location. Here, a flexible modeling framework is proposed to capture such spatial and temporal lagged effects between a predictor and a response. Specifically, kernel functions are used to weight a spatio-temporal covariate surface in a regression model for the response. The kernels are assumed to be parametric and non-stationary with the data informing the parameter values of the kernel. The methodology is illustrated on simulated data as well as a physical data set of ozone concentrations to be explained by temperature. PMID:24010051

  5. Supporting user-defined granularities in a spatiotemporal conceptual model

    USGS Publications Warehouse

    Khatri, V.; Ram, S.; Snodgrass, R.T.; O'Brien, G. M.

    2002-01-01

    Granularities are integral to spatial and temporal data. A large number of applications require storage of facts along with their temporal and spatial context, which needs to be expressed in terms of appropriate granularities. For many real-world applications, a single granularity in the database is insufficient. In order to support any type of spatial or temporal reasoning, the semantics related to granularities needs to be embedded in the database. Specifying granularities related to facts is an important part of conceptual database design because under-specifying the granularity can restrict an application, affect the relative ordering of events and impact the topological relationships. Closely related to granularities is indeterminacy, i.e., an occurrence time or location associated with a fact that is not known exactly. In this paper, we present an ontology for spatial granularities that is a natural analog of temporal granularities. We propose an upward-compatible, annotation-based spatiotemporal conceptual model that can comprehensively capture the semantics related to spatial and temporal granularities, and indeterminacy without requiring new spatiotemporal constructs. We specify the formal semantics of this spatiotemporal conceptual model via translation to a conventional conceptual model. To underscore the practical focus of our approach, we describe an on-going case study. We apply our approach to a hydrogeologic application at the United States Geologic Survey and demonstrate that our proposed granularity-based spatiotemporal conceptual model is straightforward to use and is comprehensive.

  6. Fast Spatio-Temporal Data Mining from Large Geophysical Datasets

    NASA Technical Reports Server (NTRS)

    Stolorz, P.; Mesrobian, E.; Muntz, R.; Santos, J. R.; Shek, E.; Yi, J.; Mechoso, C.; Farrara, J.

    1995-01-01

    Use of the UCLA CONQUEST (CONtent-based Querying in Space and Time) is reviewed for performance of automatic cyclone extraction and detection of spatio-temporal blocking conditions on MPP. CONQUEST is a data analysis environment for knowledge and data mining to aid in high-resolution modeling of climate modeling.

  7. Adaptive spatio-temporal filtering for movement related potentials in EEG-based brain-computer interfaces.

    PubMed

    Lu, Jun; Xie, Kan; McFarland, Dennis J

    2014-07-01

    Movement related potentials (MRPs) are used as features in many brain-computer interfaces (BCIs) based on electroencephalogram (EEG). MRP feature extraction is challenging since EEG is noisy and varies between subjects. Previous studies used spatial and spatio-temporal filtering methods to deal with these problems. However, they did not optimize temporal information or may have been susceptible to overfitting when training data are limited and the feature space is of high dimension. Furthermore, most of these studies manually select data windows and low-pass frequencies. We propose an adaptive spatio-temporal (AST) filtering method to model MRPs more accurately in lower dimensional space. AST automatically optimizes all parameters by employing a Gaussian kernel to construct a low-pass time-frequency filter and a linear ridge regression (LRR) algorithm to compute a spatial filter. Optimal parameters are simultaneously sought by minimizing leave-one-out cross-validation error through gradient descent. Using four BCI datasets from 12 individuals, we compare the performances of AST filter to two popular methods: the discriminant spatial pattern filter and regularized spatio-temporal filter. The results demonstrate that our AST filter can make more accurate predictions and is computationally feasible.

  8. Monitoring and validating spatio-temporal dynamics of biogeochemical properties in Mersin Bay (Turkey) using Landsat ETM+.

    PubMed

    Karakaya, Nusret; Evrendilek, Fatih

    2011-10-01

    The objective of this study was to devise and validate simple models for estimating spatio-temporal dynamics of seven optically (in)active biogeochemical properties in Mersin Bay using Landsat 7 Enhanced Thematic Mapper Plus (ETM+) data and GIS. Spatio-temporal dynamics of Secchi depth (S (depth)), dissolved oxygen (DO), nitrite nitrogen (NO(2)-N), nitrate nitrogen (NO₃-N), silicate (SiO₄), 5-day biological oxygen demand (BOD5), and chlorophyll-a (Chl-a) were estimated using best-fit multiple linear regression (MLR) models as a function of Landsat 7 ETM+ and ground data in 2007 and 2008, latitude, longitude, and day of year. Validation of the MLR models against Landsat and ground data in 2005 led to r values ranging from 0.39 for NO₂-N (P = 0.008) to 0.79 for S (depth) (P < 0.001). Parsimonious MLR models built in this study appear to be promising for monitoring and predicting spatio-temporal dynamics of optically (in)active water quality characteristics in Mersin Bay.

  9. Monitoring and validating spatio-temporal dynamics of biogeochemical properties in Mersin Bay (Turkey) using Landsat ETM+.

