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Sample records for interactome predicts spatiotemporal

  1. Bayesian Modeling of the Yeast SH3 Domain Interactome Predicts Spatiotemporal Dynamics of Endocytosis

    E-print Network

    Gerstein, Mark

    of Endocytosis Proteins Raffi Tonikian1,2. , Xiaofeng Xin1,2. , Christopher P. Toret3.¤a , David Gfeller1-confidence yeast SH3 domain interaction map. The interaction map was enriched for proteins involved in endocytosis Interactome Predicts Spatiotemporal Dynamics of Endocytosis Proteins. PLoS Biol 7(10): e1000218. doi:10

  2. Mycobacterium tuberculosis and Clostridium difficille interactomes: demonstration of rapid development of computational system for bacterial interactome prediction

    PubMed Central

    2012-01-01

    Background Protein-protein interaction (PPI) networks (interactomes) of most organisms, except for some model organisms, are largely unknown. Experimental methods including high-throughput techniques are highly resource intensive. Therefore, computational discovery of PPIs can accelerate biological discovery by presenting "most-promising" pairs of proteins that are likely to interact. For many bacteria, genome sequence, and thereby genomic context of proteomes, is readily available; additionally, for some of these proteomes, localization and functional annotations are also available, but interactomes are not available. We present here a method for rapid development of computational system to predict interactome of bacterial proteomes. While other studies have presented methods to transfer interologs across species, here, we propose transfer of computational models to benefit from cross-species annotations, thereby predicting many more novel interactions even in the absence of interologs. Mycobacterium tuberculosis (Mtb) and Clostridium difficile (CD) have been used to demonstrate the work. Results We developed a random forest classifier over features derived from Gene Ontology annotations and genetic context scores provided by STRING database for predicting Mtb and CD interactions independently. The Mtb classifier gave a precision of 94% and a recall of 23% on a held out test set. The Mtb model was then run on all the 8 million protein pairs of the Mtb proteome, resulting in 708 new interactions (at 94% expected precision) or 1,595 new interactions at 80% expected precision. The CD classifier gave a precision of 90% and a recall of 16% on a held out test set. The CD model was run on all the 8 million protein pairs of the CD proteome, resulting in 143 new interactions (at 90% expected precision) or 580 new interactions (at 80% expected precision). We also compared the overlap of predictions of our method with STRING database interactions for CD and Mtb and also with interactions identified recently by a bacterial 2-hybrid system for Mtb. To demonstrate the utility of transfer of computational models, we made use of the developed Mtb model and used it to predict CD protein-pairs. The cross species model thus developed yielded a precision of 88% at a recall of 8%. To demonstrate transfer of features from other organisms in the absence of feature-based and interaction-based information, we transferred missing feature values from Mtb orthologs into the CD data. In transferring this data from orthologs (not interologs), we showed that a large number of interactions can be predicted. Conclusions Rapid discovery of (partial) bacterial interactome can be made by using existing set of GO and STRING features associated with the organisms. We can make use of cross-species interactome development, when there are not even sufficient known interactions to develop a computational prediction system. Computational model of well-studied organism(s) can be employed to make the initial interactome prediction for the target organism. We have also demonstrated successfully, that annotations can be transferred from orthologs in well-studied organisms enabling accurate predictions for organisms with no annotations. These approaches can serve as building blocks to address the challenges associated with feature coverage, missing interactions towards rapid interactome discovery for bacterial organisms. Availability The predictions for all Mtb and CD proteins are made available at: http://severus.dbmi.pitt.edu/TB and http://severus.dbmi.pitt.edu/CD respectively for browsing as well as for download. PMID:22587966

  3. Predicting Malaria Interactome Classifications from Time-Course Transcriptomic Data along the

    E-print Network

    Mishra, Bud

    Predicting Malaria Interactome Classifications from Time-Course Transcriptomic Data along Cummington Street, Boston, MA, 02215 August 4, 2009 Summary Objective: Even though a vaccine for malaria- mated method for predicting functions for the malaria parasite, which capitalizes on the importance

  4. Predicting the Interactome of Xanthomonas oryzae pathovar oryzae for target selection and DB service

    PubMed Central

    Kim, Jeong-Gu; Park, Daeui; Kim, Byoung-Chul; Cho, Seong-Woong; Kim, Yeong Tae; Park, Young-Jin; Cho, Hee Jung; Park, Hyunseok; Kim, Ki-Bong; Yoon, Kyong-Oh; Park, Soo-Jun; Lee, Byoung-Moo; Bhak, Jong

    2008-01-01

    Background Protein-protein interactions (PPIs) play key roles in various cellular functions. In addition, some critical inter-species interactions such as host-pathogen interactions and pathogenicity occur through PPIs. Phytopathogenic bacteria infect hosts through attachment to host tissue, enzyme secretion, exopolysaccharides production, toxins release, iron acquisition, and effector proteins secretion. Many such mechanisms involve some kind of protein-protein interaction in hosts. Our first aim was to predict the whole protein interaction pairs (interactome) of Xanthomonas oryzae pathovar oryzae (Xoo) that is an important pathogenic bacterium that causes bacterial blight (BB) in rice. We developed a detection protocol to find possibly interacting proteins in its host using whole genome PPI prediction algorithms. The second aim was to build a DB server and a bioinformatic procedure for finding target proteins in Xoo for developing pesticides that block host-pathogen protein interactions within critical biochemical pathways. Description A PPI network in Xoo proteome was predicted by bioinformatics algorithms: PSIMAP, PEIMAP, and iPfam. We present the resultant species specific interaction network and host-pathogen interaction, XooNET. It is a comprehensive predicted initial PPI data for Xoo. XooNET can be used by experimentalists to pick up protein targets for blocking pathological interactions. XooNET uses most of the major types of PPI algorithms. They are: 1) Protein Structural Interactome MAP (PSIMAP), a method using structural domain of SCOP, 2) Protein Experimental Interactome MAP (PEIMAP), a common method using public resources of experimental protein interaction information such as HPRD, BIND, DIP, MINT, IntAct, and BioGrid, and 3) Domain-domain interactions, a method using Pfam domains such as iPfam. Additionally, XooNET provides information on network properties of the Xoo interactome. Conclusion XooNET is an open and free public database server for protein interaction information for Xoo. It contains 4,538 proteins and 26,932 possible interactions consisting of 18,503 (PSIMAP), 3,118 (PEIMAP), and 8,938 (iPfam) pairs. In addition, XooNET provides 3,407 possible interaction pairs between two sets of proteins; 141 Xoo proteins that are predicted as membrane proteins and rice proteomes. The resultant interacting partners of a query protein can be easily retrieved by users as well as the interaction networks in graphical web interfaces. XooNET is freely available from . PMID:18215330

  5. 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

  6. 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

  7. Evidence That a Psychopathology Interactome Has Diagnostic Value, Predicting Clinical Needs: An Experience Sampling Study

    PubMed Central

    van Os, Jim; Lataster, Tineke; Delespaul, Philippe; Wichers, Marieke; Myin-Germeys, Inez

    2014-01-01

    Background For the purpose of diagnosis, psychopathology can be represented as categories of mental disorder, symptom dimensions or symptom networks. Also, psychopathology can be assessed at different levels of temporal resolution (monthly episodes, daily fluctuating symptoms, momentary fluctuating mental states). We tested the diagnostic value, in terms of prediction of treatment needs, of the combination of symptom networks and momentary assessment level. Method Fifty-seven patients with a psychotic disorder participated in an ESM study, capturing psychotic experiences, emotions and circumstances at 10 semi-random moments in the flow of daily life over a period of 6 days. Symptoms were assessed by interview with the Positive and Negative Syndrome Scale (PANSS); treatment needs were assessed using the Camberwell Assessment of Need (CAN). Results Psychotic symptoms assessed with the PANSS (Clinical Psychotic Symptoms) were strongly associated with psychotic experiences assessed with ESM (Momentary Psychotic Experiences). However, the degree to which Momentary Psychotic Experiences manifested as Clinical Psychotic Symptoms was determined by level of momentary negative affect (higher levels increasing probability of Momentary Psychotic Experiences manifesting as Clinical Psychotic Symptoms), momentary positive affect (higher levels decreasing probability of Clinical Psychotic Symptoms), greater persistence of Momentary Psychotic Experiences (persistence predicting increased probability of Clinical Psychotic Symptoms) and momentary environmental stress associated with events and activities (higher levels increasing probability of Clinical Psychotic Symptoms). Similarly, the degree to which momentary visual or auditory hallucinations manifested as Clinical Psychotic Symptoms was strongly contingent on the level of accompanying momentary paranoid delusional ideation. Momentary Psychotic Experiences were associated with CAN unmet treatment needs, over and above PANSS measures of psychopathology, similarly moderated by momentary interactions with emotions and context. Conclusion The results suggest that psychopathology, represented as an interactome at the momentary level of temporal resolution, is informative in diagnosing clinical needs, over and above traditional symptom measures. PMID:24466189

  8. Rapid, optimized interactomic screening.

    PubMed

    Hakhverdyan, Zhanna; Domanski, Michal; Hough, Loren E; 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

    2015-06-01

    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 screening method that comprehensively explores the parameters affecting the stability of interactions in affinity-captured complexes, enabling the discovery of physiological binding partners in unparalleled detail. We have implemented this screen on several macromolecular complexes from a variety of organisms, revealing novel profiles for even well-studied proteins. Our approach is robust, economical and automatable, providing inroads to the rigorous, systematic dissection of cellular interactomes. PMID:25938370

  9. 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

  10. 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

  11. A Spatiotemporal Approach to Tornado Prediction V Lakshmanan

    E-print Network

    Lakshmanan, Valliappa

    A Spatiotemporal Approach to Tornado Prediction V Lakshmanan University of Oklahoma and National Weather Service Abstract-- Automated tornado detection or prediction tech- niques in the literature have all been based on analyzing "signa- tures" of tornadoes that appear in Doppler radar velocity data

  12. The interactome challenge.

    PubMed

    Aitchison, John D; Rout, Michael P

    2015-11-23

    The properties of living cells are mediated by a huge number of ever-changing interactions of their component macromolecules forming living machines; collectively, these are termed the interactome. Pathogenic alterations in interactomes mechanistically underlie diseases. Therefore, there exists an essential need for much better tools to reveal and dissect interactomes. This need is only now beginning to be met. PMID:26572620

  13. Triangle network motifs predict complexes by complementing high-error interactomes with structural information

    PubMed Central

    Andreopoulos, Bill; Winter, Christof; Labudde, Dirk; Schroeder, Michael

    2009-01-01

    Background A lot of high-throughput studies produce protein-protein interaction networks (PPINs) with many errors and missing information. Even for genome-wide approaches, there is often a low overlap between PPINs produced by different studies. Second-level neighbors separated by two protein-protein interactions (PPIs) were previously used for predicting protein function and finding complexes in high-error PPINs. We retrieve second level neighbors in PPINs, and complement these with structural domain-domain interactions (SDDIs) representing binding evidence on proteins, forming PPI-SDDI-PPI triangles. Results We find low overlap between PPINs, SDDIs and known complexes, all well below 10%. We evaluate the overlap of PPI-SDDI-PPI triangles with known complexes from Munich Information center for Protein Sequences (MIPS). PPI-SDDI-PPI triangles have ~20 times higher overlap with MIPS complexes than using second-level neighbors in PPINs without SDDIs. The biological interpretation for triangles is that a SDDI causes two proteins to be observed with common interaction partners in high-throughput experiments. The relatively few SDDIs overlapping with PPINs are part of highly connected SDDI components, and are more likely to be detected in experimental studies. We demonstrate the utility of PPI-SDDI-PPI triangles by reconstructing myosin-actin processes in the nucleus, cytoplasm, and cytoskeleton, which were not obvious in the original PPIN. Using other complementary datatypes in place of SDDIs to form triangles, such as PubMed co-occurrences or threading information, results in a similar ability to find protein complexes. Conclusion Given high-error PPINs with missing information, triangles of mixed datatypes are a promising direction for finding protein complexes. Integrating PPINs with SDDIs improves finding complexes. Structural SDDIs partially explain the high functional similarity of second-level neighbors in PPINs. We estimate that relatively little structural information would be sufficient for finding complexes involving most of the proteins and interactions in a typical PPIN. PMID:19558694

  14. 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.

  15. 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.

  16. Towards a Predictive Model for Opal Exploration using a Spatio-temporal Data Mining Approach

    E-print Network

    Müller, Dietmar

    Towards a Predictive Model for Opal Exploration using a Spatio-temporal Data Mining Approach Andrew exploration using a powerful data mining ap- proach, which considers almost the entire Great Artesian Basin-f). By combining these data sets as layers enabling spatio-temporal data mining using the GPlates PaleoGIS software

  17. Predicting BCI Subject Performance Using Probabilistic Spatio-Temporal Filters

    PubMed Central

    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 ? - or ? -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. PMID:24551050

  18. Decentralized Data Fusion and Active Sensing with Mobile Sensors for Modeling and Predicting Spatiotemporal Traffic Phenomena

    E-print Network

    Jaillet, Patrick

    The problem of modeling and predicting spatiotemporal traffic phenomena over an urban road network is important to many traffic applications such as detecting and forecasting congestion hotspots. This paper presents a ...

  19. Spatio-Temporal Meme Prediction: Learning What Hashtags Will Be Popular Where

    E-print Network

    Caverlee, James

    Spatio-Temporal Meme Prediction: Learning What Hashtags Will Be Popular Where Krishna Y. Kamath of predicting what online memes will be popular in what locations. Specif- ically, we develop data on the problem of predicting what online memes will be popular in what locations, which has Permission to make

  20. Panda: A Predictive Spatio-Temporal Query Processor Abdeltawab M. Hendawi Mohamed F. Mokbel

    E-print Network

    Minnesota, University of

    Panda: A Predictive Spatio-Temporal Query Processor Abdeltawab M. Hendawi Mohamed F. Mokbel, mokbel}@cs.umn.edu ABSTRACT This paper presents the Panda system for efficient support of a wide variety, Panda targets long-term query prediction as it relies on adapting a well-designed long-term prediction

  1. Plant Protein-Protein Interaction Network and Interactome

    PubMed Central

    Zhang, Yixiang; Gao, Peng; Yuan, Joshua S

    2010-01-01

    Protein-protein interaction network represents an important aspect of systems biology. The understanding of the plant protein-protein interaction network and interactome will provide crucial insights into the regulation of plant developmental, physiological, and pathological processes. In this review, we will first define the concept of plant interactome and the protein-protein interaction network. The significance of the plant interactome study will be discussed. We will then compare the pros and cons for different strategies for interactome mapping including yeast two-hybrid system (Y2H), affinity purification mass spectrometry (AP-MS), bimolecular fluorescence complementation (BiFC), and in silico prediction. The application of these platforms on specific plant biology questions will be further discussed. The recent advancements revealed the great potential for plant protein-protein interaction network and interactome to elucidate molecular mechanisms for signal transduction, stress responses, cell cycle control, pattern formation, and others. Mapping the plant interactome in model species will provide important guideline for the future study of plant biology. PMID:20808522

  2. From link-prediction in brain connectomes and protein interactomes to the local-community-paradigm in complex networks

    PubMed Central

    Cannistraci, Carlo Vittorio; Alanis-Lobato, Gregorio; Ravasi, Timothy

    2013-01-01

    Growth and remodelling impact the network topology of complex systems, yet a general theory explaining how new links arise between existing nodes has been lacking, and little is known about the topological properties that facilitate link-prediction. Here we investigate the extent to which the connectivity evolution of a network might be predicted by mere topological features. We show how a link/community-based strategy triggers substantial prediction improvements because it accounts for the singular topology of several real networks organised in multiple local communities - a tendency here named local-community-paradigm (LCP). We observe that LCP networks are mainly formed by weak interactions and characterise heterogeneous and dynamic systems that use self-organisation as a major adaptation strategy. These systems seem designed for global delivery of information and processing via multiple local modules. Conversely, non-LCP networks have steady architectures formed by strong interactions, and seem designed for systems in which information/energy storage is crucial. PMID:23563395

  3. 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

  4. 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.

  5. Epileptic Seizure Prediction by Exploiting Spatiotemporal Relationship of EEG Signals Using Phase Correlation.

    PubMed

    Parvez, Mohammad Zavid; Paul, Manoranjan

    2016-01-01

    Automated seizure prediction has a potential in epilepsy monitoring, diagnosis, and rehabilitation. Electroencephalogram (EEG) is widely used for seizure detection and prediction. This paper proposes a new seizure prediction approach based on spatiotemporal relationship of EEG signals using phase correlation. This measures the relative change between current and reference vectors of EEG signals which can be used to identify preictal/ictal (before the actual seizure onset/ actual seizure period) and interictal (period between adjacent seizures) EEG signals to predict the seizure. The experiments show that the proposed method is less sensitive to artifacts and provides higher prediction accuracy (i.e., 91.95%) and lower number of false alarms compared to the state-of-the-art methods using intracranial EEG signals in different brain locations of 21 patients from a benchmark data set. PMID:26208360

  6. 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 ?m. 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. PMID:26536256

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

    E-print Network

    2009-12-03

    Prot, 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...

  8. Viruses and Interactomes in Translation*

    PubMed Central

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

    2012-01-01

    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. PMID:22371486

  9. 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 (1,1). In addition, the combined analysis of the prediction of IHD hospital admissions and the general hospital distributions shows that Pingshan and Longgang might experience the most serious burden of IHD hospital services in the near future, although Futian would still have the greatest number and the highest incidence rate of hospital admissions for IHD. PMID:24806191

  10. 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-runoff models, indicating their potential for reducing flood damage through real-time control.

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

    NASA Astrophysics Data System (ADS)

    Nowosad, Jakub

    2015-10-01

    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.

  12. Multi-Sensor Spatio-Temporal Vector Prediction History Tree (V-PHT) Model for Error Correction

    E-print Network

    Jagannatham, Aditya K.

    correlation in sensor data arising out of geographical proximity of the sensor nodes. Towards this endMulti-Sensor Spatio-Temporal Vector Prediction History Tree (V-PHT) Model for Error Correction in Wireless Sensor Networks Aman Jaiswal Electrical Engineering Department Indian Institute of Technology

  13. Neurobiological Mechanisms Behind the Spatiotemporal Illusions of Awareness Used for Advocating Prediction or Postdiction

    PubMed Central

    Bachmann, Talis

    2013-01-01

    The fact that it takes time for the brain to process information from the changing environment underlies many experimental phenomena of awareness of spatiotemporal events, including a number of astonishing illusions. These phenomena have been explained from the predictive and postdictive theoretical perspectives. Here I describe the most extensively studied phenomena in order to see how well the two perspectives can explain them. Next, the neurobiological perceptual retouch mechanism of producing stimulation awareness is characterized and its work in causing the listed illusions is described. A perspective on how brain mechanisms of conscious perception produce the phenomena supportive of the postdictive view is presented in this article. At the same time, some of the phenomena cannot be explained by the traditional postdictive account, but can be interpreted from the perceptual retouch theory perspective. PMID:23293625

  14. 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

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

    PubMed

    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

  16. 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

  17. Predicting gross primary production with high spatio-temporal resolution remote sensing datasets at regional scale

    NASA Astrophysics Data System (ADS)

    Fu, D.; Chen, B.

    2012-04-01

    Remote sensing has great potential for estimating gross primary production (GPP) without resorting to interpolation of many surface observations. Meanwhile, it can be applied to analyzing the variation of GPP at different ecosystems across a wide range of spatial, temporal, and spectral resolutions. However, the availability of input data for remote-sensing-based GPP models is the bottleneck. The input data of remote-sensing-based greenness and radiation (GR) model is more independent on climate or ground-based observations, and the result is promising. Previous work using this modeling approach only used coarse spatial resolution data (e.g. MODerate resolution Imaging Spectroradiometer, MODIS), the estimated spatio-temporal distributions of GPP with higher resolution remains unclear. To overcome this limitation, a modified image fusion method was developed based on Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (mESTARFM), producing images with high spatial and temporal resolutions based on Landsat Thematic Mapper (TM) / Enhanced TM Plus (ETM+) (high spatial resolution, low temporal resolution) and MODIS (low spatial resolution, high temporal resolution). Meanwhile, the Simple Analytical Footprint model on Eulerian coordinates (SAFE) model to estimate the flux tower's footprint, which will be helpful for GR model's calibration, and improve the accuracy of GPP estimate. In the study, twelve flux sites belonging to Fluxnet-Canada Research Network (FCRN)/Canadian Carbon Program (CCP) were selected, covering grassland, forest, and wetland biomes. The remote sensing dataset acquired in this study for each site include MODIS reflectance product (MOD09A1, 500 m), Landsat TM /ETM+ (30 m), MODIS BRDF/ Albedo model parameter product (MCD43A1, 500 m), MODIS BRDF/ Albedo quality product (MCD43A2, 500 m). The steps are as follows:: (i) Landsat TM /ETM+ and MODIS data were used as mESTARFM inputs to produce reflectance datasets with high spatio-temporal resolution; (ii) the estimated GPP is produced by GR model using available reflectance data with high spatial resolution; (iii) the GR model's calibration process is done combined with SAFE model's pure footprint result and the observations of flux sites; (iv) the spatio-temporal distribution of GPP values at regional scale are predicted with specific parameters correspond to different ecosystem.

  18. 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

  19. 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.

  20. Interactome analysis brings splicing into focus

    E-print Network

    Dominguez, Daniel

    The spliceosome is a huge molecular machine that assembles dynamically onto its pre-mRNA substrates. A new study based on interactome analysis provides clues about how splicing-regulatory proteins modulate assembly of the ...

  1. Information Flow Analysis of Interactome Networks

    E-print Network

    Liu, Kesheng

    Recent studies of cellular networks have revealed modular organizations of genes and proteins. For example, in interactome networks, a module refers to a group of interacting proteins that form molecular complexes and/or ...

  2. Predicting the spatiotemporal dynamics of hair follicle patterns in the developing mouse

    PubMed Central

    Cheng, Chi Wa; Niu, Ben; Warren, Mya; Pevny, Larysa Halyna; Lovell-Badge, Robin; Hwa, Terence; Cheah, Kathryn S. E.

    2014-01-01

    Reaction–diffusion models have been used as a paradigm for describing the de novo emergence of biological patterns such as stripes and spots. In many organisms, these initial patterns are typically refined and elaborated over the subsequent course of development. Here we study the formation of secondary hair follicle patterns in the skin of developing mouse embryos. We used the expression of sex-determining region Y box 2 to identify and distinguish the primary and secondary hair follicles and to infer the spatiotemporal dynamics of the follicle formation process. Quantitative analysis of the specific follicle patterns observed reveals a simple geometrical rule governing the formation of secondary follicles, and motivates an expansion–induction (EI) model in which new follicle formation is driven by the physical growth of the embryo. The EI model requires only one diffusible morphogen and provides quantitative, accurate predictions on the relative positions and timing of secondary follicle formation, using only the observed configuration of primary follicles as input. The same model accurately describes the positions of additional follicles that emerge from skin explants treated with an activator. Thus, the EI model provides a simple and robust mechanism for predicting secondary space-filling patterns in growing embryos. PMID:24550288

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

    PubMed Central

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

    2014-01-01

    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

  4. 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.

  5. 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. PMID:25700523

  6. An instantaneous spatiotemporal model to predict a bicyclist's Black Carbon exposure based on mobile noise measurements

    NASA Astrophysics Data System (ADS)

    Dekoninck, Luc; Botteldooren, Dick; Int Panis, Luc

    2013-11-01

    Several studies have shown that a significant amount of daily air pollution exposure, in particular Black Carbon (BC), is inhaled during trips. Assessing this contribution to exposure remains difficult because on the one hand local air pollution maps lack spatio-temporal resolution, at the other hand direct measurement of particulate matter concentration remains expensive. This paper proposes to use in-traffic noise measurements in combination with geographical and meteorological information for predicting BC exposure during commuting trips. Mobile noise measurements are cheaper and easier to perform than mobile air pollution measurements and can easily be used in participatory sensing campaigns. The uniqueness of the proposed model lies in the choice of noise indicators that goes beyond the traditional overall A-weighted noise level used in previous work. Noise and BC exposures are both related to the traffic intensity but also to traffic speed and traffic dynamics. Inspired by theoretical knowledge on the emission of noise and BC, the low frequency engine related noise and the difference between high frequency and low frequency noise that indicates the traffic speed, are introduced in the model. In addition, it is shown that splitting BC in a local and a background component significantly improves the model. The coefficients of the proposed model are extracted from 200 commuter bicycle trips. The predicted average exposure over a single trip correlates with measurements with a Pearson coefficient of 0.78 using only four parameters: the low frequency noise level, wind speed, the difference between high and low frequency noise and a street canyon index expressing local air pollution dispersion properties.

  7. Inferring modules from human protein interactome classes

    PubMed Central

    2010-01-01

    Background The integration of protein-protein interaction networks derived from high-throughput screening approaches and complementary sources is a key topic in systems biology. Although integration of protein interaction data is conventionally performed, the effects of this procedure on the result of network analyses has not been examined yet. In particular, in order to optimize the fusion of heterogeneous interaction datasets, it is crucial to consider not only their degree of coverage and accuracy, but also their mutual dependencies and additional salient features. Results We examined this issue based on the analysis of modules detected by network clustering methods applied to both integrated and individual (disaggregated) data sources, which we call interactome classes. Due to class diversity, we deal with variable dependencies of data features arising from structural specificities and biases, but also from possible overlaps. Since highly connected regions of the human interactome may point to potential protein complexes, we have focused on the concept of modularity, and elucidated the detection power of module extraction algorithms by independent validations based on GO, MIPS and KEGG. From the combination of protein interactions with gene expressions, a confidence scoring scheme has been proposed before proceeding via GO with further classification in permanent and transient modules. Conclusions Disaggregated interactomes are shown to be informative for inferring modularity, thus contributing to perform an effective integrative analysis. Validation of the extracted modules by multiple annotation allows for the assessment of confidence measures assigned to the modules in a protein pathway context. Notably, the proposed multilayer confidence scheme can be used for network calibration by enabling a transition from unweighted to weighted interactomes based on biological evidence. PMID:20653930

  8. 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.

  9. 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 temperature suitability data developed here will be essential for the rational assessment of changing patterns of malaria risk. PMID:24886586

  10. Identification of SRC as a potent drug target for asthma, using an integrative approach of protein interactome analysis and in silico drug discovery.

    PubMed

    Randhawa, Vinay; Bagler, Ganesh

    2012-10-01

    Network-biology inspired modeling of interactome data and computational chemistry have the potential to revolutionize drug discovery by complementing conventional methods. We consider asthma, a complex disease characterized by intricate molecular mechanisms, for our study. We aim to integrate prediction of potent drug targets using graph-theoretical methods and subsequent identification of small molecules capable of modulating activity of the best target. In this work, we construct the protein interactome underlying this disease: Asthma Protein Interactome (API). Using a strategy based on network analysis of the interactome, we identify a set of potential drug targets for asthma. Topologically and dynamically, v-src sarcoma (Schmidt-Ruppin A-2) viral oncogene homolog (SRC) emerges as the most central target in API. SRC is known to play an important role in promoting airway smooth muscle cell growth and facilitating migration in airway remodeling. From interactome analysis, and with the reported role in respiratory mechanisms, SRC emerges as a promising drug target for asthma. Further, we proceed to identify leads for SRC from a public database of small molecules. We predict two potential leads for SRC using ligand-based virtual screening methodology. PMID:22775150

  11. 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. PMID:26442112

  12. AIM: a comprehensive Arabidopsis interactome module database and related interologs in plants.

    PubMed

    Wang, Yi; Thilmony, Roger; Zhao, Yunjun; Chen, Guoping; Gu, Yong Q

    2014-01-01

    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 that were generated using multiple analysis methods and integration of microarray expression data. All the modules in AIM are well annotated using multiple gene function knowledge databases. AIM provides a user-friendly interface for different types of searches and offers a powerful graphical viewer for displaying module networks linked to the enrichment annotation terms. Both interactive Venn diagram and power graph viewer are integrated into the database for easy comparison of modules. In addition, predicted interologs from other plant species (homologous proteins from different species that share a conserved interaction module) are available for each Arabidopsis module. AIM is a powerful systems biology platform for obtaining valuable insights into the function of proteins in Arabidopsis and other plants using the modules of the Arabidopsis interactome. Database URL:http://probes.pw.usda.gov/AIM PMID:25480687

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

    PubMed Central

    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. PMID:26442112

  14. 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

  15. 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

  16. Using Genetic Programming to Learn Predictive Models from Spatio-Temporal Data

    E-print Network

    Fernandez, Thomas

    's course through a network of CCTV cameras. This thesis also describes the incorporation of qualitative on the card game Uno, and predicting a person's course through a network of CCTV cam- eras. This work a person's course through a network of CCTV cameras, aircraft turnarounds, and the game of Tic Tac Toe

  17. 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 3DCityDB incorporating a PostgreSQL geo-database is used to manage and manipulate 3D data and their semantics.

  18. Two-dimensional transient model for prediction of arteriolar NO/O2 modulation by spatiotemporal variations in cell-free layer width.

    PubMed

    Ng, Yan Cheng; Namgung, Bumseok; Kim, Sangho

    2015-01-01

    Despite the significant roles of the cell-free layer (CFL) in balancing nitric oxide (NO) and oxygen (O2) bioavailability in arteriolar tissue, many previous numerical approaches have relied on a one-dimensional (1-D) steady-state model for simplicity. However, these models are unable to demonstrate the influence of spatiotemporal variations in the CFL on the NO/O2 transport under dynamic flow conditions. Therefore, the present study proposes a new two-dimensional (2-D) transient model capable of predicting NO/O2 transport modulated by the spatiotemporal variations in the CFL width. Our model predicted that NO bioavailability was inversely related to the CFL width as expected. The enhancement of NO production by greater wall shear stress with a thinner CFL could dominate the diffusion barrier role of the CFL. In addition, NO/O2 availability along the vascular wall was inhomogeneous and highly regulated by dynamic changes of local CFL width variation. The spatial variations of CFL widths on opposite sides of the arteriole exhibited a significant inverse relation. This asymmetric formation of CFL resulted in a significantly imbalanced NO/O2 bioavailability on opposite sides of the arteriole. The novel integrative methodology presented here substantially highlighted the significance of spatiotemporal variations of the CFL in regulating the bioavailability of NO/O2, and provided further insight about the opposing effects of the CFL on arteriolar NO production. PMID:25312045

  19. 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 the observed variability, whereas a linear combination of environmental variables is able to do so. By further comparing environmental processes associated with the spatiotemporal variability of NEE from the observations and from each TBM, we find that TBMs perform well when radiation-related processes are dominant; however, TBMs perform less well when water-availability (and temperature) are more important. It thus appears that the representation of water availability and its impact on fluxes within TBMs are areas of opportunity for improving TBM predictions, for example, in the seasonal transition. Further exploration of the processes associated with water availability in state-of-the-art TBMs, such as soil respiration, could therefore lead to improvements in their ability to represent the spatiotemporal variability of fluxes during the dormant season and their ability to represent phenology and carbon exchange during transition months.

  20. Spatio-Temporal Asynchronous Co-Occurrence Pattern for Big Climate Data towards Long-Lead Flood Prediction

    E-print Network

    Ding, Wei

    Spatio-Temporal Asynchronous Co-Occurrence Pattern for Big Climate Data towards Long-Lead Flood floods 5 to 15 days in advance. Current simulation models forecasting heavy precipitation, a major factor related with flood occurrences, are computationally ex- pensive and limited by their error amplification

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

    PubMed Central

    Rolland, Thomas; Ta?an, 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

  2. Hierarchical modularity and the evolution of genetic interactomes across species.

    PubMed

    Ryan, Colm J; Roguev, Assen; Patrick, Kristin; Xu, Jiewei; Jahari, Harlizawati; Tong, Zongtian; Beltrao, Pedro; Shales, Michael; Qu, Hong; Collins, Sean R; Kliegman, Joseph I; Jiang, Lingli; Kuo, Dwight; Tosti, Elena; Kim, Hyun-Soo; Edelmann, Winfried; Keogh, Michael-Christopher; Greene, Derek; Tang, Chao; Cunningham, Pádraig; Shokat, Kevan M; Cagney, Gerard; Svensson, J Peter; Guthrie, Christine; Espenshade, Peter J; Ideker, Trey; Krogan, Nevan J

    2012-06-01

    To date, cross-species comparisons of genetic interactomes have been restricted to small or functionally related gene sets, limiting our ability to infer evolutionary trends. To facilitate a more comprehensive analysis, we constructed a genome-scale epistasis map (E-MAP) for the fission yeast Schizosaccharomyces pombe, providing phenotypic signatures for ~60% of the nonessential genome. Using these signatures, we generated a catalog of 297 functional modules, and we assigned function to 144 previously uncharacterized genes, including mRNA splicing and DNA damage checkpoint factors. Comparison with an integrated genetic interactome from the budding yeast Saccharomyces cerevisiae revealed a hierarchical model for the evolution of genetic interactions, with conservation highest within protein complexes, lower within biological processes, and lowest between distinct biological processes. Despite the large evolutionary distance and extensive rewiring of individual interactions, both networks retain conserved features and display similar levels of functional crosstalk between biological processes, suggesting general design principles of genetic interactomes. PMID:22681890

  3. Next-Generation Technologies for Multiomics Approaches Including Interactome Sequencing

    PubMed Central

    Ohashi, Hiroyuki; Miyamoto-Sato, Etsuko

    2015-01-01

    The development of high-speed analytical techniques such as next-generation sequencing and microarrays allows high-throughput analysis of biological information at a low cost. These techniques contribute to medical and bioscience advancements and provide new avenues for scientific research. Here, we outline a variety of new innovative techniques and discuss their use in omics research (e.g., genomics, transcriptomics, metabolomics, proteomics, and interactomics). We also discuss the possible applications of these methods, including an interactome sequencing technology that we developed, in future medical and life science research. PMID:25649523

  4. 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.

  5. Identification of the Interactome of a Palmitoylated Membrane Protein, Phosphatidylinositol 4-Kinase Type II Alpha.

    PubMed

    Gokhale, Avanti; Ryder, Pearl V; Zlatic, Stephanie A; Faundez, Victor

    2016-01-01

    Phosphatidylinositol 4-kinases (PI4K) are enzymes responsible for the production of phosphatidylinositol 4-phosphates, important intermediates in several cell signaling pathways. PI4KII? is the most abundant membrane-associated kinase in mammalian cells and is involved in a variety of essential cellular functions. However, the precise role(s) of PI4KII? in the cell is not yet completely deciphered. Here we present an experimental protocol that uses a chemical cross-linker, DSP, combined with immunoprecipitation and immunoaffinity purification to identify novel PI4KII? interactors. As predicted, PI4KII? participates in transient, low-affinity interactions that are stabilized by the use of DSP. Using this optimized protocol we have successfully identified actin cytoskeleton regulators-the WASH complex and RhoGEF1, as major novel interactors of PI4KII?. While this chapter focuses on the PI4KII? interactome, this protocol can and has been used to generate other membrane interactome networks. PMID:26552673

  6. ?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. PMID:26618866

  7. 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

  8. Charting the NF-?B 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 ?B (NF-?B) 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-?B 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-?B 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-?B activation system. Such a reconstruction shows that the NF-?B 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-?B 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

  9. Charting the NF-?B 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 ?B (NF-?B) 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-?B 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-?B 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-?B activation system. Such a reconstruction shows that the NF-?B 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-?B 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

  10. 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 application of HJ-1A/1B CCD images, and data and methods for productivity study of rubber plantation in future.

  11. A comparative study of disease genes and drug targets in the human protein interactome

    PubMed Central

    2015-01-01

    Background Disease genes cause or contribute genetically to the development of the most complex diseases. Drugs are the major approaches to treat the complex disease through interacting with their targets. Thus, drug targets are critical for treatment efficacy. However, the interrelationship between the disease genes and drug targets is not clear. Results In this study, we comprehensively compared the network properties of disease genes and drug targets for five major disease categories (cancer, cardiovascular disease, immune system disease, metabolic disease, and nervous system disease). We first collected disease genes from genome-wide association studies (GWAS) for five disease categories and collected their corresponding drugs based on drugs' Anatomical Therapeutic Chemical (ATC) classification. Then, we obtained the drug targets for these five different disease categories. We found that, though the intersections between disease genes and drug targets were small, disease genes were significantly enriched in targets compared to their enrichment in human protein-coding genes. We further compared network properties of the proteins encoded by disease genes and drug targets in human protein-protein interaction networks (interactome). The results showed that the drug targets tended to have higher degree, higher betweenness, and lower clustering coefficient in cancer Furthermore, we observed a clear fraction increase of disease proteins or drug targets in the near neighborhood compared with the randomized genes. Conclusions The study presents the first comprehensive comparison of the disease genes and drug targets in the context of interactome. The results provide some foundational network characteristics for further designing computational strategies to predict novel drug targets and drug repurposing. PMID:25861037

  12. Quality of video affected by packet loss distortion compared to the predictions of a spatio-temporal model

    NASA Astrophysics Data System (ADS)

    Brunnstrom, Kjell E.; Schenkman, Bo N.

    2002-06-01

    Image quality of images as judged by human observers may be determined by different simulation models. The results of an image discrimination model is discussed and compared to the results of the peak signal-to-noise ratio. The image discrimination model simulates how people analyze spatial-temporal information and it predicts detection of distortion. Peak signal-to-noise ratio measures the physical difference between an original and a distorted image sequence. To test if the model could without modifications be used to predict image quality in small moving images, a perceptual experiment was carried out with ten observers. Image quality judgments were measured with five different video scenes using eight category scales and magnitude estimations. Packet loss of transmissions was simulated for two H.263 coders, one with two layers and one with only one layer. The reliability of the judgments was generally high. The judged image quality depended on type of scene and coder. There was a strong inter-correlation between the category scales. Both magnitude estimations of image quality and ratings of a category scale for image quality could to some extent be predicted by the model, but there were no advantages for the visual model.

  13. Dissecting noncoding and pathogen RNA-protein interactomes.

    PubMed

    Flynn, Ryan A; Martin, Lance; Spitale, Robert C; Do, Brian T; Sagan, Selena M; Zarnegar, Brian; Qu, Kun; Khavari, Paul A; Quake, Stephen R; Sarnow, Peter; Chang, Howard Y

    2015-01-01

    RNA-protein interactions are central to biological regulation. Cross-linking immunoprecipitation (CLIP)-seq is a powerful tool for genome-wide interrogation of RNA-protein interactomes, but current CLIP methods are limited by challenging biochemical steps and fail to detect many classes of noncoding and nonhuman RNAs. Here we present FAST-iCLIP, an integrated pipeline with improved CLIP biochemistry and an automated informatic pipeline for comprehensive analysis across protein coding, noncoding, repetitive, retroviral, and nonhuman transcriptomes. FAST-iCLIP of Poly-C binding protein 2 (PCBP2) showed that PCBP2-bound CU-rich motifs in different topologies to recognize mRNAs and noncoding RNAs with distinct biological functions. FAST-iCLIP of PCBP2 in hepatitis C virus-infected cells enabled a joint analysis of the PCBP2 interactome with host and viral RNAs and their interplay. These results show that FAST-iCLIP can be used to rapidly discover and decipher mechanisms of RNA-protein recognition across the diversity of human and pathogen RNAs. PMID:25411354

  14. Dissecting noncoding and pathogen RNA–protein interactomes

    PubMed Central

    Flynn, Ryan A.; Martin, Lance; Spitale, Robert C.; Do, Brian T.; Sagan, Selena M.; Zarnegar, Brian; Qu, Kun; Khavari, Paul A.; Quake, Stephen R.; Sarnow, Peter

    2015-01-01

    RNA–protein interactions are central to biological regulation. Cross-linking immunoprecipitation (CLIP)-seq is a powerful tool for genome-wide interrogation of RNA–protein interactomes, but current CLIP methods are limited by challenging biochemical steps and fail to detect many classes of noncoding and nonhuman RNAs. Here we present FAST-iCLIP, an integrated pipeline with improved CLIP biochemistry and an automated informatic pipeline for comprehensive analysis across protein coding, noncoding, repetitive, retroviral, and nonhuman transcriptomes. FAST-iCLIP of Poly-C binding protein 2 (PCBP2) showed that PCBP2-bound CU-rich motifs in different topologies to recognize mRNAs and noncoding RNAs with distinct biological functions. FAST-iCLIP of PCBP2 in hepatitis C virus-infected cells enabled a joint analysis of the PCBP2 interactome with host and viral RNAs and their interplay. These results show that FAST-iCLIP can be used to rapidly discover and decipher mechanisms of RNA–protein recognition across the diversity of human and pathogen RNAs. PMID:25411354

  15. Predicted spatio-temporal dynamics of radiocesium deposited on forests following the Fukushima Dai-ichi nuclear power plant accident

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

    Radiocesium (134Cs and 137Cs) released from the Fukushima Dai-ichi nuclear power plant to the atmosphere contaminated a large area of Japan's land surface, the majority of which is covered by forest. Here we simulated the dynamics of radiocesium deposited on Japanese forest ecosystems in 2011 using a model that was developed for tracking radionuclides in forest ecosystems after the Chernobyl accident in 1986. The fate of the radiocesium was simulated using the initial conditions observed following the Fukushima accident. In addition, the simulation results were incorporated with a spatial distribution map of deposited radionuclides that was based on an air-borne survey. The simulation demonstrated that in the first two years after initial deposition radiocesium is retained primarily in the soil surface organic layer. Over a period of five to ten years radiocesium is predicted to move from the surface organic soil to the deeper mineral soil, which will eventually become the largest reservoir of radiocesium within forest ecosystems. Spatial analysis clearly shows the reduction in the extent of contaminated areas which will occur as a result of natural decay of radiocesium, as well as the spatial distribution of radiocesium in each forest component. Considering the heavier rainfall and warmer conditions in Japan than in the countries contaminated by the Chernobyl accident, migration of radiocesium from organic to mineral soil may be faster than predicted. Although the uncertainty of our simulations should be taken into account, they provide a basis for understanding and anticipating the future dynamics of radiocesium in Japanese forests following the Fukushima accident.