    PubMed

    Karakaya, Nusret; Evrendilek, Fatih

    2011-10-01

    The objective of this study was to devise and validate simple models for estimating spatio-temporal dynamics of seven optically (in)active biogeochemical properties in Mersin Bay using Landsat 7 Enhanced Thematic Mapper Plus (ETM+) data and GIS. Spatio-temporal dynamics of Secchi depth (S (depth)), dissolved oxygen (DO), nitrite nitrogen (NO(2)-N), nitrate nitrogen (NO₃-N), silicate (SiO₄), 5-day biological oxygen demand (BOD5), and chlorophyll-a (Chl-a) were estimated using best-fit multiple linear regression (MLR) models as a function of Landsat 7 ETM+ and ground data in 2007 and 2008, latitude, longitude, and day of year. Validation of the MLR models against Landsat and ground data in 2005 led to r values ranging from 0.39 for NO₂-N (P = 0.008) to 0.79 for S (depth) (P < 0.001). Parsimonious MLR models built in this study appear to be promising for monitoring and predicting spatio-temporal dynamics of optically (in)active water quality characteristics in Mersin Bay. PMID:21181257

  10. Spatiotemporal Dynamics of Vibrio spp. within the Sydney Harbour Estuary

    PubMed Central

    Siboni, Nachshon; Balaraju, Varunan; Carney, Richard; Labbate, Maurizio; Seymour, Justin R.

    2016-01-01

    Vibrio are a genus of marine bacteria that have substantial environmental and human health importance, and there is evidence that their impact may be increasing as a consequence of changing environmental conditions. We investigated the abundance and composition of the Vibrio community within the Sydney Harbour estuary, one of the most densely populated coastal areas in Australia, and a region currently experiencing rapidly changing environmental conditions. Using quantitative PCR (qPCR) and Vibrio-specific 16S rRNA amplicon sequencing approaches we observed significant spatial and seasonal variation in the abundance and composition of the Vibrio community. Total Vibrio spp. abundance, derived from qPCR analysis, was higher during the late summer than winter and within locations with mid-range salinity (5–26 ppt). In addition we targeted three clinically important pathogens: Vibrio cholerae, V. Vulnificus, and V. parahaemolyticus. While toxigenic strains of V. cholerae were not detected in any samples, non-toxigenic strains were detected in 71% of samples, spanning a salinity range of 0–37 ppt and were observed during both late summer and winter. In contrast, pathogenic V. vulnificus was only detected in 14% of samples, with its occurrence restricted to the late summer and a salinity range of 5–26 ppt. V. parahaemolyticus was not observed at any site or time point. A Vibrio-specific 16S rRNA amplicon sequencing approach revealed clear shifts in Vibrio community composition across sites and between seasons, with several Vibrio operational taxonomic units (OTUs) displaying marked spatial patterns and seasonal trends. Shifts in the composition of the Vibrio community between seasons were primarily driven by changes in temperature, salinity and NO2, while a range of factors including pH, salinity, dissolved oxygen (DO) and NOx (Nitrogen Oxides) explained the observed spatial variation. Our evidence for the presence of a spatiotemporally dynamic Vibrio community

  11. Amplitude equation approach to spatiotemporal dynamics of cardiac alternans

    NASA Astrophysics Data System (ADS)

    Echebarria, Blas; Karma, Alain

    2007-11-01

    Amplitude equations are derived that describe the spatiotemporal dynamics of cardiac alternans during periodic pacing of one- [B. Echebarria and A. Karma, Phys. Rev. Lett. 88, 208101 (2002)] and two-dimensional homogeneous tissue and one-dimensional anatomical reentry in a ring of homogeneous tissue. These equations provide a simple physical understanding of arrhythmogenic patterns of period-doubling oscillations of action potential duration with a spatially varying phase and amplitude, as well as explicit quantitative predictions that can be compared to ionic model simulations or experiments. The form of the equations is expected to be valid for a large class of ionic models but the coefficients are derived analytically only for a two-variable ionic model and calculated numerically for the original Noble model of Purkinje fiber action potential. In paced tissue, this theory explains the formation of “spatially discordant alternans” by a linear instability mechanism that produces a periodic pattern of out-of-phase domains of alternans. The wavelength of this pattern, equal to twice the spacing between nodes separating out-of-phase domains, is shown to depend on three fundamental length scales that are determined by the strength of cell-to-cell coupling and conduction velocity (CV) restitution. Moreover, the patterns of alternans can be either stationary, with fixed nodes, or traveling, with moving nodes and hence quasiperiodic oscillations of action potential duration, depending on the relative strength of the destabilizing effect of CV restitution and the stabilizing effect of diffusive coupling. For the ring geometry, we recover the results of Courtemanche, Glass, and Keener [Phys. Rev. Lett. 70, 2182 (1993)] with two important modifications due to cell-to-cell diffusive coupling. First, this coupling breaks the degeneracy of an infinite-dimensional Hopf bifurcation such that the most unstable mode of alternans corresponds to the longest quantized wavelength

  12. Amplitude equation approach to spatiotemporal dynamics of cardiac alternans.

    PubMed

    Echebarria, Blas; Karma, Alain

    2007-11-01

    Amplitude equations are derived that describe the spatiotemporal dynamics of cardiac alternans during periodic pacing of one- [B. Echebarria and A. Karma, Phys. Rev. Lett. 88, 208101 (2002)] and two-dimensional homogeneous tissue and one-dimensional anatomical reentry in a ring of homogeneous tissue. These equations provide a simple physical understanding of arrhythmogenic patterns of period-doubling oscillations of action potential duration with a spatially varying phase and amplitude, as well as explicit quantitative predictions that can be compared to ionic model simulations or experiments. The form of the equations is expected to be valid for a large class of ionic models but the coefficients are derived analytically only for a two-variable ionic model and calculated numerically for the original Noble model of Purkinje fiber action potential. In paced tissue, this theory explains the formation of "spatially discordant alternans" by a linear instability mechanism that produces a periodic pattern of out-of-phase domains of alternans. The wavelength of this pattern, equal to twice the spacing between nodes separating out-of-phase domains, is shown to depend on three fundamental length scales that are determined by the strength of cell-to-cell coupling and conduction velocity (CV) restitution. Moreover, the patterns of alternans can be either stationary, with fixed nodes, or traveling, with moving nodes and hence quasiperiodic oscillations of action potential duration, depending on the relative strength of the destabilizing effect of CV restitution and the stabilizing effect of diffusive coupling. For the ring geometry, we recover the results of Courtemanche, Glass, and Keener [Phys. Rev. Lett. 70, 2182 (1993)] with two important modifications due to cell-to-cell diffusive coupling. First, this coupling breaks the degeneracy of an infinite-dimensional Hopf bifurcation such that the most unstable mode of alternans corresponds to the longest quantized wavelength of