  16. 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...

  17. 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.

  18. The red blood cell proteome and interactome: an update.

    PubMed

    D'Alessandro, Angelo; Righetti, Pier Giorgio; Zolla, Lello

    2010-01-01

    Although a preliminary portrait of the red blood cell proteome and interactome has already been provided, the recent identification of 1578 gene products from the erythrocyte cytosol asks for an updated and improved view. In this paper, we exploit data available from recent literature to compile a nonredundant list of 1989 proteins and elaborate it with pathway and network analyses. Upon network analysis, it is intuitively confirmed that red blood cells likely suffer of exacerbated oxidative stress and continuously strive against protein and cytoskeletal damage. It also emerges that erythrocyte interaction networks display a high degree of maturity. Indeed, a series of core proteins were individuated to play a central role. A catalytic ring of proteins counteracting oxidative stress was individuated as well. In parallel, pathway analysis confirmed the validity of observations about the SEC23B gene role in CDA II in a fast and unbiased way. PMID:19886704

  19. 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

  20. 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. PMID:24501395

  1. Calciomics: integrative studies of Ca2+-binding proteins and their interactomes in biological systems

    PubMed Central

    Zhou, Yubin; Xue, Shenghui; Yang, Jenny J.

    2013-01-01

    Calcium ion (Ca2+), the fifth most common chemical element in the earth’s crust, represents the most abundant mineral in the human body. By binding to a myriad of proteins distributed in different cellular organelles, Ca2+ impacts nearly every aspect of cellular life. In prokaryotes, Ca2+ plays an important role in bacterial movement, chemotaxis, survival reactions and sporulation. In eukaryotes, Ca2+ has been chosen through evolution to function as a universal and versatile intracellular signal. Viruses, as obligate intracellular parasites, also develop smart strategies to manipulate the host Ca2+ signaling machinery to benefit their own life cycles. This review focuses on recent advances in applying both bioinformatic and experimental approaches to predict and validate Ca2+-binding proteins and their interactomes in biological systems on genome-wide scale (termed “calciomics”). Calmodulin is used as an example of Ca2+-binding protein (CaBP) to demonstrate the role of CaBPs on the regulation of biological functions. This review is anticipated to rekindle interest in investigating Ca2+-binding proteins and Ca2+-modulated functions at the systems level in the post-genomic era. PMID:23235533

  2. Exploring bacterial organelle interactomes: a model of the protein-protein interaction network in the Pdu microcompartment.

    PubMed

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

    2015-02-01

    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 ?-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

  3. 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 ?-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

  4. Computational polypharmacology analysis of the heat shock protein 90 interactome.

    PubMed

    Anighoro, Andrew; Stumpfe, Dagmar; Heikamp, Kathrin; Beebe, Kristin; Neckers, Leonard M; Bajorath, Jürgen; Rastelli, Giulio

    2015-03-23

    The design of a single drug molecule that is able to simultaneously and specifically interact with multiple biological targets is gaining major consideration in drug discovery. However, the rational design of drugs with a desired polypharmacology profile is still a challenging task, especially when these targets are distantly related or unrelated. In this work, we present a computational approach aimed at the identification of suitable target combinations for multitarget drug design within an ensemble of biologically relevant proteins. The target selection relies on the analysis of activity annotations present in molecular databases and on ligand-based virtual screening. A few target combinations were also inspected with structure-based methods to demonstrate that the identified dual-activity compounds are able to bind target combinations characterized by remote binding site similarities. Our approach was applied to the heat shock protein 90 (Hsp90) interactome, which contains several targets of key importance in cancer. Promising target combinations were identified, providing a basis for the computational design of compounds with dual activity. The approach may be used on any ensemble of proteins of interest for which known inhibitors are available. PMID:25686391

  5. Competing endogenous RNA and interactome bioinformatic analyses on human telomerase.

    PubMed

    Arancio, Walter; Pizzolanti, Giuseppe; Genovese, Swonild Ilenia; Baiamonte, Concetta; Giordano, Carla

    2014-04-01

    We present a classic interactome bioinformatic analysis and a study on competing endogenous (ce) RNAs for hTERT. The hTERT gene codes for the catalytic subunit and limiting component of the human telomerase complex. Human telomerase reverse transcriptase (hTERT) is essential for the integrity of telomeres. Telomere dysfunctions have been widely reported to be involved in aging, cancer, and cellular senescence. The hTERT gene network has been analyzed using the BioGRID interaction database (http://thebiogrid.org/) and related analysis tools such as Osprey (http://biodata.mshri.on.ca/osprey/servlet/Index) and GeneMANIA (http://genemania.org/). The network of interaction of hTERT transcripts has been further analyzed following the competing endogenous (ce) RNA hypotheses (messenger [m] RNAs cross-talk via micro [mi] RNAs) using the miRWalk database and tools (www.ma.uni-heidelberg.de/apps/zmf/mirwalk/). These analyses suggest a role for Akt, nuclear factor-?B (NF-?B), heat shock protein 90 (HSP90), p70/p80 autoantigen, 14-3-3 proteins, and dynein in telomere functions. Roles for histone acetylation/deacetylation and proteoglycan metabolism are also proposed. PMID:24713059

  6. 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

  7. Transcriptional atlas of cardiogenesis maps congenital heart disease interactome

    PubMed Central

    Li, Xing; Martinez-Fernandez, Almudena; Hartjes, Katherine A.; Kocher, Jean-Pierre A.; Olson, Timothy M.; Terzic, Andre

    2014-01-01

    Mammalian heart development is built on highly conserved molecular mechanisms with polygenetic perturbations resulting in a spectrum of congenital heart diseases (CHD). However, knowledge of cardiogenic ontogeny that regulates proper cardiogenesis remains largely based on candidate-gene approaches. Mapping the dynamic transcriptional landscape of cardiogenesis from a genomic perspective is essential to integrate the knowledge of heart development into translational applications that accelerate disease discovery efforts toward mechanistic-based treatment strategies. Herein, we designed a time-course transcriptome analysis to investigate the genome-wide dynamic expression landscape of innate murine cardiogenesis ranging from embryonic stem cells to adult cardiac structures. This comprehensive analysis generated temporal and spatial expression profiles, revealed stage-specific gene functions, and mapped the dynamic transcriptome of cardiogenesis to curated pathways. Reconciling known genetic underpinnings of CHD, we deconstructed a disease-centric dynamic interactome encoded within this cardiogenic atlas to identify stage-specific developmental disturbances clustered on regulation of epithelial-to-mesenchymal transition (EMT), BMP signaling, NF-AT signaling, TGFb-dependent EMT, and Notch signaling. Collectively, this cardiogenic transcriptional landscape defines the time-dependent expression of cardiac ontogeny and prioritizes regulatory networks at the interface between health and disease. PMID:24803680

  8. Exploring a Structural Protein-Drug Interactome for New Therapeutics in Lung Cancer

    PubMed Central

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

    2014-01-01

    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 (http://www.biodrugscreen.org) by scoring the interaction among 1,000 FDA-approved drugs docked to 2,500 pockets on protein structures of the human genome. This afforded a drug-target network whose properties compared favorably with previous networks constructed with experimental data. Among drugs with 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 possible association of exposure to three of these drugs with occurrence of lung cancer. Preliminary in vivo studies using 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 vehicle. These results set the stage for further exploration of these drugs and to uncover new drugs for lung cancer. PMID:24402119

  9. 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

  10. E V O L U T I O N Cross-Species Protein Interactome Mapping

    E-print Network

    Roth, Frederick

    , it is essential to construct a high-coverage interactome net- work for an intermediate species. The fission yeast,9,10,11,12,13 Haiyuan Yu1,2 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

  11. Improved Microarray-Based Decision Support with Graph Encoded Interactome Data

    E-print Network

    Improved Microarray-Based Decision Support with Graph Encoded Interactome Data Anneleen Daemen to improve the accuracy of diagnosis and prognosis in cancer. As prior knowledge, we investigated interaction pathways could be incorporated in a support vector machine classifier based on spectral graph theory. Using

  12. 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

  13. A Microtubule Interactome: Complexes with Roles in Cell Cycle and Mitosis

    E-print Network

    A Microtubule Interactome: Complexes with Roles in Cell Cycle and Mitosis Julian R. Hughes1[¤a of mitosis. These functions are coordinated by MT-associated proteins (MAPs), which work in concert with each regulation and mitosis. This study therefore demonstrates that biologically relevant data can be harvested

  14. A “Candidate-Interactome” Aggregate Analysis of Genome-Wide Association Data in Multiple Sclerosis

    PubMed Central

    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. PMID:23696811

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

    PubMed

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

    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

  16. Dynamic modularity in protein interaction networks predicts breast cancer outcome

    E-print Network

    Morris, Quaid

    Dynamic modularity in protein interaction networks predicts breast cancer outcome Ian W Taylor1 associated with oncogenesis. Analysis of two breast cancer patient cohorts revealed that altered modularity of the human interactome may be useful as an indicator of breast cancer prognosis. Transcriptome analyses have

  17. Vitamin C as Cancer Destroyer, Investigating Sulfhydration, and the Variability in CFTR Interactome.

    PubMed

    2015-12-17

    Each month, Chemistry & Biology Select highlights a selection of research reports from the recent literature. These highlights are a snapshot of interesting research done across the field of chemical biology. Our December 2015 selection includes an insight into how vitamin C destroys cancer cells, a new method that makes possible the investigatation of sulfhydration, and the mapping of the CFTR interactome and how it depends on the environmental conditions and differs between wild-type and disease-causing mutant. PMID:26687480

  18. Expression of DISC1-Interactome Members Correlates with Cognitive Phenotypes Related to Schizophrenia

    PubMed Central

    Rampino, Antonio; Walker, Rosie May; Torrance, Helen Scott; Anderson, Susan Maguire; Fazio, Leonardo; Di Giorgio, Annabella; Taurisano, Paolo; Gelao, Barbara; Romano, Raffaella; Masellis, Rita; Ursini, Gianluca; Caforio, Grazia; Blasi, Giuseppe; Millar, J. Kirsty; Porteous, David John; Thomson, Pippa Ann; Bertolino, Alessandro; Evans, Kathryn Louise

    2014-01-01

    Cognitive dysfunction is central to the schizophrenia phenotype. Genetic and functional studies have implicated Disrupted-in-Schizophrenia 1 (DISC1), a leading candidate gene for schizophrenia and related psychiatric conditions, in cognitive function. Altered expression of DISC1 and DISC1-interactors has been identified in schizophrenia. Dysregulated expression of DISC1-interactome genes might, therefore, contribute to schizophrenia susceptibility via disruption of molecular systems required for normal cognitive function. Here, the blood RNA expression levels of DISC1 and DISC1-interacting proteins were measured in 63 control subjects. Cognitive function was assessed using neuropsychiatric tests and functional magnetic resonance imaging was used to assess the activity of prefrontal cortical regions during the N-back working memory task, which is abnormal in schizophrenia. Pairwise correlations between gene expression levels and the relationship between gene expression levels and cognitive function and N-back-elicited brain activity were assessed. Finally, the expression levels of DISC1, AKAP9, FEZ1, NDEL1 and PCM1 were compared between 63 controls and 69 schizophrenic subjects. We found that DISC1-interactome genes showed correlated expression in the blood of healthy individuals. The expression levels of several interactome members were correlated with cognitive performance and N-back-elicited activity in the prefrontal cortex. In addition, DISC1 and NDEL1 showed decreased expression in schizophrenic subjects compared to healthy controls. Our findings highlight the importance of the coordinated expression of DISC1-interactome genes for normal cognitive function and suggest that dysregulated DISC1 and NDEL1 expression might, in part, contribute to susceptibility for schizophrenia via disruption of prefrontal cortex-dependent cognitive functions. PMID:24940743

  19. Interactome Mapping Reveals Important Pathways in Skeletal Muscle Development of Pigs

    PubMed Central

    Cao, Jianhua; Huang, Tinghua; Li, Xinyun; Zhao, Shuhong

    2014-01-01

    The regulatory relationship and connectivity among genes involved in myogenesis and hypertrophy of skeletal muscle in pigs still remain large challenges. Presentation of gene interactions is a potential way to understand the mechanisms of developmental events in skeletal muscle. In this study, genome-wide transcripts and miRNA profiling was determined for Landrace pigs at four time points using microarray chips. A comprehensive method integrating gene ontology annotation and interactome network mapping was conducted to analyze the biological patterns and interaction modules of muscle development events based on differentially expressed genes and miRNAs. Our results showed that in total 484 genes and 34 miRNAs were detected for the duration from embryonic stage to adult in pigs, which composed two linear expression patterns with consensus changes. Moreover, the gene ontology analysis also disclosed that there were three typical biological events i.e., microstructure assembly of sarcomere at early embryonic stage, myofibril formation at later embryonic stage and function establishments of myoblast cells at postnatal stage. The interactome mappings of different time points also found the down-regulated trend of gene expression existed across the whole duration, which brought a possibility to introduce the myogenesis related miRNAs into the interactome regulatory networks of skeletal muscle in pigs. PMID:25431924

  20. Comprehensive Identification of RNA-Binding Proteins by RNA Interactome Capture.

    PubMed

    Castello, Alfredo; Horos, Rastislav; Strein, Claudia; Fischer, Bernd; Eichelbaum, Katrin; Steinmetz, Lars M; Krijgsveld, Jeroen; Hentze, Matthias W

    2016-01-01

    RNA associates with RNA-binding proteins (RBPs) from synthesis to decay, forming dynamic ribonucleoproteins (RNPs). In spite of the preeminent role of RBPs regulating RNA fate, the scope of cellular RBPs has remained largely unknown. We have recently developed a novel and comprehensive method to identify the repertoire of active RBPs of cultured cells, called RNA interactome capture. Using in vivo UV cross-linking on cultured cells, proteins are covalently bound to RNA if the contact between the two is direct ("zero distance"). Protein-RNA complexes are purified by poly(A) tail-dependent oligo(dT) capture and analyzed by quantitative mass spectrometry. Because UV irradiation is applied to living cells and purification is performed using highly stringent washes, RNA interactome capture identifies physiologic and direct protein-RNA interactions. Applied to HeLa cells, this protocol revealed the near-complete repertoire of RBPs, including hundreds of novel RNA binders. Apart from its RBP discovery capacity, quantitative and comparative RNA interactome capture can also be used to study the responses of the RBP repertoire to different physiological cues and processes, including metabolic stress, differentiation, development, or the response to drugs. PMID:26463381

  1. Perturbation of the mutated EGFR interactome identifies vulnerabilities and resistance mechanisms

    PubMed Central

    Li, Jiannong; Bennett, Keiryn; Stukalov, Alexey; Fang, Bin; Zhang, Guolin; Yoshida, Takeshi; Okamoto, Isamu; Kim, Jae-Young; Song, Lanxi; Bai, Yun; Qian, Xiaoning; Rawal, Bhupendra; Schell, Michael; Grebien, Florian; Winter, Georg; Rix, Uwe; Eschrich, Steven; Colinge, Jacques; Koomen, John; Superti-Furga, Giulio; Haura, Eric B

    2013-01-01

    We hypothesized that elucidating the interactome of epidermal growth factor receptor (EGFR) forms that are mutated in lung cancer, via global analysis of protein–protein interactions, phosphorylation, and systematically perturbing the ensuing network nodes, should offer a new, more systems-level perspective of the molecular etiology. Here, we describe an EGFR interactome of 263 proteins and offer a 14-protein core network critical to the viability of multiple EGFR-mutated lung cancer cells. Cells with acquired resistance to EGFR tyrosine kinase inhibitors (TKIs) had differential dependence of the core network proteins based on the underlying molecular mechanisms of resistance. Of the 14 proteins, 9 are shown to be specifically associated with survival of EGFR-mutated lung cancer cell lines. This included EGFR, GRB2, MK12, SHC1, ARAF, CD11B, ARHG5, GLU2B, and CD11A. With the use of a drug network associated with the core network proteins, we identified two compounds, midostaurin and lestaurtinib, that could overcome drug resistance through direct EGFR inhibition when combined with erlotinib. Our results, enabled by interactome mapping, suggest new targets and combination therapies that could circumvent EGFR TKI resistance. PMID:24189400

  2. Wong L, Liu G. Protein interactome analysis for countering pathogen drug resistance. JOURNAL OF COMPUTER SCI-ENCE AND TECHNOLOGY 25(1): 1 Jan. 2010

    E-print Network

    Wong, Limsoon

    OF COMPUTER SCI- ENCE AND TECHNOLOGY 25(1): 1­ Jan. 2010 Protein Interactome Analysis for Countering Pathogen diseases, especially those that have spread globally, such as drug- resistant tuberculosis[1] . Approaches protein interactome of Mycobacterium tuberculosis is available. Then one can identify a mini- mal set

  3. Received 1 Nov 2012 | Accepted 4 Jul 2013 | Published 6 Aug 2013 Counting motifs in the human interactome

    E-print Network

    Zhang, Louxin

    unique to human beings5. As the number of genes alone does not fully characterize the biological-increasing pace, the human PPI and GRI networks are far from being complete and, hence, their dynamics have yet in the human interactome Ngoc Hieu Tran1, Kwok Pui Choi1,2 & Louxin Zhang2,3 Small over-represented motifs

  4. A human B-cell interactome identifies MYB and FOXM1 as master regulators of proliferation in germinal

    E-print Network

    Kaski, Samuel

    in germinal centers Celine Lefebvre1,2,3 , Presha Rajbhandari1,2,3 , Mariano J Alvarez1,2,3 , Pradeep Bandaru1, where MYB and FOXM1 act as synergistic master regulators of proliferation in the germinal center (GC: functional genomics; immunology Keywords: B cell; germinal centers; interactome; master regulator

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

    PubMed

    Gato-Cañas, Maria; Martinez de Morentin, Xabier; Blanco-Luquin, Idoia; Fernandez-Irigoyen, Joaquin; Zudaire, Isabel; Liechtenstein, Therese; Arasanz, Hugo; Lozano, Teresa; Casares, Noelia; Chaikuad, Apirat; Knapp, Stefan; Guerrero-Setas, David; Escors, David; Kochan, Grazyna; Santamaría, Enrique

    2015-09-29

    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

  6. Clathrin complexes with the inhibitor kappa B kinase signalosome: imaging the interactome

    PubMed Central

    Gamboni, Fabia; Escobar, Guillermo A.; Moore, Ernest E.; Dzieciatkowska, Monika; Hansen, Kirk C.; Mitra, Sanchayita; Nydam, Trevor A.; Silliman, Christopher C.; Banerjee, Anirban

    2014-01-01

    Abstract Many receptors involved with innate immunity activate the inhibitor kappa B kinase signalosome (IKK). The active complex appears to be assembled from the two kinase units, IKK? and IKK? with the regulatory protein NEMO. Because we previously found that RNA silencing of clathrin heavy chains (CHC), in transformed human lung pneumocytes (A549), decreased TNF??induced signaling and phosphorylation of inhibitor kappa B (I?B), we hypothesized that CHC forms cytoplasmic complexes with members of the IKK signalosome. Widely available antibodies were used to immunoprecipitate IKK? and NEMO interactomes. Analysis of the affinity interactomes by mass spectrometry detected clathrin with both baits with high confidence. Using the same antibodies for indirect digital immunofluorescence microscopy and FRET, the CHC–IKK complexes were visualized together with NEMO or HSP90. The natural variability of protein amounts in unsynchronized A549 cells was used to obtain statistical correlation for several complexes, at natural levels and without invasive labeling. Analyses of voxel numbers indicated that: (i) CHC–IKK complexes are not part of the IKK signalosome itself but, likely, precursors of IKK–NEMO complexes. (ii) CHC–IKK? complexes may arise from IKK?–HSP90 complexes. PMID:24994893

  7. The Liver Connexin32 Interactome Is a Novel Plasma Membrane-Mitochondrial Signaling Nexus

    PubMed Central

    2013-01-01

    Connexins are the structural subunits of gap junctions and act as protein platforms for signaling complexes. Little is known about tissue-specific connexin signaling nexuses, given significant challenges associated with affinity-purifying endogenous channel complexes to the level required for interaction analyses. Here, we used multiple subcellular fractionation techniques to isolate connexin32-enriched membrane microdomains from murine liver. We show, for the first time, that connexin32 localizes to both the plasma membrane and inner mitochondrial membrane of hepatocytes. Using a combination of immunoprecipitation-high throughput mass spectrometry, reciprocal co-IP, and subcellular fractionation methodologies, we report a novel interactome validated using null mutant controls. Eighteen connexin32 interacting proteins were identified. The majority represent resident mitochondrial proteins, a minority represent plasma membrane, endoplasmic reticulum, or cytoplasmic partners. In particular, connexin32 interacts with connexin26 and the mitochondrial protein, sideroflexin-1, at the plasma membrane. Connexin32 interaction enhances connexin26 stability. Converging bioinformatic, biochemical, and confocal analyses support a role for connexin32 in transiently tethering mitochondria to connexin32-enriched plasma membrane microdomains through interaction with proteins in the outer mitochondrial membrane, including sideroflexin-1. Complex formation increases the pool of sideroflexin-1 that is present at the plasma membrane. Together, these data identify a novel plasma membrane/mitochondrial signaling nexus in the connexin32 interactome. PMID:23590695

  8. Interactomes, manufacturomes and relational biology: analogies between systems biology and manufacturing systems

    PubMed Central

    2011-01-01

    Background We review and extend the work of Rosen and Casti who discuss category theory with regards to systems biology and manufacturing systems, respectively. Results We describe anticipatory systems, or long-range feed-forward chemical reaction chains, and compare them to open-loop manufacturing processes. We then close the loop by discussing metabolism-repair systems and describe the rationality of the self-referential equation f = f (f). This relationship is derived from some boundary conditions that, in molecular systems biology, can be stated as the cardinality of the following molecular sets must be about equal: metabolome, genome, proteome. We show that this conjecture is not likely correct so the problem of self-referential mappings for describing the boundary between living and nonliving systems remains an open question. We calculate a lower and upper bound for the number of edges in the molecular interaction network (the interactome) for two cellular organisms and for two manufacturomes for CMOS integrated circuit manufacturing. Conclusions We show that the relevant mapping relations may not be Abelian, and that these problems cannot yet be resolved because the interactomes and manufacturomes are incomplete. PMID:21689427

  9. Time-space Kriging to address the spatiotemporal misalignment in the large datasets

    NASA Astrophysics Data System (ADS)

    Liang, Dong; Kumar, Naresh

    2013-06-01

    This paper presents a Bayesian hierarchical spatiotemporal method of interpolation, termed as Markov Cube Kriging (MCK). The classical Kriging methods become computationally prohibitive, especially for large datasets due to the O(n3) matrix decomposition. MCK offers novel and computationally efficient solutions to address spatiotemporal misalignment, mismatch in the spatiotemporal scales and missing values across space and time in large spatiotemporal datasets. MCK is flexible in that it allows for non-separable spatiotemporal structure and nonstationary covariance at the hierarchical spatiotemporal scales. Employing MCK we developed estimates of daily concentration of fine particulates matter ?2.5 ?m in aerodynamic diameter (PM2.5) at 2.5 km spatial grid for the Cleveland Metropolitan Statistical Area, 2000 to 2009. Our validation and cross-validation suggest that MCK achieved robust prediction of spatiotemporal random effects and underlying hierarchical and nonstationary spatiotemporal structure in air pollution data. MCK has important implications for environmental epidemiology and environmental sciences for exposure quantification and collocation of data from different sources, available at different spatiotemporal scales.

  10. Support Vector Machines for Spatiotemporal Tornado INDRA ADRIANTO1

    E-print Network

    Lakshmanan, Valliappa

    1 Support Vector Machines for Spatiotemporal Tornado Prediction INDRA ADRIANTO1 , THEODORE B and time of tornadoes is presented. In this paper, we extend the work by Lakshmanan et al. (2005a) to use the probability of a tornado event at a particular spatial location within a given time window. We utilize a least

  11. Spatial and Spatiotemporal Data Mining: Recent Advances

    SciTech Connect

    Shekhar, Shashi; Vatsavai, Raju; Celik, Mete

    2008-01-01

    Explosive growth in geospatial data and the emergence of new spatial technologies emphasize the need for automated discovery of spatial knowledge. Spatial data mining is the process of discovering interesting and previously unknown, but potentially useful patterns from large spatial databases. The complexity of spatial data and intrinsic spatial relationships limits the usefulness of conventional data mining techniques for extracting spatial patterns. In this chapter we explore the emerging field of spatial data mining, focusing on four major topics: prediction and classification, outlier detection, co-location mining, and clustering. Spatiotemporal data mining is also briefly discussed.

  12. Cost-effective strategies for completing the interactome.

    PubMed

    Schwartz, Ariel S; Yu, Jingkai; Gardenour, Kyle R; Finley, Russell L; Ideker, Trey

    2009-01-01

    Comprehensive protein-interaction mapping projects are underway for many model species and humans. A key step in these projects is estimating the time, cost and personnel required for obtaining an accurate and complete map. Here we modeled the cost of interaction-map completion for various experimental designs. We showed that current efforts may require up to 20 independent tests covering each protein pair to approach completion. We explored designs for reducing this cost substantially, including prioritization of protein pairs, probability thresholding and interaction prediction. The best experimental designs lowered cost by fourfold overall and >100-fold in early stages of mapping. We demonstrate the best strategy in an ongoing project in Drosophila melanogaster, in which we mapped 450 high-confidence interactions using 47 microtiter plates, versus thousands of plates expected using current designs. This study provides a framework for assessing the feasibility of interaction mapping projects and for future efforts to increase their efficiency. PMID:19079254

  13. Spatio-temporal modulated polarimetry

    NASA Astrophysics Data System (ADS)

    LaCasse, Charles F.; Ririe, Tyson; Chipman, Russell A.; Tyo, J. Scott

    2011-10-01

    Recently, a polarimetric data reduction technique has been developed that in the presence of a time varying signals and noise free measurement process can achieve an error free reconstruction provided that the signal was band limited. Error free reconstruction for such a signal is not possible using conventional data reduction methods. The new approach provides insight for processing arbitrary modulation schemes in space, time, and wavelength. Theory predicts that a polarimeter that employs a spatio-temporal modulation scheme may be able to use the high temporal resolution of a spatially modulated device combined with the high spatial resolution of a temporally modulated system to attain greater combined resolution capabilities than either modulation on scheme can produce alone. A polarimeter that contains both spatial and temporal modulation can be constructed (for example) by placing a rotating retarder in front of a micropolarizer array (microgrid). This study develops theory and analysis for the rotating retarder microgrid polarimeter to show how the available bandwidth for each channel is affected by additional dimensions of modulation and demonstrates a working polarimeter with a simulation of Stokes parameters that are band limited in both space and time with a noisy measurement process.

  14. 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 preceded by falling temperatures. Climate influences on pandemic spread seem important and should be further investigated. PMID:25011543

  15. Spatiotemporal exploratory models for broad-scale survey data.

    PubMed

    Fink, Daniel; Hochachka, Wesley M; Zuckerberg, Benjamin; Winkler, David W; Shaby, Ben; Munson, M Arthur; Hooker, Giles; Riedewald, Mirek; Sheldon, Daniel; Kelling, Steve

    2010-12-01

    The distributions of animal populations change and evolve through time. Migratory species exploit different habitats at different times of the year. Biotic and abiotic features that determine where a species lives vary due to natural and anthropogenic factors. This spatiotemporal variation needs to be accounted for in any modeling of species' distributions. In this paper we introduce a semiparametric model that provides a flexible framework for analyzing dynamic patterns of species occurrence and abundance from broad-scale survey data. The spatiotemporal exploratory model (STEM) adds essential spatiotemporal structure to existing techniques for developing species distribution models through a simple parametric structure without requiring a detailed understanding of the underlying dynamic processes. STEMs use a multi-scale strategy to differentiate between local and global-scale spatiotemporal structure. A user-specified species distribution model accounts for spatial and temporal patterning at the local level. These local patterns are then allowed to "scale up" via ensemble averaging to larger scales. This makes STEMs especially well suited for exploring distributional dynamics arising from a variety of processes. Using data from eBird, an online citizen science bird-monitoring project, we demonstrate that monthly changes in distribution of a migratory species, the Tree Swallow (Tachycineta bicolor), can be more accurately described with a STEM than a conventional bagged decision tree model in which spatiotemporal structure has not been imposed. We also demonstrate that there is no loss of model predictive power when a STEM is used to describe a spatiotemporal distribution with very little spatiotemporal variation; the distribution of a nonmigratory species, the Northern Cardinal (Cardinalis cardinalis). PMID:21265447

  16. Quantitative analysis of PPT1 interactome in human neuroblastoma cells

    PubMed Central

    Scifo, Enzo; Szwajda, Agnieszka; Soliymani, Rabah; Pezzini, Francesco; Bianchi, Marzia; Dapkunas, Arvydas; D?bski, Janusz; Uusi-Rauva, Kristiina; Dadlez, Micha?; Gingras, Anne-Claude; Tyynelä, Jaana; Simonati, Alessandro; Jalanko, Anu; Baumann, Marc H.; Lalowski, Maciej

    2015-01-01

    Mutations in the CLN1 gene that encodes Palmitoyl protein thioesterase 1 (PPT1) or CLN1, cause Infantile NCL (INCL, MIM#256730). PPT1 removes long fatty acid chains such as palmitate from modified cysteine residues of proteins. The data shown here result from isolated protein complexes from PPT1-expressing SH-SY5Y stable cells that were subjected to single step affinity purification coupled to mass spectrometry (AP-MS). Prior to the MS analysis, we utilised a modified filter-aided sample preparation (FASP) protocol. Based on label free quantitative analysis of the data by SAINT, 23 PPT1 interacting partners (IP) were identified. A dense connectivity in PPT1 network was further revealed by functional coupling and extended network analyses, linking it to mitochondrial ATP synthesis coupled protein transport and thioester biosynthetic process. Moreover, the terms: inhibition of organismal death, movement disorders and concentration of lipid were predicted to be altered in the PPT1 network. Data presented here are related to Scifo et al. (J. Proteomics, 123 (2015) 42–53). PMID:26217791

  17. Genome Annotation and Intraviral Interactome for the Streptococcus pneumoniae Virulent Phage Dp-1? ¶

    PubMed Central

    Sabri, Mourad; Häuser, Roman; Ouellette, Marc; Liu, Jing; Dehbi, Mohammed; Moeck, Greg; García, Ernesto; Titz, Björn; Uetz, Peter; Moineau, Sylvain

    2011-01-01

    Streptococcus pneumoniae causes several diseases, including pneumonia, septicemia, and meningitis. Phage Dp-1 is one of the very few isolated virulent S. pneumoniae bacteriophages, but only a partial characterization is currently available. Here, we confirmed that Dp-1 belongs to the family Siphoviridae. Then, we determined its complete genomic sequence of 56,506 bp. It encodes 72 open reading frames, of which 44 have been assigned a function. We have identified putative promoters, Rho-independent terminators, and several genomic clusters. We provide evidence that Dp-1 may be using a novel DNA replication system as well as redirecting host protein synthesis through queuosine-containing tRNAs. Liquid chromatography-mass spectrometry analysis of purified phage Dp-1 particles identified at least eight structural proteins. Finally, using comprehensive yeast two-hybrid screens, we identified 156 phage protein interactions, and this intraviral interactome was used to propose a structural model of Dp-1. PMID:21097633

  18. Genome annotation and intraviral interactome for the Streptococcus pneumoniae virulent phage Dp-1.

    PubMed

    Sabri, Mourad; Häuser, Roman; Ouellette, Marc; Liu, Jing; Dehbi, Mohammed; Moeck, Greg; García, Ernesto; Titz, Björn; Uetz, Peter; Moineau, Sylvain

    2011-01-01

    Streptococcus pneumoniae causes several diseases, including pneumonia, septicemia, and meningitis. Phage Dp-1 is one of the very few isolated virulent S. pneumoniae bacteriophages, but only a partial characterization is currently available. Here, we confirmed that Dp-1 belongs to the family Siphoviridae. Then, we determined its complete genomic sequence of 56,506 bp. It encodes 72 open reading frames, of which 44 have been assigned a function. We have identified putative promoters, Rho-independent terminators, and several genomic clusters. We provide evidence that Dp-1 may be using a novel DNA replication system as well as redirecting host protein synthesis through queuosine-containing tRNAs. Liquid chromatography-mass spectrometry analysis of purified phage Dp-1 particles identified at least eight structural proteins. Finally, using comprehensive yeast two-hybrid screens, we identified 156 phage protein interactions, and this intraviral interactome was used to propose a structural model of Dp-1. PMID:21097633

  19. 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

  20. Disrupted-In-Schizophrenia-1 (DISC1) interactome and mental disorders: impact of mouse models.

    PubMed

    Lipina, Tatiana V; Roder, John C

    2014-09-01

    Disrupted-In-Schizophrenia-1 (DISC1) has captured much attention because it predisposes individuals to a wide range of mental illnesses. Notably, a number of genes encoding proteins interacting with DISC1 are also considered to be relevant risk factors of mental disorders. We reasoned that the understanding of DISC1-associated mental disorders in the context of network principles will help to address fundamental properties of DISC1 as a disease gene. Systematic integration of behavioural phenotypes of genetic mouse lines carrying perturbation in DISC1 interacting proteins would contribute to a better resolution of neurobiological mechanisms of mental disorders associated with the impaired DISC1 interactome and lead to a development of network medicine. This review also makes specific recommendations of how to assess DISC1 associated mental disorders in mouse models and discuss future directions. PMID:25016072

  1. Geometrical resonance in spatiotemporal systems

    E-print Network

    J. A. Gonzalez; A. Bellorin; L. I. Reyes; C. Vasquez; L. E. Guerrero

    2003-10-19

    We generalize the concept of geometrical resonance to perturbed sine-Gordon, Nonlinear Schrödinger and Complex Ginzburg-Landau equations. Using this theory we can control different dynamical patterns. For instance, we can stabilize breathers and oscillatory patterns of large amplitudes successfully avoiding chaos. On the other hand, this method can be used to suppress spatiotemporal chaos and turbulence in systems where these phenomena are already present. This method can be generalized to even more general spatiotemporal systems.

  2. Spatiotemporal dynamics of HIV infection

    NASA Astrophysics Data System (ADS)

    Strain, Matthew Carl

    Mathematical models of the dynamics of infection with the human immunodeficiency virus (HIV) have contributed to tremendous advances over the past 20 years. This thesis extends this previous work by exploring the importance of spatial heterogeneity in HIV infection both in vitro and in vivo in patients treated with highly-active antiretroviral therapy. Viral infections propagate locally in space, yet HIV infection has been widely regarded as equilibrated over the entire body of an infected patient. This dissertation constructs and explores a cellular automata model of viral spread at the cellular level. Coupling the automata to a blood compartment represented by a differential equation leads to a whole-body model of HIV infection that explicitly includes spatial effects at both the cellular and tissue levels. These models are tested by comparison with experimental data. A central prediction of the spatial model is that, due to competition between Brownian motion and viral lability, HIV infectivity increases with target cell density. This production is verified in a series of in vitro experiments in cell culture. The predicted independence of inhibitory concentrations of antiretoviral agents is verified for nevirapine, but azidothymidine inhibits HIV replication less efficiently in more dense cultures. These in vitro results suggest that systems allowing cell concentrations closer to tissue densities would better reflect virus replication kinetics, although standard measures of relative drug susceptibility may accurately reflect in vivo conditions. The coupled spatial model of in vivo dynamics is compared with novel mathematical analysis of experiments in HIV-infected patients. These analyses indicate that HIV DNA provides a useful marker of the size of long-lived cellular reservoirs of HIV. Levels of HIV DNA in peripheral blood are predictive of the average rate of residual virus production after years of treatment, regardless of whether patients initiate therapy 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. 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, Dezs?; 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

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

    E-print Network

    Perez-Lopez, Aron R; Turei, Denes; Modos, Dezso; Lenti, Katalin; Korcsmaros, Tamas; 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 understan...

  5. 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, Dezs?; 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.

  6. Spatiotemporal Dynamics of Actomyosin Networks

    PubMed Central

    Hussain, Saman; Molloy, Justin E.; Khan, Shahid M.

    2013-01-01

    Rhodamine–phalloidin-labeled actin filaments were visualized gliding over a skeletal heavy meromyosin (HMM)-coated surface. Experiments at low filament densities showed that when two filaments collided, their paths were affected in a manner that depended on collision angle. Some collisions resulted in complete alignment of the filament paths; in others, the filaments crossed over one another. Filament crossover or alignment was equally probable at ?40° contact angle. Filaments often underwent significant bending during collision and analysis of filament shape indicated an energy requirement of ?13 kBT. Experiments were performed over a wide range of HMM surface density and actin filament bulk concentration. Actin filament gliding speed and path persistence plateaued above a critical HMM surface density, and at high (micromolar) actin filament concentrations, filament motion became dramatically aligned in a common direction. Spatiotemporal features of alignment behavior were determined by correlation analysis, supported by simulations. The thermal drift of individual filament tracks was suppressed as the population became more oriented. Spatial correlation analysis revealed that long-range alignment was due to incremental recruitment rather than fusion of locally ordered seed domains. The global alignment of filament movement, described by an “order parameter,” peaked at optimal actin concentrations and myosin surface densities, in contrast to previous predictions of a critical phase transition. Either hydrodynamic coupling or exchange of filaments between the surface bound and adjacent bulk phase layers might degrade order at high actin filament concentration, and high HMM surface densities might decrease alignment probability during collisions. Our results are compatible with generation of long-range order from mechanical interaction between individual actin filaments. Furthermore, we show that randomly oriented myosin motors align relatively short, submicrometer actin filaments into motile surface domains that extend over many tens of micrometers and these patterns persist for several minutes. PMID:24047997

  7. Spatiotemporal interpolation methods in GIS

    NASA Astrophysics Data System (ADS)

    Li, Lixin

    In this dissertation, spatiotemporal interpolation of geographic data is considered. Two methods are discussed which are the reduction and the extension methods. The reduction method treats time as an independent dimension, whereas the extension method treats time equivalent to a spatial dimension. Both 2-D and 3-D shape functions are adopted, usually used in finite element methods, for the spatiotemporal interpolation of 2-D spatial & 1-D temporal and 3-D spatial & 1-D temporal data sets. Domains are divided into a finite number of sub-domains (such as triangles and tetrahedra) in which local shape functions are assumed. New 4-D shape functions that can be applied for each 4-D Delaunay Tessellation element are developed using the extension method for 3-D spatial & 1-D temporal problems. The visualization of shape function interpolation results is also explained and illustrated. Using an actual real estate data set with house prices, we compare these methods with other spatiotemporal interpolation methods based on inverse distance weighting and kriging. We compare these methods with respect to interpolation accuracy, error-proneness to time aggregation, invariance to scaling on the coordinate axes, and the type of constraints used in the representation of the interpolated data. Our experimental results show that the extension method based on shape functions is the most accurate and the overall best spatiotemporal interpolation method. Constraint databases provide a general approach to express and solve constraint problems. We show that spatiotemporal interpolation data can be represented in constraint databases efficiently and accurately. The advantage of constraint databases is that many queries that could not be done in traditional GIS systems can now be easily expressed and evaluated in constraint database systems. Finally, the constraint database system MLPQ (Management of Linear Programming Queries) is used to animate and query some spatiotemporal data examples. A translation algorithm between ArcGIS shape files and MLPQ input data files is also discussed.

  8. Spatio-Temporal Statistical Models with Application to Atmospheric Processes.

    NASA Astrophysics Data System (ADS)

    Wikle, Christopher Kim

    This dissertation is concerned with spatio-temporal processes in the atmospheric sciences. In the first chapter, a comprehensive overview of spatio-temporal methods from the atmospheric science literature is presented. Focus is on Empirical Orthogonal Function (EOF), Principal Interaction Pattern (PIP), Principal Oscillation Pattern (POP), and spatio-temporal Canonical Correlation Analysis (CCA) methods. Previously unexamined issues related to measurement error, continuous space, and Bayesian ideas are considered. In the second chapter, harmonic analysis is used to make diagnostic inference about the spatial variation of the semiannual oscillation (SAO) in the Northern Hemisphere (NH) 500-hPa height field. The SAO is explained by the spatial and temporal asymmetries in the annual variation of stationary eddies. The SAO in the NH extratropics is a result of east-west land-sea contrasts, analogous to the well-known Southern Hemisphere (SH) SAO, which is explained by north-south land-sea contrasts. The third chapter examines the seasonal variability of mixed Rossby-gravity waves (MRGWs) in the lower stratosphere over the tropical western Pacific. Thirty-one years of lower stratospheric wind observations from four tropical Pacific stations are examined with seasonally varying cross -spectral analysis, which suggests significant twice-yearly peaks in the v-wind power and the mean squared coherence between the u- and v-winds, with peaks occurring in the winter-early spring and in summer-early fall. Horizontal momentum flux convergence is found with these waves, with the sign of the convergence opposite during the two seasonal maxima. Cyclic spectral analyses show that the frequency of the maximum v-wind power in the MRGW frequency band shifts seasonally. In the fourth chapter, a spatio-temporal statistical model is proposed that assumes a first-order Markov dynamic process combined with a spatially descriptive colored noise process. With a measurement error equation, a spatio-temporal Kalman filter gives predictions in time and at any spatial location. The model prediction equation includes a simple kriging analog as a special case. The model predicts well with simulated spatio-temporal data, and is superior to simple kriging applied independently at each time. Predictions of precipitation over the data-sparse South China Sea captures the dynamic variation of the spatial precipitation.