  13. Spatiotemporal Dynamics of Vibrio spp. within the Sydney Harbour Estuary.

    PubMed

    Siboni, Nachshon; Balaraju, Varunan; Carney, Richard; Labbate, Maurizio; Seymour, Justin R

    2016-01-01

    Vibrio are a genus of marine bacteria that have substantial environmental and human health importance, and there is evidence that their impact may be increasing as a consequence of changing environmental conditions. We investigated the abundance and composition of the Vibrio community within the Sydney Harbour estuary, one of the most densely populated coastal areas in Australia, and a region currently experiencing rapidly changing environmental conditions. Using quantitative PCR (qPCR) and Vibrio-specific 16S rRNA amplicon sequencing approaches we observed significant spatial and seasonal variation in the abundance and composition of the Vibrio community. Total Vibrio spp. abundance, derived from qPCR analysis, was higher during the late summer than winter and within locations with mid-range salinity (5-26 ppt). In addition we targeted three clinically important pathogens: Vibrio cholerae, V. Vulnificus, and V. parahaemolyticus. While toxigenic strains of V. cholerae were not detected in any samples, non-toxigenic strains were detected in 71% of samples, spanning a salinity range of 0-37 ppt and were observed during both late summer and winter. In contrast, pathogenic V. vulnificus was only detected in 14% of samples, with its occurrence restricted to the late summer and a salinity range of 5-26 ppt. V. parahaemolyticus was not observed at any site or time point. A Vibrio-specific 16S rRNA amplicon sequencing approach revealed clear shifts in Vibrio community composition across sites and between seasons, with several Vibrio operational taxonomic units (OTUs) displaying marked spatial patterns and seasonal trends. Shifts in the composition of the Vibrio community between seasons were primarily driven by changes in temperature, salinity and NO2, while a range of factors including pH, salinity, dissolved oxygen (DO) and NOx (Nitrogen Oxides) explained the observed spatial variation. Our evidence for the presence of a spatiotemporally dynamic Vibrio community within

  14. A High Performance Bayesian Computing Framework for Spatiotemporal Uncertainty Modeling

    NASA Astrophysics Data System (ADS)

    Cao, G.

    2015-12-01

    All types of spatiotemporal measurements are subject to uncertainty. With spatiotemporal data becomes increasingly involved in scientific research and decision making, it is important to appropriately model the impact of uncertainty. Quantitatively modeling spatiotemporal uncertainty, however, is a challenging problem considering the complex dependence and dataheterogeneities.State-space models provide a unifying and intuitive framework for dynamic systems modeling. In this paper, we aim to extend the conventional state-space models for uncertainty modeling in space-time contexts while accounting for spatiotemporal effects and data heterogeneities. Gaussian Markov Random Field (GMRF) models, also known as conditional autoregressive models, are arguably the most commonly used methods for modeling of spatially dependent data. GMRF models basically assume that a geo-referenced variable primarily depends on its neighborhood (Markov property), and the spatial dependence structure is described via a precision matrix. Recent study has shown that GMRFs are efficient approximation to the commonly used Gaussian fields (e.g., Kriging), and compared with Gaussian fields, GMRFs enjoy a series of appealing features, such as fast computation and easily accounting for heterogeneities in spatial data (e.g, point and areal). This paper represents each spatial dataset as a GMRF and integrates them into a state-space form to statistically model the temporal dynamics. Different types of spatial measurements (e.g., categorical, count or continuous), can be accounted for by according link functions. A fast alternative to MCMC framework, so-called Integrated Nested Laplace Approximation (INLA), was adopted for model inference.Preliminary case studies will be conducted to showcase the advantages of the described framework. In the first case, we apply the proposed method for modeling the water table elevation of Ogallala aquifer over the past decades. In the second case, we analyze the

  15. The spatiotemporal patterns of rainfall erosivity in Yunnan Province, southwest China: An analysis of empirical orthogonal functions

    NASA Astrophysics Data System (ADS)

    Duan, Xingwu; Gu, Zhijia; Li, Yungang; Xu, Huijuan

    2016-09-01

    Rainfall erosivity (R) influences the formation mechanisms and succession processes of soil erosion. Knowing of the R factor facilitates the prediction of soil erosion and of the impact of climate change on erosion. However, defining of the R factor is challenging because its spatiotemporal variation can be complex. We combined the Empirical Orthogonal Function (EOF), North criteria, and Mann-Kendall test (M-K) to investigate the spatiotemporal patterns of the R factor for a study area in a typical mountain plateau region of Yunnan Province (YP), China. Daily rainfall records from 1960 to 2012 were collected from 115 national meteorological observation stations in YP. Based on the daily rainfall erosivity estimating model, we determined that the average annual R factor was 4383.85 MJ·mm·ha- 1·h- 1, the seasonal R factor exhibited an order of summer > autumn > spring > winter, and the summer R was significantly higher than winter R. The spatiotemporal variation of the R factor was complex and did not reveal a uniform pattern. The spatial distribution revealed that the annual and seasonal R factors in the west were higher than those in the east, and R in the south were higher than those in the north. The temporal trends of annual, summer, and autumn R factors had decreasing trends from 1960 to 2012. On the contrary, the spring and winter R factors showed an increasing trend. The EOF analysis identified two typical spatiotemporal patterns of the annual R factor in YP, and three for spring, summer, autumn, and winter R factors. These patterns represented the influence of the monsoon, circulation systems, and complex terrain conditions on the rainfall in the YP.

  16. Spatio-temporal variability of shallow groundwater quality in a typical agricultural catchment in subtropical central China

    NASA Astrophysics Data System (ADS)

    Liu, X.

    2015-12-01

    Excessive agriculture-sourced N leaching into shallow groundwater has deteriorated the domestic water quality in rural China. To effectively prevent the above environmental contamination issue, it is an essential prerequisite of exploring the spatio-temporal variability (stV) of the groundwater quality. In this study, a large observation program was deployed to observe ammonium-N (NH4N), nitrate-N (NO3N) and total N (TN) concentrations in 194 groundwater observation wells (1.5 m deep from soil surface) from April 2010 to November 2012 in the Jinjing river catchment in Hunan Province of China. A logit function was applied to transform NH4N, NO3N and TN data for normality; the resultant variables were thus named as NH4Nt, NO3Nt and TNt, respectively. A spatio-temporal semivariogram model in a sum-metric form was used to quantify the stV of NH4Nt, NO3Nt and TNt. The results indicated that the 33-month means ± standard deviations of the NH4N, NO3N and TN concentrations were 0.75±0.10, 1.60±0.19 and 2.99±0.29 mg N L-1, respectively. NH4Nt and NO3Nt exhibited a strong spatio-temporal dependence, while TNt only presented a strong temporal structure. Spatio-temporal ordinary kriging (stOK) was applied to predict the spatio-temporal distributions of NH4N, NO3N and TN over the catchment. The cross-validation results indicated that the stOK predictions for NH4N (r=0.48, RMSE=1.11 mg N L-1), NO3N (r=0.46, RMSE=1.21 mg N L-1) outperformed that for TN (r=0.29, RMSE=2.11 mg N L-1). Referenced to the Chinese Environmental Quality Standards for Groundwater (GB/T 14848-93), the proportions of areas contaminated by NH4N, NO3N and TN in the catchment over a 33-month period were 20.5%, 1.46%, and 5.07%, respectively. Our findings suggested that the Jinjing groundwater was mainly polluted by NH4N, which is probably attributed to the intensive rice agriculture featured with high urea fertilizer applications in the catchment.

  17. A stochastic spatiotemporal model of a response-regulator network in the Caulobacter crescentus cell cycle

    NASA Astrophysics Data System (ADS)

    Li, Fei; Subramanian, Kartik; Chen, Minghan; Tyson, John J.; Cao, Yang

    2016-06-01

    The asymmetric cell division cycle in Caulobacter crescentus is controlled by an elaborate molecular mechanism governing the production, activation and spatial localization of a host of interacting proteins. In previous work, we proposed a deterministic mathematical model for the spatiotemporal dynamics of six major regulatory proteins. In this paper, we study a stochastic version of the model, which takes into account molecular fluctuations of these regulatory proteins in space and time during early stages of the cell cycle of wild-type Caulobacter cells. We test the stochastic model with regard to experimental observations of increased variability of cycle time in cells depleted of the divJ gene product. The deterministic model predicts that overexpression of the divK gene blocks cell cycle progression in the stalked stage; however, stochastic simulations suggest that a small fraction of the mutants cells do complete the cell cycle normally.

  18. Spatio-Temporally Restricted Expression of Cell Adhesion Molecules during Chicken Embryonic Development

    PubMed Central

    Roy, Priti; Bandyopadhyay, Amitabha

    2014-01-01

    Differential cell adhesive properties are known to regulate important developmental events like cell sorting and cell migration. Cadherins and protocadherins are known to mediate these cellular properties. Though a large number of such molecules have been predicted, their characterization in terms of interactive properties and cellular roles is far from being comprehensive. To narrow down the tissue context and collect correlative evidence for tissue specific roles of these molecules, we have carried out whole-mount in situ hybridization based RNA expression study for seven cadherins and four protocadherins. In developing chicken embryos (HH stages 18, 22, 26 and 28) cadherins and protocadherins are expressed in tissue restricted manner. This expression study elucidates precise expression domains of cell adhesion molecules in the context of developing embryos. These expression domains provide spatio-temporal context in which the function of these genes can be further explored. PMID:24806091

  19. Global spatiotemporal order and induced stochastic resonance due to a locally applied signal

    NASA Astrophysics Data System (ADS)

    Samoletov, A.; Chaplain, M.; Levi, V.

    2004-04-01

    We study the phenomenon of spatiotemporal stochastic resonance (STSR) in a chain of diffusively coupled bistable oscillators. In particular, we examine the situation in which the global STSR response is controlled by a locally applied signal and reveal a wave-front propagation. In order to deepen the understanding of the system dynamics, we introduce, on the time scale of STSR, the study of the effective statistical renormalization of a generic lattice system. Using this technique we provide a criterion for STSR, and predict and observe numerically a bifurcationlike behavior that reflects the difference between the most probable value of the local quasiequilibrium density and its mean value. Our results, tested with a chain of nonlinear oscillators, appear to possess some universal qualities and may stimulate a deeper search for more generic phenomena.