  9. SPATIOTEMPORAL GESTURE SEGMENTATION JONATHAN ALON

    E-print Network

    OF ARTS AND SCIENCES Dissertation SPATIOTEMPORAL GESTURE SEGMENTATION by JONATHAN ALON B.Sc., Tel Aviv Stan Sclaroff, PhD Associate Professor of Computer Science Boston University Second Reader Margrit Betke, PhD Associate Professor of Computer Science Boston University Third Reader Trevor Darrell, Ph

  10. Spatiotemporal Gradient Modeling with Applications

    E-print Network

    Carlin, Bradley P.

    Spatiotemporal Gradients in Interval-Censored Airborne Exposures Data from the Clean-Up of the Deepwater Horizon Quality 3. Airborne Exposure Levels from the Deepwater Horizon Oil Spill #12;Introduction Exposures Data from the Clean-Up of the Deepwater Horizon Oil Spill Discussion #12;Methods

  11. Auditory Perception of Spatiotemporal Patterns

    ERIC Educational Resources Information Center

    Tolkmitt, Frank J.; Brindley, Robin

    1977-01-01

    To test the tendency of subjects to perceptually organize discrete temporal patterns with regard to runs of identical stimulus events, spatiotemporal patterns of white noise were presented for reproduction. It is suggested that changes in runs of auditory patterns are perceptually analogous to changes in contours of visual patterns. (Editor/RK)

  12. The dynamic interactome of human Aha1 upon Y223 phosphorylation

    PubMed Central

    Wolfgeher, Donald; Dunn, Diana M.; Woodford, Mark R.; Bourboulia, Dimitra; Bratslavsky, Gennady; Mollapour, Mehdi; Kron, Stephen J.; Truman, Andrew W.

    2015-01-01

    Heat Shock Protein 90 (Hsp90) is an essential chaperone that supports the function of a wide range of signaling molecules. Hsp90 binds to a suite of co-chaperone proteins that regulate Hsp90 function through alteration of intrinsic ATPase activity. Several studies have determined Aha1 to be an important co-chaperone whose binding to Hsp90 is modulated by phosphorylation, acetylation and SUMOylation of Hsp90 [1], [2]. In this study, we applied quantitative affinity-purification mass spectrometry (AP-MS) proteomics to understand how phosphorylation of hAha1 at Y223 altered global client/co-chaperone interaction [3]. Specifically, we characterized and compared the interactomes of Aha1–Y223F (phospho-mutant form) and Aha1–Y223E (phospho-mimic form). We identified 99 statistically significant interactors of hAha1, a high proportion of which (84%) demonstrated preferential binding to the phospho-mimic form of hAha1. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository [4] with the dataset identifier PXD001737.

  13. Characterization of hampin/MSL1 as a node in the nuclear interactome

    SciTech Connect

    Dmitriev, Ruslan I.; Korneenko, Tatyana V.; Bessonov, Alexander A.; Shakhparonov, Mikhail I.; Modyanov, Nikolai N.; Pestov, Nikolay B.; E-mail: korn@mail.ibch.ru

    2007-04-20

    Hampin, homolog of Drosophila MSL1, is a partner of histone acetyltransferase MYST1/MOF. Functions of these proteins remain poorly understood beyond their participation in chromatin remodeling complex MSL. In order to identify new proteins interacting with hampin, we screened a mouse cDNA library in yeast two-hybrid system with mouse hampin as bait and found five high-confidence interactors: MYST1, TPR proteins TTC4 and KIAA0103, NOP17 (homolog of a yeast nucleolar protein), and transcription factor GC BP. Subsequently, all these proteins were used as baits in library screenings and more new interactions were found: tumor suppressor RASSF1C and spliceosome component PRP3 for KIAA0103, ring finger RNF10 for RASSF1C, and RNA polymerase II regulator NELF-C for MYST1. The majority of the observed interactions was confirmed in vitro by pull-down of bacterially expressed proteins. Reconstruction of a fragment of mammalian interactome suggests that hampin may be linked to diverse regulatory processes in the nucleus.

  14. A Synthetic Coiled-Coil Interactome Provides Heterospecific Modules for Molecular Engineering

    SciTech Connect

    Reinke, Aaron W.; Grant, Robert A.; Keating, Amy E.

    2010-06-21

    The versatile coiled-coil protein motif is widely used to induce and control macromolecular interactions in biology and materials science. Yet the types of interaction patterns that can be constructed using known coiled coils are limited. Here we greatly expand the coiled-coil toolkit by measuring the complete pairwise interactions of 48 synthetic coiled coils and 7 human bZIP coiled coils using peptide microarrays. The resulting 55-member protein 'interactome' includes 27 pairs of interacting peptides that preferentially heteroassociate. The 27 pairs can be used in combinations to assemble sets of 3 to 6 proteins that compose networks of varying topologies. Of special interest are heterospecific peptide pairs that participate in mutually orthogonal interactions. Such pairs provide the opportunity to dimerize two separate molecular systems without undesired crosstalk. Solution and structural characterization of two such sets of orthogonal heterodimers provide details of their interaction geometries. The orthogonal pair, along with the many other network motifs discovered in our screen, provide new capabilities for synthetic biology and other applications.

  15. “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

  16. Telomere-regulating Genes and the Telomere Interactome in Familial Cancers

    PubMed Central

    Robles-Espinoza, Carla Daniela; del Castillo Velasco-Herrera, Martin; Hayward, Nicholas K.; Adams, David J.

    2014-01-01

    Telomeres are repetitive sequence structures at the ends of linear chromosomes that consist of double-stranded DNA repeats followed by a short single-stranded DNA (ssDNA) protrusion. Telomeres need to be replicated each cell cycle and protected from DNA-processing enzymes, tasks that cells execute using specialized protein complexes such as telomerase (TERT), which aids in telomere maintenance and replication, and the shelterin complex, which protects chromosome ends. These complexes are also able to interact with a variety of other proteins, referred to as the telomere interactome, in order to fulfil their biological functions and control signaling cascades originating from telomeres. Given their essential role in genomic maintenance and cell cycle control, germline mutations in telomere-regulating proteins and their interacting partners have been found to underlie a variety of diseases and cancer-predisposition syndromes. These syndromes can be characterized by progressively shortening telomeres, in which carriers can present with organ failure due to stem cell senescence among other characteristics, or can also present with long or unprotected telomeres, providing an alternative route for cancer formation. This review, summarizes the critical roles that telomere-regulating proteins play in cell cycle control and cell fate and explores the current knowledge on different cancer-predisposing conditions that have been linked to germline defects in these proteins and their interacting partners. PMID:25244922

  17. DULIP: A Dual Luminescence-Based Co-Immunoprecipitation Assay for Interactome Mapping in Mammalian Cells.

    PubMed

    Trepte, Philipp; Buntru, Alexander; Klockmeier, Konrad; Willmore, Lindsay; Arumughan, Anup; Secker, Christopher; Zenkner, Martina; Brusendorf, Lydia; Rau, Kirstin; Redel, Alexandra; Wanker, Erich E

    2015-10-23

    Mapping of protein-protein interactions (PPIs) is critical for understanding protein function and complex biological processes. Here, we present DULIP, a dual luminescence-based co-immunoprecipitation assay, for systematic PPI mapping in mammalian cells. DULIP is a second-generation luminescence-based PPI screening method for the systematic and quantitative analysis of co-immunoprecipitations using two different luciferase tags. Benchmarking studies with positive and negative PPI reference sets revealed that DULIP allows the detection of interactions with high sensitivity and specificity. Furthermore, the analysis of a PPI reference set with known binding affinities demonstrated that both low- and high-affinity interactions can be detected with DULIP assays. Finally, using the well-characterized interaction between Syntaxin-1 and Munc18, we found that DULIP is capable of detecting the effects of point mutations on interaction strength. Taken together, our studies demonstrate that DULIP is a sensitive and reliable method of great utility for systematic interactome research. It can be applied for interaction screening and validation of PPIs in mammalian cells. Moreover, DULIP permits the specific analysis of mutation-dependent binding patterns. PMID:26264872

  18. Interactome maps of mouse gene regulatory domains reveal basic principles of transcriptional regulation

    PubMed Central

    Kwon, Kyong-Rim Kieffer; Tang, Zhonghui; Mathe, Ewy; Qian, Jason; Sung, Myong-Hee; Li, Guoliang; Resch, Wolfgang; Baek, Songjoon; Pruett, Nathanael; Grøntved, Lars; Vian, Laura; Nelson, Steevenson; Zare, Hossein; Hakim, Ofir; Reyon, Deepak; Yamane, Arito; Nakahashi, Hirotaka; Kovalchuk, Alexander L.; Zou, Jizhong; Joung, J. Keith; Sartorelli, Vittorio; Wei, Chia-Lin; Ruan, Xiaoan; Hager, Gordon L.; Ruan, Yijun; Casellas, Rafael

    2014-01-01

    A key finding of the ENCODE project is that the enhancer landscape of mammalian cells undergoes marked alterations during ontogeny. However, the nature and extent of these changes are unclear. As part of the NIH Mouse Regulome Project, we here combined DNaseI hypersensitivity, ChIP-Seq, and ChIA-PET technologies to map the promoter-enhancer interactomes of pluripotent ES cells and differentiated B lymphocytes. We confirm that enhancer usage varies widely across tissues. Unexpectedly, we find that this feature extends to broadly-transcribed genes, including Myc and Pim1 cell cycle regulators, which associate with an entirely different set of enhancers in ES and B cells. By means of high-resolution CpG methylomes, genome editing, and digital footprinting we show that these enhancers recruit lineage-determining factors. Furthermore, we demonstrate that the turning on and off of enhancers during development correlates with promoter activity. We propose that organisms rely on a dynamic enhancer landscape to control basic cellular functions in a tissue-specific manner. PMID:24360274

  19. 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. PMID:26179741

  20. 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. PMID:26702402

  1. 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 of stick-slip front motion.

  2. 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

  3. Large-scale De Novo Prediction of Physical Protein-Protein Association*

    PubMed Central

    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

    2011-01-01

    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. PMID:21836163

  4. Anticancer activity of galactoxyloglucan polysaccharide-conjugated doxorubicin nanoparticles: Mechanistic insights and interactome analysis.

    PubMed

    Joseph, Manu M; Aravind, S R; George, Suraj K; Raveendran Pillai, K; Mini, S; Sreelekha, T T

    2015-06-01

    Toxicity associated with chemotherapeutic drugs such as doxorubicin (Dox), is one of the major obstacles that is currently affecting patients. PST-Dox (Galactoxyloglucan, PST001-conjugated Dox) nanoparticles were synthesized by encapsulating Dox with polysaccharide PST001, isolated from Tamarindus indica (Ti) by ionic gelation with tripolyphosphate (TPP). Herein, we demonstrate a detailed mechanistic and interactome network analysis that is specific to PST-Dox action in cancer cells and normal lymphocytes. Our results show that PST-Dox is superior to its parental counterparts, exhibiting a greater cytotoxicity by the induction of apoptosis against a wide variety of cancers by enhanced cellular uptake of Dox from the nanoparticle conjugates. Also, PST-Dox nanoparticles were non-toxic to normal lymphocytes with limited immunostimulatory effects up to certain doses. Elucidation of molecular mechanism by whole genome microarray in cancer cells and lymphocytes revealed that a large number of genes were dysregulated specifically in cancer cells. Specifically, a unique target gene EGR1, contextually determined translational activation of P53 in the cancerous and non-cancerous cells. Most of the key downregulated genes were tyrosine kinases, indicating the potential inhibitory action of PST-Dox on tyrosine kinase oncogenic pathways. Western blotting of proteins corresponding to the genes that were altered at the genomic level was very well correlated in the majority of them, except in a few that demonstrated post-transcriptional modifications. The important findings and highly disciplined approaches highlighted in the present study will speed up the therapeutic potential of this augmented nanoparticle formulation for more robust clinical studies and testing in several cancers. PMID:25864443

  5. Spatiotemporal Monitoring of Urban Vegetation Christopher Small

    E-print Network

    Small, Christopher

    . The spatiotemporal distribution of vegetation may be effectively monitored with multispectral satellite observations measurements from high resolution aerial photography shows agreement to within fractional abundances of 0

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

    PubMed Central

    Merkulova, Maria; P?unescu, 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

  7. 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

  8. The cyclin D1-CDK4 oncogenic interactome enables identification of potential novel oncogenes and clinical prognosis

    PubMed Central

    Jirawatnotai, Siwanon; Sharma, Samanta; Michowski, Wojciech; Suktitipat, Bhoom; Geng, Yan; Quackenbush, John; Elias, Joshua E; Gygi, Steven P; Wang, Yaoyu E; Sicinski, Piotr

    2014-01-01

    Overexpression of cyclin D1 and its catalytic partner, CDK4, is frequently seen in human cancers. We constructed cyclin D1 and CDK4 protein interaction network in a human breast cancer cell line MCF7, and identified novel CDK4 protein partners. Among CDK4 interactors we observed several proteins functioning in protein folding and in complex assembly. One of the novel partners of CDK4 is FKBP5, which we found to be required to maintain CDK4 levels in cancer cells. An integrative analysis of the extended cyclin D1 cancer interactome and somatic copy number alterations in human cancers identified BAIAPL21 as a potential novel human oncogene. We observed that in several human tumor types BAIAPL21 is expressed at higher levels as compared to normal tissue. Forced overexpression of BAIAPL21 augmented anchorage independent growth, increased colony formation by cancer cells and strongly enhanced the ability of cells to form tumors in vivo. Lastly, we derived an Aggregate Expression Score (AES), which quantifies the expression of all cyclin D1 interactors in a given tumor. We observed that AES has a prognostic value among patients with ER-positive breast cancers. These studies illustrate the utility of analyzing the interactomes of proteins involved in cancer to uncover potential oncogenes, or to allow better cancer prognosis. PMID:25486477

  9. a Spatio-Temporal Framework for Modeling Active Layer Thickness

    NASA Astrophysics Data System (ADS)

    Touyz, J.; Streletskiy, D. A.; Nelson, F. E.; Apanasovich, T. V.

    2015-07-01

    The Arctic is experiencing an unprecedented rate of environmental and climate change. The active layer (the uppermost layer of soil between the atmosphere and permafrost that freezes in winter and thaws in summer) is sensitive to both climatic and environmental changes, and plays an important role in the functioning, planning, and economic activities of Arctic human and natural ecosystems. This study develops a methodology for modeling and estimating spatial-temporal variations in active layer thickness (ALT) using data from several sites of the Circumpolar Active Layer Monitoring network, and demonstrates its use in spatial-temporal interpolation. The simplest model's stochastic component exhibits no spatial or spatio-temporal dependency and is referred to as the naïve model, against which we evaluate the performance of the other models, which assume that the stochastic component exhibits either spatial or spatio-temporal dependency. The methods used to fit the models are then discussed, along with point forecasting. We compare the predicted fit of the various models at key study sites located in the North Slope of Alaska and demonstrate the advantages of space-time models through a series of error statistics such as mean squared error, mean absolute and percent deviance from observed data. We find the difference in performance between the spatio-temporal and remaining models is significant for all three error statistics. The best stochastic spatio-temporal model increases predictive accuracy, compared to the naïve model, of 33.3%, 36.2% and 32.5% on average across the three error metrics at the key sites for a one-year hold out period.

  10. Computational genomic analysis of PARK7 interactome reveals high BBS1 gene expression as a prognostic factor favoring survival in malignant pleural mesothelioma.

    PubMed

    Vavougios, Georgios D; Solenov, Evgeniy I; Hatzoglou, Chrissi; Baturina, Galina S; Katkova, Liubov E; Molyvdas, Paschalis Adam; Gourgoulianis, Konstantinos I; Zarogiannis, Sotirios G

    2015-10-01

    The aim of our study was to assess the differential gene expression of Parkinson protein 7 (PARK7) interactome in malignant pleural mesothelioma (MPM) using data mining techniques to identify novel candidate genes that may play a role in the pathogenicity of MPM. We constructed the PARK7 interactome using the ConsensusPathDB database. We then interrogated the Oncomine Cancer Microarray database using the Gordon Mesothelioma Study, for differential gene expression of the PARK7 interactome. In ConsensusPathDB, 38 protein interactors of PARK7 were identified. In the Gordon Mesothelioma Study, 34 of them were assessed out of which SUMO1, UBC3, KIAA0101, HDAC2, DAXX, RBBP4, BBS1, NONO, RBBP7, HTRA2, and STUB1 were significantly overexpressed whereas TRAF6 and MTA2 were significantly underexpressed in MPM patients (network 2). Furthermore, Kaplan-Meier analysis revealed that MPM patients with high BBS1 expression had a median overall survival of 16.5 vs. 8.7 mo of those that had low expression. For validation purposes, we performed a meta-analysis in Oncomine database in five sarcoma datasets. Eight network 2 genes (KIAA0101, HDAC2, SUMO1, RBBP4, NONO, RBBP7, HTRA2, and MTA2) were significantly differentially expressed in an array of 18 different sarcoma types. Finally, Gene Ontology annotation enrichment analysis revealed significant roles of the PARK7 interactome in NuRD, CHD, and SWI/SNF protein complexes. In conclusion, we identified 13 novel genes differentially expressed in MPM, never reported before. Among them, BBS1 emerged as a novel predictor of overall survival in MPM. Finally, we identified that PARK7 interactome is involved in novel pathways pertinent in MPM disease. PMID:26254420

  11. 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 existed. Soltani and Modarres (2006) classified the sites by using only average rainfall of sites, they did not consider time replications and spatial coordinates. Kerby et.al (2007) purposed spatial clustering method based on likelihood. They took account of the geographic locations through the variance covariance matrix. Their purposed method works like hierarchical clustering methods. Moreovere, it is inappropiriate for time replication data and could not perform well for large number of sites. Tuia.et.al (2008) used scan statistics for identifying spatio-temporal clusters for fire sequences in the Tuscany region in Italy. The scan statistics clustering method was developed by Kulldorff et al. (1997) to detect spatio-temporal clusters in epidemiology and assessing their significance. The purposed scan statistics method is used only for univariate discrete stochastic random variables. In this paper we make use of a very simple approach for spatio-temporal clustering which can create separable and homogeneous clusters. Most of the clustering methods are based on Euclidean distances. It is well known that geographic coordinates are spherical coordinates and estimating Euclidean distances from spherical coordinates is inappropriate. As a transformation from geographic coordinates to rectangular (D-plane) coordinates we use the Lambert projection method. The partition around medoids clustering method is incorporated on the data including D-plane coordinates. Ordinary kriging is taken as validity measure for the precipitation data. The kriging results for clusters are more accurate and have less variation compared to complete monitoring network precipitation data. References Casto.V.E and Murray.A.T (1997). Spatial Clustering with Data Mining with Genetic Algorithms. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.56.8573 Kaufman.L and Rousseeuw.P.J (1990). Finding Groups in Data: An Introduction to Cluster Analysis. Wiley series of Probability and Mathematical Statistics, New York. Kulldorf.M (1997). A spatial scan statistic. Commun. Stat.-Theor. Math. 26(6)

  12. Spatiotemporal Dynamics of Insect-Fire Interactions

    E-print Network

    Moorcroft, Paul R.

    Spatiotemporal Dynamics of Insect-Fire Interactions A thesis presented by Heather Joan Lynch Heather Joan Lynch Spatiotemporal Dynamics of Insect-Fire Interactions Abstract Insect outbreaks and forest fires individually represent significant forest disturbances which have long-term effects

  13. Spatiotemporal Patterns in Mathematical Models for Predator

    E-print Network

    Fournier, John J.F.

    . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.1.1 Oscillatory predator-prey systems . . . . . . . . . . . 2 1.1.2 Biological invasionsSpatiotemporal Patterns in Mathematical Models for Predator Invasions by Sandra M. Merchant B-prey systems recently because, in the wake of predator invasions, they can ex- hibit complex spatiotemporal

  14. Structured reservoir computing with spatiotemporal chaotic attractors

    E-print Network

    Lisboa, Universidade Técnica de

    Structured reservoir computing with spatiotemporal chaotic attractors Carlos Louren¸co1,2 1 as reservoir properties. The ar- chitectures share a common topology of close-neighbor connections which of spatiotemporal structure and associated symme- tries in reservoir-mediated pattern processing. Such type

  15. Structured reservoir computing with spatiotemporal chaotic attractors

    E-print Network

    Lourenço, Carlos

    Structured reservoir computing with spatiotemporal chaotic attractors Carlos Louren�co 1,2 # 1 as reservoir properties. The ar­ chitectures share a common topology of close­neighbor connections which of spatiotemporal structure and associated symme­ tries in reservoir­mediated pattern processing. Such type

  16. 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.

  17. Spatiotemporal System Identification With Continuous Spatial Maps and Sparse Estimation.

    PubMed

    Aram, Parham; Kadirkamanathan, Visakan; Anderson, Sean R

    2015-11-01

    We present a framework for the identification of spatiotemporal linear dynamical systems. We use a state-space model representation that has the following attributes: 1) the number of spatial observation locations are decoupled from the model order; 2) the model allows for spatial heterogeneity; 3) the model representation is continuous over space; and 4) the model parameters can be identified in a simple and sparse estimation procedure. The model identification procedure we propose has four steps: 1) decomposition of the continuous spatial field using a finite set of basis functions where spatial frequency analysis is used to determine basis function width and spacing, such that the main spatial frequency contents of the underlying field can be captured; 2) initialization of states in closed form; 3) initialization of state-transition and input matrix model parameters using sparse regression-the least absolute shrinkage and selection operator method; and 4) joint state and parameter estimation using an iterative Kalman-filter/sparse-regression algorithm. To investigate the performance of the proposed algorithm we use data generated by the Kuramoto model of spatiotemporal cortical dynamics. The identification algorithm performs successfully, predicting the spatiotemporal field with high accuracy, whilst the sparse regression leads to a compact model. PMID:25647667

  18. 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.

  19. 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 TIF1?, 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 conserved across eukaryotes. PMID:26184334

  20. 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 Score_S cutoff values, single data source, or the data from STITCH, the inference of 264 SCZ-related drugs had the highest performance. Conclusions The WinDTome generated in this study contains comprehensive drug-target associations with confidence scores. Its application to the SCZ drug repurposing demonstrated that the WinDTome is promising to serve as a useful resource for drug repurposing. PMID:26100720

  1. 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.

  2. Ocean Wave Reconstruction Algorithms Based on Spatio-temporal Data Acquired by a Flash LIDAR Camera

    E-print Network

    Grilli, Stéphan T.

    Ocean Wave Reconstruction Algorithms Based on Spatio-temporal Data Acquired by a Flash LIDAR Camera St´ephan T. Grilli , Charles-Antoine Gu´erin and Bart Goldstein (1) Department of Ocean Engineering on the development of free surface reconstruction algorithms to predict ocean waves, based on spatial observations

  3. Notch3 interactome analysis identified WWP2 as a negative regulator of Notch3 signaling in ovarian cancer.

    PubMed

    Jung, Jin-Gyoung; Stoeck, Alexander; Guan, Bin; Wu, Ren-Chin; Zhu, Heng; Blackshaw, Seth; Shih, Ie-Ming; Wang, Tian-Li

    2014-10-01

    The Notch3 signaling pathway is thought to play a critical role in cancer development, as evidenced by the Notch3 amplification and rearrangement observed in human cancers. However, the molecular mechanism by which Notch3 signaling contributes to tumorigenesis is largely unknown. In an effort to identify the molecular modulators of the Notch3 signaling pathway, we screened for Notch3-intracellular domain (N3-ICD) interacting proteins using a human proteome microarray. Pathway analysis of the Notch3 interactome demonstrated that ubiquitin C was the molecular hub of the top functional network, suggesting the involvement of ubiquitination in modulating Notch3 signaling. Thereby, we focused on functional characterization of an E3 ubiquitin-protein ligase, WWP2, a top candidate in the Notch3 interactome list. Co-immunoprecipitation experiments showed that WWP2 interacted with N3-ICD but not with intracellular domains from other Notch receptors. Wild-type WWP2 but not ligase-deficient mutant WWP2 increases mono-ubiquitination of the membrane-tethered Notch3 fragment, therefore attenuating Notch3 pathway activity in cancer cells and leading to cell cycle arrest. The mono-ubiquitination by WWP2 may target an endosomal/lysosomal degradation fate for Notch3 as suggested by the fact that the process could be suppressed by the endosomal/lysosomal inhibitor. Analysis of The Cancer Genome Atlas dataset showed that the majority of ovarian carcinomas harbored homozygous or heterozygous deletions in WWP2 locus, and there was an inverse correlation in the expression levels between WWP2 and Notch3 in ovarian carcinomas. Furthermore, ectopic expression of WWP2 decreased tumor development in a mouse xenograft model and suppressed the Notch3-induced phenotypes including increase in cancer stem cell-like cell population and platinum resistance. Taken together, our results provide evidence that WWP2 serves as a tumor suppressor by negatively regulating Notch3 signaling in ovarian cancer. PMID:25356737

  4. Spatiotemporal control of nanooptical excitations

    PubMed Central

    Aeschlimann, Martin; Bauer, Michael; Bayer, Daniela; Brixner, Tobias; Cunovic, Stefan; Dimler, Frank; Fischer, Alexander; Pfeiffer, Walter; Rohmer, Martin; Schneider, Christian; Steeb, Felix; Strüber, Christian; Voronine, Dmitri V.

    2010-01-01

    The most general investigation and exploitation of light-induced processes require simultaneous control over spatial and temporal properties of the electromagnetic field on a femtosecond time and nanometer length scale. Based on the combination of polarization pulse shaping and time-resolved two-photon photoemission electron microscopy, we demonstrate such control over nanoscale spatial and ultrafast temporal degrees of freedom of an electromagnetic excitation in the vicinity of a nanostructure. The time-resolved cross-correlation measurement of the local photoemission yield reveals the switching of the nanolocalized optical near-field distribution with a lateral resolution well below the diffraction limit and a temporal resolution on the femtosecond time scale. In addition, successful adaptive spatiotemporal control demonstrates the flexibility of the method. This flexible simultaneous control of temporal and spatial properties of nanophotonic excitations opens new possibilities to tailor and optimize the light–matter interaction in spectroscopic methods as well as in nanophotonic applications. PMID:20212153

  5. 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

  6. Bayesian spatio-temporal analysis and geospatial risk factors of human monocytic ehrlichiosis.

    PubMed

    Raghavan, Ram K; Neises, Daniel; Goodin, Douglas G; Andresen, Daniel A; Ganta, Roman R

    2014-01-01

    Variations in spatio-temporal patterns of Human Monocytic Ehrlichiosis (HME) infection in the state of Kansas, USA were examined and the relationship between HME relative risk and various environmental, climatic and socio-economic variables were evaluated. HME data used in the study was reported to the Kansas Department of Health and Environment between years 2005-2012, and geospatial variables representing the physical environment [National Land cover/Land use, NASA Moderate Resolution Imaging Spectroradiometer (MODIS)], climate [NASA MODIS, Prediction of Worldwide Renewable Energy (POWER)], and socio-economic conditions (US Census Bureau) were derived from publicly available sources. Following univariate screening of candidate variables using logistic regressions, two Bayesian hierarchical models were fit; a partial spatio-temporal model with random effects and a spatio-temporal interaction term, and a second model that included additional covariate terms. The best fitting model revealed that spatio-temporal autocorrelation in Kansas increased steadily from 2005-2012, and identified poverty status, relative humidity, and an interactive factor, 'diurnal temperature range x mixed forest area' as significant county-level risk factors for HME. The identification of significant spatio-temporal pattern and new risk factors are important in the context of HME prevention, for future research in the areas of ecology and evolution of HME, and as well as climate change impacts on tick-borne diseases. PMID:24992684

  7. Integrate Omics Data and Molecular Dynamics Simulations toward Better Understanding of Human 14-3-3 Interactomes and Better Drugs for Cancer Therapy.

    PubMed

    Babula, JoAnne J; Liu, Jing-Yuan

    2015-10-20

    The 14-3-3 protein family is among the most extensively studied, yet still largely mysterious protein families in mammals to date. As they are well recognized for their roles in apoptosis, cell cycle regulation, and proliferation in healthy cells, aberrant 14-3-3 expression has unsurprisingly emerged as instrumental in the development of many cancers and in prognosis. Interestingly, while the seven known 14-3-3 isoforms in humans have many similar functions across cell types, evidence of isoform-specific functions and localization has been observed in both healthy and diseased cells. The strikingly high similarity among 14-3-3 isoforms has made it difficult to delineate isoform-specific functions and for isoform-specific targeting. Here, we review our knowledge of 14-3-3 interactome(s) generated by high-throughput techniques, bioinformatics, structural genomics and chemical genomics and point out that integrating the information with molecular dynamics (MD) simulations may bring us new opportunity to the design of isoform-specific inhibitors, which can not only be used as powerful research tools for delineating distinct interactomes of individual 14-3-3 isoforms, but also can serve as potential new anti-cancer drugs that selectively target aberrant 14-3-3 isoform. PMID:26554908

  8. A meta-analysis to evaluate the cellular processes regulated by the interactome of endogenous and over-expressed estrogen receptor alpha

    PubMed Central

    Simões, Joana; Amado, Francisco M.

    2015-01-01

    The nature of the proteins complexes that regulate ER? subcellular localization and activity is still an open question in breast cancer biology. Identification of such complexes will help understand development of endocrine resistance in ER+ breast cancer. Mass spectrometry (MS) has allowed comprehensive analysis of the ER? interactome. We have compared six published works analyzing the ER? interactome of MCF-7 and HeLa cells in order to identify a shared or different pathway-related fingerprint. Overall, 806 ER? interacting proteins were identified. The cellular processes were differentially represented according to the ER? purification methodology, indicating that the methodologies used are complementary. While in MCF-7 cells, the interactome of endogenous and over-expressed ER? essentially represents the same biological processes and cellular components, the proteins identified were not over-lapping; thus, suggesting that the biological response may differ as the regulatory/participating proteins in these complexes are different. Interestingly, biological processes uniquely associated to ER? over-expressed in HeLa cell line included L-serine biosynthetic process, cellular amino acid biosynthetic process and cell redox homeostasis. In summary, all the approaches analyzed in this meta-analysis are valid and complementary; in particular, for those cases where the processes occur at low frequency with normal ER? levels, and can be identified when the receptor is over-expressed. However special effort should be put into validating these findings in cells expressing physiological ER? levels. PMID:26097882

  9. Assessing Protein Co-evolution in the Context of the Tree of Life Assists in the Prediction of the Interactome

    E-print Network

    Pazos, Florencio

    in the largest set of annotated interacting proteins for Escherichia coli. This assessment of co Spain The identification of the whole set of protein interactions taking place in an organism is one by the expected background similarity due to the underlying speciation events. We test the new approach

  10. Spatiotemporal features for asynchronous event-based data

    PubMed Central

    Lagorce, Xavier; Ieng, Sio-Hoi; Clady, Xavier; Pfeiffer, Michael; Benosman, Ryad B.

    2015-01-01

    Bio-inspired asynchronous event-based vision sensors are currently introducing a paradigm shift in visual information processing. These new sensors rely on a stimulus-driven principle of light acquisition similar to biological retinas. They are event-driven and fully asynchronous, thereby reducing redundancy and encoding exact times of input signal changes, leading to a very precise temporal resolution. Approaches for higher-level computer vision often rely on the reliable detection of features in visual frames, but similar definitions of features for the novel dynamic and event-based visual input representation of silicon retinas have so far been lacking. This article addresses the problem of learning and recognizing features for event-based vision sensors, which capture properties of truly spatiotemporal volumes of sparse visual event information. A novel computational architecture for learning and encoding spatiotemporal features is introduced based on a set of predictive recurrent reservoir networks, competing via winner-take-all selection. Features are learned in an unsupervised manner from real-world input recorded with event-based vision sensors. It is shown that the networks in the architecture learn distinct and task-specific dynamic visual features, and can predict their trajectories over time. PMID:25759637

  11. Spatiotemporal recurrences of sandpile avalanches

    NASA Astrophysics Data System (ADS)

    Tarun, Anjali B.; Paguirigan, Antonino A.; Batac, Rene C.

    2015-10-01

    We study the space and time properties of avalanches in a continuous sandpile model by constructing a temporally directed network linking together the recurrent avalanche events based on their spatial separation. We use two different criteria for network construction: a later event is connected to a previous one if it is either nearest or farthest from it among all the later events. With this, we observe scale-free regimes emerge as characterized by the following power-law exponents: (a) ? = 1.7 for the avalanche size distributions; (b) ?F = 2.1 in the in-degree distribution of farthest recurrences; (c) ? = 1 for the separation distances; and (d) ? = 1 for the temporal separations of recurrences. Our results agree with earlier observations that describe the sandpile avalanches as repulsive events, i.e. the next avalanche is more likely to be physically separated from an earlier one. These observations, which are not captured by usual interoccurrence statistics and by random connection mechanisms, suggest an underlying spatiotemporal organization in the sandpile that makes it useful for modeling real-world systems.

  12. Anomalous Behaviour Detection Using Spatiotemporal Oriented Energies, Subset Inclusion Histogram

    E-print Network

    Wildes, Richard P.

    Anomalous Behaviour Detection Using Spatiotemporal Oriented Energies, Subset Inclusion Histogram of spatiotemporal oriented energy are used to model behaviour. This representation can capture a wide range.g., backgrounds of fluttering vegetation or water waves), including multimodal behaviour. Modeling must

  13. 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.

  14. 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.

  15. Spatio-temporal Feature Recogntion using Randomised Ferns

    E-print Network

    Bowden, Richard

    Spatio-temporal Feature Recogntion using Randomised Ferns Olusegun Oshin, Andrew Gilbert, John Bayesian classifier of Ferns to the spatio-temporal domain and learn clas- sifiers that duplicate video sequence. We extend a Naive Bayesian classifier called Ferns [1] to the spatio-temporal domain

  16. Formal classification of integrity constraints in spatiotemporal database applications$

    E-print Network

    Formal classification of integrity constraints in spatiotemporal database applications$ Mehrdad model Integrity constraint Spatiotemporal modeling Data quality Spatiotemporal database a b s t r a c t Imposing integrity constraints is an efficient way to improve data quality in databases. Effective

  17. 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

  18. 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.

  19. 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

  20. 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

  1. Interactome analysis identifies a new paralogue of XRCC4 in non-homologous end joining DNA repair pathway

    PubMed Central

    Xing, Mengtan; Yang, Mingrui; Huo, Wei; Feng, Feng; Wei, Leizhen; Jiang, Wenxia; Ning, Shaokai; Yan, Zhenxin; Li, Wen; Wang, Qingsong; Hou, Mei; Dong, Chunxia; Guo, Rong; Gao, Ge; Ji, Jianguo; Zha, Shan; Lan, Li; Liang, Huanhuan; Xu, Dongyi

    2015-01-01

    Non-homologous end joining (NHEJ) is a major pathway to repair DNA double-strand breaks (DSBs), which can display different types of broken ends. However, it is unclear how NHEJ factors organize to repair diverse types of DNA breaks. Here, through systematic analysis of the human NHEJ factor interactome, we identify PAXX as a direct interactor of Ku. The crystal structure of PAXX is similar to those of XRCC4 and XLF. Importantly, PAXX-deficient cells are sensitive to DSB-causing agents. Moreover, epistasis analysis demonstrates that PAXX functions together with XLF in response to ionizing radiation-induced complex DSBs, whereas they function redundantly in response to Topo2 inhibitor-induced simple DSBs. Consistently, PAXX and XLF coordinately promote the ligation of complex but not simple DNA ends in vitro. Altogether, our data identify PAXX as a new NHEJ factor and provide insight regarding the organization of NHEJ factors responding to diverse types of DSB ends. PMID:25670504

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

    PubMed

    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

  3. A non-synonymous single-nucleotide polymorphism associated with multiple sclerosis risk affects the EVI5 interactome.

    PubMed

    Didonna, Alessandro; Isobe, Noriko; Caillier, Stacy J; Li, Kathy H; Burlingame, Alma L; Hauser, Stephen L; Baranzini, Sergio E; Patsopoulos, Nikolaos A; Oksenberg, Jorge R

    2015-12-15

    Despite recent progress in the characterization of genetic loci associated with multiple sclerosis (MS) risk, the ubiquitous linkage disequilibrium operating across the genome has stalled efforts to distinguish causative variants from proxy single-nucleotide polymorphisms (SNPs). Here, we have identified through fine mapping and meta-analysis EVI5 as the most plausible disease risk gene within the 1p22.1 locus. We further show that an exonic SNP associated with risk induces changes in superficial hydrophobicity patterns of the coiled-coil domain of EVI5, which, in turns, affects the EVI5 interactome. Immunoprecipitation of wild-type and mutated EVI5 followed by mass spectrometry generated a roster of disease-specific interactors functionally linked to lipid metabolism. Among the exclusive binding partners of the risk variant, we describe the novel interaction with sphingosine 1-phosphate lyase (SGPL1)-a key enzyme for the creation of the sphingosine-1 phosphate gradient, which is relevant to the pathogenic process and therapeutic management of MS. PMID:26433934

  4. Proteomic identification of Hsc70 as a mediator of RGS9-2 degradation by in vivo interactome analysis

    PubMed Central

    Posokhova, Ekaterina; Uversky, Vladimir; Martemyanov, Kirill A.

    2010-01-01

    Changes in interactions between signaling proteins underlie many cellular functions. In the mammalian nervous system a member of the Regulator of G protein Signaling family, RGS9-2 (Regulator of G protein Signaling, type 9) is a key regulator of dopamine and opioid signaling pathways that mediate motor control and reward behavior. Dynamic association of RGS9-2 with a neuronal protein R7BP (R7 family Binding Protein) has been found to be critically important for the regulation of the expression level of the complex by proteolytic mechanisms. Changes in RGS9-2 expression are observed in response to a number of signaling events and are thought to contribute to the plasticity of the neurotransmitter action. In this study, we report an identification of molecular chaperone Hsc70 (Heat shock cognate protein 70) as a critical mediator of RGS9-2 expression that is specifically recruited to the intrinsically disordered C-terminal domain of RGS9-2 following its dissociation from R7BP. Hsc70 was identified by a novel application of the quantitative proteomics approach developed to monitor interactome dynamics in mice using a set of controls contributed by knockout strains. We propose this application to be a useful tool for studying the dynamics of protein assemblies in complex models, such as signaling in the mammalian nervous system. PMID:20095651

  5. 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-sensitive vector-borne diseases. PMID:26154506

  6. 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 speculate that small molecule activators of HspB2 might be deployed to mitigate mitochondrial related diseases such as cardiomyopathy and neurodegenerative disease. PMID:26465331

  7. ORIGINAL PAPER Regional landslide susceptibility: spatiotemporal

    E-print Network

    ORIGINAL PAPER Regional landslide susceptibility: spatiotemporal variations under dynamic soil / Accepted: 25 April 2011 Ó Springer Science+Business Media B.V. 2011 Abstract Quantification of landslide and number of periods during which sites are highly susceptible. Because the mapped landslide locations

  8. Recursive Sparse, Spatiotemporal Coding Thomas Dean

    E-print Network

    Cortes, Corinna

    Recursive Sparse, Spatiotemporal Coding Thomas Dean Google Inc. tld@google.com Greg Corrado Stanford University gcorrado@stanford.edu Rich Washington Google Inc. rwashington@google.com Abstract We greater success using L1 regularized regression in a variation on Olshausen and Field's original SPARSENET

  9. Towards distributed coverage of complex spatiotemporal profiles

    E-print Network

    Hu, Huosheng

    distributed hazardous substance is presented. Such a resource would enable humans observe and stay away fromTowards distributed coverage of complex spatiotemporal profiles John Oyekan and Huosheng Hu School monitoring, Bio-inspired Algorithms, Optimal Coverage, Template learning. I. INTRODUCTION Monitoring

  10. METHODS FOR SPATIOTEMPORAL DITHERING Jeffrey B. Mulligan

    E-print Network

    Watson, Andrew B.

    METHODS FOR SPATIOTEMPORAL DITHERING N Jeffrey B. Mulligan ASA Ames Research Center 1. Introduction The problem of representing gray-level images o on a binary display device is known as "dithering" r evoke a sensation approximating that of a y e uniform gray area even when the individual displa lements

  11. 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.

  12. 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.

  13. 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.

  14. The spatiotemporal transfer function of the Limulus lateral eye

    PubMed Central

    1978-01-01

    The dynamics of the Limulus retina may be well described by the spatiotemporal transfer function, which measures the response of the eye to moving sinusoidal gratings. We consider a model for this system, which incorporates an excitatory generator potential, and self- and lateral inhibitory processes. Procedures are described which allow estimation of parameters for the model consistent with the empirical transfer function data. Transfer functions calculated from the model show good agreement with laboratory measurements, and may be used to predict accurately the response of the eye to arbitrary moving stimuli. The model allows convenient interpretation of the transfer function measurements in terms of physiological processes which underly the response of the Limulus retina. PMID:211177

  15. Resonant spatio-temporal forcing of oscillatory media

    NASA Astrophysics Data System (ADS)

    Utzny, C.; Zimmermann, W.; Bär, M.

    2002-01-01

    An extension of the complex Ginzburg-Landau equation describing resonant spatio-temporal forcing of oscillatory media is investigated. Periodic forcing in space and time leads to spatial structures with two different symmetries: harmonic patterns with the same and subharmonic patterns with twice the wavelength of the external forcing. A linear stability analysis of the homogeneous state carried out analytically leads to subharmonic patterns for intermediate forcing strength, while harmonic modes prevail for very weak and strong forcing amplitudes. Numerical simulations confirm the analytical predictions for weak forcing and show coexistence between the two types of patterns beyond threshold. In addition, traveling localized patterns such as phase flips in subharmonic patterns and traveling patches of subharmonic patterns in a harmonic background have been discovered. In the parameter range of Benjamin-Feir turbulence, stable subharmonic patterns occur upon forcing, which undergo a transition scenario back to irregular dynamics for increasing values of the control parameter.