  20. Challenges for modelling spatio-temporal variations of malaria risk in Malawi

    NASA Astrophysics Data System (ADS)

    Lowe, R.; Chirombo, J.; Tompkins, A. M.

    2012-04-01

    the unobserved confounding factors that influence malaria, which are not accounted for using measured covariates, a negative binomial generalised linear mixed model (GLMM) is adopted, which includes structured and unstructured spatial and temporal random effects. The parameters in this spatio-temporal Bayesian hierarchical model are estimated using Markov Chain Monte Carlo (MCMC). This allows posterior predictive distributions for disease risk to be derived for each spatial location and time period. A novel visualisation technique is then used to display seasonal probabilistic forecasts of malaria risk, derived from the developed model using pre-defined risk category thresholds, on a map. This technique allows decision makers to identify areas where the model predicts with certainty a particular malaria risk category (high, medium or low); in order to effectively target limited resources to those districts most at risk for a given season.

  1. Geophysical Factor Resolving of Rainfall Mechanism for Super Typhoons by Using Multiple Spatiotemporal Components Analysis

    NASA Astrophysics Data System (ADS)

    Huang, Chien-Lin; Hsu, Nien-Sheng

    2016-04-01

    This study develops a novel methodology to resolve the geophysical cause of typhoon-induced rainfall considering diverse dynamic co-evolution at multiple spatiotemporal components. The multi-order hidden patterns of complex hydrological process in chaos are detected to understand the fundamental laws of rainfall mechanism. The discovered spatiotemporal features are utilized to develop a state-of-the-art descriptive statistical model for mechanism validation, modeling and further prediction during typhoons. The time series of hourly typhoon precipitation from different types of moving track, atmospheric field and landforms are respectively precede the signal analytical process to qualify each type of rainfall cause and to quantify the corresponding affected degree based on the measured geophysical atmospheric-hydrological variables. This study applies the developed methodology in Taiwan Island which is constituted by complex diverse landform formation. The identified driving-causes include: (1) cloud height to ground surface; (2) co-movement effect induced by typhoon wind field with monsoon; (3) stem capacity; (4) interaction between typhoon rain band and terrain; (5) structural intensity variance of typhoon; and (6) integrated cloudy density of rain band. Results show that: (1) for the central maximum wind speed exceeding 51 m/sec, Causes (1) and (3) are the primary ones to generate rainfall; (2) for the typhoon moving toward the direction of 155° to 175°, Cause (2) is the primary one; (3) for the direction of 90° to 155°, Cause (4) is the primary one; (4) for the typhoon passing through mountain chain which above 3500 m, Cause (5) is the primary one; and (5) for the moving speed lower than 18 km/hr, Cause (6) is the primary one. Besides, the multiple geophysical component-based precipitation modeling can achieve 81% of average accuracy and 0.732 of average correlation coefficient (CC) within average 46 hours of duration, that improve their predictability.

  2. Effective and efficient analysis of spatio-temporal data

    NASA Astrophysics Data System (ADS)

    Zhang, Zhongnan

    Spatio-temporal data mining, i.e., mining knowledge from large amount of spatio-temporal data, is a highly demanding field because huge amounts of spatio-temporal data have been collected in various applications, ranging from remote sensing, to geographical information systems (GIS), computer cartography, environmental assessment and planning, etc. The collection data far exceeded human's ability to analyze which make it crucial to develop analysis tools. Recent studies on data mining have extended to the scope of data mining from relational and transactional datasets to spatial and temporal datasets. Among the various forms of spatio-temporal data, remote sensing images play an important role, due to the growing wide-spreading of outer space satellites. In this dissertation, we proposed two approaches to analyze the remote sensing data. The first one is about applying association rules mining onto images processing. Each image was divided into a number of image blocks. We built a spatial relationship for these blocks during the dividing process. This made a large number of images into a spatio-temporal dataset since each image was shot in time-series. The second one implemented co-occurrence patterns discovery from these images. The generated patterns represent subsets of spatial features that are located together in space and time. A weather analysis is composed of individual analysis of several meteorological variables. These variables include temperature, pressure, dew point, wind, clouds, visibility and so on. Local-scale models provide detailed analysis and forecasts of meteorological phenomena ranging from a few kilometers to about 100 kilometers in size. When some of above meteorological variables have some special change tendency, some kind of severe weather will happen in most cases. Using the discovery of association rules, we found that some special meteorological variables' changing has tight relation with some severe weather situation that will happen

  3. New insights into schizophrenia disease genes interactome in the human brain: emerging targets and therapeutic implications in the postgenomics era.

    PubMed

    Podder, Avijit; Latha, Narayanan

    2014-12-01

    Schizophrenia, a complex neurological disorder, is comprised of interactions between multiple genetic and environmental factors wherein each of the factors individually exhibits a small effect. In this regard a network-based strategy is best suited to capture the combined effect of multiple genes with their definite pattern of interactions. Given that schizophrenia affects multiple regions of the brain, we postulated that instead of any single specific tissue, a mutual set of interactions occurs between different regions of brain in a well-defined pattern responsible for the disease phenotype. To validate, we constructed and compared tissue specific co-expression networks of schizophrenia candidate genes in twenty diverse brain tissues. As predicted, we observed a common interaction network of certain genes in all the studied brain tissues. We examined fundamental network topologies of the common network to sequester essential common candidates for schizophrenia. We also performed a gene set analysis to identify the essential biological pathways enriched by the common candidates in the network. Finally, the candidate drug targets were prioritized and scored against known available schizophrenic drugs by molecular docking studies. We distinctively identified protein kinases as the top candidates in the network that can serve as probable drug targets for the disease. Conclusively, we propose that a comprehensive study of the connectivity amongst the disease genes themselves may turn out to be more informative to understand schizophrenia disease etiology and the underlying complexity.