  16. Working with Spatio-Temporal Data Type

    NASA Astrophysics Data System (ADS)

    Raza, A.

    2012-07-01

    Several aspects of spatiotemporal databases have been explored in past decades, ranging from basic data structure to query processing and indexing. But today, operational temporal GIS does not exist. The key impediments have been the complexity of integrating space and time and the lack of standards. OpenGIS standards for simple feature access (spatial type) do exist, but unlike the spatial type, standards for spatiotemporal data type do not exist. This paper explores a new approach to modeling space and time to provide the basis for implementing a temporal GIS. This approach is based on the concept of data types in databases. A data type provides constructors, accessors, and operators. Most commercial and open source databases provide data types to deal with the spatial component of a GIS, called spatial type. Oracle Spatial, DB2 Spatial Extender and Informix Spatial DataBlade, ST_Geometry for PostgreSQL and Oracle from Esri, PostGIS for PostgreSQL, etc., are some examples. This new spatiotemporal data type is called spatiotemporal type (STT). This STT is implemented in PostgreSQL, an open source relational database management system. The STT is an extension of Esri's ST_Geometry type for PostgreSQL, in which each spatial object has a life span. Constructors, accessors, and relational functions are provided to create STT and support spatial, spatiotemporal, and temporal queries. Some functions are extended based on OpenGIS standards for the spatial type. Examples are provided to demonstrate the application of these functions. The paper concludes with limitations and challenges of implementing STT.

  17. 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

  18. 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:21420499

  19. Spatiotemporal-specific lncRNAs in the brain, colon, liver and lung of macaque during development.

    PubMed

    Li, Feng; Xiao, Yun; Huang, Fei; Deng, Wei; Zhao, Hongying; Shi, Xinrui; Wang, Shuyuan; Yu, Xuexin; Zhang, Lianfeng; Han, Zujing; Luo, Longhai; Zhu, Qianhua; Jiang, Wei; Cheng, Shujun; Li, Xia; Zhang, Kaitai

    2015-11-10

    Genome-wide expression profiling during development provides useful information to uncover the potential molecular mechanisms of development in mammals. Recent studies have revealed that a subset of lncRNAs can regulate major biological processes during development. Here, we sequenced four tissues, including brain, colon, liver and lung, using RNA-seq across three developmental stages (early, middle and late stage), and then constructed genome-wide expression profiles during macaque development. In each tissue, we identified developmental time-specific lncRNA and mRNA clusters that displayed diverse expression alteration patterns, including a gradual increase, a gradual decrease, or a reversal of expression. These lncRNAs showed more specific functional associations with their corresponding tissues relative to the developmental time-specific mRNAs. Furthermore, we identified 20 spatiotemporal-specific co-modules including 101 lncRNAs and 609 mRNAs distributed at different developmental stages in different tissues. Our findings suggested that lncRNAs could play critical roles in the development of macaques through close cooperation with mRNAs. Finally, we predicted the functions of the spatiotemporal-specific lncRNAs by their spatiotemporal cooperation with mRNAs and further validated our findings using gene knockdown data of mouse. Our study reveals the spatiotemporal characteristics of lncRNAs and provides a functional map of the spatiotemporal-specific lncRNAs during the development of macaques. PMID:26456323

  20. 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

  1. Mining spatiotemporal co-occurrence patterns in solar datasets

    NASA Astrophysics Data System (ADS)

    Aydin, B.; Kempton, D.; Akkineni, V.; Angryk, R.; Pillai, K. G.

    2015-11-01

    We address the problem of mining spatiotemporal co-occurrence patterns (STCOPs) in solar datasets with extended polygon-based geometric representations. Specifically designed spatiotemporal indexing techniques are used in the mining of STCOPs. These include versions of two well-known spatiotemporal trajectory indexing techniques: the scalable and efficient trajectory index and Chebyshev polynomial indexing. We present a framework, STCOP-MINER, implementing a filter-and-refine STCOP mining algorithm, with the indexing techniques mentioned for efficiently performing data analysis.

  2. Spatiotemporal coupling in dispersive nonlinear planar waveguides

    NASA Astrophysics Data System (ADS)

    Ryan, Andrew T.; Agrawal, Govind P.

    1995-12-01

    The multidimensional nonlinear Schrodinger equation governs the spatial and temporal evolution of an optical field inside a nonlinear dispersive medium. Although spatial (diffractive) and temporal (dispersive) effects can be studied independently in a linear medium, they become mutually coupled in a nonlinear medium. We present the results of numerical simulations showing this spatiotemporal coupling for ultrashort pulses propagating in dispersive Kerr media. We investigate how spatiotemporal coupling affects the behavior of the optical field in each of the four regimes defined by the type of group-velocity dispersion (normal or anomalous) and the type of nonlinearity (focusing or defocusing). We show that dispersion, through spatiotemporal coupling, can either enhance or suppress self-focusing and self-defocusing. Similarly, we demonstrate that diffraction can either enhance or suppress pulse compression or broadening. We also discuss how these effects can be controlled with optical phase modulation, such as that provided by a lens (spatial phase modulation) or frequency chirping (temporal phase modulation). Copyright (c) 1995 Optical Society of America

  3. Spatiotemporal transcriptome of the human brain

    PubMed Central

    Kang, Hyo Jung; Kawasawa, Yuka Imamura; Cheng, Feng; Zhu, Ying; Xu, Xuming; Li, Mingfeng; Sousa, André M. M.; Pletikos, Mihovil; Meyer, Kyle A.; Sedmak, Goran; Guennel, Tobias; Shin, Yurae; Johnson, Matthew B.; Krsnik, Željka; Mayer, Simone; Fertuzinhos, Sofia; Umlauf, Sheila; Lisgo, Steven N.; Vortmeyer, Alexander; Weinberger, Daniel R.; Mane, Shrikant; Hyde, Thomas M.; Huttner, Anita; Reimers, Mark; Kleinman, Joel E.; Šestan, Nenad

    2012-01-01

    Summary Here we report the generation and analysis of genome-wide exon-level transcriptome data from 16 brain regions comprising the cerebellar cortex, mediodorsal nucleus of the thalamus, striatum, amygdala, hippocampus, and 11 areas of the neocortex. The dataset was generated from 1,340 tissue samples collected from one or both hemispheres of 57 postmortem human brains, spanning from embryonic development to late adulthood and representing males and females of multiple ethnicities. We also performed genotyping of 2.5 million SNPs and assessed copy number variations for all donors. Approximately 86% of protein-coding genes were found to be expressed using stringent criteria, and over 90% of these were differentially regulated at the whole transcript or exon level across regions and/or time. The majority of these spatiotemporal differences occurred before birth, followed by an increase in the similarity among regional transcriptomes during postnatal lifespan. Genes were organized into functionally distinct co-expression networks, and sex differences were present in gene expression and exon usage. Finally, we demonstrate how these results can be used to profile trajectories of genes associated with neurodevelopmental processes, cell types, neurotransmitter systems, autism, and schizophrenia, as well as to discover associations between SNPs and spatiotemporal gene expression. This study provides a comprehensive, publicly available dataset on the spatiotemporal human brain transcriptome and new insights into the transcriptional foundations of human neurodevelopment. PMID:22031440

  4. 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. PMID:26133675

  5. 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.

  6. Controlling spatiotemporal chaos in active dissipative-dispersive nonlinear systems

    NASA Astrophysics Data System (ADS)

    Gomes, S. N.; Pradas, M.; Kalliadasis, S.; Papageorgiou, D. T.; Pavliotis, G. A.

    2015-08-01

    We present an alternative methodology for the stabilization and control of infinite-dimensional dynamical systems exhibiting low-dimensional spatiotemporal chaos. We show that with an appropriate choice of time-dependent controls we are able to stabilize and/or control all stable or unstable solutions, including steady solutions, traveling waves (single and multipulse ones or bound states), and spatiotemporal chaos. We exemplify our methodology with the generalized Kuramoto-Sivashinsky equation, a paradigmatic model of spatiotemporal chaos, which is known to exhibit a rich spectrum of wave forms and wave transitions and a rich variety of spatiotemporal structures.

  7. Algorithms for enhanced spatiotemporal imaging of human brain function

    E-print Network

    Krishnaswamy, Pavitra

    2014-01-01

    Studies of human brain function require technologies to non-invasively image neuronal dynamics with high spatiotemporal resolution. The electroencephalogram (EEG) and magnetoencephalogram (MEG) measure neuronal activity ...

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

    NASA Astrophysics Data System (ADS)

    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.

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

    PubMed Central

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

    2015-01-01

    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. PMID:26631976

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

    PubMed

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

    2015-01-01

    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. PMID:26631976

  11. MINING SPATIOTEMPORAL CO-OCCURRENCE PATTERNS FROM MASSIVE DATA SETS WITH EVOLVING REGIONS

    E-print Network

    Dyer, Bill

    MINING SPATIOTEMPORAL CO-OCCURRENCE PATTERNS FROM MASSIVE DATA SETS WITH EVOLVING REGIONS.5 Spatiotemporal Data Mining.....................................................................9 3. CURRENT...........................................................................................5 2.1 Spatial Data Types

  12. Spatio-temporal population estimates for risk management

    NASA Astrophysics Data System (ADS)

    Cockings, Samantha; Martin, David; Smith, Alan; Martin, Rebecca

    2013-04-01

    Accurate estimation of population at risk from hazards and effective emergency management of events require not just appropriate spatio-temporal modelling of hazards but also of population. While much recent effort has been focused on improving the modelling and predictions of hazards (both natural and anthropogenic), there has been little parallel advance in the measurement or modelling of population statistics. Different hazard types occur over diverse temporal cycles, are of varying duration and differ significantly in their spatial extent. Even events of the same hazard type, such as flood events, vary markedly in their spatial and temporal characteristics. Conceptually and pragmatically then, population estimates should also be available for similarly varying spatio-temporal scales. Routine population statistics derived from traditional censuses or surveys are usually static representations in both space and time, recording people at their place of usual residence on census/survey night and presenting data for administratively defined areas. Such representations effectively fix the scale of population estimates in both space and time, which is unhelpful for meaningful risk management. Over recent years, the Pop24/7 programme of research, based at the University of Southampton (UK), has developed a framework for spatio-temporal modelling of population, based on gridded population surfaces. Based on a data model which is fully flexible in terms of space and time, the framework allows population estimates to be produced for any time slice relevant to the data contained in the model. It is based around a set of origin and destination centroids, which have capacities, spatial extents and catchment areas, all of which can vary temporally, such as by time of day, day of week, season. A background layer, containing information on features such as transport networks and landuse, provides information on the likelihood of people being in certain places at specific times. Unusual patterns associated with special events can also be modelled and the framework is fully volume preserving. Outputs from the model are gridded population surfaces for the specified time slice, either for total population or by sub-groups (e.g. age). Software to implement the models (SurfaceBuilder247) has been developed and pre-processed layers for typical time slices for England and Wales in 2001 and 2006 are available for UK academic purposes. The outputs and modelling framework from the Pop24/7 programme provide significant opportunities for risk management applications. For estimates of mid- to long-term cumulative population exposure to hazards, such as in flood risk mapping, populations can be produced for numerous time slices and integrated with flood models. For applications in emergency response/ management, time-specific population models can be used as seeds for agent-based models or other response/behaviour models. Estimates for sub-groups of the population also permit exploration of vulnerability through space and time. This paper outlines the requirements for effective spatio-temporal population models for risk management. It then describes the Pop24/7 framework and illustrates its potential for risk management through presentation of examples from natural and anthropogenic hazard applications. The paper concludes by highlighting key challenges for future research in this area.

  13. 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.

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

    PubMed Central

    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. PMID:26516188

  15. Mapping the miRNA interactome by crosslinking ligation and sequencing of hybrids (CLASH)

    PubMed Central

    Helwak, Aleksandra; Tollervey, David

    2014-01-01

    RNA-RNA interactions play critical roles in many cellular processes but studying them is difficult and laborious. Here, we describe an experimental procedure, termed crosslinking ligation and sequencing of hybrids (CLASH), which allows high-throughput identification of sites of RNA-RNA interaction. During CLASH, a tagged bait protein is UV crosslinked in vivo to stabilise RNA interactions and purified under denaturing conditions. RNAs associated with the bait protein are partially truncated, and the ends of RNA-duplexes are ligated together. Following linker addition, cDNA library preparation and high-throughput sequencing, the ligated duplexes give rise to chimeric cDNAs, which unambiguously identify RNA-RNA interaction sites independent of bioinformatic predictions. This protocol is optimized for studying miRNA targets bound by Argonaute proteins, but should be easily adapted for other RNA-binding proteins and classes of RNA. The protocol requires around 5 days to complete, excluding the time required for high-throughput sequencing and bioinformatic analyses. PMID:24577361

  16. Gestural Interaction with Spatiotemporal Linked Open Data Gestural Interaction with Spatiotemporal

    E-print Network

    Köbben, Barend

    - grated into an exhibit. We present a set of gestures that visitors to a science fair can use to explore Information Science to the pub- lic, for example in an exhibition, in a science museum or science center for complex spatiotemporal data is a contribution towards Linked Open Science [14] to support transparency

  17. 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…

  18. Fast Spatiotemporal Smoothing of Calcium Measurements in Dendritic Trees

    E-print Network

    Columbia University

    1 Fast Spatiotemporal Smoothing of Calcium Measurements in Dendritic Trees Eftychios A Institute for Biological Studies, La Jolla, CA, USA Abstract We discuss methods for fast spatiotemporal through a smaller set of hidden vari- ables that incorporate fast transients due to backpropagating action

  19. Chronus: A Spatiotemporal Macroprogramming Language for Autonomic Wireless Sensor Networks

    E-print Network

    Suzuki, Jun

    to the current event. This chapter proposes a new programming paradigm, called spatiotemporal macroprogram- ming Science University of Massachusetts, Boston Boston, MA 02125-3393, USA This chapter considers autonomic wireless sensor networks (WSNs) to detect and monitor spatiotemporally dynamic events, which dynamically

  20. 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…

  1. Spacetime Texture Representation and Recognition Based on a Spatiotemporal

    E-print Network

    Wildes, Richard P.

    1 Spacetime Texture Representation and Recognition Based on a Spatiotemporal Orientation Analysis and recognition of the observed dynamics (i.e., excluding purely spatial appearance cues) of spacetime texture based on a spatiotemporal orientation analysis. The term "spacetime texture" is taken to refer

  2. The nuclear basket proteins Mlp1p and Mlp2p are part of a dynamic interactome including Esc1p and the proteasome

    PubMed Central

    Niepel, Mario; Molloy, Kelly R.; Williams, Rosemary; Farr, Julia C.; Meinema, Anne C.; Vecchietti, Nicholas; Cristea, Ileana M.; Chait, Brian T.; Rout, Michael P.; Strambio-De-Castillia, Caterina

    2013-01-01

    The basket of the nuclear pore complex (NPC) is generally depicted as a discrete structure of eight protein filaments that protrude into the nucleoplasm and converge in a ring distal to the NPC. We show that the yeast proteins Mlp1p and Mlp2p are necessary components of the nuclear basket and that they also embed the NPC within a dynamic protein network, whose extended interactome includes the spindle organizer, silencing factors, the proteasome, and key components of messenger ribonucleoproteins (mRNPs). Ultrastructural observations indicate that the basket reduces chromatin crowding around the central transporter of the NPC and might function as a docking site for mRNP during nuclear export. In addition, we show that the Mlps contribute to NPC positioning, nuclear stability, and nuclear envelope morphology. Our results suggest that the Mlps are multifunctional proteins linking the nuclear transport channel to multiple macromolecular complexes involved in the regulation of gene expression and chromatin maintenance. PMID:24152732

  3. Spatiotemporal rogue events in femtosecond filamentation

    SciTech Connect

    Majus, D.; Jukna, V.; Valiulis, G.; Dubietis, A.; Faccio, D.

    2011-02-15

    We present experimental and numerical investigations of optical extreme (rogue) event statistics recorded in the regime of femtosecond pulse filamentation in water. In the spectral domain, the extreme events manifest themselves as either large or small extremes of the spectral intensity, justified by right- or left-tailed statistical distributions, respectively. In the time domain, the observed extreme events are associated with pulse splitting and energy redistribution in space and therefore are exquisitely linked to three-dimensional, spatiotemporal dynamics and formation of the X waves.

  4. 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. PMID:26258340

  5. 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.

  6. 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

  7. 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).

  8. 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.

  9. Spatio-temporal autocorrelation measures for nonstationary series: A new temporally detrended spatio-temporal Moran's index

    NASA Astrophysics Data System (ADS)

    Shen, Chenhua; Li, Chaoling; Si, Yali

    2016-01-01

    In order to measure the spatio-temporal autocorrelation's degree for spatio-temporal nonstationary series, the new temporally detrended global and local spatio-temporal Moran's indexes (TDGSTI and TDLSTI) are proposed. The implementation of the new Moran's indexes is illustrated through artificial and real examples. Analyses of the influencing factors on TDGSTI are performed. A statistical test of TDGSTI is taken. The Moran's scatter plot, which discloses the spatio-temporal cluster pattern's characteristics and pattern's change, is extended. TDGSTI is found to reveal the autocorrelation level of spatio-temporal objects. For a positive TDGSTI, the higher the TDGSTI, the higher the autocorrelation level, and vice versa. TDGSTI is closely related to time-scale s, time-lag h and spatio-temporal weight matrix. For s ? h, TDGSTI is significant, while for s ? h and s < h, TDGSTI is insignificant. TDGSTI has clear potential to test the spatio-temporal autocorrelation's degree for spatio-temporal nonstationary series in other research fields.

  10. Predicting Peptide-Mediated Interactions on a Genome-Wide Scale

    PubMed Central

    Chen, T. Scott; Petrey, Donald; Garzon, Jose Ignacio; Honig, Barry

    2015-01-01

    We describe a method to predict protein-protein interactions (PPIs) formed between structured domains and short peptide motifs. We take an integrative approach based on consensus patterns of known motifs in databases, structures of domain-motif complexes from the PDB and various sources of non-structural evidence. We combine this set of clues using a Bayesian classifier that reports the likelihood of an interaction and obtain significantly improved prediction performance when compared to individual sources of evidence and to previously reported algorithms. Our Bayesian approach was integrated into PrePPI, a structure-based PPI prediction method that, so far, has been limited to interactions formed between two structured domains. Around 80,000 new domain-motif mediated interactions were predicted, thus enhancing PrePPI’s coverage of the human protein interactome. PMID:25938916

  11. 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

  12. Controllable spatiotemporal nonlinear effects in multimode fibres

    NASA Astrophysics Data System (ADS)

    Wright, Logan G.; Christodoulides, Demetrios N.; Wise, Frank W.

    2015-05-01

    Multimode fibres are of interest for next-generation telecommunications systems and the construction of high-energy fibre lasers. However, relatively little work has explored nonlinear pulse propagation in multimode fibres. Here, we consider highly nonlinear ultrashort pulse propagation in the anomalous-dispersion regime of a graded-index multimode fibre. Low modal dispersion and strong nonlinear coupling between the fibre's many spatial modes result in interesting behaviour. We observe spatiotemporal effects reminiscent of nonlinear optics in bulk media—self-focusing and multiple filamentation—at a fraction of the usual power. By adjusting the spatial initial conditions, we generate on-demand, megawatt, ultrashort pulses tunable between 1,550 and 2,200?nm dispersive waves over one octave; intense combs of visible light; and a multi-octave-spanning supercontinuum. Our results indicate that multimode fibres present unique opportunities for observing new spatiotemporal dynamics and phenomena. They also enable the realization of a new type of tunable, broadband fibre source that could be useful for many applications.

  13. Responses of spatiotemporal chaos to oscillating forces

    NASA Astrophysics Data System (ADS)

    Iino, Misato; Hidaka, Yoshiki; Nugroho, Fahrudin; Anugraha, Rinto; Okabe, Hirotaka; Hara, Kazuhiro

    2015-07-01

    The responses of soft-mode turbulence, a kind of spatiotemporal chaos seen in electroconvection of a nematic liquid crystal, to alternating-current magnetic fields is investigated to uncover the dynamical properties of spatiotemporal chaos. The dynamical responses can be measured by an order parameter, Mp(t ) , which indicates ordering in the convective roll pattern induced by the magnetic field. Determined by properties of the liquid crystal in a magnetic field, Mp(t ) oscillates in accordance with the square of the magnetic field. The relaxation time of the system was obtained by fitting the frequency dependence of the complex susceptibility for the pattern obtained from the oscillation of Mp(t ) to the Debye-type relaxation spectra. However, for the high-frequency regime, the susceptibility deviates from the spectra because slow and large fluctuations of Mp(t ) contribute to the oscillation. The properties of this type of fluctuation were investigated by introducing a dynamic ordering parameter defined as the period average of Mp(t ) .

  14. Bilinearity in Spatiotemporal Integration of Synaptic Inputs

    PubMed Central

    Li, Songting; Liu, Nan; Zhang, Xiao-hui; Zhou, Douglas; Cai, David

    2014-01-01

    Neurons process information via integration of synaptic inputs from dendrites. Many experimental results demonstrate dendritic integration could be highly nonlinear, yet few theoretical analyses have been performed to obtain a precise quantitative characterization analytically. Based on asymptotic analysis of a two-compartment passive cable model, given a pair of time-dependent synaptic conductance inputs, we derive a bilinear spatiotemporal dendritic integration rule. The summed somatic potential can be well approximated by the linear summation of the two postsynaptic potentials elicited separately, plus a third additional bilinear term proportional to their product with a proportionality coefficient . The rule is valid for a pair of synaptic inputs of all types, including excitation-inhibition, excitation-excitation, and inhibition-inhibition. In addition, the rule is valid during the whole dendritic integration process for a pair of synaptic inputs with arbitrary input time differences and input locations. The coefficient is demonstrated to be nearly independent of the input strengths but is dependent on input times and input locations. This rule is then verified through simulation of a realistic pyramidal neuron model and in electrophysiological experiments of rat hippocampal CA1 neurons. The rule is further generalized to describe the spatiotemporal dendritic integration of multiple excitatory and inhibitory synaptic inputs. The integration of multiple inputs can be decomposed into the sum of all possible pairwise integration, where each paired integration obeys the bilinear rule. This decomposition leads to a graph representation of dendritic integration, which can be viewed as functionally sparse. PMID:25521832

  15. Using atmospheric observations to evaluate the spatiotemporal variability of CO2 fluxes simulated by terrestrial biospheric models

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

    Terrestrial biospheric models (TBMs) are used to extrapolate local observations and process-level understanding of land-atmosphere carbon exchange to larger regions, and serve as predictive tools for examining carbon-climate interactions. Understanding the performance of TBMs is thus crucial to the carbon cycle and climate science communities. In this study, we present and assess an approach to evaluating the spatiotemporal patterns, rather than aggregated magnitudes, of net ecosystem exchange (NEE) simulated by TBMs using atmospheric CO2 measurements. The approach is based on statistical model selection implemented within a high-resolution atmospheric inverse model. Using synthetic data experiments, we find that current atmospheric observations are sensitive to the underlying spatiotemporal flux variability at sub-biome scales for a large portion of North America, and that atmospheric observations can therefore be used to evaluate simulated spatiotemporal flux patterns as well as to differentiate between multiple competing TBMs. Experiments using real atmospheric observations and four prototypical TBMs further confirm the applicability of the method, and demonstrate that the performance of TBMs in simulating the spatiotemporal patterns of NEE varies substantially across seasons, with best performance during the growing season and more limited skill during transition seasons. This result is consistent with previous work showing that the ability of TBMs to model flux magnitudes is also seasonally-dependent. Overall, the proposed approach provides a new avenue for evaluating TBM performance based on sub-biome-scale flux patterns, presenting an opportunity for assessing and informing model development using atmospheric observations.

  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. 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.

  18. 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

  19. 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

    2014-01-01

    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

  20. Spatiotemporal modeling and analysis of transient gene delivery.

    PubMed

    Jandt, Uwe; Shao, Shi; Wirth, Manfred; Zeng, An-Ping

    2011-09-01

    A quantitative and mechanistic understanding of intracellular transport processes in eukaryotic cells during transient transfection is an important prerequisite for the systematic and specific optimization of transient gene expression procedures for pharmaceutic and industrial protein production. There is evidence that intracellular transport processes during gene delivery and their regulation may have significant influence on the transfection efficiency. This contribution describes a compartmented, spatiotemporally resolved and stochastic modeling approach that describes intracellular transport processes responsible for gene delivery during transient transfection. It enables a detailed prediction and analysis and identification of potential bottlenecks. This model is currently being adapted to a model cell line, HEK293s. The simulated results are compared with experimental quantitative polymerase chain reaction (qPCR) data and confocal imaging data obtained with transfected and stained HEK293 cells. Global parameter estimation is performed to qPCR data based on two different novel plasmid constructs in order to identify candidates for plasmid-specific transport parameter variations. The influence of the specific property of HEK293 cells to grow in clusters is investigated and the impact of active microtubule transport depending on cell morphology and clustering is examined. A general sensitivity analysis allows for the identification of the sensitive parameters. PMID:21538332

  1. Spatiotemporal characteristics of soil temperature memory in China from observation

    NASA Astrophysics Data System (ADS)

    Yang, Kai; Zhang, Jingyong

    2015-08-01

    Similar to soil moisture, soil temperature has a memory of atmospheric anomalies. However, soil temperature memory over China is still largely unclear, especially in observation. In this study, we investigate the spatiotemporal characteristics of soil temperature memory over China using subsurface (10-80 cm) and deep (160-320 cm) soil temperature data for 626 stations during the period of 1981 to 2005. The red noise method is adopted to estimate soil temperature memory. Results show that the soil temperature memory differs spatially and varies with soil depth and season. Influenced by climate regimes, soil temperature memory at all six layers (with depths of 10, 20, 40, 80, 160, and 320 cm) shows a similar spatial pattern dominated by a northwest to southeast gradient, with relatively high values over arid and semiarid areas of northwestern part of China and relatively low values over humid and semihumid areas of southeastern part of China. During all four seasons, memory lengths increase with soil depth. The average memory of subsurface soil over China can last several months, and for soil at 320 cm, it can be 1 year or more. We also find that seasonal and regional differences of soil temperature memory are stronger in deep soil layers than those in subsurface soil layers. Our findings suggest that soil temperature memory can offer potential for improving seasonal climate prediction over northwestern China. In the meanwhile, the limitations of the methods used in this study should be recognized.

  2. 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

  3. 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.

  4. Emergence of spatiotemporal dislocation chains in drifting patterns

    NASA Astrophysics Data System (ADS)

    Clerc, M. G.; Falcón, C.; García-Áustes, M. A.; Odent, V.; Ortega, I.

    2014-06-01

    One-dimensional patterns subjected to counter-propagative flows or speed jumps exhibit a rich and complex spatiotemporal dynamics, which is characterized by the perpetual emergence of spatiotemporal dislocation chains. Using a universal amplitude equation of drifting patterns, we show that this behavior is a result of a combination of a phase instability and an advection process caused by an inhomogeneous drift force. The emergence of spatiotemporal dislocation chains is verified in numerical simulations on an optical feedback system with a non-uniform intensity pump. Experimentally this phenomenon is also observed in a tilted quasi-one-dimensional fluidized shallow granular bed mechanically driven by a harmonic vertical vibration.

  5. Emergence of spatiotemporal dislocation chains in drifting patterns.

    PubMed

    Clerc, M G; Falcón, C; García-Ñustes, M A; Odent, V; Ortega, I

    2014-06-01

    One-dimensional patterns subjected to counter-propagative flows or speed jumps exhibit a rich and complex spatiotemporal dynamics, which is characterized by the perpetual emergence of spatiotemporal dislocation chains. Using a universal amplitude equation of drifting patterns, we show that this behavior is a result of a combination of a phase instability and an advection process caused by an inhomogeneous drift force. The emergence of spatiotemporal dislocation chains is verified in numerical simulations on an optical feedback system with a non-uniform intensity pump. Experimentally this phenomenon is also observed in a tilted quasi-one-dimensional fluidized shallow granular bed mechanically driven by a harmonic vertical vibration. PMID:24985447

  6. Spatiotemporal localized modes in PT-symmetric optical media

    SciTech Connect

    Wang, Yue-Yue; Dai, Chao-Qing Wang, Xiao-Gang

    2014-09-15

    We firstly obtain spatiotemporal localized mode solutions of a (3+1)-dimensional nonlinear Schrödinger equation in PT-symmetric potentials, and then discuss the linear stability of LMs, which are also tested by means of direct simulations. Moreover, phase switches and transverse power-flow density associated with these localized modes have also been examined. At last, we investigate the dynamical behaviors of spatiotemporal LMs in three kinds of inhomogeneous media. - Highlights: • Spatiotemporal LMs of a (3+1)-dimensional NLSE in PT-symmetric potentials are obtained. • Phase switches and transverse power-flow density of LM are examined. • Dynamical behaviors of LMs in three kinds of inhomogeneous media are studied.

  7. 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.

  8. 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 ?m (PM2.5; fine particles), ? 10 ?m, and 2.5–10 ?m, 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 topic. Citation: Dadvand P, Figueras F, Basagaña X, Beelen R, Martinez D, Cirach M, Schembari A, Hoek G, Brunekreef B, Nieuwenhuijsen MJ. 2013. Ambient air pollution and preeclampsia: a spatiotemporal analysis. Environ Health Perspect 121:1365–1371;?http://dx.doi.org/10.1289/ehp.1206430 PMID:24021707

  9. Predicting the Fission Yeast Protein Interaction Network

    PubMed Central

    Pancaldi, Vera; Saraç, Ömer S.; Rallis, Charalampos; McLean, Janel R.; P?evorovský, Martin; Gould, Kathleen; Beyer, Andreas; Bähler, Jürg

    2012-01-01

    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). PMID:22540037

  10. 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

  11. Secure communication based on spatiotemporal chaos

    NASA Astrophysics Data System (ADS)

    Ren, Hai-Peng; Bai, Chao

    2015-08-01

    In this paper, we propose a novel approach to secure communication based on spatiotemporal chaos. At the transmitter end, the state variables of the coupled map lattice system are divided into two groups: one is used as the key to encrypt the plaintext in the N-shift encryption function, and the other is used to mix with the output of the N-shift function to further confuse the information to transmit. At the receiver end, the receiver lattices are driven by the received signal to synchronize with the transmitter lattices and an inverse procedure of the encoding is conducted to decode the information. Numerical simulation and experiment based on the TI TMS320C6713 Digital Signal Processor (DSP) show the feasibility and the validity of the proposed scheme. Project supported by the National Natural Science Foundation of China (Grant No. 61172070) and the Funds from the Science and Technology Innovation Team of Shaanxi Province, China (Grant No. 2013CKT-04).

  12. 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

  13. Spatiotemporal dynamics of counterpropagating Airy beams.

    PubMed

    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

  14. Spatiotemporal structure of isodiffracting ultrashort electromagnetic pulses

    PubMed

    Feng; Winful

    2000-01-01

    We present a model of isodiffracting single-cycle and few-cycle ultrashort electromagnetic pulses. The model is based on exact solutions of the time-dependent paraxial wave equation with space-time coupling effects included. The spatiotemporal structure of these pulses is characterized by a scaling parameter which relates off-axis pulse shapes to the axial temporal waveforms. Depending on the spectrum a pulse may transform itself from a single-cycle pulse to a multicycle pulse along the radial coordinate. This model is also used to describe recirculating pulses in a curved mirror cavity resonator. The Gouy phase shift contributes an absolute phase that results in a pulse-to-pulse temporal instability. PMID:11046334

  15. Non-invertible transformations and spatiotemporal randomness

    E-print Network

    J. A. Gonzalez; A. J. Moreno; L. E. Guerrero

    2006-02-12

    We generalize the exact solution to the Bernoulli shift map. Under certain conditions, the generalized functions can produce unpredictable dynamics. We use the properties of the generalized functions to show that certain dynamical systems can generate random dynamics. For instance, the chaotic Chua's circuit coupled to a circuit with a non-invertible I-V characteristic can generate unpredictable dynamics. In general, a nonperiodic time-series with truncated exponential behavior can be converted into unpredictable dynamics using non-invertible transformations. Using a new theoretical framework for chaos and randomness, we investigate some classes of coupled map lattices. We show that, in some cases, these systems can produce completely unpredictable dynamics. In a similar fashion, we explain why some wellknown spatiotemporal systems have been found to produce very complex dynamics in numerical simulations. We discuss real physical systems that can generate random dynamics.

  16. 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 of RNA splicing interactomes that is important for understanding T cell activation. PMID:26641092

  17. 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 remains constrained to a commensurate value of the subthreshold frequency. The stimuli induced spatio-temporal patterns can reverberate for long periods, which contributes to the computational properties of the IO. We also show that the presence of regions with different excitability levels creates sinks and sources of coordinated activity which shape the propagation of spike wave fronts. These results can be generalized beyond IO studies, as the control of wave pattern propagation is a highly relevant problem in the context of normal and pathological states in neural systems (e.g., related to tremor, migraine, epilepsy) where the study of the modulation of activity sinks and sources can have a potential large impact. PMID:24046731

  18. A full time-domain approach to spatio-temporal dynamics of semiconductor lasers. II. Spatio-temporal dynamics

    NASA Astrophysics Data System (ADS)

    Böhringer, Klaus; Hess, Ortwin

    The spatio-temporal dynamics of novel semiconductor lasers is discussed on the basis of a space- and momentum-dependent full time-domain approach. To this means the space-, time-, and momentum-dependent Full-Time Domain Maxwell Semiconductor Bloch equations, derived and discussed in our preceding paper I [K. Böhringer, O. Hess, A full time-domain approach to spatio-temporal dynamics of semiconductor lasers. I. Theoretical formulation], are solved by direct numerical integration. Focussing on the device physics of novel semiconductor lasers that profit, in particular, from recent advances in nanoscience and nanotechnology, we discuss the examples of photonic band edge surface emitting lasers (PBE-SEL) and semiconductor disc lasers (SDLs). It is demonstrated that photonic crystal effects can be obtained for finite crystal structures, and leading to a significant improvement in laser performance such as reduced lasing thresholds. In SDLs, a modern device concept designed to increase the power output of surface-emitters in combination with near-diffraction-limited beam quality, we explore the complex interplay between the intracavity optical fields and the quantum well gain material in SDL structures. Our simulations reveal the dynamical balance between carrier generation due to pumping into high energy states, momentum relaxation of carriers, and stimulated recombination from states near the band edge. Our full time-domain approach is shown to also be an excellent framework for the modelling of the interaction of high-intensity femtosecond and picosecond pulses with semiconductor nanostructures. It is demonstrated that group velocity dispersion, dynamical gain saturation and fast self-phase modulation (SPM) are the main causes for the induced changes and asymmetries in the amplified pulse shape and spectrum of an ultrashort high-intensity pulse. We attest that the time constants of the intraband scattering processes are critical to gain recovery. Moreover, we present new insight into the physics of nonlinear coherent pulse propagation phenomena in active (semiconductor) gain media. Our numerical full time-domain simulations are shown to generally agree well with analytical predictions, while in the case of optical pulses with large pulse areas or few-cycle pulses they reveal the limits of analytic approaches. Finally, it is demonstrated that coherent ultrafast nonlinear propagation effects become less distinctive if we apply a realistic model of the quantum well semiconductor gain material, consider characteristic loss channels and take into account de-phasing processes and homogeneous broadening.

  19. Using Ca-Markov Model to Model the Spatiotemporal Change of Land Use/cover in Fuxian Lake for Decision Support

    NASA Astrophysics Data System (ADS)

    Li, S. H.; Jin, B. X.; Wei, X. Y.; Jiang, Y. Y.; Wang, J. L.

    2015-07-01

    Spatiotemporal modelling of land use/cover change (LUCC) has become increasingly important in recent years, especially for environmental change and regional planning. There have been many approaches and software packages for modelling LUCC, but developing a model for a specific region is still a difficult task, because it requires large volume of data input and elaborate model adjustment. Fuxian Lake watershed is one of the most important ecological protection area in China and located in southeast of Kunming city, Yunnan province. In this paper, the CA-Markov model is used to analyse the spatiotemporal LUCC and project its course into the future. Specifically, the model uses high resolution remote sensing images of 2006 and 2009 as input data, and then makes prediction for 2014. A quantitative comparison with remote sensing images of 2014 suggests an overall accuracy of 88%. This spatiotemporal modelling method is expected to facilitate the research of many land cover and use applications modelling.

  20. Regionalised spatiotemporal rainfall and temperature models for flood studies in the Basque Country, Spain

    NASA Astrophysics Data System (ADS)

    Cowpertwait, P.; Ocio, D.; Collazos, G.; de Cos, O.; Stocker, C.

    2013-02-01

    A spatiotemporal point process model of rainfall is fitted to data taken from three homogeneous regions in the Basque Country, Spain. The model is the superposition of two spatiotemporal Neyman-Scott processes, in which rain cells are modelled as discs with radii that follow exponential distributions. In addition, the model includes a parameter for the radius of storm discs, so that rain only occurs when both a cell and a storm disc overlap a point. The model is fitted to data for each month, taken from each of the three homogeneous regions, using a modified method of moments procedure that ensures a smooth seasonal variation in the parameter estimates. Daily temperature data from 23 sites are used to fit a stochastic temperature model. A principal component analysis of the maximum daily temperatures across the sites indicates that 92% of the variance is explained by the first component, implying that this component can be used to account for spatial variation. A harmonic equation with autoregressive error terms is fitted to the first principal component. The temperature model is obtained by regressing the maximum daily temperature on the first principal component, an indicator variable for the region, and altitude. This, together with scaling and a regression model of temperature range, enables hourly temperatures to be predicted. Rainfall is included as an explanatory variable but has only a marginal influence when predicting temperatures. A distributed model (TETIS; Francés et al., 2007) is calibrated for a selected catchment. Five hundred years of data are simulated using the rainfall and temperature models and used as input to the calibrated TETIS model to obtain simulated discharges to compare with observed discharges. Kolmogorov-Smirnov tests indicate that there is no significant difference in the distributions of observed and simulated maximum flows at the same sites, thus supporting the use of the spatiotemporal models for the intended application.

  1. 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)...

  2. UNDERSTANDING SEVERE WEATHER PROCESSES THROUGH SPATIOTEMPORAL RELATIONAL RANDOM FORESTS

    E-print Network

    McGovern, Amy

    the formation of tornadoes near strong frontal boundaries, and understanding the translation of drought across. For example, a thunderstorm evolves over time and may eventually produce a tornado through the spatiotemporal

  3. Modelling pandemic influenza progression using Spatiotemporal Epidemiological Modeller (STEM)

    E-print Network

    Zhang, Hui, S.M. Massachusetts Institute of Technology

    2009-01-01

    The purpose of this project is to incorporate a Poisson disease model into the Spatiotemporal Epidemiological Modeler (STEM) and visualize the disease spread on Google Earth. It is done through developing a Poisson disease ...

  4. Title of dissertation: PROBLEMS IN SPATIOTEMPORAL CHAOS Matthew Tyler Cornick

    E-print Network

    Anlage, Steven

    spatiotemporally chaotic systems prevents the use of classical data assimilation techniques such as the Kalman filter. Here, a recently developed data assimilation method, the local ensemble transform Kalman Filter

  5. Spatiotemporal Response Properties of Optic-Flow Processing Neurons

    E-print Network

    Machens, Christian

    Neuron Article Spatiotemporal Response Properties of Optic-Flow Processing Neurons Franz Weber,1,3,* Christian K. Machens,2 and Alexander Borst1 1Department of Systems and Computational Neurobiology, Max

  6. 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.

  7. 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.

  8. Spatiotemporal patterns of induced resistance and susceptibility linking diverse plant parasites.

    PubMed

    Mouttet, Raphaëlle; Kaplan, Ian; Bearez, Philippe; Amiens-Desneux, Edwige; Desneux, Nicolas

    2013-12-01

    Induced defenses mediate interactions between parasites sharing the same host plant, but the outcomes of these interactions are challenging to predict because of spatiotemporal variation in plant responses and differences in defense pathways elicited by herbivores or pathogens. Dissecting these mediating factors necessitates an approach that encompasses a diversity of parasitic feeding styles and tracks interactions over space and time. We tested indirect plant-mediated relationships across three tomato (Solanum lycopersicum) consumers: (1) the fungal pathogen-powdery mildew, Oidium neolycopersici; (2) a sap-feeding insect-silverleaf whitefly, Bemisia tabaci; and (3) a chewing insect-the leaf miner, Tuta absoluta. Further, we evaluated insect/pathogen responses on local vs. systemic leaves and over short (1 day) vs. long (4 days) time scales. Overall, we documented: (1) a bi-directional negative effect between O. neolycopersici and B. tabaci; (2) an asymmetrical negative effect of B. tabaci on T. absoluta; and (3) an asymmetrical positive effect of T. absoluta on O. neolycopersici. Spatiotemporal patterns varied depending on the species pair (e.g., whitefly effects on leaf miner performance were highly localized to the induced leaf, whereas effects on pathogen growth were both local and systemic). These results highlight the context-dependent effects of induced defenses on a diverse community of tomato parasites. Notably, the outcomes correspond to those predicted by phytohormonal theory based on feeding guild differences with key implications for the recent European invasion by T. absoluta. PMID:23851986

  9. Spatio-temporal change modeling with array data

    NASA Astrophysics Data System (ADS)

    Lu, Meng; Pebesma, Edzer

    2015-04-01

    Spatio-temporal change modeling of our ecosystems is critical for environmental conservation. Open access to remote sensing satellite image archives provides new opportunities for change modeling, such as near real-time change monitoring with long term image time series. Newly developed time series analysis methods allow the detection of quantitative changes in trend and seasonality for each pixel of the image. A drawback of pure time series analysis is that spatial dependence is neglected. There are several spatio-temporal statistical approaches to incorporate spatial context. One method is to build hierarchical models with spatial effects for time series parameters. Other methods include representing regression parameters as spatially correlated random fields, or integrating spatial autoregressive models to time series analysis. Apart from spatio-temporal statistical modeling, the results can be further improved by qualification of detected change points with their spatio-temporal neighbors. Spatio-temporal modeling approaches are typically complex and large in scale, and call for new data management and analysis tools. Remote sensing satellite images, which are continuous and regular in space and time, can naturally be represented as three- or four-dimensional arrays for spatio-temporal data management and analysis. The developed spatio-temporal statistical algorithms can be flexibly applied within array partitions that span the relevant array-based dimensions. This study investigates the potential of array-based Data Data Management and Analytic Software (DMAS) for fast data access, data integration and large-scale complex spatio-temporal analysis. A study case is developed in near-real time deforestation monitoring in Amazonian rainforest with long-term 250 m, 8-day resolution MODIS image time series. A novel spatio-temporal change modeling process is being developed and implemented in DMAS to realize rapid and automated analysis of satellite image time series for forest disturbance detection. The study expects results that improve over a pure time series analysis approach, and that is practically applicable to massive complex spatio-temporal data.

  10. 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 enables us to detect genotoxic as well as non-genotoxic hepatocarcinogens.

  11. The nuclear F-actin interactome of Xenopus oocytes reveals an actin-bundling kinesin that is essential for meiotic cytokinesis

    PubMed Central

    Samwer, Matthias; Dehne, Heinz-Jürgen; Spira, Felix; Kollmar, Martin; Gerlich, Daniel W; Urlaub, Henning; Görlich, Dirk

    2013-01-01

    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-? 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

  12. Interactome analysis of AMP-activated protein kinase (AMPK)-?1 and -?1 in INS-1 pancreatic beta-cells by affinity purification-mass spectrometry

    PubMed Central

    Moon, Sungyoon; Han, Dohyun; Kim, Yikwon; Jin, Jonghwa; Ho, Won-Kyung; Kim, Youngsoo

    2014-01-01

    The heterotrimeric enzyme AMP-activated protein kinase (AMPK) is a major metabolic factor that regulates the homeostasis of cellular energy. In particular, AMPK mediates the insulin resistance that is associated with type 2 diabetes. Generally, cellular processes require tight regulation of protein kinases, which is effected through their formation of complex with other proteins and substrates. Despite their critical function in regulation and pathogenesis, there are limited data on the interaction of protein kinases. To identify proteins that interact with AMPK, we performed large-scale affinity purification (AP)-mass spectrometry (MS) of the AMPK-?1 and -?1 subunits. Through a comprehensive analysis, using a combination of immunoprecipitaion and ion trap mass spectrometry, we identified 381 unique proteins in the AMPK?/? interactomes: 325 partners of AMPK-?1 and 243 for AMPK-?1. Further, we identified 196 novel protein-protein interactions with AMPK-?1 and AMPK-?1. Notably, in our bioinformatics analysis, the novel interaction partners mediated functions that are related to the regulation of actin organization. Specifically, several such proteins were linked to pancreatic beta-cell functions, including glucose-stimulated insulin secretion, beta-cell development, beta-cell differentiation, and cell-cell communication. PMID:24625528

  13. Contextualized trajectory parsing with spatiotemporal graph.

    PubMed

    Liu, Xiaobai; Lin, Liang; Jin, Hai

    2013-12-01

    This work investigates how to automatically parse object trajectories in surveillance videos, which aims at jointly solving three subproblems: 1) spatial segmentation, 2) temporal tracking, and 3) object categorization. We present a novel representation spatiotemporal graph (ST-Graph) in which: 1) Graph nodes express the motion primitives, each representing a short sequence of small-size patches over consecutive images, and 2) every two neighbor nodes are linked with either a positive edge or a negative edge to describe their collaborative or exclusive relationship of belonging to the same object trajectory. Phrasing the trajectory parsing as a graph multicoloring problem, we propose a unified probabilistic formulation to integrate various types of context knowledge as informative priors. An efficient composite cluster sampling algorithm is employed in search of the optimal solution by exploiting both the collaborative and the exclusive relationships between nodes. The proposed framework is evaluated over challenging videos from public datasets, and results show that it can achieve state-of-the-art tracking accuracy. PMID:24136437

  14. Spatio-temporal registration of multiple trajectories.

    PubMed

    Padoy, Nicolas; Hager, Gregory D

    2011-01-01

    A growing number of medical datasets now contain both a spatial and a temporal dimension. Trajectories, from tools or body features, are thus becoming increasingly important for their analysis. In this paper, we are interested in recovering the spatial and temporal differences between trajectories coming from different datasets. In particular, we address the case of surgical gestures, where trajectories contain both spatial transformations and speed differences in the execution. We first define the spatio-temporal registration problem between multiple trajectories. We then propose an optimization method to jointly recover both the rigid spatial motions and the non-linear time warpings. The optimization generates also a generic trajectory template, in which spatial and temporal differences have been factored out. This approach can be potentially used to register and compare gestures side-by-side for training sessions, to build gesture trajectory models for automation by a robot, or to register the trajectories of natural or artificial markers which follow similar motions. We demonstrate its usefulness with synthetic and real experiments. In particular, we register and analyze complex surgical gestures performed by tele-manipulation using the da Vinci robot. PMID:22003611

  15. Multisensory control of hippocampal spatiotemporal selectivity.

    PubMed

    Ravassard, Pascal; Kees, Ashley; Willers, Bernard; Ho, David; Aharoni, Daniel; Cushman, Jesse; Aghajan, Zahra M; Mehta, Mayank R

    2013-06-14

    The hippocampal cognitive map is thought to be driven by distal visual cues and self-motion cues. However, other sensory cues also influence place cells. Hence, we measured rat hippocampal activity in virtual reality (VR), where only distal visual and nonvestibular self-motion cues provided spatial information, and in the real world (RW). In VR, place cells showed robust spatial selectivity; however, only 20% were track active, compared with 45% in the RW. This indicates that distal visual and nonvestibular self-motion cues are sufficient to provide selectivity, but vestibular and other sensory cues present in RW are necessary to fully activate the place-cell population. In addition, bidirectional cells preferentially encoded distance along the track in VR, while encoding absolute position in RW. Taken together, these results suggest the differential contributions of these sensory cues in shaping the hippocampal population code. Theta frequency was reduced, and its speed dependence was abolished in VR, but phase precession was unaffected, constraining mechanisms governing both hippocampal theta oscillations and temporal coding. These results reveal cooperative and competitive interactions between sensory cues for control over hippocampal spatiotemporal selectivity and theta rhythm. PMID:23641063

  16. 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.

  17. Ultrashort relativistic electron bunches and spatio-temporal radiation biology

    NASA Astrophysics Data System (ADS)

    Gauduel, Y. A.; Faure, J.; Malka, V.

    2008-08-01

    The intensive developments of terawatt Ti:Sa lasers permit to extend laser-plasma interactions into the relativistic regime, providing very-short electron or proton bunches. Experimental researches developed at the interface of laser physics and radiation biology, using the combination of sub-picosecond electron beams in the energy range 2-15 MeV with femtosecond near-IR optical pulses might conjecture the real-time investigation of penetrating radiation effects. A perfect synchronization between the particle beam (pump) and optical beam at 820 nm (probe) allows subpicosecond time resolution. This emerging domain involves high-energy radiation femtochemistry (HERF) for which the early spatial energy deposition is decisive for the prediction of cellular and tissular radiation damages. With vacuum-focused intensities of 2.7 x 1019 W cm-2 and a high energy electron total charge of 2.5 nC, radiation events have been investigated in the temporal range 10-13 - 10-10s. The early radiation effects of secondary electron on biomolecular sensors may be investigated inside sub-micrometric ionisation, considering the radial direction of Gaussian electron bunches. It is shown that short range electron-biosensor interactions lower than 10 A take place in nascent track structures triggered by penetrating radiation bunches. The very high dose delivery 1013 Gy s-1 performed with laser plasma accelerator may challenge our understanding of nanodosimetry on the time scale of molecular target motions. High-quality ultrashort penetrating radiation beams open promising opportunities for the development of spatio-temporal radiation biology, a crucial domain of cancer therapy, and would favor novating applications in nanomedicine such as highly-selective shortrange pro-drug activation.

  18. 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

  19. Spatio-temporal coupling of EEG signals in epilepsy

    NASA Astrophysics Data System (ADS)

    Senger, Vanessa; Müller, Jens; Tetzlaff, Ronald

    2011-05-01

    Approximately 1% of the world's population suffer from epileptic seizures throughout their lives that mostly come without sign or warning. Thus, epilepsy is the most common chronical disorder of the neurological system. In the past decades, the problem of detecting a pre-seizure state in epilepsy using EEG signals has been addressed in many contributions by various authors over the past two decades. Up to now, the goal of identifying an impending epileptic seizure with sufficient specificity and reliability has not yet been achieved. Cellular Nonlinear Networks (CNN) are characterized by local couplings of dynamical systems of comparably low complexity. Thus, they are well suited for an implementation as highly parallel analogue processors. Programmable sensor-processor realizations of CNN combine high computational power comparable to tera ops of digital processors with low power consumption. An algorithm allowing an automated and reliable detection of epileptic seizure precursors would be a"huge step" towards the vision of an implantable seizure warning device that could provide information to patients and for a time/event specific treatment directly in the brain. Recent contributions have shown that modeling of brain electrical activity by solutions of Reaction-Diffusion-CNN as well as the application of a CNN predictor taking into account values of neighboring electrodes may contribute to the realization of a seizure warning device. In this paper, a CNN based predictor corresponding to a spatio-temporal filter is applied to multi channel EEG data in order to identify mutual couplings for different channels which lead to a enhanced prediction quality. Long term EEG recordings of different patients are considered. Results calculated for these recordings with inter-ictal phases as well as phases with seizures will be discussed in detail.

  20. Modeling sediment transport as a spatio-temporal Markov process.

    NASA Astrophysics Data System (ADS)

    Heyman, Joris; Ancey, Christophe

    2014-05-01

    Despite a century of research about sediment transport by bedload occuring in rivers, its constitutive laws remain largely unknown. The proof being that our ability to predict mid-to-long term transported volumes within reasonable confidence interval is almost null. The intrinsic fluctuating nature of bedload transport may be one of the most important reasons why classical approaches fail. Microscopic probabilistic framework has the advantage of taking into account these fluctuations at the particle scale, to understand their effect on the macroscopic variables such as sediment flux. In this framework, bedload transport is seen as the random motion of particles (sand, gravel, pebbles...) over a two-dimensional surface (the river bed). The number of particles in motion, as well as their velocities, are random variables. In this talk, we show how a simple birth-death Markov model governing particle motion on a regular lattice accurately reproduces the spatio-temporal correlations observed at the macroscopic level. Entrainment, deposition and transport of particles by the turbulent fluid (air or water) are supposed to be independent and memoryless processes that modify the number of particles in motion. By means of the Poisson representation, we obtained a Fokker-Planck equation that is exactly equivalent to the master equation and thus valid for all cell sizes. The analysis shows that the number of moving particles evolves locally far from thermodynamic equilibrium. Several analytical results are presented and compared to experimental data. The index of dispersion (or variance over mean ratio) is proved to grow from unity at small scales to larger values at larger scales confirming the non Poisonnian behavior of bedload transport. Also, we study the one and two dimensional K-function, which gives the average number of moving particles located in a ball centered at a particle centroid function of the ball's radius.

  1. Spatiotemporal correlations in Earth's temperature field from fractional stochastic-diffusive energy balance models

    NASA Astrophysics Data System (ADS)

    Rypdal, Kristoffer; Rypdal, Martin; Fredriksen, Hege-Beate

    2015-04-01

    In the Earth temperature field, spatiotemporal long-range dependence is usually explained as a result of nonlinear cross-scale coupling and cascading. In this contribution we challenge that paradigm, demonstrating that the observed correlation structure can arise from simple, linear, conceptual models. A two-dimensional stochastic-diffusive energy balance model (EBM) formulated on a sphere by G. R. North et al., J. Climate, 24:5850-5862, 2011, is explored and generalized. We compute instantaneous and frequency-dependent spatial autocorrelation functions, and local temporal power spectral densities for local sites and for spatially averaged signal up to the global scale. On time scales up to the relaxation time scale given by the effective heat capacities of the ocean mixed layer and land surface, respectively, we obtain scaling features reminiscent of what can be derived from the observed temperature field. On longer time scales, however, the EBM predicts a transition to a white-noise scaling, which is not reflected in the observed records. We propose and explore a fractional generalization (FEBM), which can be considered as a spatiotemporal version of the zero-dimensional, long-memory EBM of M. Rypdal and K. Rypdal, J. Climate, 27:5240-5258, 2014. The fractional equation introduces a power-law (rather than exponential) impulse response representing the delayed action due to the slow heat exchange between the mixed layer and the deep ocean. It is demonstrated that this generalized model describes qualitatively the main spatiotemporal correlation characteristics of the temperature field derived from instrumental data and from a 500 yr control run of the Nor-ESM model. For instance, the FEBM implies temporal power-law spectra where the spectral exponent for globally averaged temperature is twice that of local temperatures, and spatial autocorrelation lengths increases with time scale, in good agreement with the Nor-ESM simulations. It also reproduces the long-time response to a step-function forcing in the Nor-ESM model.

  2. Prediction model of potential hepatocarcinogenicity of rat hepatocarcinogens using a large-scale toxicogenomics database.

    PubMed

    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. PMID:21784091

  3. 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 nonlinearity and demonstrate that it accommodates many different classes of scientific-based parameterizations as special cases. The model is presented in a hierarchical Bayesian framework and is illustrated with examples from ecology and oceanography. ?? 2010 Sociedad de Estad??stica e Investigaci??n Operativa.

  4. Spatio-temporal topological relationships between land parcels in cadastral database

    NASA Astrophysics Data System (ADS)

    Song, W.; Zhang, F.

    2014-04-01

    There are complex spatio-temporal relationships among cadastral entities. Cadastral spatio-temporal data model should not only describe the data structure of cadastral objects, but also express cadastral spatio-temporal relationships between cadastral objects. In the past, many experts and scholars have proposed a variety of cadastral spatio-temporal data models, but few of them concentrated on the representation of spatiotemporal relationships and few of them make systematic studies on spatiotemporal relationships between cadastral objects. The studies on spatio-temporal topological relationships are not abundant. In the paper, we initially review current approaches to the studies of spatio-temporal topological relationships, and argue that spatio-temporal topological relation is the combination of temporal topology on the time dimension and spatial topology on the spatial dimension. Subsequently, we discuss and develop an integrated representation of spatio-temporal topological relationships within a 3-dimensional temporal space. In the end, based on the semantics of spatiotemporal changes between land parcels, we conclude the possible spatio-temporal topological relations between land parcels, which provide the theoretical basis for creating, updating and maintaining of land parcels in the cadastral database.

  5. ECEM/EAML 2004 Segmentation of paleoecological spatio-temporal count data

    E-print Network

    Toivonen, Hannu

    ECEM/EAML 2004 Segmentation of paleoecological spatio-temporal count data Kari Vasko1 , Hannu will consider applications of segmentation analysis towards analysis of paleoecological spatio-temporal time framework for the spatio-temporal segmentation problems that occurs in paleoecology and discuss

  6. Spatiotemporal evolution and nonlinear kinetic simulations of stimulated Brillouin scattering

    NASA Astrophysics Data System (ADS)

    Giacone, Rodolfo E.

    The spatiotemporal evolution of stimulated Brillouin scattering (SBS) in homogeneous plasmas and some aspects of the influence that nonlinear and kinetic effects have on the evolution of SBS were studied. A one-dimensional analytical linear model based on a fluid description of the plasma was developed initially. It was found that the threshold intensity of the absolute instability and the steady-state spatial growth rate of the convective instability are both independent of the scattering angle. However, the saturation time of the convective instability exhibits a strong inverse dependence on the scattering angle. The basic model was improved by extending the one- dimensional analysis to include two spatial dimensions and time. In order to assess the effects that the finite size of the laser beam has on SBS, wide and narrow laser- beam geometries were considered. Detailed comparisons were made between the predictions of reduced one- and two-dimensional models, which can be solved analytically, and the results of two-dimensional numerical simulations. It was found that the linear evolution of SBS was characterized by three parameters: the spatial growth rate in the direction of the Stokes wave, the spatial damping rate of the ion-acoustic wave in the direction of the Stokes wave and the normalized width of the interaction region. SBS can be saturated by the damping or the lateral convection of the ion-acoustic wave, both of which limit the growth of the ion- acoustic wave (directly) and the Stokes wave (indirectly). For most scattering angles the predicted saturation mechanism, and the corresponding saturation time and gain factor agree with the simulation results. The influence that nonlinear and kinetic effects have on SBS was investigated by performing particle-in-cell (PIC) simulations. The results of these PIC simulations were compared against fluid simulations, and good agreement was obtained for weak laser intensities. When the laser intensity is strong enough, PIC and fluid simulations differ substantially. It was shown that among various saturation mechanisms such as pump depletion, wavebreaking and generation of ion-acoustic wave harmonics, ion-trapping is the mechanism responsible for the observed differences. The SBS reflectivity is shown to depend sensitively on the frequency mismatch between the light wave used to seed the instability and the incident laser.

  7. 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

  8. 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.

  9. Complex network based techniques to identify extreme events and (sudden) transitions in spatio-temporal systems.

    PubMed

    Marwan, Norbert; Kurths, Jürgen

    2015-09-01

    We present here two promising techniques for the application of the complex network approach to continuous spatio-temporal systems that have been developed in the last decade and show large potential for future application and development of complex systems analysis. First, we discuss the transforming of a time series from such systems to a complex network. The natural approach is to calculate the recurrence matrix and interpret such as the adjacency matrix of an associated complex network, called recurrence network. Using complex network measures, such as transitivity coefficient, we demonstrate that this approach is very efficient for identifying qualitative transitions in observational data, e.g., when analyzing paleoclimate regime transitions. Second, we demonstrate the use of directed spatial networks constructed from spatio-temporal measurements of such systems that can be derived from the synchronized-in-time occurrence of extreme events in different spatial regions. Although there are many possibilities to investigate such spatial networks, we present here the new measure of network divergence and how it can be used to develop a prediction scheme of extreme rainfall events. PMID:26428562

  10. Complex network based techniques to identify extreme events and (sudden) transitions in spatio-temporal systems

    NASA Astrophysics Data System (ADS)

    Marwan, Norbert; Kurths, Jürgen

    2015-09-01

    We present here two promising techniques for the application of the complex network approach to continuous spatio-temporal systems that have been developed in the last decade and show large potential for future application and development of complex systems analysis. First, we discuss the transforming of a time series from such systems to a complex network. The natural approach is to calculate the recurrence matrix and interpret such as the adjacency matrix of an associated complex network, called recurrence network. Using complex network measures, such as transitivity coefficient, we demonstrate that this approach is very efficient for identifying qualitative transitions in observational data, e.g., when analyzing paleoclimate regime transitions. Second, we demonstrate the use of directed spatial networks constructed from spatio-temporal measurements of such systems that can be derived from the synchronized-in-time occurrence of extreme events in different spatial regions. Although there are many possibilities to investigate such spatial networks, we present here the new measure of network divergence and how it can be used to develop a prediction scheme of extreme rainfall events.

  11. Spatiotemporal Spike Coding of Behavioral Adaptation in the Dorsal Anterior Cingulate Cortex

    PubMed Central

    Logiaco, Laureline; Quilodran, René; Procyk, Emmanuel; Arleo, Angelo

    2015-01-01

    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

  12. 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.

  13. Functional Principal Component Analysis of Spatio-Temporal Point Processes with Applications in Disease Surveillance.

    PubMed

    Li, Yehua; Guan, Yongtao

    2014-08-01

    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

  14. 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

  15. Stabilization of spatiotemporal solitons in Kerr media by dispersive coupling.

    PubMed

    Kartashov, Yaroslav V; Malomed, Boris A; Konotop, Vladimir V; Lobanov, Valery E; Torner, Lluis

    2015-03-15

    We introduce a mechanism to stabilize spatiotemporal solitons in Kerr nonlinear media, based on the dispersion of linear coupling between the field components forming the soliton states. Specifically, we consider solitons in a two-core guiding structure with inter-core coupling dispersion (CD). We show that CD profoundly affects properties of the solitons, causing the complete stabilization of the otherwise highly unstable spatiotemporal solitons in Kerr media with focusing nonlinearity. We also find that the presence of CD stimulates the formation of bound states, which, however, are unstable. PMID:25768178

  16. 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.

  17. 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.

  18. 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 season. 5. The ‘NPI – sexual selection hypothesis’ best explained spatiotemporal segregation in our study system. We suggest that females with cubs-of-the-year alter their resource selection to avoid infanticidal males. In species exhibiting NPI as a male reproductive strategy, female avoidance of infanticidal males is probably more common than observed or reported, and may come with a fitness cost if females trade safety for optimal resources. PMID:23461483

  19. 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.

  20. Using atmospheric observations to evaluate the spatiotemporal variability of CO2 fluxes simulated by terrestrial biospheric models

    NASA Astrophysics Data System (ADS)

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

    2014-06-01

    Terrestrial biospheric models (TBMs) are used to extrapolate local observations and process-level understanding of land-atmosphere carbon exchange to larger regions, and serve as a predictive tool for examining carbon-climate interactions. Understanding the performance of TBMs is thus crucial to the carbon cycle and climate science. In this study, we propose a statistical model selection approach for evaluating the spatiotemporal patterns of net ecosystem exchange (NEE) simulated by TBMs using atmospheric CO2 measurements. We find that current atmospheric observations are sensitive to the underlying spatiotemporal flux variability at sub-biome scales for a large portion of the North American continent, and that atmospheric observations can therefore be used to evaluate simulated spatiotemporal flux patterns, rather than focusing solely on flux magnitudes at aggregated scales. Results show that the proposed approach can be used to assess whether a TBM represents a substantial portion of the underlying flux variability as well as to differentiate among multiple competing TBMs. When applying the proposed approach to four prototypical TBMs, we find that the performance of TBMs varies substantially across seasons, with best performance during the growing season and limited skill during transition seasons. This seasonal difference in the ability of TBMs to represent the spatiotemporal flux variability may reflect the models' capability to represent the seasonally-varying influence of environmental drivers on fluxes. While none of the TBMs consistently outperforms the others, differences among the examined models are at least partially attributable to their internal structures. Overall, the proposed approach provides a new avenue for evaluating TBM performance based on sub-biome scale flux patterns, presenting an opportunity for assessing and informing model development using atmospheric observations.

  1. PSO2004/FU5766 Improved wind power prediction

    E-print Network

    PSO2004/FU5766 Improved wind power prediction Spatio-temporal modelling of short-term wind power of wind power generation in power systems. The quality of the forecast is very important, and a reliable estimate of the uncertainty of the forecast is known to be essential. Today the forecasts of wind power

  2. Spatio-temporal dynamics before population collapse

    E-print Network

    Dai, Lei, Ph. D. Massachusetts Institute of Technology

    2014-01-01

    Theory predicts that the approach of catastrophic thresholds in natural systems may result in an increasingly slow recovery from small perturbations, a phenomenon called critical slowing down. In this thesis, we used ...

  3. Asymmetric spatiotemporal chaos induced by a polypoid mass in the excised larynx

    NASA Astrophysics Data System (ADS)

    Zhang, Yu; Jiang, Jack J.

    2008-12-01

    In this paper, asymmetric spatiotemporal chaos induced by a polypoid mass simulating the laryngeal pathology of a vocal polyp is experimentally observed using high-speed imaging in an excised larynx. Spatiotemporal analysis reveals that the normal vocal folds show spatiotemporal correlation and symmetry. Normal vocal fold vibrations are dominated mainly by the first vibratory eigenmode. However, pathological vocal folds with a polypoid mass show broken symmetry and spatiotemporal irregularity. The spatial correlation is decreased. The pathological vocal folds spread vibratory energy across a large number of eigenmodes and induce asymmetric spatiotemporal chaos. High-order eigenmodes show complicated dynamics. Spatiotemporal analysis provides a valuable biomedical application for investigating the spatiotemporal chaotic dynamics of pathological vocal fold systems with a polypoid mass and may represent a valuable clinical tool for the detection of laryngeal mass lesion using high-speed imaging.

  4. Spatiotemporal quantile regression for detecting distributional changes in environmental processes

    E-print Network

    Reich, Brian J.

    aspect of climate change research that has received considerable attention is global warming, which Brian J Reich Department of Statistics North Carolina State University October 18, 2011 Abstract Climate, warming hole. #12;Spatiotemporal quantile regression for detecting distributional changes in environmental

  5. The GLIMS Glacier Database: a spatio-temporal database

    E-print Network

    Raup, Bruce H.

    The GLIMS Glacier Database: a spatio-temporal database implemented using Open Source tools Bruce countries #12;#12;#12;#12;#12;System components PostgreSQL (relational database) PostGIS (geospatial) GDAL (Geospatial Data Abstraction Library) Perl, PHP, Shapelib, ... #12;GLIMS Glacier Database System

  6. Spatiotemporal cues for tracking multiple objects through occlusion

    E-print Network

    Scholl, Brian

    object across a brief disappearance. There are at least two major spatiotemporal features that could's link to the original object. Additionally, the history of the object's motion could be an important Franconeri, UBC Department of Psychology, 3531-2136 West Mall, Vancouver, BC, V6T 1Z4, Canada. Tel: 604

  7. 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…

  8. 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.

  9. Spatio-temporal evaluation matrices for geospatial data

    NASA Astrophysics Data System (ADS)

    Triglav, Joc; Petrovi?, 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.

  10. Spatiotemporal Relational Probability Trees: An Introduction Amy McGovern

    E-print Network

    McGovern, Amy

    . On the smaller spatial and temporal scale, phenomena such as tor- nadoes, severe thunderstorms, hail, and flash motivated by severe thunderstorms and tornadoes and we are currently examining the application to drought. Brown NOAA/National Severe Storms Lab Rodger.Brown@noaa.gov Abstract We introduce spatiotemporal

  11. Hierarchical Bayesian Spatio-Temporal Models for Population Spread

    E-print Network

    is a serious concern. Given the increasing economic, environmental, and human health impact of such invasionsHierarchical Bayesian Spatio-Temporal Models for Population Spread Christopher K. Wikle and Mevin, Columbia, MO 65211; wikle@stat.missouri.edu 1 #12;1 Introduction The spread of populations has long been

  12. GIScience Grand Research Challenges: from Spatial Integration to Spatiotemporal Inspiration

    E-print Network

    Wright, Dawn Jeannine

    -time geographic nowcasting ­ Cloud computing: data centric to app centric · Space-time and geographic dynamics ­ Networks and Topology ­ Pattern and Dispersion #12;iPhone and Space-Time #12;Spatial Intelligence http://www.blog.iqmatrix.com/wp-content/uploads/2008/05/7-intelligences-spatial.jpg #12;Spatiotemporal Inspiration · Space-time as a source

  13. Spatiotemporal dynamics of epidemics: synchrony in metapopulation models

    E-print Network

    to a simple linear term. The technique considerably simplifies the analysis as it decouples the nk dimensional of this technique, the dynamical behavior in the vicinity of the endemic equilibrium of a symmetric SIR modelSpatiotemporal dynamics of epidemics: synchrony in metapopulation models Alun L. Lloyd a

  14. Spatiotemporal Transition to Conduction Block in Canine Ventricle

    E-print Network

    Bailey-Kellogg, Chris

    Spatiotemporal Transition to Conduction Block in Canine Ventricle Jeffrey J. Fox, Mark L. Riccio potential duration and conduction velocity. How alternans causes the local conduction block required for initiation of spiral wave reentry remains unclear, however. In the present study, a mechanism for conduction

  15. BLIND SIGNAL DECONVOLUTION BY SPATIO-TEMPORAL DECORRELATION AND

    E-print Network

    Cichocki, Andrzej

    BLIND SIGNAL DECONVOLUTION BY SPATIO-TEMPORAL DECORRELATION AND DEMIXING Seungjin CHOI and Andrzej-line adaptive multichannel blind deconvolution and sepa- ration of i.i.d. sources. Under mild conditions which consists of blind equalization and source separation. In blind equalization stage, we employ anti

  16. 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.

  17. Spatiotemporal Receptive Fields of MT Cells during Smooth Eye Movements

    E-print Network

    Krekelberg, Bart

    Spatiotemporal Receptive Fields of MT Cells during Smooth Eye Movements T.S.Hartmann1,2 ; B systematic localization errors during eye-movements. These localization errors may provide insight of awake, behaving monkeys (M. mulatta) to study the changes in space-time RF properties during smooth eye-movements

  18. Submission PDF Spatio-Temporal Distribution of Holocene Populations

    E-print Network

    Schmidt, Volker

    these methods and documented the impact of human activities on the vegetation (1, 6-10). Although some studiesSubmission PDF Spatio-Temporal Distribution of Holocene Populations in North America Michelle A As the Cordilleran and Laurentide Ice Sheets retreated, North America was colonized by human populations; however

  19. Football analysis using spatio-temporal tools Joachim Gudmundsson

    E-print Network

    Wolle, Thomas

    Football analysis using spatio-temporal tools Joachim Gudmundsson University of Sydney and NICTA, Australia thomas.wolle@gmail.com ABSTRACT Analysing a football match is without doubt an important task specifically for analysing the performance of football players and teams. The aim, functionality

  20. Spatiotemporal information during unsupervised learning enhances viewpoint invariant object recognition

    PubMed Central

    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. PMID:26024454

  1. Nonequilibrium pattern formation and spatiotemporal chaos in fluid convection

    SciTech Connect

    Michael Cross

    2006-09-13

    The final report for grant number DE-FG03-98ER14891 summarizes the application of the unique simulation capabilities developed under DOE support to investigations of important issues in pattern formation and spatiotemporal chaos in Rayleigh-Benard convection, particularly emphasizing quantitative contact with the active experimental programs.

  2. Crime Forecasting Using Spatio-Temporal Pattern with Ensemble Learning

    E-print Network

    Ding, Wei

    Crime Forecasting Using Spatio-Temporal Pattern with Ensemble Learning Chung-Hsien Yu1 , Wei Ding1 University Avenue, Lowell, MA 01854, USA Melissa_Morabito@uml.edu Abstract. Crime forecasting is notoriously difficult. A crime incident is a multi-dimensional complex phenomenon that is closely associated

  3. Applying Spatiotemporal and Demographic Data to Locate Next Crime Location

    E-print Network

    Morrow, James A.

    Applying Spatiotemporal and Demographic Data to Locate Next Crime Location Control #7501 February of a serial criminal's next crime. A typical geographic profile outputs estimated probabilities with the input of time and location of previous crimes. In this paper, we develop a new geographic profile that is able

  4. Spatiotemporal coherent control using shaped, temporally focused pulses

    E-print Network

    Silberberg, Yaron

    Spatiotemporal coherent control using shaped, temporally focused pulses Dan Oron and Yaron, the temporal shape of the pulses is maintained throughout the interaction re- gion. Here we show how pulses can micrometers. This changing pulse shape has a significant effect on coherent nonlinear optical processes. Here

  5. 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)

  6. SPATIOTEMPORAL VARIATION IN SURVIVAL OF MALE YELLOW-BELLIED MARMOTS

    E-print Network

    Blumstein, Daniel T.

    SPATIOTEMPORAL VARIATION IN SURVIVAL OF MALE YELLOW-BELLIED MARMOTS NATALIA BORREGO,a ARPAT OZGUL variation in age-specific survival rates of male yellow-bellied marmots (Marmota flaviventris) in Colorado in survival rates. Our results suggest that male marmots of different ages respond differentially to temporal

  7. 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…

  8. Spatio-Temporal Signal Recovery from Political Tweets in Indonesia

    E-print Network

    Davulcu, Hasan

    Spatio-Temporal Signal Recovery from Political Tweets in Indonesia Anisha Mazumder, Arun Das activity in the provinces of Indonesia. Based on analysis of radical/counter radical sentiments expressed in tweets by Twitter users, we create a Heat Map of Indonesia which visually demonstrates the degree

  9. 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.

  10. Toward Understanding Tornado Formation Through Spatiotemporal Data Mining

    E-print Network

    McGovern, Amy

    Toward Understanding Tornado Formation Through Spatiotemporal Data Mining Amy McGovern and Derek H. Rosendahl and Rodger A. Brown 1 Motivation Tornadoes, which are one of the most feared natural phenomena produce tornadoes. There are no obvious clues within any of the routinely observed data to indicate which

  11. The Truncated Tornado in TMBB: A Spatiotemporal Uncertainty Model for

    E-print Network

    Bae, Wan

    The Truncated Tornado in TMBB: A Spatiotemporal Uncertainty Model for Moving Objects Shayma and system performance. In this paper, we propose an uncertainty model called the Truncated Tornado model as a significant advance in minimizing uncertainty re- gion sizes. The Truncated Tornado model removes uncertainty

  12. Spatiotemporal modeling of irregularly spaced Aerosol Optical Depth data

    PubMed Central

    Oleson, Jacob J.; Kumar, Naresh; Smith, Brian J.

    2012-01-01

    Many advancements have been introduced to tackle spatial and temporal structures in data. When the spatial and/or temporal domains are relatively large, assumptions must be made to account for the sheer size of the data. The large data size, coupled with realities that come with observational data, make it difficult for all of these assumptions to be met. In particular, air quality data are very sparse across geographic space and time, due to a limited air pollution monitoring network. These “missing” values make it diffcult to incorporate most dimension reduction techniques developed for high-dimensional spatiotemporal data. This article examines aerosol optical depth (AOD), an indirect measure of radiative forcing, and air quality. The spatiotemporal distribution of AOD can be influenced by both natural (e.g., meteorological conditions) and anthropogenic factors (e.g., emission from industries and transport). After accounting for natural factors influencing AOD, we examine the spatiotemporal relationship in the remaining human influenced portion of AOD. The presented data cover a portion of India surrounding New Delhi from 2000 – 2006. The proposed method is demonstrated showing how it can handle the large spatiotemporal structure containing so much missing data for both meteorologic conditions and AOD over time and space. PMID:24470786

  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. Towards Integrating Real-World Spatiotemporal Data with Social Networks

    E-print Network

    Shahabi, Cyrus

    such as target advertising, sale promotions, and marketing campaigns. Although most social interactionsTowards Integrating Real-World Spatiotemporal Data with Social Networks Huy Pham Ling Hu Cyrus Shahabi Integrated Media Systems Center University of Southern California (USC) Los Angeles, California

  15. OPTIMAL CONTROL OF SPATIOTEMPORAL CHAOS IN COUPLED MAP LATTICES

    E-print Network

    Grigoriev, Roman

    OPTIMAL CONTROL OF SPATIOTEMPORAL CHAOS IN COUPLED MAP LATTICES R. O. GRIGORIEV Condensed Matter Physics 114­36 California Institute of Technology, Pasadena CA 91125 Abstract. An optimal control approach is used to develop a localized linear control scheme for Coupled Map Lattices. The optimal arrangement

  16. Actin Filament Segmentation using Spatiotemporal Active-Surface and

    E-print Network

    Huang, Xiaolei

    Actin Filament Segmentation using Spatiotemporal Active-Surface and Active-Contour Models Hongsheng a novel algorithm for actin filament segmen- tation in a 2D TIRFM image sequence. We treat the 2D time of a filament on all slices simultaneously. In order to locate the two ends of the filament on the over

  17. 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;…

  18. Spatiotemporal evolution of erythema migrans, the hallmark rash of Lyme disease.

    PubMed

    Vig, Dhruv K; Wolgemuth, Charles W

    2014-02-01

    To elucidate pathogen-host interactions during early Lyme disease, we developed a mathematical model that explains the spatiotemporal dynamics of the characteristic first sign of the disease, a large (?5-cm diameter) rash, known as an erythema migrans. The model predicts that the bacterial replication and dissemination rates are the primary factors controlling the speed that the rash spreads, whereas the rate that active macrophages are cleared from the dermis is the principle determinant of rash morphology. In addition, the model supports the clinical observations that antibiotic treatment quickly clears spirochetes from the dermis and that the rash appearance is not indicative of the efficacy of the treatment. The quantitative agreement between our results and clinical data suggest that this model could be used to develop more efficient drug treatments and may form a basis for modeling pathogen-host interactions in other emerging infectious diseases. PMID:24507617

  19. Spatiotemporal Evolution of Erythema Migrans, the Hallmark Rash of Lyme Disease

    PubMed Central

    Vig, Dhruv K.; Wolgemuth, Charles W.

    2014-01-01

    To elucidate pathogen-host interactions during early Lyme disease, we developed a mathematical model that explains the spatiotemporal dynamics of the characteristic first sign of the disease, a large (?5-cm diameter) rash, known as an erythema migrans. The model predicts that the bacterial replication and dissemination rates are the primary factors controlling the speed that the rash spreads, whereas the rate that active macrophages are cleared from the dermis is the principle determinant of rash morphology. In addition, the model supports the clinical observations that antibiotic treatment quickly clears spirochetes from the dermis and that the rash appearance is not indicative of the efficacy of the treatment. The quantitative agreement between our results and clinical data suggest that this model could be used to develop more efficient drug treatments and may form a basis for modeling pathogen-host interactions in other emerging infectious diseases. PMID:24507617

  20. Relationships between predicted moonlighting proteins, human diseases, and comorbidities from a network perspective

    PubMed Central

    Zanzoni, Andreas; Chapple, Charles E.; Brun, Christine

    2015-01-01

    Moonlighting proteins are a subset of multifunctional proteins characterized by their multiple, independent, and unrelated biological functions. We recently set up a large-scale identification of moonlighting proteins using a protein-protein interaction (PPI) network approach. We established that 3% of the current human interactome is composed of predicted moonlighting proteins. We found that disease-related genes are over-represented among those candidates. Here, by comparing moonlighting candidates to non-candidates as groups, we further show that (i) they are significantly involved in more than one disease, (ii) they contribute to complex rather than monogenic diseases, (iii) the diseases in which they are involved are phenotypically different according to their annotations, finally, (iv) they are enriched for diseases pairs showing statistically significant comorbidity patterns based on Medicare records. Altogether, our results suggest that some observed comorbidities between phenotypically different diseases could be due to a shared protein involved in unrelated biological processes. PMID:26157390

  1. Protein-protein interaction network of the marine microalga Tetraselmis subcordiformis: prediction and application for starch metabolism analysis.

    PubMed

    Ji, Chaofan; Cao, Xupeng; Yao, Changhong; Xue, Song; Xiu, Zhilong

    2014-08-01

    Under stressful conditions, the non-model marine microalga Tetraselmis subcordiformis can accumulate a substantial amount of starch, making it a potential feedstock for the production of fuel ethanol. Investigating the interactions of the enzymes and the regulatory factors involved in starch metabolism will provide potential genetic manipulation targets for optimising the starch productivity of T. subcordiformis. For this reason, the proteome of T. subcordiformis was utilised to predict the first protein-protein interaction (PPI) network for this marine alga based on orthologous interactions, mainly from the general PPI repositories. Different methods were introduced to evaluate the credibility of the predicted interactome, including the confidence value of each PPI pair and Pfam-based and subcellular location-based enrichment analysis. Functional subnetworks analysis suggested that the two enzymes involved in starch metabolism, starch phosphorylase and trehalose-phosphate synthase may be the potential ideal genetic engineering targets. PMID:24879479

  2. 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

    Malaria is the leading cause of morbidity and mortality in Malawi with more than 6 million episodes reported each year. Malaria poses a huge economic burden to Malawi in terms of the direct cost of treating malaria patients and also indirect costs resulting from workdays lost in agriculture and industry and absenteeism from school. Malawi implements malaria control activities within the Roll Back Malaria framework, with the objective to provide those most at risk (i.e. children under five years, pregnant woman and individuals with suppressed immune systems) access to personal and community protective measures. However, at present there is no mechanism by which to target the most 'at risk' populations ahead of an impending epidemic. Malaria transmission is influenced by variations in meteorological conditions, which impact the biology of the mosquito and the availability of breeding sites, but also socio-economic conditions such as levels of urbanisation, poverty and education, which influence human vulnerability and vector habitat. The many potential drivers of malaria, both extrinsic, such as climate, and intrinsic, such as population immunity are often difficult to disentangle. This presents a challenge for modelling of malaria risk in space and time. Using an age-stratified spatio-temporal dataset of malaria cases at the district level from July 2004 - June 2011, we use a spatio-temporal modelling framework to model variations in malaria risk in Malawi. Climatic and topographic variations are accounted for using an interpolation method to relate gridded products to administrative districts. District level data is tested in the model to account for confounding factors, including the proportion of the population living in urban areas; residing in traditional housing; with no toilet facilities; who do not attend school, etc, the number of health facilities per population and yearly estimates of insecticide-treated mosquito net distribution. In order to account for 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.

  3. Quantifying Uncertainty in Spatio-temporal Forest Composition Changes Inferred from Fossil Pollen Records

    NASA Astrophysics Data System (ADS)

    Dawson, A.; Paciorek, C. J.; McLachlan, J. S.; Goring, S. J.; Williams, J. W.; Jackson, S. T.