  4. Method for Fusing Observational Data and Chemical Transport Model Simulations To Estimate Spatiotemporally Resolved Ambient Air Pollution.

    PubMed

    Friberg, Mariel D; Zhai, Xinxin; Holmes, Heather A; Chang, Howard H; Strickland, Matthew J; Sarnat, Stefanie Ebelt; Tolbert, Paige E; Russell, Armistead G; Mulholland, James A

    2016-04-01

    Investigations of ambient air pollution health effects rely on complete and accurate spatiotemporal air pollutant estimates. Three methods are developed for fusing ambient monitor measurements and 12 km resolution chemical transport model (CMAQ) simulations to estimate daily air pollutant concentrations across Georgia. Temporal variance is determined by observations in one method, with the annual mean CMAQ field providing spatial structure. A second method involves scaling daily CMAQ simulated fields using mean observations to reduce bias. Finally, a weighted average of these results based on prediction of temporal variance provides optimized daily estimates for each 12 × 12 km grid. These methods were applied to daily metrics of 12 pollutants (CO, NO2, NOx, O3, SO2, PM10, PM2.5, and five PM2.5 components) over the state of Georgia for a seven-year period (2002-2008). Cross-validation demonstrates a wide range in optimized model performance across pollutants, with SO2 predicted most poorly due to limitations in coal combustion plume monitoring and modeling. For the other pollutants studied, 54-88% of the spatiotemporal variance (Pearson R(2) from cross-validation) was captured, with ozone and PM2.5 predicted best. The optimized fusion approach developed provides daily spatial field estimates of air pollutant concentrations and uncertainties that are consistent with observations, emissions, and meteorology. PMID:26923334

  5. Sniffing and spatiotemporal coding in olfaction.

    PubMed

    Scott, John W

    2006-02-01

    The act of sniffing increases the air velocity and changes the duration of airflow in the nose. It is not yet clear how these changes interact with the intrinsic timing within the olfactory bulb, but this is a matter of current research activity. An action of sniffing in generating a high velocity that alters the sorption of odorants onto the lining of the nasal cavity is expected from the established work on odorant properties and sorption in the frog nose. Recent work indicates that the receptor properties in the olfactory epithelium and olfactory bulb are correlated with the receptor gene expression zones. The responses in both the epithelium and the olfactory bulb are predictable to a considerable extent by the hydrophobicity of odorants. Furthermore, receptor expression in both rodent and salamander nose interacts with the shapes of the nasal cavity to place the receptor sensitivity to odorants in optimal places according to the aerodynamic properties of the nose.

  6. Spatiotemporal analysis of ERP data in emotional processing

    NASA Astrophysics Data System (ADS)

    Hu, Jin; Tian, Jie; Yang, Lei; Pan, Xiaohong; Liu, Jianggang

    2006-03-01

    The aim of this paper is to analyze spatiotemporal patterns of Event-related potential (ERP) in emotional processing by using fuzzy k-means clustering method to segment ERP data into microstates.108 pictures (categorized as positive, negative and neutral) were presented to 24 healthy, right-handed subjects while 128-channel EEG data were recorded. For each subject, 3 artifact-free ERPs were computed under each condition. A modified fuzzy k-mean clustering method based on shape similarity is applied to the grand mean ERPs and the statistical analysis is performed to define the significance of each segmentation map. In the results, positive and negative conditions showed different spatiotemporal patterns of ERP. The results were in accord with other emotional study by fMRI or PET.

  7. Dynamics of light propagation in spatiotemporal dielectric structures.

    PubMed

    Biancalana, Fabio; Amann, Andreas; Uskov, Alexander V; O'Reilly, Eoin P

    2007-04-01

    Propagation, transmission and reflection properties of linearly polarized plane waves and arbitrarily short electromagnetic pulses in one-dimensional dispersionless dielectric media possessing an arbitrary space-time dependence of the refractive index are studied by using a two-component, highly symmetric version of Maxwell's equations. The use of any slow varying amplitude approximation is avoided. Transfer matrices of sharp nonstationary interfaces are calculated explicitly, together with the amplitudes of all secondary waves produced in the scattering. Time-varying multilayer structures and spatiotemporal lenses in various configurations are investigated analytically and numerically in a unified approach. Several effects are reported, such as pulse compression, broadening and spectral manipulation of pulses by a spatiotemporal lens, and the closure of the forbidden frequency gaps with the subsequent opening of wave number band gaps in a generalized Bragg reflector. PMID:17501007

  8. Broadband spatiotemporal Gaussian Schell-model pulse trains.

    PubMed

    Dutta, Rahul; Korhonen, Minna; Friberg, Ari T; Genty, Göery; Turunen, Jari

    2014-03-01

    A new class of partially coherent model sources is introduced on the basis of the second-order coherence theory of nonstationary optical fields. These model sources are spatially fully coherent at each frequency but can have broadband spectra and variable spectral coherence properties, which lead to reduced spatiotemporal coherence in the time domain. The source model is motivated by the spectral coherence properties of supercontinuum pulse trains generated in single-spatial-mode optical fibers. We demonstrate that such broadband light is highly (but not completely) spatially coherent, even though the spectral and temporal coherence properties may vary over a wide range. The model sources introduced here are convenient in assessing the spatiotemporal coherence of broadband pulses in optical systems. PMID:24690663

  9. Dynamics of light propagation in spatiotemporal dielectric structures

    NASA Astrophysics Data System (ADS)

    Biancalana, Fabio; Amann, Andreas; Uskov, Alexander V.; O'Reilly, Eoin P.