    2014-12-01

    Understanding past compositional changes in vegetation provides insight about ecosystem dynamics in response to changing environments. Past vegetation reconstructions rely predominantly on fossil pollen data from sedimentary lake cores, which acts as a proxy record for the surrounding vegetation. Stratigraphic changes in these pollen records allow us to infer changes in composition and species distributions. Pollen records collected from a network of sites allow us to make inference about the spatio-temporal changes in vegetation over thousands of years. However, the complexity of the relationship between pollen deposits and surrounding vegetation, as well as the spatially sparse set of fossil pollen sites are important sources of uncertainty. In addition, uncertainty arises from the carbon dating and age-depth modelling processes. To reconstruct vegetation composition including uncertainty for the Upper Midwestern USA, we build a Bayesian hierarchical model that links vegetation composition to fossil pollen data via a dispersal model. In the calibration phase, we estimate the relationship between vegetation and pollen for the settlement era using Public Land Survey data and a network of pollen records. In the prediction phase, parameter estimates obtained during the calibration phase are used to estimate latent species distributions and relative abundances over the last 2500 years. We account for additional uncertainty in the pollen records by: allowing expert palynologists to identify pre-settlement pollen samples to be included in our calibration data, and through the incorporation of age uncertainty obtained from the Bayesian age-depth model BACON in our prediction data. Resulting spatio-temporal composition and abundance estimates will be used to improve forecasting capabilities of ecosystem models.

  4. Spatiotemporal psychopathology I: No rest for the brain's resting state activity in depression? Spatiotemporal psychopathology of depressive symptoms.

    PubMed

    Northoff, Georg

    2016-01-15

    Despite intense neurobiological investigation in psychiatric disorders like major depressive disorder (MDD), the basic disturbance that underlies the psychopathological symptoms of MDD remains, nevertheless, unclear. Neuroimaging has focused mainly on the brain's extrinsic activity, specifically task-evoked or stimulus-induced activity, as related to the various sensorimotor, affective, cognitive, and social functions. Recently, the focus has shifted to the brain's intrinsic activity, otherwise known as its resting state activity. While various abnormalities have been observed during this activity, their meaning and significance for depression, along with its various psychopathological symptoms, are yet to be defined. Based on findings in healthy brain resting state activity and its particular spatial and temporal structure - defined in a functional and physiological sense rather than anatomical and structural - I claim that the various depressive symptoms are spatiotemporal disturbances of the resting state activity and its spatiotemporal structure. This is supported by recent findings that link ruminations and increased self-focus in depression to abnormal spatial organization of resting state activity. Analogously, affective and cognitive symptoms like anhedonia, suicidal ideation, and thought disorder can be traced to an increased focus on the past, increased past-focus as basic temporal disturbance o the resting state. Based on these findings, I conclude that the various depressive symptoms must be conceived as spatiotemporal disturbances of the brain's resting state's activity and its spatiotemporal structure. Importantly, this entails a new form of psychopathology, "Spatiotemporal Psychopathology" that directly links the brain and psyche, therefore having major diagnostic and therapeutic implications for clinical practice. PMID:26048657

  5. Structure-based algorithms for protein-protein interaction prediction

    E-print Network

    Hosur, Raghavendra

    2012-01-01

    Protein-protein interactions (PPIs) play a central role in all biological processes. Akin to the complete sequencing of genomes, complete descriptions of interactomes is a fundamental step towards a deeper understanding ...

  6. Bayesian spatio-temporal discard model in a demersal trawl fishery

    NASA Astrophysics Data System (ADS)

    Grazia Pennino, M.; Muñoz, Facundo; Conesa, David; López-Quílez, Antonio; Bellido, José M.

    2014-07-01

    Spatial management of discards has recently been proposed as a useful tool for the protection of juveniles, by reducing discard rates and can be used as a buffer against management errors and recruitment failure. In this study Bayesian hierarchical spatial models have been used to analyze about 440 trawl fishing operations of two different metiers, sampled between 2009 and 2012, in order to improve our understanding of factors that influence the quantity of discards and to identify their spatio-temporal distribution in the study area. Our analysis showed that the relative importance of each variable was different for each metier, with a few similarities. In particular, the random vessel effect and seasonal variability were identified as main driving variables for both metiers. Predictive maps of the abundance of discards and maps of the posterior mean of the spatial component show several hot spots with high discard concentration for each metier. We argue how the seasonal/spatial effects, and the knowledge about the factors influential to discarding, could potentially be exploited as potential mitigation measures for future fisheries management strategies. However, misidentification of hotspots and uncertain predictions can culminate in inappropriate mitigation practices which can sometimes be irreversible. The proposed Bayesian spatial method overcomes these issues, since it offers a unified approach which allows the incorporation of spatial random-effect terms, spatial correlation of the variables and the uncertainty of the parameters in the modeling process, resulting in a better quantification of the uncertainty and accurate predictions.

  7. Spatio-temporal Averaging of Removal Rate constants in River Networks: Is there an Emergent Pattern?

    NASA Astrophysics Data System (ADS)

    Basu, N. B.; Rao, P. C.; Zanardo, S.; Donner, S. D.; Ye, S.; Sivapalan, M.

    2009-12-01

    Scaling of nutrient loads across river networks is a function of complex interactions between hydrologic and biogeochemical processes that modulate the contaminant input signals from the hillslope via aggregation and attenuation in a converging network. We examined the inter-annual variability in stream nutrient delivery ratio (NDR) as moderated by the coupling between hydrologic and biogeochemical processes across the climate-landscape continuum. Experimental and modeling studies at the reach scale suggest an inverse dependence of the biogeochemical cycling rate constant (k; T-1) on the stream stage (h, L). This inverse function was implemented in the THMB large-scale hydrology and biogeochemistry model to describe nutrient processing at the reach scale, and simulate nitrogen export across Mississippi Basin. The spatio-temporally averaged reaction rate (kavg) constant from THMB exhibited similar inverse dependence on the stage at the outlet of large basins (~50,000 km2). Such emergent k-h dependence is hypothesized to be indicative of fractal scaling behavior of in-stream biogeochemical processing. Two parsimonious models were developed to scale up from the reach-scale to watershed scale, and explore the spatio-temporal averaging within the network under diverse climate forcing conditions. The first model was derived from THREW, and was enhanced by adding a two-compartment biogeochemical reaction module. The second model used the inverse k-h dependence at the daily time scale, without invoking the two-compartment model, similar to that used in the basin-scale model. Preliminary analyses indicated that temporal averaging decreased the exponent of the k-h relationship at smaller spatial scales (e.g., first- or second- order watersheds); however, the relationship converged towards the reach-scale dependence function at larger scales. The average k value at the smaller scales, and the trajectory of convergence, is a function of climatic (e.g., rainfall frequency,depth) and geomorphic (e.g., network structure, channel dimensions) controls. The reach-scale k-h relationship thus acts as an “attractor” for the entire system, such that at larger spatial scales an effective k, derived solely from the mean stage at the watershed outlet, is adequate to describe nutrient processing within the entire network. Implications of this unique spatio-temporal averaging behavior on the development of predictive models that describe nutrient loads in catchments across scales are discussed.

  8. Spatiotemporal Chaotic unjamming and jamming in granular avalanches

    E-print Network

    Ziwei Wang; Jie Zhang

    2014-10-23

    We have investigated the spatiotemporal chaotic dynamics of unjamming and jamming of particles in a toy-model system -- a rotating drum partially filled with bidisperse disks to create avalanches. The magnitudes of the first Lyapunov vector $\\delta u(t)$ and velocity $v(t)$ of particles are directly measured for the first time to yield insights into their spatial correlation $C_{\\delta u,v}$, which is stronger near the unjamming but is weaker near the jamming transition, consistent with the recent work of Banigan et al., Nature Phys. $\\bf{9}$, 288, (2013). $v(t)$ shows rich dynamics: it grows exponentially for unstable particles and keeps increasing despite stochastic interactions; after the maximum, it decays with large fluctuations. Hence the spatiotemporal chaotic dynamics of avalanche particles are entangled, causing temporal correlations of macroscopic quantities of the system. We propose a simple model for these observations.

  9. Ordering spatiotemporal chaos in complex thermosensitive neuron networks

    NASA Astrophysics Data System (ADS)

    Gong, Yubing; Xu, Bo; Xu, Qiang; Yang, Chuanlu; Ren, Tingqi; Hou, Zhonghuai; Xin, Houwen

    2006-04-01

    We have studied the effect of random long-range connections in chaotic thermosensitive neuron networks with each neuron being capable of exhibiting diverse bursting behaviors, and found stochastic synchronization and optimal spatiotemporal patterns. For a given coupling strength, the chaotic burst-firings of the neurons become more and more synchronized as the number of random connections (or randomness) is increased and, rather, the most pronounced spatiotemporal pattern appears for an optimal randomness. As the coupling strength is increased, the optimal randomness shifts towards a smaller strength. This result shows that random long-range connections can tame the chaos in the neural networks and make the neurons more effectively reach synchronization. Since the model studied can be used to account for hypothalamic neurons of dogfish, catfish, etc., this result may reflect the significant role of random connections in transferring biological information.

  10. Spatiotemporal Investigation of Phosphorylation Events During Cell Cycle Progression.

    PubMed

    Gheghiani, Lilia; Gavet, Olivier

    2016-01-01

    Polo-like kinase 1 (Plk1) is an essential kinase for mitotic commitment and progression through mitosis. In contrast to its well characterized roles during mitosis, the precise molecular events controlled by Plk1 during G2/M progression and their spatiotemporal regulation are still poorly elucidated. We recently investigated Plk1-dependent regulation of Cdc25C phosphatase, an activator of the master mitotic driver Cyclin B1-Cdk1. To this end, we generated a genetically encoded FRET (Förster Resonance Energy Transfer)-based Cdc25C phosphorylation biosensor to observe Cdc25 spatiotemporal phosphorylation during cell cycle progression in live single cell assays. Because this approach proved to be powerful, we provide here guidelines for the development of biosensors for any phosphorylation site of interest. PMID:26254922

  11. The spatio-temporal spectrum of turbulent flows

    E-print Network

    di Leoni, P Clark; Mininni, P D

    2015-01-01

    Identification and extraction of vortical structures and of waves in a disorganized flow is a mayor challegen in the study of turbulence. We present a study of the spatio-temporal behavior of turbulent flows in the presence of different restitutive forces. We show how to compute and analyze the spatio-temporal spectrum from data stemming from numerical simulations and from laboratory experiments. Four cases are considered: homogeneous and isotropic turbulence, rotating turbulence, stratified turbulence, and water wave turbulence. For homogeneous and isotropic turbulence, the spectrum allows identification of random sweeping. For rotating and for stratified turbulence, the spectrum allows identification of the waves, quantification of the energy in the waves and in the turbulent eddies, and identification of physical mechanisms such as Doppler shift and wave absorption in critical layers. Finally, in water wave turbulence the spectrum shows a transition from gravity-capillary waves to bound waves as the amplit...

  12. Three dimensional electromagnetic wavepackets in a plasma: Spatiotemporal modulational instability

    SciTech Connect

    Borhanian, J.; Hosseini Faradonbe, F.

    2014-04-15

    The nonlinear interaction of an intense electromagnetic beam with relativistic collisionless unmagnetized plasma is investigated by invoking the reductive perturbation technique, resting on the model of three-dimensional nonlinear Schrödinger (NLS) equation with cubic nonlinearity which incorporates the effects of self-focusing, self-phase modulation, and diffraction on wave propagation. Relying on the derived NLS equation, the occurrence of spatiotemporal modulational instability is investigated in detail.

  13. Cortical Activation During Spatiotemporal Processing in the Infant Brain 

    E-print Network

    Armstrong, Jennifer R.

    2010-01-14

    in order for the event to occur. Second, Wynn (1992) presented infants with a spatiotemporal-discontinuity event in which a Mickey Mouse doll stood on a stage and then disappeared behind a screen. Subsequently, infants viewed an experimenter placing... another doll behind the screen. Infants were surprised when the screen was removed and revealed only one object. Wynn argues that there was not a continuous path to unite the first and second doll, and therefore infants derive the presence of two dolls...

  14. Ultrabroadband Dispersive Radiation by Spatiotemporal Oscillation of Multimode Waves

    NASA Astrophysics Data System (ADS)

    Wright, Logan G.; Wabnitz, Stefan; Christodoulides, Demetrios N.; Wise, Frank W.

    2015-11-01

    In nonlinear dynamical systems, qualitatively distinct phenomena occur depending continuously on the size of the bounded domain containing the system. For nonlinear waves, a multimode waveguide is a bounded three-dimensional domain, allowing observation of dynamics impossible in open settings. Here we study radiation emitted by bounded nonlinear waves: the spatiotemporal oscillations of solitons in multimode fiber generate multimode dispersive waves over an ultrabroadband spectral range. This work suggests routes to sources of coherent electromagnetic waves with unprecedented spectral range.

  15. 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.

  16. Interactive Information Visualization for Exploratory Analysis of Spatiotemporal Trend Information

    NASA Astrophysics Data System (ADS)

    Takama, Yasufumi; Yamada, Takashi

    This paper proposes an interactive information visualization system that supports exploratory data analysis of spatiotemporal trend information. A trend generally means a general direction in which a situation is changing / developing. Recent growth of computer and network systems has enabled us to obtain trend information at less cost, and it becomes important how to utilize such information. Exploratory data analysis is one of necessary activities of users to utilize trend information, in which users examine data space from various viewpoints using various views, notice interesting trend, and find interpretation useful for decision making or problem solving. As exploratory data analysis essentially involves trial and error, an interactive information visualization system that supports users' exploratory analysis of trend information should encourage users' trial and error. In order to design such systems, adequate interaction model that covers various actions to data space is necessary. In this paper, the visualization cube is proposed as abstract data model of spatiotemporal trend information, based on which interaction model for exploratory data analysis of spatiotemporal trend information is defined. The visualization cube consists of 4 axes; spatial and temporal axes, statistical data axis, and type-of-views axis. Interactions for generating views are defined as the operations on the visualization cube, which include drill down / up, comparison, spin, and transition. The interactive information visualization system for spatiotemporal trend information is developed based on the concept of visualization cube. Experiment is performed to compare the operating time between users with / without experience of using the system. The result shows the operations of the system based on the proposed interaction model are easy to understand without training. The system was also used in actual classes of an elementary school, of which the result shows the system has enough usability for 5th-grade elementary school children to perform exploratory data analysis.

  17. Video event detection: from subvolume localization to spatiotemporal path search.

    PubMed

    Tran, Du; Yuan, Junsong; Forsyth, David

    2014-02-01

    Although sliding window-based approaches have been quite successful in detecting objects in images, it is not a trivial problem to extend them to detecting events in videos. We propose to search for spatiotemporal paths for video event detection. This new formulation can accurately detect and locate video events in cluttered and crowded scenes, and is robust to camera motions. It can also well handle the scale, shape, and intraclass variations of the event. Compared to event detection using spatiotemporal sliding windows, the spatiotemporal paths correspond to the event trajectories in the video space, thus can better handle events composed by moving objects. We prove that the proposed search algorithm can achieve the global optimal solution with the lowest complexity. Experiments are conducted on realistic video data sets with different event detection tasks, such as anomaly event detection, walking person detection, and running detection. Our proposed method is compatible with different types of video features or object detectors and robust to false and missed local detections. It significantly improves the overall detection and localization accuracy over the state-of-the-art methods. PMID:24356358

  18. 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

  19. The Applicability of Spatiotemporal Oriented Energy Features to Region Tracking.

    PubMed

    Cannons, Kevin J; Wildes, Richard P

    2013-12-01

    This paper proposes the novel application of an uncommonly rich feature representation to the domain of visual tracking. The proposed representation for tracking models both the spatial structure and dynamics of a target in a unified fashion, while simultaneously offering robustness to illumination variations. Specifically, the proposed feature is derived from spatiotemporal energy measurements that are computed by filtering in 3D, (x, y, t), image spacetime. These spatiotemporal energy measurements capture the underlying local spacetime orientation structure of the target across multiple scales. The breadth of applicability of these features within the field of visual tracking is demonstrated by their instantiation within three disparate tracking paradigms that are representative of the various basic types of region trackers in the field. Instantiation within these three tracking paradigms requires that the raw oriented energy measurements be post-processed using different methodologies that range from histogram accumulation to the identity transform. Qualitative and quantitative empirical evaluation on a challenging suite of videos demonstrates the strength and applicability of the proposed representation to tracking, as it outperforms other commonly-used features across all tracking paradigms. Moreover, it is shown that overall high tracking accuracy can be obtained with this proposed representation, as spatiotemporal oriented energy instantiations are shown to outperform several recent, state-of-the-art trackers. PMID:24323883

  20. The Applicability of Spatiotemporal Oriented Energy Features to Region Tracking.

    PubMed

    Cannons, Kevin J; Wildes, Richard P

    2014-04-01

    This paper proposes the novel application of an uncommonly rich feature representation to the domain of visual tracking. The proposed representation for tracking models both the spatial structure and dynamics of a target in a unified fashion, while simultaneously offering robustness to illumination variations. Specifically, the proposed feature is derived from spatiotemporal energy measurements that are computed by filtering in 3D, (x, y, t), image spacetime. These spatiotemporal energy measurements capture the underlying local spacetime orientation structure of the target across multiple scales. The breadth of applicability of these features within the field of visual tracking is demonstrated by their instantiation within three disparate tracking paradigms that are representative of the various basic types of region trackers in the field. Instantiation within these three tracking paradigms requires that the raw oriented energy measurements be post-processed using different methodologies that range from histogram accumulation to the identity transform. Qualitative and quantitative empirical evaluation on a challenging suite of videos demonstrates the strength and applicability of the proposed representation to tracking, as it outperforms other commonly-used features across all tracking paradigms. Moreover, it is shown that overall high tracking accuracy can be obtained with this proposed representation, as spatiotemporal oriented energy instantiations are shown to outperform several recent, state-of-the-art trackers. PMID:26353200

  1. Plasticity of recurring spatiotemporal activity patterns in cortical networks

    NASA Astrophysics Data System (ADS)

    Madhavan, Radhika; Chao, Zenas C.; Potter, Steve M.

    2007-09-01

    How do neurons encode and store information for long periods of time? Recurring patterns of activity have been reported in various cortical structures and were suggested to play a role in information processing and memory. To study the potential role of bursts of action potentials in memory mechanisms, we investigated patterns of spontaneous multi-single-unit activity in dissociated rat cortical cultures in vitro. Spontaneous spikes were recorded from networks of approximately 50 000 neurons and glia cultured on a grid of 60 extracellular substrate- embedded electrodes (multi-electrode arrays). These networks expressed spontaneous culture- wide bursting from approximately one week in vitro. During bursts, a large portion of the active electrodes showed elevated levels of firing. Spatiotemporal activity patterns within spontaneous bursts were clustered using a correlation-based clustering algorithm, and the occurrences of these burst clusters were tracked over several hours. This analysis revealed spatiotemporally diverse bursts occurring in well-defined patterns, which remained stable for several hours. Activity evoked by strong local tetanic stimulation resulted in significant changes in the occurrences of spontaneous bursts belonging to different clusters, indicating that the dynamical flow of information in the neuronal network had been altered. The diversity of spatiotemporal structure and long-term stability of spontaneous bursts together with their plastic nature strongly suggests that such network patterns could be used as codes for information transfer and the expression of memories stored in cortical networks.

  2. Spatio-Temporal Simulation of First Pass Drug Perfusion in the Liver

    PubMed Central

    Schwen, Lars Ole; Krauss, Markus; Niederalt, Christoph; Gremse, Felix; Kiessling, Fabian; Schenk, Andrea; Preusser, Tobias; Kuepfer, Lars

    2014-01-01

    The liver is the central organ for detoxification of xenobiotics in the body. In pharmacokinetic modeling, hepatic metabolization capacity is typically quantified as hepatic clearance computed as degradation in well-stirred compartments. This is an accurate mechanistic description once a quasi-equilibrium between blood and surrounding tissue is established. However, this model structure cannot be used to simulate spatio-temporal distribution during the first instants after drug injection. In this paper, we introduce a new spatially resolved model to simulate first pass perfusion of compounds within the naive liver. The model is based on vascular structures obtained from computed tomography as well as physiologically based mass transfer descriptions obtained from pharmacokinetic modeling. The physiological architecture of hepatic tissue in our model is governed by both vascular geometry and the composition of the connecting hepatic tissue. In particular, we here consider locally distributed mass flow in liver tissue instead of considering well-stirred compartments. Experimentally, the model structure corresponds to an isolated perfused liver and provides an ideal platform to address first pass effects and questions of hepatic heterogeneity. The model was evaluated for three exemplary compounds covering key aspects of perfusion, distribution and metabolization within the liver. As pathophysiological states we considered the influence of steatosis and carbon tetrachloride-induced liver necrosis on total hepatic distribution and metabolic capacity. Notably, we found that our computational predictions are in qualitative agreement with previously published experimental data. The simulation results provide an unprecedented level of detail in compound concentration profiles during first pass perfusion, both spatio-temporally in liver tissue itself and temporally in the outflowing blood. We expect our model to be the foundation of further spatially resolved models of the liver in the future. PMID:24625393

  3. Spatio-temporal attributes of left ventricular pressure decay rate during isovolumic relaxation.

    PubMed

    Ghosh, Erina; Kovács, Sándor J

    2012-03-01

    Global left ventricular (LV) isovolumic relaxation rate has been characterized: 1) via the time constant of isovolumic relaxation ? or 2) via the logistic time constant ?(L). An alternate kinematic method, characterizes isovolumic relaxation (IVR) in accordance with Newton's Second Law. The model's parameters, stiffness E(k), and damping/relaxation ? result from best fit of model-predicted pressure to in vivo data. All three models (exponential, logistic, and kinematic) characterize global relaxation in terms of pressure decay rates. However, IVR is inhomogeneous and anisotropic. Apical and basal LV wall segments untwist at different times and rates, and transmural strain and strain rates differ due to the helically variable pitch of myocytes and sheets. Accordingly, we hypothesized that the exponential model (?) or kinematic model (? and E(k)) parameters will elucidate the spatiotemporal variation of IVR rate. Left ventricular pressures in 20 subjects were recorded using a high-fidelity, multipressure transducer (3 cm apart) catheter. Simultaneous, dual-channel pressure data was plotted in the pressure phase-plane (dP/dt vs. P) and ?, ?, and E(k) were computed in 1631 beats (average: 82 beats per subject). Tau differed significantly between the two channels (P < 0.05) in 16 of 20 subjects, whereas ? and E(k) differed significantly (P < 0.05) in all 20 subjects. These results show that quantifying the relaxation rate from data recorded at a single location has limitations. Moreover, kinematic model based analysis allows characterization of restoring (recoil) forces and resistive (crossbridge uncoupling) forces during IVR and their spatio-temporal dependence, thereby elucidating the relative roles of stiffness vs. relaxation as IVR rate determinants. PMID:22210748

  4. Evolution of Predator Dispersal in Relation to Spatio-Temporal Prey Dynamics: How Not to Get Stuck in the Wrong Place!

    PubMed Central

    Travis, Justin M. J.; Palmer, Stephen C. F.; Coyne, Steven; Millon, Alexandre; Lambin, Xavier

    2013-01-01

    The eco-evolutionary dynamics of dispersal are recognised as key in determining the responses of populations to environmental changes. Here, by developing a novel modelling approach, we show that predators are likely to have evolved to emigrate more often and become more selective over their destination patch when their prey species exhibit spatio-temporally complex dynamics. We additionally demonstrate that the cost of dispersal can vary substantially across space and time. Perhaps as a consequence of current environmental change, many key prey species are currently exhibiting major shifts in their spatio-temporal dynamics. By exploring similar shifts in silico, we predict that predator populations will be most vulnerable when prey dynamics shift from stable to complex. The more sophisticated dispersal rules, and greater variance therein, that evolve under complex dynamics will enable persistence across a broader range of prey dynamics than the rules which evolve under relatively stable prey conditions. PMID:23408940

  5. Evolution of predator dispersal in relation to spatio-temporal prey dynamics: how not to get stuck in the wrong place!

    PubMed

    Travis, Justin M J; Palmer, Stephen C F; Coyne, Steven; Millon, Alexandre; Lambin, Xavier

    2013-01-01

    The eco-evolutionary dynamics of dispersal are recognised as key in determining the responses of populations to environmental changes. Here, by developing a novel modelling approach, we show that predators are likely to have evolved to emigrate more often and become more selective over their destination patch when their prey species exhibit spatio-temporally complex dynamics. We additionally demonstrate that the cost of dispersal can vary substantially across space and time. Perhaps as a consequence of current environmental change, many key prey species are currently exhibiting major shifts in their spatio-temporal dynamics. By exploring similar shifts in silico, we predict that predator populations will be most vulnerable when prey dynamics shift from stable to complex. The more sophisticated dispersal rules, and greater variance therein, that evolve under complex dynamics will enable persistence across a broader range of prey dynamics than the rules which evolve under relatively stable prey conditions. PMID:23408940

  6. Dengue-2 Structural Proteins Associate with Human Proteins to Produce a Coagulation and Innate Immune Response Biased Interactome

    PubMed Central

    2011-01-01

    Background Dengue virus infection is a public health threat to hundreds of millions of individuals in the tropical regions of the globe. Although Dengue infection usually manifests itself in its mildest, though often debilitating clinical form, dengue fever, life-threatening complications commonly arise in the form of hemorrhagic shock and encephalitis. The etiological basis for the virus-induced pathology in general, and the different clinical manifestations in particular, are not well understood. We reasoned that a detailed knowledge of the global biological processes affected by virus entry into a cell might help shed new light on this long-standing problem. Methods A bacterial two-hybrid screen using DENV2 structural proteins as bait was performed, and the results were used to feed a manually curated, global dengue-human protein interaction network. Gene ontology and pathway enrichment, along with network topology and microarray meta-analysis, were used to generate hypothesis regarding dengue disease biology. Results Combining bioinformatic tools with two-hybrid technology, we screened human cDNA libraries to catalogue proteins physically interacting with the DENV2 virus structural proteins, Env, cap and PrM. We identified 31 interacting human proteins representing distinct biological processes that are closely related to the major clinical diagnostic feature of dengue infection: haemostatic imbalance. In addition, we found dengue-binding human proteins involved with additional key aspects, previously described as fundamental for virus entry into cells and the innate immune response to infection. Construction of a DENV2-human global protein interaction network revealed interesting biological properties suggested by simple network topology analysis. Conclusions Our experimental strategy revealed that dengue structural proteins interact with human protein targets involved in the maintenance of blood coagulation and innate anti-viral response processes, and predicts that the interaction of dengue proteins with a proposed human protein interaction network produces a modified biological outcome that may be behind the hallmark pathologies of dengue infection. PMID:21281507

  7. Spatiotemporal fuzzy based climate forecasting for Australia

    NASA Astrophysics Data System (ADS)

    Montazerolghaem, M.; Vervoort, R. W.; Minasny, B.; McBratney, A.

    2012-12-01

    Variation in weather and climate events impacts agriculture production processes, and profits across years. Therefore, seasonal rainfall prediction is an important factor for strategic and tactical decision making in agricultural, land and water resource management. This study aims to apply optimal data-driven techniques for fine resolution climate classification and forecasting over South-eastern Australia. Data were used in this study were included daily precipitation, maximum and minimum temperature data collected over 40 years from 107 weather stations in Southeast Australia acquired from the Bureau of Meteorology (BOM). Fuzzy-k means clustering techniques (FKM) were applied on one year weekly time series. Cluster centroids and memberships of rainfall and temperature weekly time series for one year period provide meaningful and insight into weather variability in time and space over the study. Stations are grouped based on their memberships in rainfall and temperature classes. The result showed that FKM is a useful method for trend analysis and pattern discovery in space and time. Outcomes indicate improvement in the climate classification of the area at the station level. An associate project is gathering higher spatial density on-farm data. This high-resolution climate data collected at the farm scale will be analyzed similarly in the future to improve spatial resolution of our classification. The second stage of this study consists of development of a fine-resolution forecasting model for predicting rainfall. FKM was applied on a metrics which included input and output time series to extract rules and relationships between them. After classification, rules were extracted within each class based on forecasting time, space and extreme climate events followed by effective sea surface temperature anomalies. These rules and a lookup table of input and output centroids were used for rainfall prediction in the form of weekly time series for the next six months. One major advantage of this method is its flexibility, which allows analyst to have clear view regarding weather variability over time and space. Correspondingly, it will assist the analyst to interact with the model by adding new rules based on expert knowledge of climate conditions and variability. Improvements in this model are currently under investigation. This study and model results may well be significant because they consider both local climate feedbacks and the continental drivers in time series format.

  8. Spatio-temporal analysis of brain electrical activity in epilepsy based on cellular nonlinear networks

    NASA Astrophysics Data System (ADS)

    Gollas, Frank; Tetzlaff, Ronald

    2009-05-01

    Epilepsy is the most common chronic disorder of the nervous system. Generally, epileptic seizures appear without foregoing sign or warning. The problem of detecting a possible pre-seizure state in epilepsy from EEG signals has been addressed by many authors over the past decades. Different approaches of time series analysis of brain electrical activity already are providing valuable insights into the underlying complex dynamics. But the main goal the identification of an impending epileptic seizure with a sufficient specificity and reliability, has not been achieved up to now. An algorithm for a reliable, automated prediction of epileptic seizures would enable the realization of implantable seizure warning devices, which could provide valuable information to the patient and time/event specific drug delivery or possibly a direct electrical nerve stimulation. Cellular Nonlinear Networks (CNN) are promising candidates for future seizure warning devices. CNN are characterized by local couplings of comparatively simple dynamical systems. With this property these networks are well suited to be realized as highly parallel, analog computer chips. Today available CNN hardware realizations exhibit a processing speed in the range of TeraOps combined with low power consumption. In this contribution new algorithms based on the spatio-temporal dynamics of CNN are considered in order to analyze intracranial EEG signals and thus taking into account mutual dependencies between neighboring regions of the brain. In an identification procedure Reaction-Diffusion CNN (RD-CNN) are determined for short segments of brain electrical activity, by means of a supervised parameter optimization. RD-CNN are deduced from Reaction-Diffusion Systems, which usually are applied to investigate complex phenomena like nonlinear wave propagation or pattern formation. The Local Activity Theory provides a necessary condition for emergent behavior in RD-CNN. In comparison linear spatio-temporal autoregressive filter models are considered, for a prediction of EEG signal values. Thus Signal features values for successive, short, quasi stationary segments of brain electrical activity can be obtained, with the objective of detecting distinct changes prior to impending epileptic seizures. Furthermore long term recordings gained during presurgical diagnostics in temporal lobe epilepsy are analyzed and the predictive performance of the extracted features is evaluated statistically. Therefore a Receiver Operating Characteristic analysis is considered, assessing the distinguishability between distributions of supposed preictal and interictal periods.

  9. Spatiotemporal Patterns of Urban Human Mobility

    NASA Astrophysics Data System (ADS)

    Hasan, Samiul; Schneider, Christian M.; Ukkusuri, Satish V.; González, Marta C.

    2013-04-01

    The modeling of human mobility is adopting new directions due to the increasing availability of big data sources from human activity. These sources enclose digital information about daily visited locations of a large number of individuals. Examples of these data include: mobile phone calls, credit card transactions, bank notes dispersal, check-ins in internet applications, among several others. In this study, we consider the data obtained from smart subway fare card transactions to characterize and model urban mobility patterns. We present a simple mobility model for predicting peoples' visited locations using the popularity of places in the city as an interaction parameter between different individuals. This ingredient is sufficient to reproduce several characteristics of the observed travel behavior such as: the number of trips between different locations in the city, the exploration of new places and the frequency of individual visits of a particular location. Moreover, we indicate the limitations of the proposed model and discuss open questions in the current state of the art statistical models of human mobility.

  10. Spatiotemporal Variability of Precipitation, Modeled Soil Moisture, and Vegetation Greenness in North America within the Recent Observational Record

    E-print Network

    Castro, Christopher L.

    Spatiotemporal Variability of Precipitation, Modeled Soil Moisture, and Vegetation Greenness) ABSTRACT Dominant spatiotemporal patterns of precipitation, modeled soil moisture, and vegetation in soil moisture and vegetation, respectively. The 9-yr signal is related to precipitation in late fall

  11. Spatiotemporal Patterns of Evapotranspiration in Response to Multiple Environmental Factors Simulated by the Community Land Model

    SciTech Connect

    Shi, Xiaoying; Mao, Jiafu; Thornton, P.; Huang, Maoyi

    2013-04-25

    Spatiotemporal patterns of evapotranspiration (ET) over the period from 1982 to 2008 are investigated and attributed to multiple environmental factors using the Community Land Model version 4 (CLM4). Our results show that CLM4 captures the spatial distribution and interannual variability of ET well when compared to observation-based estimates. We find that climate dominates the predicted variability in ET. Elevated atmospheric CO2 concentration also plays an important role in modulating the trend of predicted ET over most land areas, and replaces climate to function as the dominant factor controlling ET changes over the North America, South America and Asia regions. Compared to the effect of climate and CO2 concentration, the roles of other factors such as nitrogen deposition, land use change and aerosol deposition are less pronounced and regionally dependent. The aerosol deposition contribution is the third most important factor for trends of ET over Europe, while it has the smallest impact over other regions. As ET is a dominant component of the terrestrial water cycle, our results suggest that environmental factors like elevated CO2, nitrogen and aerosol depositions, and land use change, in addition to climate, could have significant impact on future projections of water resources and water cycle dynamics at global and regional scales.

  12. Spatiotemporal variation in linear natural selection on body color in wild guppies (Poecilia reticulata).

    PubMed

    Weese, Dylan J; Gordon, Swanne P; Hendry, Andrew P; Kinnison, Michael T

    2010-06-01

    We conducted 10 mark-recapture experiments in natural populations of Trinidadian guppies to test hypotheses concerning the role of viability selection in geographic patterns of male color variation. Previous work has reported that male guppies are more colorful in low-predation sites than in high-predation sites. This pattern of phenotypic variation has been theorized to reflect differences in the balance between natural (viability) selection that disfavors bright male color (owing to predation) and sexual selection that favors bright color (owing to female choice). Our results support the prediction that male color is disfavored by viability selection in both predation regimes. However, it does not support the prediction that viability selection against male color is weaker in low-predation experiments. Instead, some of the most intense bouts of selection against color occurred in low-predation experiments. Our results illustrate considerable spatiotemporal variation in selection among experiments, but such variation was not generally correlated with local patterns of color diversity. More complex selective interactions, possibly including the indirect effects of predators on variation in mating behavior, as well as other environmental factors, might be required to more fully explain patterns of secondary sexual trait variation in this system. PMID:20067520

  13. Climate-Driven Phenological Change: Developing Robust Spatiotemporal Modeling and Projection Capability

    PubMed Central

    Prieto, Carmen; Destouni, Georgia

    2015-01-01

    Our possibility to appropriately detect, interpret and respond to climate-driven phenological changes depends on our ability to model and predict the changes. This ability may be hampered by non-linearity in climate-phenological relations, and by spatiotemporal variability and scale mismatches of climate and phenological data. A modeling methodology capable of handling such complexities can be a powerful tool for phenological change projection. Here we develop such a methodology using citizen scientists’ observations of first flight dates for orange tip butterflies (Anthocharis cardamines) in three areas extending along a steep climate gradient. The developed methodology links point data of first flight observations to calculated cumulative degree-days until first flight based on gridded temperature data. Using this methodology we identify and quantify a first flight model that is consistent across different regions, data support scales and assumptions of subgrid variability and observation bias. Model application to observed warming over the past 60 years demonstrates the model usefulness for assessment of climate-driven first flight change. The cross-regional consistency of the model implies predictive capability for future changes, and calls for further application and testing of analogous modeling approaches to other species, phenological variables and parts of the world. PMID:26545112

  14. Climate-Driven Phenological Change: Developing Robust Spatiotemporal Modeling and Projection Capability.

    PubMed

    Prieto, Carmen; Destouni, Georgia

    2015-01-01

    Our possibility to appropriately detect, interpret and respond to climate-driven phenological changes depends on our ability to model and predict the changes. This ability may be hampered by non-linearity in climate-phenological relations, and by spatiotemporal variability and scale mismatches of climate and phenological data. A modeling methodology capable of handling such complexities can be a powerful tool for phenological change projection. Here we develop such a methodology using citizen scientists' observations of first flight dates for orange tip butterflies (Anthocharis cardamines) in three areas extending along a steep climate gradient. The developed methodology links point data of first flight observations to calculated cumulative degree-days until first flight based on gridded temperature data. Using this methodology we identify and quantify a first flight model that is consistent across different regions, data support scales and assumptions of subgrid variability and observation bias. Model application to observed warming over the past 60 years demonstrates the model usefulness for assessment of climate-driven first flight change. The cross-regional consistency of the model implies predictive capability for future changes, and calls for further application and testing of analogous modeling approaches to other species, phenological variables and parts of the world. PMID:26545112

  15. Finding Spatio-Temporal Patterns in Earth Science Data * Pang-Ning Tan+

    E-print Network

    Kumar, Vipin

    1 Finding Spatio-Temporal Patterns in Earth Science Data * Pang-Ning Tan+ Michael Steinbach+ Vipin-temporal patterns from Earth Science data. The data consists of time series measurements for various Earth science of the spatio-temporal issues. Earth Science data has strong seasonal components that need to be removed prior

  16. Journal of Statistical Physics, Vol. 54, Nos. 5/6, 1989 Spatiotemporal Chaos and Noise

    E-print Network

    Kaneko, Kunihiko

    ; spatiotemporal chaos; noise-induced transitions. 1. INTRODUCTION The study of chaotic dynamics has given us a new, in the case of turbulence or spatiotemporal chaos. If the spatial correlations decay at length scales smaller a nontrivial incoherent structure in space. It can serve as model for fluid turbulence, chemical reaction

  17. Diffusion weighted MRI by spatiotemporal encoding: Analytical description and in vivo validations

    E-print Network

    Frydman, Lucio

    Diffusion weighted MRI by spatiotemporal encoding: Analytical description and in vivo validations Diffusion-weighted MRI Spatiotemporal encoding a b s t r a c t Diffusion-weighted (DW) MRI is a powerful impart different diffusion weightings along the spatial axes. These will be further complicated in DW

  18. Data Repository Spatiotemporal trends in erosion rates across a pronounced rainfall

    E-print Network

    Bookhagen, Bodo

    Data Repository Spatiotemporal trends in erosion rates across a pronounced rainfall gradient. Geologic and Climatic Setting #12;B. Bookhagen and M.R. Strecker: Spatiotemporal trends in erosion rates trends in erosion rates Figure DR 2: Comparison of mean annual discharges from high spatial resolution

  19. Spatiotemporal Assignment of Energy Harvesters on a Self-Sustaining Medical Shoe

    E-print Network

    Potkonjak, Miodrag

    Spatiotemporal Assignment of Energy Harvesters on a Self-Sustaining Medical Shoe James B. Wendt for spatiotemporal as- signment and scheduling of energy harvesters on a medical shoe tasked with measuring gait does it address integration into existing sensing systems. We solve these issues and present a self

  20. Spatio-Temporal Sequence Learning of Visual Place Cells for Robotic Navigation

    E-print Network

    Starzyk, Janusz A.

    Spatio-Temporal Sequence Learning of Visual Place Cells for Robotic Navigation Vu Anh Nguyen-temporal sequence learning architecture of visual place cells to leverage autonomous navigation. The construction the efficiency and efficacy of a hippocampal-inspired visual place cell model and its spatio-temporal sequence

  1. Spatio-Temporal Data Warehouses and Mobility Data: Current Status and Research Issues

    E-print Network

    Libre de Bruxelles, Université

    Spatio-Temporal Data Warehouses and Mobility Data: Current Status and Research Issues Esteban Zim in this respect concerns mobility data management, i.e., storing mobility data in a data warehouse for their subsuquent analysis. This paper introduces the notion of spatio-temporal data warehouses and shows how

  2. Indexing Spatio-Temporal Data Warehouses Dimitris Papadias, Yufei Tao, Panos Kalnis, and Jun Zhang

    E-print Network

    Papadias, Dimitris

    Indexing Spatio-Temporal Data Warehouses Dimitris Papadias, Yufei Tao, Panos Kalnis, and Jun Zhang. A vital solution is the construction of a spatiotemporal data warehouse. In this paper, we describe retrieval [GBE+ 00], motion and trajectory preservation [PJT00], future location estimation [SJLL00] etc

  3. Scale-free model for spatio-temporal distribution of outbreaks of avian influenza

    E-print Network

    Tse, Chi K. "Michael"

    Scale-free model for spatio-temporal distribution of outbreaks of avian influenza Michael Small influenza outbreaks among wild and domestic birds, we show that this model is not appropriate. We find the global spatio-temporal distribution of avian influenza cases in both wild and domestic birds and find

  4. ClusterSheddy: Load Shedding Using Moving Clusters over Spatio-Temporal Data Streams

    E-print Network

    ClusterSheddy: Load Shedding Using Moving Clusters over Spatio-Temporal Data Streams Rimma V. Nehme randomly, the most fre- quently used approach in the literature for load shedding, may adversely affect the accuracy of the results. We thus propose a load shedding tech- nique customized for spatio-temporal stream

  5. BLMP-1/Blimp-1 Regulates the Spatiotemporal Cell Migration Pattern in C.

    E-print Network

    Wu, Yih-Min

    Spatiotemporal regulation of cell migration is crucial for animal development and organogenesis. ComparedBLMP-1/Blimp-1 Regulates the Spatiotemporal Cell Migration Pattern in C. elegans PLOS Genetics. In the Caenorhabditis elegans hermaphrodite, the stereotyped migration pattern of two somatic distal tip cells (DTCs

  6. Mining Association Rules in Spatio-Temporal Data J. Mennis and J.W. Liu

    E-print Network

    Mennis, Jeremy

    Mining Association Rules in Spatio-Temporal Data J. Mennis and J.W. Liu Department of Geography mining to spatio- temporal data. Association rule mining seeks to discover associations among of a certain type of data mining technique, association rule mining, to spatio-temporal data. As a case study

  7. INCORPORATING THE SPATIO-TEMPORAL DISTRIBUTION OF RAINFALL AND BASIN GEOMORPHOLOGY INTO NONLINEAR

    E-print Network

    Foufoula-Georgiou, Efi

    1 INCORPORATING THE SPATIO-TEMPORAL DISTRIBUTION OF RAINFALL AND BASIN GEOMORPHOLOGY INTO NONLINEAR streamflow series, spatio-temporal structure of precipitation and catchment geomorphology into a nonlinear of incorporating process-specific information (in terms of catchment geomorphology and an a-priori chosen

  8. Mercury: A Memory-Constrained Spatio-temporal Real-time Search on Microblogs

    E-print Network

    Mokbel, Mohamed F.