    2007-04-01

    Propagation, transmission and reflection properties of linearly polarized plane waves and arbitrarily short electromagnetic pulses in one-dimensional dispersionless dielectric media possessing an arbitrary space-time dependence of the refractive index are studied by using a two-component, highly symmetric version of Maxwell’s equations. The use of any slow varying amplitude approximation is avoided. Transfer matrices of sharp nonstationary interfaces are calculated explicitly, together with the amplitudes of all secondary waves produced in the scattering. Time-varying multilayer structures and spatiotemporal lenses in various configurations are investigated analytically and numerically in a unified approach. Several effects are reported, such as pulse compression, broadening and spectral manipulation of pulses by a spatiotemporal lens, and the closure of the forbidden frequency gaps with the subsequent opening of wave number band gaps in a generalized Bragg reflector.

  10. Dynamics of light propagation in spatiotemporal dielectric structures.

    PubMed

    Biancalana, Fabio; Amann, Andreas; Uskov, Alexander V; O'Reilly, Eoin P

    2007-04-01

    Propagation, transmission and reflection properties of linearly polarized plane waves and arbitrarily short electromagnetic pulses in one-dimensional dispersionless dielectric media possessing an arbitrary space-time dependence of the refractive index are studied by using a two-component, highly symmetric version of Maxwell's equations. The use of any slow varying amplitude approximation is avoided. Transfer matrices of sharp nonstationary interfaces are calculated explicitly, together with the amplitudes of all secondary waves produced in the scattering. Time-varying multilayer structures and spatiotemporal lenses in various configurations are investigated analytically and numerically in a unified approach. Several effects are reported, such as pulse compression, broadening and spectral manipulation of pulses by a spatiotemporal lens, and the closure of the forbidden frequency gaps with the subsequent opening of wave number band gaps in a generalized Bragg reflector.

  11. Nature of Spatiotemporal Light Bullets in Bulk Kerr Media

    NASA Astrophysics Data System (ADS)

    Majus, D.; Tamošauskas, G.; GražulevičiÅ«tÄ--, I.; Garejev, N.; Lotti, A.; Couairon, A.; Faccio, D.; Dubietis, A.

    2014-05-01

    We present a detailed experimental investigation which uncovers the nature of light bullets generated from self-focusing in a bulk dielectric medium with Kerr nonlinearity in the anomalous group velocity dispersion regime. By high dynamic range measurements of three-dimensional intensity profiles, we demonstrate that the light bullets consist of a sharply localized high-intensity core, which carries the self-compressed pulse and contains approximately 25% of the total energy, and a ring-shaped spatiotemporal periphery. Subdiffractive propagation along with dispersive broadening of the light bullets in free space after they exit the nonlinear medium indicate a strong space-time coupling within the bullet. This finding is confirmed by measurements of a spatiotemporal energy density flux that exhibits the same features as a stationary, polychromatic Bessel beam, thus highlighting the nature of the light bullets.

  12. Spatiotemporal causal modeling for the management of Dengue Fever

    NASA Astrophysics Data System (ADS)

    Yu, Hwa-Lung; Huang, Tailin; Lee, Chieh-Han

    2015-04-01

    Increasing climatic extremes have caused growing concerns about the health effects and disease outbreaks. The association between climate variation and the occurrence of epidemic diseases play an important role on a country's public health systems. Part of the impacts are direct casualties associated with the increasing frequency and intensity of typhoons, the proliferation of disease vectors and the short-term increase of clinic visits on gastro-intestinal discomforts, diarrhea, dermatosis, or psychological trauma. Other impacts come indirectly from the influence of disasters on the ecological and socio-economic systems, including the changes of air/water quality, living environment and employment condition. Previous risk assessment studies on dengue fever focus mostly on climatic and non-climatic factors and their association with vectors' reproducing pattern. The public-health implication may appear simple. Considering the seasonal changes and regional differences, however, the causality of the impacts is full of uncertainties. Without further investigation, the underlying dengue fever risk dynamics may not be assessed accurately. The objective of this study is to develop an epistemic framework for assessing dynamic dengue fever risk across space and time. The proposed framework integrates cross-departmental data, including public-health databases, precipitation data over time and various socio-economic data. We explore public-health issues induced by typhoon through literature review and spatiotemporal analytic techniques on public health databases. From those data, we identify relevant variables and possible causal relationships, and their spatiotemporal patterns derived from our proposed spatiotemporal techniques. Eventually, we create a spatiotemporal causal network and a framework for modeling dynamic dengue fever risk.

  13. Selecting salient frames for spatiotemporal video modeling and segmentation.

    PubMed

    Song, Xiaomu; Fan, Guoliang

    2007-12-01

    We propose a new statistical generative model for spatiotemporal video segmentation. The objective is to partition a video sequence into homogeneous segments that can be used as "building blocks" for semantic video segmentation. The baseline framework is a Gaussian mixture model (GMM)-based video modeling approach that involves a six-dimensional spatiotemporal feature space. Specifically, we introduce the concept of frame saliency to quantify the relevancy of a video frame to the GMM-based spatiotemporal video modeling. This helps us use a small set of salient frames to facilitate the model training by reducing data redundancy and irrelevance. A modified expectation maximization algorithm is developed for simultaneous GMM training and frame saliency estimation, and the frames with the highest saliency values are extracted to refine the GMM estimation for video segmentation. Moreover, it is interesting to find that frame saliency can imply some object behaviors. This makes the proposed method also applicable to other frame-related video analysis tasks, such as key-frame extraction, video skimming, etc. Experiments on real videos demonstrate the effectiveness and efficiency of the proposed method.