    Mercury: A Memory-Constrained Spatio-temporal Real-time Search on Microblogs Amr Magdy1§ , Mohamed Mercury; a system for real-time support of top-k spatio-temporal queries on microblogs, where users are able to browse recent microblogs near their locations. With high arrival rates of microblogs, Mercury

  9. Spatiotemporal trends in erosion rates across a pronounced rainfall gradient: Examples from the southern Central Andes

    E-print Network

    Bookhagen, Bodo

    Spatiotemporal trends in erosion rates across a pronounced rainfall gradient: Examples from online 7 March 2012 Editor: T.M. Harrison Keywords: erosion landscape evolution specific stream power analyze the impact of spatiotemporal climatic gradients on surface erosion: First, we present 41 new

  10. USING SPATIOTEMPORAL RELATIONAL RANDOM FORESTS TO IMPROVE OUR UNDERSTANDING OF SEVERE WEATHER PROCESSES

    E-print Network

    McGovern, Amy

    USING SPATIOTEMPORAL RELATIONAL RANDOM FORESTS TO IMPROVE OUR UNDERSTANDING OF SEVERE WEATHER, AND JOHN K. WILLIAMS5 Abstract. Major severe weather events can cause a significant loss of life the mining of severe weather data. Because weather is inherently a spatiotemporal phenomenon, mining

  11. Efficient Data Assimilation for Spatiotemporal Chaos: a Local Ensemble Transform Kalman Filter

    E-print Network

    Maryland at College Park, University of

    Efficient Data Assimilation for Spatiotemporal Chaos: a Local Ensemble Transform Kalman Filter assimilation in large, spatiotemporally chaotic systems. The method is a type of "ensemble Kalman filter previously published approaches to ensemble 1 #12;Kalman filtering. We include some numerical results

  12. Virtualized Traffic: Reconstructing Traffic Flows from Discrete Spatio-Temporal Data

    E-print Network

    North Carolina at Chapel Hill, University of

    Virtualized Traffic: Reconstructing Traffic Flows from Discrete Spatio-Temporal Data Jur van den continuous traffic flows from discrete spatio-temporal data provided by traffic sensors or generated artificially to enhance a sense of immersion in a dynamic virtual world. Given the po- sitions of each car

  13. Random coupling of chaotic maps leads to spatiotemporal synchronization Sudeshna Sinha*

    E-print Network

    Sinha, Sudeshna

    Random coupling of chaotic maps leads to spatiotemporal synchronization Sudeshna Sinha* Institute of randomness in coupling connections. While strictly nearest neighbor coupling never allows spatiotemporal synchronization in our system, randomly rewiring some of those connections stabilizes entire networks at x*, where

  14. The Spatiotemporal Land use/cover Change of Adana City

    NASA Astrophysics Data System (ADS)

    Ak?n, A.; Erdo?an, M. A.; Berbero?lu, S.

    2013-10-01

    The major driving factors for land use planning are largely limited to socio-economic inputs that do not completely represent the spatio-temporal patterns and ecological inputs have often been neglected. Integration of remote sensing and GIS techniques enabled successful applications in characterizing the spatiotemporal trends of land use/land cover (LULC) change. This study demonstrated an approach that combines remote sensing, landscape metrics, and LULC change analysis as a promising tool for understanding spatiotemporal patterns of Adana city. Calculation of spatial metrics was based on a categorical, patch-based representation of the landscape. Landscape metrics are conceptual framework for sustainable landscape and ecological planning. LULC change analysis was performed by considering the metric calculation. Post-classification technique was used for the metric based change detection and two different remotely sensed data set recorded in 1967 (CORONA) and 2007 (ALOS AVNIR) were used for the analysis. Additionally, a LULC projection for the year 2023 was also generated and integrated to the change analysis. SLEUTH model was utilised as a urban growth model for the future developments of study area in the scope of Cellular Automata (CA). SLEUTH model contains the main elements that characterize the core characteristics of CA: it works in a grid space of homogeneous cells, with a neighburhood of eight cells, two cell states and five transition rules that act in sequential time steps. Most useful and relevant metrics for landscape including: percentage of landscape, patch density, edge density, largest patch index, Euclidian mean nearest neighbor distance, area weighted mean patch fractal dimension and contagion were calculated for the 1967, 2007 and 2023 LULC maps and temporal changes were determined for the study area. Most considerable change was observed on the agricultural areas. Urban sprawl is the major driving factor of the LULC change.

  15. Spatiotemporal Dynamics of Word Processing in the Human Brain

    PubMed Central

    Canolty, Ryan T.; Soltani, Maryam; Dalal, Sarang S.; Edwards, Erik; Dronkers, Nina F.; Nagarajan, Srikantan S.; Kirsch, Heidi E.; Barbaro, Nicholas M.; Knight, Robert T.

    2007-01-01

    We examined the spatiotemporal dynamics of word processing by recording the electrocorticogram (ECoG) from the lateral frontotemporal cortex of neurosurgical patients chronically implanted with subdural electrode grids. Subjects engaged in a target detection task where proper names served as infrequent targets embedded in a stream of task-irrelevant verbs and nonwords. Verbs described actions related to the hand (e.g, throw) or mouth (e.g., blow), while unintelligible nonwords were sounds which matched the verbs in duration, intensity, temporal modulation, and power spectrum. Complex oscillatory dynamics were observed in the delta, theta, alpha, beta, low, and high gamma (HG) bands in response to presentation of all stimulus types. HG activity (80–200?Hz) in the ECoG tracked the spatiotemporal dynamics of word processing and identified a network of cortical structures involved in early word processing. HG was used to determine the relative onset, peak, and offset times of local cortical activation during word processing. Listening to verbs compared to nonwords sequentially activates first the posterior superior temporal gyrus (post-STG), then the middle superior temporal gyrus (mid-STG), followed by the superior temporal sulcus (STS). We also observed strong phase-locking between pairs of electrodes in the theta band, with weaker phase-locking occurring in the delta, alpha, and beta frequency ranges. These results provide details on the first few hundred milliseconds of the spatiotemporal evolution of cortical activity during word processing and provide evidence consistent with the hypothesis that an oscillatory hierarchy coordinates the flow of information between distinct cortical regions during goal-directed behavior. PMID:18982128

  16. Refined estimate of China's CO2 emissions in spatiotemporal distributions

    NASA Astrophysics Data System (ADS)

    Liu, M.-M.; Wang, H.-K.; Wang, H.-M.; Oda, T.; Zhao, Y.; Yang, X.-H.; Zhang, R.-R.; Zhang, B.; Bi, J.; Chen, J.-M.

    2013-07-01

    Being the largest contributor to the global source of fossil-fuel CO2 emissions, China's emissions need to be accurately quantified and well understood. Previous studies have usually focused on the amount of national emissions and rarely discussed their spatiotemporal distributions, which are also crucial for both carbon flux and carbon management. In this study, we calculated China's CO2 emissions from fossil fuel use and industrial processes using provincial statistics and then mapped those emissions at 0.25° resolution on monthly basis. Several key steps have been implemented to gain a better understanding of the spatiotemporal distributions, including (1) development and application of China's CO2 emission inventories using provincial statistics; (2) separate calculations of emissions from large point sources and accurate identification of their geographical locations; (3) development of 1 km×1 km gridded population and GDP data for China from 2000 to 2009 and application of them as dynamic spatial proxies to allocate emissions; and (4) monthly variation curves of CO2 emissions from various sectors were developed for each province and applied to our inventory. China's total CO2 emission from fossil fuel and industrial process have increased from 3.6 billion tons in 2000 to 8.6 billion tons in 2009, which may be off by 14-18% and are enough to skew global totals. And the resulting spatiotemporal distributions of our inventories also differed greatly in several ways from those derived using national statistics and population-based approach for the various economic development levels, industrial and energy structures, and even large point emissions sources within China and each province.

  17. Refined estimate of China's CO2 emissions in spatiotemporal distributions

    NASA Astrophysics Data System (ADS)

    Liu, M.; Wang, H.; Wang, H.; Oda, T.; Zhao, Y.; Yang, X.; Zang, R.; Zang, B.; Bi, J.; Chen, J.

    2013-11-01

    Being the largest contributor to the global source of fossil-fuel CO2 emissions, China's emissions need to be accurately quantified and well understood. Previous studies have usually focused on the amount of national emissions and rarely discussed their spatiotemporal distributions, which are also crucial for both carbon flux and carbon management. In this study, we calculated China's CO2 emissions from fossil fuel use and industrial processes using provincial statistics and then mapped those emissions at 0.25° resolution on a monthly basis. Several key steps have been implemented to gain a better understanding of the spatiotemporal distributions, including (1) development and application of China's CO2 emission inventories using provincial statistics; (2) separate calculations of emissions from large point sources and accurate identification of their geographical locations; (3) development of 1 km × 1 km gridded population and GDP (gross domestic product) data for China from 2000 to 2009 and application of them as dynamic spatial proxies to allocate emissions; and (4) monthly variation curves of CO2 emissions from various sectors that were developed for each province and applied to our inventory. China's total CO2 emission from fossil fuels and industrial processes has increased from 3.6 billion tons in 2000 to 8.6 billion tons in 2009, which may be off by 14-18% and is enough to skew global totals. The resulting spatiotemporal distributions of our inventories also differed greatly in several ways from those derived using a national statistics and population-based approach for the various economic development levels, industrial and energy structures, and even large point emission sources within China and each province.

  18. The spatiotemporal organization of cerebellar network activity resolved by two-photon imaging of multiple single neurons

    PubMed Central

    Gandolfi, Daniela; Pozzi, Paolo; Tognolina, Marialuisa; Chirico, Giuseppe; Mapelli, Jonathan; D'Angelo, Egidio

    2014-01-01

    In order to investigate the spatiotemporal organization of neuronal activity in local microcircuits, techniques allowing the simultaneous recording from multiple single neurons are required. To this end, we implemented an advanced spatial-light modulator two-photon microscope (SLM-2PM). A critical issue for cerebellar theory is the organization of granular layer activity in the cerebellum, which has been predicted by single-cell recordings and computational models. With SLM-2PM, calcium signals could be recorded from different network elements in acute cerebellar slices including granule cells (GrCs), Purkinje cells (PCs) and molecular layer interneurons. By combining WCRs with SLM-2PM, the spike/calcium relationship in GrCs and PCs could be extrapolated toward the detection of single spikes. The SLM-2PM technique made it possible to monitor activity of over tens to hundreds neurons simultaneously. GrC activity depended on the number of spikes in the input mossy fiber bursts. PC and molecular layer interneuron activity paralleled that in the underlying GrC population revealing the spread of activity through the cerebellar cortical network. Moreover, circuit activity was increased by the GABA-A receptor blocker, gabazine, and reduced by the AMPA and NMDA receptor blockers, NBQX and APV. The SLM-2PM analysis of spatiotemporal patterns lent experimental support to the time-window and center-surround organizing principles of the granular layer. PMID:24782707

  19. The spatiotemporal organization of cerebellar network activity resolved by two-photon imaging of multiple single neurons.

    PubMed

    Gandolfi, Daniela; Pozzi, Paolo; Tognolina, Marialuisa; Chirico, Giuseppe; Mapelli, Jonathan; D'Angelo, Egidio

    2014-01-01

    In order to investigate the spatiotemporal organization of neuronal activity in local microcircuits, techniques allowing the simultaneous recording from multiple single neurons are required. To this end, we implemented an advanced spatial-light modulator two-photon microscope (SLM-2PM). A critical issue for cerebellar theory is the organization of granular layer activity in the cerebellum, which has been predicted by single-cell recordings and computational models. With SLM-2PM, calcium signals could be recorded from different network elements in acute cerebellar slices including granule cells (GrCs), Purkinje cells (PCs) and molecular layer interneurons. By combining WCRs with SLM-2PM, the spike/calcium relationship in GrCs and PCs could be extrapolated toward the detection of single spikes. The SLM-2PM technique made it possible to monitor activity of over tens to hundreds neurons simultaneously. GrC activity depended on the number of spikes in the input mossy fiber bursts. PC and molecular layer interneuron activity paralleled that in the underlying GrC population revealing the spread of activity through the cerebellar cortical network. Moreover, circuit activity was increased by the GABA-A receptor blocker, gabazine, and reduced by the AMPA and NMDA receptor blockers, NBQX and APV. The SLM-2PM analysis of spatiotemporal patterns lent experimental support to the time-window and center-surround organizing principles of the granular layer. PMID:24782707

  20. Spatiotemporal chaos induces extreme events in an extended microcavity laser

    E-print Network

    F Selmi; S Coulibaly; Z Loghmari; Marcel G. Clerc; Sylvain Barbay

    2015-11-25

    Extreme events such as rogue wave in optics and fluids are often associated with the merging dynamics of coherent structures. We present experimental and numerical results on the physics of extreme events appearance in a spatially extended semiconductor microcavity laser with intracavity saturable absorber. This system can display deterministic irregular dynamics only thanks to spatial coupling through diffraction of light. We have identified parameter regions where extreme events are encountered and established the origin of this dynamics in the emergence of deterministic spatiotemporal chaos, through the correspondence between the proportion of extreme events and the dimension of the strange attractor.

  1. Spatiotemporal chaos induces extreme events in an extended microcavity laser

    E-print Network

    F Selmi; S Coulibaly; Z Loghmari; Isabelle Sagnes; Gregoire Beaudoin; Marcel G. Clerc; Sylvain Barbay

    2015-12-18

    Extreme events such as rogue wave in optics and fluids are often associated with the merging dynamics of coherent structures. We present experimental and numerical results on the physics of extreme events appearance in a spatially extended semiconductor microcavity laser with intracavity saturable absorber. This system can display deterministic irregular dynamics only thanks to spatial coupling through diffraction of light. We have identified parameter regions where extreme events are encountered and established the origin of this dynamics in the emergence of deterministic spatiotemporal chaos, through the correspondence between the proportion of extreme events and the dimension of the strange attractor.

  2. Moving target detection in thermal infrared imagery using spatiotemporal information.

    PubMed

    Akula, Aparna; Ghosh, Ripul; Kumar, Satish; Sardana, H K

    2013-08-01

    An efficient target detection algorithm for detecting moving targets in infrared imagery using spatiotemporal information is presented. The output of the spatial processing serves as input to the temporal stage in a layered manner. The spatial information is obtained using joint space-spatial-frequency distribution and Rényi entropy. Temporal information is incorporated using background subtraction. By utilizing both spatial and temporal information, it is observed that the proposed method can achieve both high detection and a low false-alarm rate. The method is validated with experimentally generated data consisting of a variety of moving targets. Experimental results demonstrate a high value of F-measure for the proposed algorithm. PMID:24323206

  3. Spatiotemporal dynamics of Kerr-Raman optical frequency combs

    NASA Astrophysics Data System (ADS)

    Chembo, Yanne K.; Grudinin, Ivan S.; Yu, Nan

    2015-10-01

    Optical frequency combs generated with ultrahigh-Q whispering-gallery-mode resonators are expected to provide a compact, versatile, and energy-efficient source for the generation of coherent lightwave and microwave signals. So far, Kerr and Raman nonlinearities in these resonators have predominantly been investigated separately, even though both effects originate from the same third-order susceptibility. We present a spatiotemporal formalism for the theoretical understanding of these Kerr-Raman combs, which allows us to describe the complex interplay between both nonlinearities and all-order dispersion. These theoretical findings are successfully compared with experiments performed with ultrahigh-Q calcium and magnesium fluoride resonators.

  4. Spatio-temporal dynamics in the origin of genetic information

    NASA Astrophysics Data System (ADS)

    Kim, Pan-Jun; Jeong, Hawoong

    2005-04-01

    We study evolutionary processes induced by spatio-temporal dynamics in prebiotic evolution. Using numerical simulations, we demonstrate that hypercycles emerge from complex interaction structures in multispecies systems. In this work, we also find that ‘hypercycle hybrid’ protects the hypercycle from its environment during the growth process. There is little selective advantage for one hypercycle to maintain coexistence with others. This brings the possibility of the outcompetition between hypercycles resulting in the negative effect on information diversity. To enrich the information in hypercycles, symbiosis with parasites is suggested. It is shown that symbiosis with parasites can play an important role in the prebiotic immunology.

  5. Oscillations, complex spatiotemporal behavior, and information transport in networks of excitatory and inhibitory neurons

    SciTech Connect

    Destexhe, A. )

    1994-08-01

    Various types of spatiotemporal behavior are described for two-dimensional networks of excitatory and inhibitory neurons with time delayed interactions. It is described how the network behaves as several structural parameters are varied, such as the number of neurons, the connectivity, and the values of synaptic weights. A transition from spatially uniform oscillations to spatiotemporal chaos via intermittentlike behavior is observed. The properties of spatiotemporally chaotic solutions are investigated by evaluating the largest positive Lyapunov exponent and the loss of correlation with distance. Finally, properties of information transport are evaluated during uniform oscillations and spatiotemporal chaos. It is shown that the diffusion coefficient increases significantly in the spatiotemporal phase similar to the increase of transport coefficients at the onset of fluid turbulence. It is proposed that such a property should be seen in other media, such as chemical turbulence or networks of oscillators. The possibility of measuring information transport from appropriate experiments is also discussed.

  6. High Speed Observation of Spatiotemporal Chaos in a Voice Production System

    NASA Astrophysics Data System (ADS)

    Zhang, Yu; Jiang, Jack J.

    2006-05-01

    The spatial-temporal chaos has recently become the subject of intensive experimental and theoretical investigations. Studying vibratory dynamics of the vocal folds is important for natural voice productions. Disordered voices are usually observed in laryngeal pathologies, such as laryngeal paralysis and vocal polyps. In this study, we report spatiotemporal chaotic vibratory behavior in a biomedical vocal fold system. Spatiotemporal chaos in excised larynx vibrations is recorded using high-speed digital imaging. Spatiotemporal analyses effectively describe the spatiotemporal dynamics of the vocal fold vibrations and investigate the effects of subglottal pressure. With the increase of subglottal pressures, correlation dimension and glottal entropy are increased. Spatiotemporal chaos plays an important role in understanding irregular dynamics of disordered voice production.

  7. Traffic dynamics in empirical probe vehicle data studied with three-phase theory: Spatiotemporal reconstruction of traffic phases and generation of jam warning messages

    NASA Astrophysics Data System (ADS)

    Kerner, Boris S.; Rehborn, Hubert; Schäfer, Ralf-Peter; Klenov, Sergey L.; Palmer, Jochen; Lorkowski, Stefan; Witte, Nikolaus

    2013-01-01

    Empirical and theoretical analyses of the spatiotemporal dynamics of traffic flow reconstructed from randomly distributed probe vehicle data are presented. For the empirical analysis, probe vehicle data generated by TomTom’s navigation devices in the commercial TomTom’s HD-traffic service as well as road detector data measured at the same road section are used. A stochastic microscopic (car-following) three-phase model is further developed for simulations of a real empirical complex spatiotemporal traffic dynamics measured over a three-lane long road stretch with several different bottlenecks. Physical features and limitations of simulations of real spatiotemporal traffic dynamics are revealed. Phase transition points between free flow (F), synchronized flow (S), and wide moving jam (J) are identified along trajectories of empirical and simulated probe vehicles randomly distributed in traffic flow. As predicted by three-phase theory, the empirical probe vehicle data shows that traffic breakdown is an F?S transition and wide moving jams emerge only in synchronized flow, i.e., due to S?J transitions. Through the use of the simulations, it has been found that already about 2% of probe vehicle data allows us to reconstruct traffic dynamics in space and time with an accuracy that is high enough for most applications like the generation of jam warning messages studied in the article.

  8. A computational approach to mechanistic and predictive toxicology of pesticides.

    PubMed

    Kongsbak, Kristine; Vinggaard, Anne Marie; Hadrup, Niels; Audouze, Karine

    2014-01-01

    Emerging challenges of managing and interpreting large amounts of complex biological data have given rise to the growing field of computational biology. We investigated the applicability of an integrated systems toxicology approach on five selected pesticides to get an overview of their modes of action in humans, to group them according to their modes of action, and to hypothesize on their potential effects on human health. We extracted human proteins associated to prochloraz, tebuconazole, epoxiconazole, procymidone, and mancozeb and enriched each protein set by using a high confidence human protein interactome. Then, we explored modes of action of the chemicals, by integrating protein-disease information to the resulting protein networks. The dominating human adverse effects affected were reproductive disorders followed by adrenal diseases. Our results indicated that prochloraz, tebuconazole, and procymidone exerted their effects mainly via interference with steroidogenesis and nuclear receptors. Prochloraz was associated to a large number of human diseases, and together with tebuconazole showed several significant associations to Testicular Dysgenesis Syndrome. Mancozeb showed a differential mode of action, involving inflammatory processes. This method provides an efficient way of overviewing data and grouping chemicals according to their mode of action and potential human adverse effects. Such information is valuable when dealing with predictions of mixture effects of chemicals and may contribute to the development of adverse outcome pathways. PMID:24037280

  9. Spatio-temporal variability of soil respiration of forest ecosystems in China: influencing factors and evaluation model.

    PubMed

    Zheng, Ze-Mei; Yu, Gui-Rui; Sun, Xiao-Min; Li, Sheng-Gong; Wang, Yue-Si; Wang, Ying-Hong; Fu, Yu-Ling; Wang, Qiu-Feng

    2010-10-01

    Understanding the influencing factors of the spatio-temporal variability of soil respiration (R (s)) across different ecosystems as well as the evaluation model of R (s) is critical to the accurate prediction of future changes in carbon exchange between ecosystems and the atmosphere. R (s) data from 50 different forest ecosystems in China were summarized and the influences of environmental variables on the spatio-temporal variability of R (s) were analyzed. The results showed that both the mean annual air temperature and precipitation were weakly correlated with annual R (s), but strongly with soil carbon turnover rate. R (s) at a reference temperature of 0°C was only significantly and positively correlated with soil organic carbon (SOC) density at a depth of 20 cm. We tested a global-scale R (s) model which predicted monthly mean R (s) (R (s,monthly)) from air temperature and precipitation. Both the original model and the reparameterized model poorly explained the monthly variability of R (s) and failed to capture the inter-site variability of R (s). However, the residual of R (s,monthly) was strongly correlated with SOC density. Thus, a modified empirical model (TPS model) was proposed, which included SOC density as an additional predictor of R (s). The TPS model explained monthly and inter-site variability of R (s) for 56% and 25%, respectively. Moreover, the simulated annual R (s) of TPS model was significantly correlated with the measured value. The TPS model driven by three variables easy to be obtained provides a new tool for R (s) prediction, although a site-specific calibration is needed for using at a different region. PMID:20571797

  10. Utilizing Real-World Transportation Data for Accurate Traffic Prediction Bei Pan, Ugur Demiryurek, Cyrus Shahabi

    E-print Network

    Shahabi, Cyrus

    , Cyrus Shahabi Integrated Media System Center University of Southern California Los Angeles, United- tiotemporal data on transportation networks of major cities have become available. This gold mine of data can the spatiotemporal behaviors of rush hours and events to perform a more accurate prediction of both short- term

  11. Spatiotemporal chaotic unjamming and jamming in granular avalanches.

    PubMed

    Wang, Ziwei; Zhang, Jie

    2015-01-01

    We have investigated the spatiotemporal chaotic dynamics of unjamming and jamming of particles in a model experiment - a rotating drum partially filled with bidisperse disks to create avalanches. The magnitudes of the first Lyapunov vector ?u(t) and velocity v(t) of particles are directly measured for the first time to yield insights into their spatial correlation C?u,v, which is on statistical average slightly larger near the unjamming than the value near the jamming transition. These results are consistent with the recent work of Banigan et al (Nature Phys. 2013), and it is for the first time to validate their theoretical models in a real scenario. v(t) shows rich dynamics: it grows exponentially for unstable particles and keeps increasing despite stochastic interactions; after the maximum, it decays with large fluctuations. Hence the spatiotemporal chaotic dynamics of avalanche particles are entangled, causing temporal correlations of macroscopic quantities of the system. We propose a simple model for these observations. PMID:25634753

  12. Carrier-envelope phase-stable spatiotemporal light bullets.

    PubMed

    Gražulevi?i?t?, I; Šuminas, R; Tamošauskas, G; Couairon, A; Dubietis, A

    2015-08-15

    We present an extensive experimental investigation of the self-focusing and filamentation of intense 90 fs, 1.8 ?m, carrier-envelope phase-stable laser pulses in fused silica in the anomalous group velocity dispersion region. Spectral measurements in a wedge-shaped sample uncover dynamics of spectral broadening, which captures the evolution of third-harmonic, resonant radiation, and supercontinuum spectra as a function of the propagation distance with unprecedented detail. The relevant events of spectral broadening are linked to the formation and propagation dynamics of spatiotemporal light bullets as measured by a three-dimensional imaging technique. We also show that at a higher input power, the light bullet splits into two bullets, which retain characteristic O-shaped spatiotemporal intensity distributions and propagate with different group velocities. Finally, we demonstrate that the light bullets have a stable carrier-envelope phase that is preserved even after the bullet splitting event, as verified by f-2f interferometric measurements. PMID:26274643

  13. Integrating GIS and ABM to Explore Spatiotemporal Dynamics

    NASA Astrophysics Data System (ADS)

    Sun, M.; Jiang, Y.; Yang, C.

    2013-12-01

    Agent-based modeling as a methodology for the bottom-up exploration with the account of adaptive behavior and heterogeneity of system components can help discover the development and pattern of the complex social and environmental system. However, ABM is a computationally intensive process especially when the number of system components becomes large and the agent-agent/agent-environmental interaction is modeled very complex. Most of traditional ABM frameworks developed based on CPU do not have a satisfying computing capacity. To address the problem and as the emergence of advanced techniques, GPU computing with CUDA can provide powerful parallel structure to enable the complex simulation of spatiotemporal dynamics. In this study, we first develop a GPU-based ABM system. Secondly, in order to visualize the dynamics generated from the movement of agent and the change of agent/environmental attributes during the simulation, we integrate GIS into the ABM system. Advanced geovisualization technologies can be utilized for representing the spatiotemporal change events, such as proper 2D/3D maps with state-of-the-art symbols, space-time cube and multiple layers each of which presents pattern in one time-stamp, etc. Thirdly, visual analytics which include interactive tools (e.g. grouping, filtering, linking, etc.) is included in our ABM-GIS system to help users conduct real-time data exploration during the progress of simulation. Analysis like flow analysis and spatial cluster analysis can be integrated according to the geographical problem we want to explore.

  14. An Intelligent Polar Cyberinfrastrucuture to Support Spatiotemporal Decision Making

    NASA Astrophysics Data System (ADS)

    Song, M.; Li, W.; Zhou, X.

    2014-12-01

    In the era of big data, polar sciences have already faced an urgent demand of utilizing intelligent approaches to support precise and effective spatiotemporal decision-making. Service-oriented cyberinfrastructure has advantages of seamlessly integrating distributed computing resources, and aggregating a variety of geospatial data derived from Earth observation network. This paper focuses on building a smart service-oriented cyberinfrastructure to support intelligent question answering related to polar datasets. The innovation of this polar cyberinfrastructure includes: (1) a problem-solving environment that parses geospatial question in natural language, builds geoprocessing rules, composites atomic processing services and executes the entire workflow; (2) a self-adaptive spatiotemporal filter that is capable of refining query constraints through semantic analysis; (3) a dynamic visualization strategy to support results animation and statistics in multiple spatial reference systems; and (4) a user-friendly online portal to support collaborative decision-making. By means of this polar cyberinfrastructure, we intend to facilitate integration of distributed and heterogeneous Arctic datasets and comprehensive analysis of multiple environmental elements (e.g. snow, ice, permafrost) to provide a better understanding of the environmental variation in circumpolar regions.

  15. Spatiotemporal Variations of Reference Crop Evapotranspiration in Northern Xinjiang, China

    PubMed Central

    Lv, Xin; Lin, Hai-rong

    2014-01-01

    To set up a reasonable crop irrigation system in the context of global climate change in Northern Xinjiang, China, reference crop evapotranspiration (ET0) was analyzed by means of spatiotemporal variations. The ET0 values from 1962 to 2010 were calculated by Penman-Monteith formula, based on meteorological data of 22 meteorological observation stations in the study area. The spatiotemporal variations of ET0 were analyzed by Mann-Kendall test, Morlet wavelet analysis, and ArcGIS spatial analysis. The results showed that regional average ET0 had a decreasing trend and there was an abrupt change around 1983. The trend of regional average ET0 had a primary period about 28 years, in which there were five alternating stages (high-low-high-low-high). From the standpoint of spatial scale, ET0 gradually increased from the northeast and southwest toward the middle; the southeast and west had slightly greater variation, with significant regional differences. From April to October, the ET0 distribution significantly influenced the distribution characteristic of annual ET0. Among them sunshine hours and wind speed were two of principal climate factors affecting ET0. PMID:25254259

  16. The spatio-temporal spectrum of turbulent flows.

    PubMed

    Clark di Leoni, P; Cobelli, P J; Mininni, P D

    2015-12-01

    Identification and extraction of vortical structures and of waves in a disorganised flow is a mayor challenge in the study of turbulence. We present a study of the spatio-temporal behavior of turbulent flows in the presence of different restitutive forces. We show how to compute and analyse the spatio-temporal spectrum from data stemming from numerical simulations and from laboratory experiments. Four cases are considered: homogeneous and isotropic turbulence, rotating turbulence, stratified turbulence, and water wave turbulence. For homogeneous and isotropic turbulence, the spectrum allows identification of sweeping by the large-scale flow. For rotating and for stratified turbulence, the spectrum allows identification of the waves, precise quantification of the energy in the waves and in the turbulent eddies, and identification of physical mechanisms such as Doppler shift and wave absorption in critical layers. Finally, in water wave turbulence the spectrum shows a transition from gravity-capillary waves to bound waves as the amplitude of the forcing is increased. PMID:26701711

  17. Spatiotemporal analysis of NORA10 data of significant wave height

    NASA Astrophysics Data System (ADS)

    Vanem, Erik

    2014-06-01

    This paper presents a spatiotemporal analysis performed by applying a Bayesian hierarchical model on NORA10 data of significant wave height. The model has previously been applied to corrected ERA-40 data of significant wave height and was generally found to perform well. However, a new set of high-resolution significant wave height data has recently become available, which is believed to be an improvement compared to the C-ERA-40 data, and a similar spatiotemporal analysis is performed on this new data set. NORA10 differs from C-ERA-40 in various ways and in particular the spatial resolution is significantly increased. Hence, one main motivation for the study presented in this paper is to investigate how the model performs on data with very high spatial resolution. In particular, the model contains a separate component for identifying long-term trends in the wave climate, possibly due to climate change. For the C-ERA-40 data, significant increasing trends were detected in the selected area in the North Atlantic Ocean. These trends are not reproduced in the NORA10 data, but there are differences in geographical and temporal coverage that may, at least partly, explain such differences. The new analysis and the results pertaining to the NORA10 data are presented in this paper.

  18. Small effects of smoking on visual spatiotemporal processing

    PubMed Central

    Kunchulia, Marina; Pilz, Karin S.; Herzog, Michael H.

    2014-01-01

    Nicotine is an important stimulant that is involved in modulating many neuronal processes, including those related to vision. Nicotine is also thought to play a key role in schizophrenia: A genetic variation of the cholinergic nicotine receptor gene, alpha-7 subunit (CHRNA7) has been shown to be associated with stronger backward masking deficits in schizophrenic patients. In this study, we tested visual backward masking in healthy smokers and non-smokers to further understand the effects of nicotine on spatiotemporal vision. In the first study, we tested 48 participants, a group of non-smokers (n = 12) and three groups of regular smokers that were either nicotine deprived (n = 12), non-deprived (n = 12) or deprived but were allowed to smoke a cigarette directly before the start of the experiment (n = 12). Performance was similar across groups, except for some small negative effects in nicotine-deprived participants. In the second study, we compared backward masking performance between regular smokers and non-smokers for older (n = 37, 13 smokers) and younger (n = 67, 21 smokers) adults. Older adults performed generally worse than younger adults but there were no significant differences in performance between smokers and non-smokers. Taken together, these findings indicate that nicotine has no long-term negative effects on visual spatiotemporal processing as determined by visual backward masking. PMID:25471068

  19. Deep Spatiotemporal Feature Learning with Application to Image Classification

    SciTech Connect

    Karnowski, Thomas Paul; Arel, Itamar; Rose, Derek C

    2010-01-01

    Deep machine learning is an emerging framework for dealing with complex high-dimensionality data in a hierarchical fashion which draws some inspiration from biological sources. Despite the notable progress made in the field, there remains a need for an architecture that can represent temporal information with the same ease that spatial information is discovered. In this work, we present new results using a recently introduced deep learning architecture called Deep Spatio-Temporal Inference Network (DeSTIN). DeSTIN is a discriminative deep learning architecture that combines concepts from unsupervised learning for dynamic pattern representation together with Bayesian inference. In DeSTIN the spatiotemporal dependencies that exist within the observations are modeled inherently in an unguided manner. Each node models the inputs by means of clustering and simple dynamics modeling while it constructs a belief state over the distribution of sequences using Bayesian inference. We demonstrate that information from the different layers of this hierarchical system can be extracted and utilized for the purpose of pattern classification. Earlier simulation results indicated that the framework is highly promising, consequently in this work we expand DeSTIN to a popular problem, the MNIST data set of handwritten digits. The system as a preprocessor to a neural network achieves a recognition accuracy of 97.98% on this data set. We further show related experimental results pertaining to automatic cluster adaptation and termination.

  20. Perception of oppositely moving verniers and spatio-temporal interpolation.

    PubMed

    Fahle, M

    1995-04-01

    Even at moderate speeds, moving objects stimulate many retinal photoreceptors within the integration time of the receptors, yet usually no motion blur is experienced. An elegant model for the elimination of motion blur was proposed by Anderson and van Essen [(1987) Proceedings of the National Academy of Science U.S.A., 84, 6297-6301]. These authors suggested that so-called shifter circuits shift the neuronal representation of retinal images on their way to the cortex. The retinal image of an object moving in the outer world is thus shifted in the opposite direction to the object motion, and the cortical representation of objects would be stable at least during short periods of time. To test the hypothesis of "shifter circuits", I measured thresholds for two vernier stimuli, moving simultaneously into opposite directions over identical parts of the retina. Motion blur for these stimuli was not stronger than with a single moving stimulus, and thresholds for the detection of vernier offsets could be below a photoreceptor diameter. This finding poses serious problems for the hypothesis of shifter circuits, since shifter circuits would be able to stabilize only one of the stimuli. In additional experiments, stimuli moved discontinuously, requiring spatio-temporal interpolation for the perception of smooth motion. The results are consistent with those obtained with continuous motion. Precision of spatio-temporal interpolation is in the hyperacuity range even for stimuli moving in opposite directions over the same small part of the visual field. PMID:7762150

  1. Adaptive changes in spatiotemporal gait characteristics in women during pregnancy.

    PubMed

    B?aszczyk, Janusz W; Opala-Berdzik, Agnieszka; Plewa, Micha?

    2016-01-01

    Spatiotemporal gait cycle characteristics were assessed at early (P1), and late (P2) pregnancy, as well as at 2 months (PP1) and 6 months (PP2) postpartum. A substantial decrease in walking speed was observed throughout the pregnancy, with the slowest speed (1±0.2m/s) being during the third trimester. Walking at slower velocity resulted in complex adaptive adjustments to their spatiotemporal gait pattern, including a shorter step length and an increased duration of both their stance and double-support phases. Duration of the swing phase remained the least susceptible to changes. Habitual walking velocity (1.13±0.2m/s) and the optimal gait pattern were fully recovered 6 months after childbirth. Documented here adaptive changes in the preferred gait pattern seem to result mainly from the altered body anthropometry leading to temporary balance impairments. All the observed changes within stride cycle aimed to improve gait safety by focusing on its dynamic stability. The pregnant women preferred to walk at a slower velocity which allowed them to spend more time in double-support compared with their habitual pattern. Such changes provided pregnant women with a safer and more tentative ambulation that reduced the single-support period and, hence, the possibility of instability. As pregnancy progressed a significant increase in stance width and a decrease in step length was observed. Both factors allow also for gait stability improvement. PMID:26480840

  2. Mining spatiotemporal patterns of urban dwellers from taxi trajectory data

    NASA Astrophysics Data System (ADS)

    Mao, Feng; Ji, Minhe; Liu, Ting

    2015-09-01

    With the widespread adoption of locationaware technology, obtaining long-sequence, massive and high-accuracy spatiotemporal trajectory data of individuals has become increasingly popular in various geographic studies. Trajectory data of taxis, one of the most widely used inner-city travel modes, contain rich information about both road network traffic and travel behavior of passengers. Such data can be used to study the microscopic activity patterns of individuals as well as the macro system of urban spatial structures. This paper focuses on trajectories obtained from GPS-enabled taxis and their applications for mining urban commuting patterns. A novel approach is proposed to discover spatiotemporal patterns of household travel from the taxi trajectory dataset with a large number of point locations. The approach involves three critical steps: spatial clustering of taxi origin-destination (OD) based on urban traffic grids to discover potentially meaningful places, identifying threshold values from statistics of the OD clusters to extract urban jobs-housing structures, and visualization of analytic results to understand the spatial distribution and temporal trends of the revealed urban structures and implied household commuting behavior. A case study with a taxi trajectory dataset in Shanghai, China is presented to demonstrate and evaluate the proposed method.

  3. Spatiotemporal patterns and predictability of cyberattacks Yu-Zhong Chen1

    E-print Network

    Xu, Shouhuai

    issue in cybersecurity science and engineering is whether there exist intrinsic patterns of cyberattacks the complex topologies of the Internet [5] and on the likelihood of large scale failures caused by node and coping with increasing cybersecurity threats. For example, attack graphs were invented to analyze

  4. The response of the Limulus retina to moving stimuli: a prediction by Fourier synthesis

    PubMed Central

    1978-01-01

    The Limulus retina responds as a linear system to light stimuli which vary moderately about a mean level. The dynamics of such a system may conveniently be summarized by means of a spatiotemporal transfer function, which describes the response of the system to moving sinusoidal gratings. The response of the system to an arbitrary stimulus may then be calculated by adding together the system's responses to suitably weighted sinusoidal stimuli. We have measured such a spatiotemporal transfer function for the Limulus eye. We have then accurately predicted, in a parameter-free calculation, the eye's response to various stimulus patterns which move across it at several different velocities. PMID:690594

  5. Spatiotemporal memory is an intrinsic property of networks of dissociated cortical neurons.

    PubMed

    Ju, Han; Dranias, Mark R; Banumurthy, Gokulakrishna; VanDongen, Antonius M J

    2015-03-01

    The ability to process complex spatiotemporal information is a fundamental process underlying the behavior of all higher organisms. However, how the brain processes information in the temporal domain remains incompletely understood. We have explored the spatiotemporal information-processing capability of networks formed from dissociated rat E18 cortical neurons growing in culture. By combining optogenetics with microelectrode array recording, we show that these randomly organized cortical microcircuits are able to process complex spatiotemporal information, allowing the identification of a large number of temporal sequences and classification of musical styles. These experiments uncovered spatiotemporal memory processes lasting several seconds. Neural network simulations indicated that both short-term synaptic plasticity and recurrent connections are required for the emergence of this capability. Interestingly, NMDA receptor function is not a requisite for these short-term spatiotemporal memory processes. Indeed, blocking the NMDA receptor with the antagonist APV significantly improved the temporal processing ability of the networks, by reducing spontaneously occurring network bursts. These highly synchronized events have disastrous effects on spatiotemporal information processing, by transiently erasing short-term memory. These results show that the ability to process and integrate complex spatiotemporal information is an intrinsic property of generic cortical networks that does not require specifically designed circuits. PMID:25740531

  6. A hybrid spatio-temporal data indexing method for trajectory databases.

    PubMed

    Ke, Shengnan; Gong, Jun; Li, Songnian; Zhu, Qing; Liu, Xintao; Zhang, Yeting

    2014-01-01

    In recent years, there has been tremendous growth in the field of indoor and outdoor positioning sensors continuously producing huge volumes of trajectory data that has been used in many fields such as location-based services or location intelligence. Trajectory data is massively increased and semantically complicated, which poses a great challenge on spatio-temporal data indexing. This paper proposes a spatio-temporal data indexing method, named HBSTR-tree, which is a hybrid index structure comprising spatio-temporal R-tree, B*-tree and Hash table. To improve the index generation efficiency, rather than directly inserting trajectory points, we group consecutive trajectory points as nodes according to their spatio-temporal semantics and then insert them into spatio-temporal R-tree as leaf nodes. Hash table is used to manage the latest leaf nodes to reduce the frequency of insertion. A new spatio-temporal interval criterion and a new node-choosing sub-algorithm are also proposed to optimize spatio-temporal R-tree structures. In addition, a B*-tree sub-index of leaf nodes is built to query the trajectories of targeted objects efficiently. Furthermore, a database storage scheme based on a NoSQL-type DBMS is also proposed for the purpose of cloud storage. Experimental results prove that HBSTR-tree outperforms TB*-tree in some aspects such as generation efficiency, query performance and query type. PMID:25051028

  7. A Hybrid Spatio-Temporal Data Indexing Method for Trajectory Databases

    PubMed Central

    Ke, Shengnan; Gong, Jun; Li, Songnian; Zhu, Qing; Liu, Xintao; Zhang, Yeting

    2014-01-01

    In recent years, there has been tremendous growth in the field of indoor and outdoor positioning sensors continuously producing huge volumes of trajectory data that has been used in many fields such as location-based services or location intelligence. Trajectory data is massively increased and semantically complicated, which poses a great challenge on spatio-temporal data indexing. This paper proposes a spatio-temporal data indexing method, named HBSTR-tree, which is a hybrid index structure comprising spatio-temporal R-tree, B*-tree and Hash table. To improve the index generation efficiency, rather than directly inserting trajectory points, we group consecutive trajectory points as nodes according to their spatio-temporal semantics and then insert them into spatio-temporal R-tree as leaf nodes. Hash table is used to manage the latest leaf nodes to reduce the frequency of insertion. A new spatio-temporal interval criterion and a new node-choosing sub-algorithm are also proposed to optimize spatio-temporal R-tree structures. In addition, a B*-tree sub-index of leaf nodes is built to query the trajectories of targeted objects efficiently. Furthermore, a database storage scheme based on a NoSQL-type DBMS is also proposed for the purpose of cloud storage. Experimental results prove that HBSTR-tree outperforms TB*-tree in some aspects such as generation efficiency, query performance and query type. PMID:25051028

  8. Spatiotemporal dynamics of a digital phase-locked loop based coupled map lattice system

    SciTech Connect

    Banerjee, Tanmoy Paul, Bishwajit; Sarkar, B. C.