  14. Spatiotemporal quantile regression for detecting distributional changes in environmental processes.

    PubMed

    Reich, Brian J

    2012-08-01

    Climate change may lead to changes in several aspects of the distribution of climate variables, including changes in the mean, increased variability, and severity of extreme events. In this paper, we propose using spatiotemporal quantile regression as a flexible and interpretable method for simultaneously detecting changes in several features of the distribution of climate variables. The spatiotemporal quantile regression model assumes that each quantile level changes linearly in time, permitting straight-forward inference on the time trend for each quantile level. Unlike classical quantile regression which uses model-free methods to analyze a single quantile or several quantiles separately, we take a model-based approach which jointly models all quantiles, and thus the entire response distribution. In the spatiotemporal quantile regression model, each spatial location has its own quantile function that evolves over time, and the quantile functions are smoothed spatially using Gaussian process priors. We propose a basis expansion for the quantile function that permits a closed-form for the likelihood, and allows for residual correlation modeling via a Gaussian spatial copula. We illustrate the methods using temperature data for the southeast US from the years 1931-2009. For these data, borrowing information across space identifies more significant time trends than classical non-spatial quantile regression. We find a decreasing time trend for much of the spatial domain for monthly mean and maximum temperatures. For the lower quantiles of monthly minimum temperature, we find a decrease in Georgia and Florida, and an increase in Virginia and the Carolinas.

  15. Visual memory performance for color depends on spatiotemporal context.

    PubMed

    Olivers, Christian N L; Schreij, Daniel

    2014-10-01

    Performance on visual short-term memory for features has been known to depend on stimulus complexity, spatial layout, and feature context. However, with few exceptions, memory capacity has been measured for abruptly appearing, single-instance displays. In everyday life, objects often have a spatiotemporal history as they or the observer move around. In three experiments, we investigated the effect of spatiotemporal history on explicit memory for color. Observers saw a memory display emerge from behind a wall, after which it disappeared again. The test display then emerged from either the same side as the memory display or the opposite side. In the first two experiments, memory improved for intermediate set sizes when the test display emerged in the same way as the memory display. A third experiment then showed that the benefit was tied to the original motion trajectory and not to the display object per se. The results indicate that memory for color is embedded in a richer episodic context that includes the spatiotemporal history of the display. PMID:25073612

  16. Spatiotemporal Distribution of Chinavia hilaris (Hemiptera: Pentatomidae) in Corn Farmscapes

    PubMed Central

    Cottrell, Ted E.; Tillman, P. Glynn

    2015-01-01

    The green stink bug, Chinavia hilaris (Say) (Hemiptera: Pentatomidae), is a pest of cotton in the southeastern United States but little is known concerning its spatiotemporal distribution in corn cropping systems. Therefore, the spatiotemporal distribution of C. hilaris in farmscapes, when corn was adjacent to cotton, peanut, or both, was examined weekly. The spatial patterns of C. hilaris counts were analyzed using Spatial Analysis by Distance Indices methodology. Interpolated maps of C. hilaris density were used to visualize abundance and distribution of C. hilaris in crops in corn–peanut–cotton farmscapes. This stink bug was detected in six of seven corn–cotton farmscapes, four of six corn–peanut farmscapes, and in both corn–peanut–cotton farmscapes. The frequency of C. hilaris in cotton (89.47%) was significantly higher than in peanut (7.02%) or corn (3.51%). This stink bug fed on noncrop hosts that grew in field borders adjacent to crops. The spatial distribution of C. hilaris in crops and the capture of C. hilaris adults and nymphs in pheromone-baited traps near noncrop hosts indicated that these hosts were sources of this stink bug dispersing into crops, primarily cotton. Significant aggregated spatial distributions were detected in cotton on some dates within corn–peanut–cotton farmscapes. Maps of local clustering indices depicted small patches of C. hilaris in cotton or cotton–sorghum at the peanut–cotton interface. Factors affecting the spatiotemporal dynamics of C. hilaris in corn farmscapes are discussed. PMID:25843581

  17. Using GeoRSS to syndicate the spatiotemporal information

    NASA Astrophysics Data System (ADS)

    Zhao, Bo; Li, Manchun; Jiang, Zhixin

    2007-06-01

    This paper describes a number of ways to encode spatiotemporal information in RSS feeds. As RSS becomes more and more prevalent as a way to publish and share information, it becomes increasingly important that location and time is described in an interoperable manner so that applications can request, aggregate, share and map spatiotemporally tagged feeds. This paper describes the GeoRSS model and encodings. With every RSS item has a timestamp, GeoRSS can represent time property for free. There are three GeoRSS encoding standards, such as W3C Geo, GeoRSS Simple, and GeoRSS GML profile. These standards differ in the number of coordinate systems they can support, and in the number of different geometric shapes they can add to the map to show where the news or event of interest is taking place. Further more, this paper described how to add time attribute to GeoRSS and implement and visualization the GeoRSS feeds through Google Map and Timeline. A few apt illustrations were given to show the powerful functions of GeoRSS in syndicating the spatiotemporal information. GeoRSS leverages this teeming ecosystem for geospatial technology, and with OGC support, GeoRSS is on firm conceptual ground and gains exposure across the industry.