    2014-03-15

    We explore the spatiotemporal dynamics of a coupled map lattice (CML) system, which is realized with a one dimensional array of locally coupled digital phase-locked loops (DPLLs). DPLL is a nonlinear feedback-controlled system widely used as an important building block of electronic communication systems. We derive the phase-error equation of the spatially extended system of coupled DPLLs, which resembles a form of the equation of a CML system. We carry out stability analysis for the synchronized homogeneous solutions using the circulant matrix formalism. It is shown through extensive numerical simulations that with the variation of nonlinearity parameter and coupling strength the system shows transitions among several generic features of spatiotemporal dynamics, viz., synchronized fixed point solution, frozen random pattern, pattern selection, spatiotemporal intermittency, and fully developed spatiotemporal chaos. We quantify the spatiotemporal dynamics using quantitative measures like average quadratic deviation and spatial correlation function. We emphasize that instead of using an idealized model of CML, which is usually employed to observe the spatiotemporal behaviors, we consider a real world physical system and establish the existence of spatiotemporal chaos and other patterns in this system. We also discuss the importance of the present study in engineering application like removal of clock-skew in parallel processors.

  9. Simulations of the Reaction-Diffusion System demonstrating the Transition from Purely Temporal to Spatio-Temporal Chaos

    NASA Astrophysics Data System (ADS)

    Olsen, Thomas; Hou, Yu; Trail, Collin; Wiener, Richard

    2004-11-01

    The Reaction-Diffusion model (H. Riecke and H.-G. Paap, Europhys. Lett. 14), 1235 (1991).has been applied to a wide variety of pattern forming systems. It correctly predicted a period doubling cascade to chaos in Taylor-Couette flow with hourglass geometry(Richard J. Wiener et al), Phys. Rev. E 55, 5489 (1997).. We have conducted a series of such simulations, varying the length of the system. This has enabled us to study the transition from a purely temporal chaos of the formation of new pairs of Taylor Vortices at a single location, to a spatio-temporal chaos of formation across a range of locations. Application to anticipated experiments will be discussed.

  10. Spatiotemporal chaos near the onset of cellular growth during thin-film solidification of a binary alloy

    NASA Technical Reports Server (NTRS)

    Lee, J. T. C.; Tsiveriotis, K.; Brown, R. A.

    1992-01-01

    Thin-film solidification experiments with a succinonitrile-acetone alloy are used to observe the long time-scale dynamics of cellular crystal growth at growth rates only slightly above the critical value VC = Vc(lambda sub c) for the onset of morphological instability. Under these conditions only very small amplitude cells are observed with wavelengths near the value predicted by linear stability theory lambda = lambda sub c. At long times, microstructures with wavelengths significantly finer than lambda suc c form by nucleation at defects across the interface. These interfaces do not have a unique microstructure, but seem to exhibit spatiotemporal chaos on a long time scale caused by the continual birth and death of cells by tip splitting and cell annihilation in grooves.

  11. Spatiotemporal chaos near the onset of cellular growth during thin-film solidification of a binary alloy

    NASA Astrophysics Data System (ADS)

    Lee, J. T. C.; Tsiveriotis, K.; Brown, R. A.

    1992-07-01

    Thin-film solidification experiments with a succinonitrile-acetone alloy are used to observe the long time-scale dynamics of cellular crystal growth at growth rates only slightly above the critical value VC = Vc(lambda sub c) for the onset of morphological instability. Under these conditions only very small amplitude cells are observed with wavelengths near the value predicted by linear stability theory lambda = lambda sub c. At long times, microstructures with wavelengths significantly finer than lambda suc c form by nucleation at defects across the interface. These interfaces do not have a unique microstructure, but seem to exhibit spatiotemporal chaos on a long time scale caused by the continual birth and death of cells by tip splitting and cell annihilation in grooves.

  12. Spatio-temporal distribution of dengue fever under scenarios of climate change in the southern Taiwan

    NASA Astrophysics Data System (ADS)

    Lee, Chieh-Han; Yu, Hwa-Lung

    2014-05-01

    Dengue fever has been recognized as the most important widespread vector-borne infectious disease in recent decades. Over 40% of the world's population is risk from dengue and about 50-100 million people are infected world wide annually. Previous studies have found that dengue fever is highly correlated with climate covariates. Thus, the potential effects of global climate change on dengue fever are crucial to epidemic concern, in particular, the transmission of the disease. This present study investigated the nonlinearity of time-delayed impact of climate on spatio-temporal variations of dengue fever in the southern Taiwan during 1998 to 2011. A distributed lag nonlinear model (DLNM) is used to assess the nonlinear lagged effects of meteorology. The statistically significant meteorological factors are considered, including weekly minimum temperature and maximum 24-hour rainfall. The relative risk and the distribution of dengue fever then predict under various climate change scenarios. The result shows that the relative risk is similar for different scenarios. In addition, the impact of rainfall on the incidence risk is higher than temperature. Moreover, the incidence risk is associated to spatially population distribution. The results can be served as practical reference for environmental regulators for the epidemic prevention under climate change scenarios.

  13. Thermally induced phase mismatching in a repetitively Gaussian pulsed pumping KTP crystal: a spatiotemporal treatment.

    PubMed

    Rezaee, Mostafa Mohammad; Sabaeian, Mohammad; Motazedian, Alireza; Jalil-Abadi, Fatemeh Sedaghat; Askari, Hadi; Khazrk, Iman

    2015-05-20

    Thermally induced phase mismatching (TIPM) has been proven to be an influential issue in nonlinear phenomena. It occurs when refractive indices of crystal are changed due to temperature rise. In this work, the authors report on a modeling of spatiotemporal dependence of TIPM in a repetitively pulsed pumping KTP crystal. Gaussian profiles for both spatial and temporal dependences of pump beam were used to generate second-harmonic waves in a type II configuration. This modeling is of importance in predicting the nonlinear conversion efficiency of crystals when heat is loaded in the system. To this end, at first, an approach to solve the heat equation in a repetitively pulsed pumping system with consideration of the temperature dependence of thermal conductivity and realistic cooling mechanisms such as conduction, convection, and radiation, is presented. The TIPM is then calculated through the use of experimental thermal dispersion relations of KTP crystal. The results show how accumulative behaviors of temperature and TIPM (with its reverse sign) happen when the number of pulses is increased. Fluctuations accompanying temperature and TIPM were observed which were attributed to the off-time between successive pulses. Moreover, in this work, a numerical procedure for solving a repetitively pulsed pumped crystal is introduced. This procedure enables us to solve the problem with home-used computing machines. PMID:26192515

  14. Stable Isotope Analysis of Precipitation Samples Obtained via Crowdsourcing Reveals the Spatiotemporal Evolution of Superstorm Sandy

    PubMed Central

    Good, Stephen P.; Mallia, Derek V.; Lin, John C.; Bowen, Gabriel J.

    2014-01-01

    Extra-tropical cyclones, such as 2012 Superstorm Sandy, pose a significant climatic threat to the northeastern United Sates, yet prediction of hydrologic and thermodynamic processes within such systems is complicated by their interaction with mid-latitude water patterns as they move poleward. Fortunately, the evolution of these systems is also recorded in the stable isotope ratios of storm-associated precipitation and water vapor, and isotopic analysis provides constraints on difficult-to-observe cyclone dynamics. During Superstorm Sandy, a unique crowdsourced approach enabled 685 precipitation samples to be obtained for oxygen and hydrogen isotopic analysis, constituting the largest isotopic sampling of a synoptic-scale system to date. Isotopically, these waters span an enormous range of values (21‰ for O, 160‰ for H) and exhibit strong spatiotemporal structure. Low isotope ratios occurred predominantly in the west and south quadrants of the storm, indicating robust isotopic distillation that tracked the intensity of the storm's warm core. Elevated values of deuterium-excess (25‰) were found primarily in the New England region after Sandy made landfall. Isotope mass balance calculations and Lagrangian back-trajectory analysis suggest that these samples reflect the moistening of dry continental air entrained from a mid-latitude trough. These results demonstrate the power of rapid-response isotope monitoring to elucidate the structure and dynamics of water cycling within synoptic-scale systems and improve our understanding of storm evolution, hydroclimatological impacts, and paleo-storm proxies. PMID:24618882

  15. Insight into others' minds: spatio-temporal representations by intrinsic frame of reference.

    PubMed

    Sun, Yanlong; Wang, Hongbin

    2014-01-01

    Recent research has seen a growing interest in connections between domains of spatial and social cognition. Much evidence indicates that processes of representing space in distinct frames of reference (FOR) contribute to basic spatial abilities as well as sophisticated social abilities such as tracking other's intention and belief. Argument remains, however, that belief reasoning in social domain requires an innately dedicated system and cannot be reduced to low-level encoding of spatial relationships. Here we offer an integrated account advocating the critical roles of spatial representations in intrinsic frame of reference. By re-examining the results from a spatial task (Tamborello etal., 2012) and a false-belief task (Onishi and Baillargeon, 2005), we argue that spatial and social abilities share a common origin at the level of spatio-temporal association and predictive learning, where multiple FOR-based representations provide the basic building blocks for efficient and flexible partitioning of the environmental statistics. We also discuss neuroscience evidence supporting these mechanisms. We conclude that FOR-based representations may bridge the conceptual as well as the implementation gaps between the burgeoning fields of social and spatial cognition. PMID:24592226

  16. Two spatiotemporally distinct value systems shape reward-based learning in the human brain

    PubMed Central

    Fouragnan, Elsa; Retzler, Chris; Mullinger, Karen; Philiastides, Marios G.

    2015-01-01

    Avoiding repeated mistakes and learning to reinforce rewarding decisions is critical for human survival and adaptive actions. Yet, the neural underpinnings of the value systems that encode different decision-outcomes remain elusive. Here coupling single-trial electroencephalography with simultaneously acquired functional magnetic resonance imaging, we uncover the spatiotemporal dynamics of two separate but interacting value systems encoding decision-outcomes. Consistent with a role in regulating alertness and switching behaviours, an early system is activated only by negative outcomes and engages arousal-related and motor-preparatory brain structures. Consistent with a role in reward-based learning, a later system differentially suppresses or activates regions of the human reward network in response to negative and positive outcomes, respectively. Following negative outcomes, the early system interacts and downregulates the late system, through a thalamic interaction with the ventral striatum. Critically, the strength of this coupling predicts participants' switching behaviour and avoidance learning, directly implicating the thalamostriatal pathway in reward-based learning. PMID:26348160

  17. A linear merging methodology for high-resolution precipitation products using spatiotemporal regression

    SciTech Connect

    Turlapaty, Anish C.; Younan, Nicolas H.; Anantharaj, Valentine G

    2012-01-01

    Currently, the only viable option for a global precipitation product is the merger of several precipitation products from different modalities. In this article, we develop a linear merging methodology based on spatiotemporal regression. Four highresolution precipitation products (HRPPs), obtained through methods including the Climate Prediction Center's Morphing (CMORPH), Geostationary Operational Environmental Satellite-Based Auto-Estimator (GOES-AE), GOES-Based Hydro-Estimator (GOES-HE) and Self-Calibrating Multivariate Precipitation Retrieval (SCAMPR) algorithms, are used in this study. The merged data are evaluated against the Arkansas Red Basin River Forecast Center's (ABRFC's) ground-based rainfall product. The evaluation is performed using the Heidke skill score (HSS) for four seasons, from summer 2007 to spring 2008, and for two different rainfall detection thresholds. It is shown that the merged data outperform all the other products in seven out of eight cases. A key innovation of this machine learning method is that only 6% of the validation data are used for the initial training. The sensitivity of the algorithm to location, distribution of training data, selection of input data sets and seasons is also analysed and presented.

  18. Sedimentological constraints to the spatio-temporal evolution of the first Cenozoic Antarctic glaciation

    NASA Astrophysics Data System (ADS)

    Stocchi, P.; Galeotti, S.; De Boer, B.; Escutia, C.; DeConto, R.; Houben, A. J.; Passchier, S.; Vermeersen, B. L.; Van de Wal, R.; Brinkhuis, H.

    2012-12-01

    Glacial Isostatic Adjustement (GIA) modeling of solid Earth and gravitational perturbations induced by the Antarctic glaciation across the Eocene/Oligocene transition (EOT; ~34 Ma) predicts a relative sea level (rsl) rise over-ice proximal marine marginal settings. Accordingly, available sedimentary records from the Ross Sea (CIROS1, CRP-3), Prydz Bay (ODP 739, 1166) and Wilkes Land (IOPD U1356, U1360) provide evidence for progressively deeper depositional environments across the late Eocene towards the Oligocene isotope event-1 (Oi-1; 33.7 Ma, which marks a major glacial advancement episode. Since bathymetric changes at these near-field sites are controlled by GIA, the analysis and inter-site comparison of their sedimentary records provide insights into the spatio-temporal evolution of the nascent Antarctic Ice Sheet. In this work we simulate the inception of the Antarctic glaciation by means of a thermomechanical ice sheet-shelf model dynamically coupled to a sea level model based on the gravitationally self-consistent Sea Level Equation (SLE). We generate a set of ice-sheet and rsl scenarios according to (i) different values for the Earth rheological parameters, (ii) initial topographic/bathymetric conditions and (iii) precipitation/temperature patterns. By comparing the observations with the modeling solutions we find that the initial undeformed topography/bathymetry, and consequently its deformations driven by the GIA described by the SLE, are important conditions for a realistic development of the Antarctic ice-sheet.

  19. Fast Pyrolysis of Wood for Biofuels: Spatiotemporally Resolved Diffuse Reflectance In?situ Spectroscopy of Particles.

    PubMed

    Paulsen, Alex D; Hough, Blake R; Williams, C Luke; Teixeira, Andrew R; Schwartz, Daniel T; Pfaendtner, Jim; Dauenhauer, Paul J

    2014-02-20

    Fast pyrolysis of woody biomass is a promising process capable of producing renewable transportation fuels to replace gasoline, diesel, and chemicals currently derived from nonrenewable sources. However, biomass pyrolysis is not yet economically viable and requires significant optimization before it can contribute to the existing oil-based transportation system. One method of optimization uses detailed kinetic models for predicting the products of biomass fast pyrolysis, which serve as the basis for the design of pyrolysis reactors capable of producing the highest value products. The goal of this work is to improve upon current pyrolysis models, usually derived from experiments with low heating rates and temperatures, by developing models that account for both transport and pyrolysis decomposition kinetics at high heating rates and high temperatures (>400?°C). A new experimental technique is proposed herein: spatiotemporally resolved diffuse reflectance in?situ spectroscopy of particles (STR-DRiSP), which is capable of measuring biomass composition during fast pyrolysis with high spatial (10??m) and temporal (1?ms) resolution. Compositional data were compared with a comprehensive 2D single-particle model, which incorporated a multistep, semiglobal reaction mechanism, prescribed particle shrinkage, and thermophysical properties that varied with temperature, composition, and orientation. The STR-DRiSP technique can be used to determine the transport-limited kinetic parameters of biomass decomposition for a wide variety of biomass feedstocks. PMID:24678023

  20. Collapse of ultrashort spatiotemporal pulses described by the cubic generalized Kadomtsev-Petviashvili equation

    SciTech Connect

    Leblond, Herve; Kremer, David; Mihalache, Dumitru

    2010-03-15

    By using a reductive perturbation method, we derive from Maxwell-Bloch equations a cubic generalized Kadomtsev-Petviashvili equation for ultrashort spatiotemporal optical pulse propagation in cubic (Kerr-like) media without the use of the slowly varying envelope approximation. We calculate the collapse threshold for the propagation of few-cycle spatiotemporal pulses described by the generic cubic generalized Kadomtsev-Petviashvili equation by a direct numerical method and compare it to analytic results based on a rigorous virial theorem. Besides, typical evolution of the spectrum (integrated over the transverse spatial coordinate) is given and a strongly asymmetric spectral broadening of ultrashort spatiotemporal pulses during collapse is evidenced.

  1. Microscale spatiotemporal dynamics during neocortical propagation of human focal seizures.

    PubMed

    Wagner, Fabien B; Eskandar, Emad N; Cosgrove, G Rees; Madsen, Joseph R; Blum, Andrew S; Potter, N Stevenson; Hochberg, Leigh R; Cash, Sydney S; Truccolo, Wilson

    2015-11-15

    Some of the most clinically consequential aspects of focal epilepsy, e.g. loss of consciousness, arise from the generalization or propagation of seizures through local and large-scale neocortical networks. Yet, the dynamics of such neocortical propagation remain poorly understood. Here, we studied the microdynamics of focal seizure propagation in neocortical patches (4×4mm) recorded via high-density microelectrode arrays (MEAs) implanted in people with pharmacologically resistant epilepsy. Our main findings are threefold: (1) a newly developed stage segmentation method, applied to local field potentials (LFPs) and multiunit activity (MUA), revealed a succession of discrete seizure stages, each lasting several seconds. These different stages showed characteristic evolutions in overall activity and spatial patterns, which were relatively consistent across seizures within each of the 5 patients studied. Interestingly, segmented seizure stages based on LFPs or MUA showed a dissociation of their spatiotemporal dynamics, likely reflecting different contributions of non-local synaptic inputs and local network activity. (2) As previously reported, some of the seizures showed a peak in MUA that happened several seconds after local seizure onset and slowly propagated across the MEA. However, other seizures had a more complex structure characterized by, for example, several MUA peaks, more consistent with the succession of discrete stages than the slow propagation of a simple wavefront of increased MUA. In both cases, nevertheless, seizures characterized by spike-wave discharges (SWDs, ~2-3Hz) eventually evolved into patterns of phase-locked MUA and LFPs. (3) Individual SWDs or gamma oscillation cycles (25-60Hz), characteristic of two different types of recorded seizures, tended to propagate with varying degrees of directionality, directions of propagation and speeds, depending on the identified seizure stage. However, no clear relationship was observed between the MUA peak onset time (in seizures where such peak onset occurred) and changes in MUA or LFP propagation patterns. Overall, our findings indicate that the recruitment of neocortical territories into ictal activity undergoes complex spatiotemporal dynamics evolving in slow discrete states, which are consistent across seizures within each patient. Furthermore, ictal states at finer spatiotemporal scales (individual SWDs or gamma oscillations) are organized by slower time scale network dynamics evolving through these discrete stages. PMID:26279211

  2. Spatiotemporal correlation structure of the Earth's surface temperature

    NASA Astrophysics Data System (ADS)

    Fredriksen, Hege-Beate; Rypdal, Kristoffer; Rypdal, Martin

    2015-04-01

    We investigate the spatiotemporal temperature variability for several gridded instrumental and climate model data sets. The temporal variability is analysed by estimating the power spectral density and studying the differences between local and global temperatures, land and sea, and among local temperature records at different locations. The spatiotemporal correlation structure is analysed through cross-spectra that allow us to compute frequency-dependent spatial autocorrelation functions (ACFs). Our results are then compared to theoretical spectra and frequency-dependent spatial ACFs derived from a fractional stochastic-diffusive energy balance model (FEBM). From the FEBM we expect both local and global temperatures to have a long-range persistent temporal behaviour, and the spectral exponent (?) is expected to increase by a factor of two when going from local to global scales. Our comparison of the average local spectrum and the global spectrum shows good agreement with this model, although the FEBM has so far only been studied for a pure land planet and a pure ocean planet, respectively, with no seasonal forcing. Hence it cannot capture the substantial variability among the local spectra, in particular between the spectra for land and sea, and for equatorial and non-equatorial temperatures. Both models and observation data show that land temperatures in general have a low persistence, while sea surface temperatures show a higher, and also more variable degree of persistence. Near the equator the spectra deviate from the power-law shape expected from the FEBM. Instead we observe large variability at time scales of a few years due to ENSO, and a flat spectrum at longer time scales, making the spectrum more reminiscent of that of a red noise process. From the frequency-dependent spatial ACFs we observe that the spatial correlation length increases with increasing time scale, which is also consistent with the FEBM. One consequence of this is that longer-lasting structures must also be wider in space. The spatial correlation length is also observed to be longer for land than for sea. The climate model simulations studied are mainly CMIP5 control runs of length 500-1000 yr. On time scales up to several centuries we do not observe that the difference between the local and global spectral exponents vanish. This also follows from the FEBM and shows that the dynamics is spatiotemporal (not just temporal) even on these time scales.

  3. Quantifying spatio-temporal variability of soil water storage and their controls at multiple scales

    NASA Astrophysics Data System (ADS)

    Biswas, Asim

    2014-05-01

    Soil water is the primary limiting factor in semiarid ecosystems and determinant of environmental health. The distribution of soil water in space and time has important hydrologic applications. However, the spatio-temporal variability of soil water is a major challenge in hydrology as their distribution in the landscape is controlled many factors and processes acting in different intensities over a variety of scales. Quantification of these variability and their dominant controls at multiple scales can only lead to a better understanding on the soil water dynamics in space and time and on the underlying processes causing the variability. In order to quantify spatio-temporal variability, soil water content (later converted to soil water storage, SWS) was measured down to 1.4 m (0.2 m depth interval) at 128 regularly spaced locations along a transect of 576 m over a five-year period from the Hummocky landscape of central Canada. The spatial pattern of SWS was very similar (large values of Spearman's rank correlation coefficient) over the entire study period and was almost a mirror image of the spatial pattern of the relative elevation. The similarity was stronger within a season (intra-season) than the same season from different years (inter-annual) and between seasons (inter-season). The variability at multiple scales was quantified using the wavelet transform. The strongest large scale (>72 m) variability contributed from the macro-topography and a moderate medium scale (18-72 m) variability contributed from the landform elements were persistent over the entire measurement period (time stability). The locations and the scales of the most persistent spatial patterns over time and depth were quantified using the wavelet coherency. The changes in the persistent patterns indicated the changes in the scales and locations of underlying hydrological processes, which can be used to identify change in sampling domain. The similarities/dissimilarities in the spatial pattern between the surface and sub-surface measurements at different scales and locations were used to infer the whole profile hydrological dynamics (depth persistence). The variability in SWS spatial patterns was controlled by different factors at different scales. Scale specific dominant controls were identified after separating the variance contribution of each scale towards the overall variance using the Hilbert-Huang transform. The large scale macro-topographical control and medium scale landform control were much stronger than very large scale soil textural control on SWS. The scale-specific relationship with controlling factors improved the prediction of SWS.

  4. Spatio-temporal modeling with GIS and remote sensing for schistosomiasis control in Sichuan, China

    NASA Astrophysics Data System (ADS)

    Xu, Bing

    Schistosomiasis is a water-borne parasitic disease endemic in tropical and subtropical areas. Its transmission requires certain kind of snail as the intermediate host. Some efforts have been made to mapping snail habitats with remote sensing and schistosomiasis transmission modeling. However, the modeling is limited to isolated residential groups and does not include spatial interaction among those groups. Remotely sensed data are only used in snail habitat classification, not in estimation of snail abundance that is an important parameter in schistosomiasis transmission modeling. This research overcomes the above two problems using innovative geographic information system (GIS) and remote sensing technology. A mountainous environment near Xichang, China, is chosen as the test site. Environmental and epidemiological data are stored in a GIS to support modeling. Snail abundance is estimated from land-cover and land-use fractions derived from high spatial resolution IKONOS satellite data. Spatial interaction is determined in consideration of neighborhoods, group areas, relative slopes among groups, and natural barriers. Land-cover and land-use information extracted from 4 m high resolution IKONOS data is used as reference in scaling up to the regional level. The scale-up is done with coarser resolution satellite data including Landsat Thematic Mapper (TM), EO-1 Advanced Land Imager (ALI) and Hyperion data all at 30 m resolution. Snail abundance is estimated by regressing snail survey data with land-cover and land-use fractions. An R2 of 0.87 is obtained between the average snail density predicted and that surveyed at the group level. With such a model, a snail density map is generated for all residential groups in the study area. A spatio-temporal model of schistosomiasis transmission is finally built to incorporate the spatial interaction caused by miracidia and cercaria migration. Comparing the model results with and without spatial interaction has revealed a number of advantages of the spatio-temporal model. Particularly, with the inclusion of spatial interaction, more effective control of schistosomiasis transmission over the whole study area can be achieved.

  5. Earthquake prediction

    NASA Technical Reports Server (NTRS)

    Turcotte, Donald L.

    1991-01-01

    The state of the art in earthquake prediction is discussed. Short-term prediction based on seismic precursors, changes in the ratio of compressional velocity to shear velocity, tilt and strain precursors, electromagnetic precursors, hydrologic phenomena, chemical monitors, and animal behavior is examined. Seismic hazard assessment is addressed, and the applications of dynamical systems to earthquake prediction are discussed.

  6. Optimizing Spatio-Temporal Sampling Designs of Synchronous, Static, or Clustered Measurements

    NASA Astrophysics Data System (ADS)

    Helle, Kristina; Pebesma, Edzer

    2010-05-01

    When sampling spatio-temporal random variables, the cost of a measurement may differ according to the setup of the whole sampling design: static measurements, i.e. repeated measurements at the same location, synchronous measurements or clustered measurements may be cheaper per measurement than completely individual sampling. Such "grouped" measurements may however not be as good as individually chosen ones because of redundancy. Often, the overall cost rather than the total number of measurements is fixed. A sampling design with grouped measurements may allow for a larger number of measurements thus outweighing the drawback of redundancy. The focus of this paper is to include the tradeoff between the number of measurements and the freedom of their location in sampling design optimisation. For simple cases, optimal sampling designs may be fully determined. To predict e.g. the mean over a spatio-temporal field having known covariance, the optimal sampling design often is a grid with density determined by the sampling costs [1, Ch. 15]. For arbitrary objective functions sampling designs can be optimised relocating single measurements, e.g. by Spatial Simulated Annealing [2]. However, this does not allow to take advantage of lower costs when using grouped measurements. We introduce a heuristic that optimises an arbitrary objective function of sampling designs, including static, synchronous, or clustered measurements, to obtain better results at a given sampling budget. Given the cost for a measurement, either within a group or individually, the algorithm first computes affordable sampling design configurations. The number of individual measurements as well as kind and number of grouped measurements are determined. Random locations and dates are assigned to the measurements. Spatial Simulated Annealing is used on each of these initial sampling designs (in parallel) to improve them. In grouped measurements either the whole group is moved or single measurements within the group, e.g. static measurements may be moved to another location or the sampling times may be rearranged. After several optimisation steps, the objective functions of the sampling designs are compared. Only for the best ones optimisation is pursued. After several iterations the sampling designs are selected again. Thus more and more of the low performing sampling designs are deleted and computational effort is concentrated on the most promising candidates. The use case is optimisation of a monitoring sampling design for a river. We use a flow model to simulate the spread of a pollutant that enters the system at different locations with known, location-dependent probabilities and at random times. The objective function to be minimised is the amount of pollution that is not detected. Keywords: spatio-temporal sampling design, static sample, synchronous sample, spatial simulated annealing, cost function References [1] Jaap de Gruijter, Dick Brus, Marc Bierkens, and Martin Knotters. Sampling for Natural Ressource Monitoring. Springer, 2006. [2] J. W. van Groenigen. Spatial simulated annealing for optimizing sampling, In: GeoENV I Geostatistics for environmental applications, pages 351 - 361, 1997.

  7. Spatio-Temporal Variability in Marine Ecosystem Models

    NASA Astrophysics Data System (ADS)

    Meacham, S. P.

    2011-12-01

    In upper ocean marine ecosystems, phytoplankton blooms and associated peaks in zooplankton grazing are relatively frequent and the biological pump constitutes one component of the global carbon cycle. When represented with simple mathematical ecosystem models (such as the multi-compartment models used in some climate models), in a system containing a background flow-field, the nonlinear dynamics of the ecosystem model can give rise to spatio-temporal structure that, although appearing biological, is a consequence of the numerical implementation of advection and mixing. Effects can include plankton blooms that are spatially coherent over a variety of mesoscale and larger scales, apparent propagation of transient biological activity at rates that are significantly different from the local flow speed, and biases in the basin-integrated flux of carbon to the sub-surface. These effects are analyzed in a purely mathematical model and demonstrated in numerical simulations in idealized basins.

  8. Adaptive Sampling of Spatiotemporal Phenomena with Optimization Criteria

    NASA Technical Reports Server (NTRS)

    Chien, Steve A.; Thompson, David R.; Hsiang, Kian

    2013-01-01

    This work was designed to find a way to optimally (or near optimally) sample spatiotemporal phenomena based on limited sensing capability, and to create a model that can be run to estimate uncertainties, as well as to estimate covariances. The goal was to maximize (or minimize) some function of the overall uncertainty. The uncertainties and covariances were modeled presuming a parametric distribution, and then the model was used to approximate the overall information gain, and consequently, the objective function from each potential sense. These candidate sensings were then crosschecked against operation costs and feasibility. Consequently, an operations plan was derived that combined both operational constraints/costs and sensing gain. Probabilistic modeling was used to perform an approximate inversion of the model, which enabled calculation of sensing gains, and subsequent combination with operational costs. This incorporation of operations models to assess cost and feasibility for specific classes of vehicles is unique.

  9. Spatio-Temporal Structure of Hooded Gull Flocks

    PubMed Central

    Yomosa, Makoto; Mizuguchi, Tsuyoshi; Hayakawa, Yoshinori

    2013-01-01

    We analyzed the spatio-temporal structure of hooded gull flocks with a portable stereo camera system. The 3-dimensional positions of individuals were reconstructed from pairs of videos. The motions of each individual were analyzed, and both gliding and flapping motions were quantified based on the velocity time series. We analyzed the distributions of the nearest neighbor’s position in terms of coordinates based on each individual’s motion. The obtained results were consistent with the aerodynamic interaction between individuals. We characterized the leader-follower relationship between individuals by a delay time to mimic the direction of a motion. A relation between the delay time and a relative position was analyzed quantitatively, which suggested the basic properties of the formation flight that maintains order in the flock. PMID:24339960

  10. Spatio-temporal characteristics of Trichel pulse at low pressure

    NASA Astrophysics Data System (ADS)

    He, Shoujie; Jing, Ha

    2014-01-01

    Trichel pulses are investigated using a needle-to-plane electrode geometry at low pressure. The evolution of current and voltage, the spatio-temporal discharge images of Trichel pulse are measured. The rising time and duration time in a pulse are about 10 ?s and several tens of microseconds, respectively. One period of pulse can be divided into three stages: the stage preceding cathode breakdown, cathode glow formation, and discharge decaying process. Besides a cathode glow and a dark space, an anode glow is also observed. The emission spectra mainly originate from the C3?u ? B3?g transition for nitrogen. In addition, the capacitances in parallel connected with the discharge cell have important influence on the pulsing frequency.

  11. Electron as Spatiotemporal Complexity due to Self-Organized Criticality

    E-print Network

    Ta Chung Meng

    2001-01-01

    The electron, which has been pictured as an elementary particle ever since J.J. Thomson's e/m-measurement in 1897, and the relativistic motion of which is described by the Dirac equation, is discussed in the light of the recent progress made in Science of Complex Systems. Theoretical arguments and experimental evidences are presented which show that such an electron exhibits characteristic properties of spatiotemporal complexities due to Self-Organized Criticality (SOC). This implies in particular that, conceptually and logically, it is neither possible nor meaningful to identify such an object with an ordinary particle, which by definition is something that has a fixed mass (size), a fixed lifetime, and a fixed structure.

  12. Depth-based selective image reconstruction using spatiotemporal image analysis

    NASA Astrophysics Data System (ADS)

    Haga, Tetsuji; Sumi, Kazuhiko; Hashimoto, Manabu; Seki, Akinobu

    1999-03-01

    In industrial plants, a remote monitoring system which removes physical tour inspection is often considered desirable. However the image sequence given from the mobile inspection robot is hard to see because interested objects are often partially occluded by obstacles such as pillars or fences. Our aim is to improve the image sequence that increases the efficiency and reliability of remote visual inspection. We propose a new depth-based image processing technique, which removes the needless objects from the foreground and recovers the occluded background electronically. Our algorithm is based on spatiotemporal analysis that enables fine and dense depth estimation, depth-based precise segmentation, and accurate interpolation. We apply this technique to a real time sequence given from the mobile inspection robot. The resulted image sequence is satisfactory in that the operator can make correct visual inspection with less fatigue.

  13. Theranostic agents for intracellular gene delivery with spatiotemporal imaging

    PubMed Central

    Knipe, Jennifer M.; Peters, Jonathan T.; Peppas, Nicholas A.

    2013-01-01

    Gene therapy is the modification of gene expression to treat a disease. However, efficient intracellular delivery and monitoring of gene therapeutic agents is an ongoing challenge. Use of theranostic agents with suitable targeted, controlled delivery and imaging modalities has the potential to greatly advance gene therapy. Inorganic nanoparticles including magnetic nanoparticles, gold nanoparticles, and quantum dots have been shown to be effective theranostic agents for the delivery and spatiotemporal tracking of oligonucleotides in vitro and even a few cases in vivo. Major concerns remain to be addressed including cytotoxicity, particularly of quantum dots; effective dosage of nanoparticles for optimal theranostic effect; development of real-time in vivo imaging; and further improvement of gene therapy efficacy. PMID:23606894

  14. Spatiotemporal reconstruction of list-mode PET data

    SciTech Connect

    Nichols, Thomas E.; Qi, Jinyi; Asma, Evren; Leahy, Richard M.

    2002-03-01

    We describe a method for computing a continuous time estimate of tracer density using list-mode positron emission tomography data. The rate function in each voxel is modeled as an inhomogeneous Poisson process whose rate function can be represented using a cubic B-spline basis. The rate functions are estimated by maximizing the likelihood of the arrival times of detected photon pairs over the control vertices of the spline, modified by quadratic spatial and temporal smoothness penalties and a penalty term to enforce nonnegativity. Randoms rate functions are estimated by assuming independence between the spatial and temporal randoms distributions. Similarly, scatter rate functions are estimated by assuming spatiotemporal independence and that the temporal distribution of the scatter is proportional to the temporal distribution of the trues. A quantitative evaluation was performed using simulated data and the method is also demonstrated in a human study using 11C-raclopride.

  15. A spatio-temporal extension to the map cube operator

    NASA Astrophysics Data System (ADS)

    Alzate, Juan C.; Moreno, Francisco J.; Echeverri, Jaime

    2012-09-01

    OLAP (On Line Analytical Processing) is a set of techniques and operators to facilitate the data analysis usually stored in a data warehouse. In this paper, we extend the functionality of an OLAP operator known as Map Cube with the definition and incorporation of a function that allows the formulation of spatio-temporal queries. For example, consider a data warehouse about crimes that includes data about the places where the crimes were committed. Suppose we want to find and visualize the trajectory (a trajectory is just the path that an object follows through space as a function of time) of the crimes of a suspect beginning with his oldest crime and ending with his most recent one. In order to meet this requirement, we extend the Map Cube operator.

  16. Building Spatiotemporal Cloud Platform for Supporting GIS Application

    NASA Astrophysics Data System (ADS)

    Song, W. W.; Jin, B. X.; Li, S. H.; Wei, X. Y.; Li, D.; Hu, F.

    2015-07-01

    Traditional geospatial information platforms are built, managed and maintained by the geoinformation agencies. They integrate various geospatial data (such as DLG, DOM, DEM, gazetteers, and thematic data) to provide data analysis services for supporting government decision making. In the era of big data, it is challenging to address the data- and computing- intensive issues by traditional platforms. In this research, we propose to build a spatiotemporal cloud platform, which uses HDFS for managing image data, and MapReduce-based computing service and workflow for high performance geospatial analysis, as well as optimizing auto-scaling algorithms for Web client users' quick access and visualization. Finally, we demonstrate the feasibility by several GIS application cases.

  17. Spatiotemporal Atlas Estimation for Developmental Delay Detection in Longitudinal Datasets

    PubMed Central

    Durrleman, Stanley; Pennec, Xavier; Trouvé, Alain; Gerig, Guido; Ayache, Nicholas

    2013-01-01

    We propose a new methodology to analyze the anatomical variability of a set of longitudinal data (population scanned at several ages). This method accounts not only for the usual 3D anatomical variability (geometry of structures), but also for possible changes in the dynamics of evolution of the structures. It does not require that subjects are scanned the same number of times or at the same ages. First a regression model infers a continuous evolution of shapes from a set of observations of the same subject. Second, spatiotemporal registrations deform jointly (1) the geometry of the evolving structure via 3D deformations and (2) the dynamics of evolution via time change functions. Third, we infer from a population a prototype scenario of evolution and its 4D variability. Our method is used to analyze the morphological evolution of 2D profiles of hominids skulls and to analyze brain growth from amygdala of autistics, developmental delay and control children. PMID:20426000

  18. Regulatory analysis of the C. elegans genome with spatiotemporal resolution

    PubMed Central

    Araya, Carlos L.; Kawli, Trupti; Kundaje, Anshul; Jiang, Lixia; Wu, Beijing; Vafeados, Dionne; Terrell, Robert; Weissdepp, Peter; Gevirtzman, Louis; Mace, Daniel; Niu, Wei; Boyle, Alan P.; Xie, Dan; Ma, Lijia; Murray, John I.; Reinke, Valerie; Waterston, Robert H.; Snyder, Michael

    2015-01-01

    Summary Discovering the structure and dynamics of transcriptional regulatory events in the genome with cellular and temporal resolution is crucial to understanding the regulatory underpinnings of development and disease. We determined the genomic distribution of binding sites for 92 transcription factors (TFs) and regulatory proteins across multiple stages of C. elegans development by performing 241 ChIP-seq experiments. Integrating regulatory binding and cellular-resolution expression data yielded a spatiotemporally-resolved metazoan TF binding map. Using this map, we explore developmental regulatory circuits that encode combinatorial logic at the levels of co-binding and co-expression of TFs, characterizing (1) the genomic coverage and clustering of regulatory binding, (2) the binding preferences of and biological processes regulated by TFs, (3) the global TF co-associations and genomic subdomains that suggest shared patterns of regulation, and (4) key TFs and TF co-associations for fate specification of individual lineages and cell-types. PMID:25164749

  19. Spatiotemporal specificity in cholinergic control of neocortical function

    PubMed Central

    Muñoz, William; Rudy, Bernardo

    2014-01-01

    Cholinergic actions are critical for normal cortical cognitive functions. The release of acetylcholine (ACh) in neocortex and the impact of this neuromodulator on cortical computations exhibit remarkable spatiotemporal precision, as required for the regulation of behavioral processes underlying attention and learning. We discuss how the organization of the cholinergic projections to the cortex and their release properties might contribute to this specificity. We also review recent studies suggesting that the modulatory influences of ACh on the properties of cortical neurons can have the necessary temporal dynamic range, emphasizing evidence of powerful interneuron subtype-specific effects. We discuss areas that require further investigation and point to technical advances in molecular and genetic manipulations that promise to make headway in understanding the neural bases of cholinergic modulation of cortical cognitive operations. PMID:24637201

  20. Control of Cardiac Arrhythmia by Nonlinear Spatiotemporal Delayed Feedback

    NASA Astrophysics Data System (ADS)

    Boroujeni, Forough Rezaei; Vasegh, Nastaran; Sedigh, Ali Khaki

    The dynamic feedback control of the cardiac pacing interval has been widely used to suppress alternans. In this paper, temporally and spatially suppressing the alternans for cardiac tissue consisting of a one-dimensional chain of cardiac units is investigated. The model employed is a nonlinear partial difference equation. The model's fixed points and their stability conditions are determined, and bifurcations and chaos phenomenon have been studied by numerical simulations. The main objective of this paper is to stabilize the unstable fixed point of the model. The proposed approach is nonlinear spatiotemporal delayed feedback, and the appropriate interval for controller feedback gain is calculated using the linear stability analysis. It is proven that the proposed approach is robust with respect to all bifurcation parameter variations. Also, set point tracking is achieved by employing delayed feedback with an integrator. Finally, simulation results are provided to show the effectiveness of the proposed methodology.

  1. Relaxation Dynamics of Spatiotemporal Chaos in the Nematic Liquid Crystal

    NASA Astrophysics Data System (ADS)

    Nugroho, Fahrudin; Ueki, Tatsuhiro; Hidaka, Yoshiki; Kai, Shoichi

    2011-11-01

    We are working on the electroconvection of nematic liquid crystals, in which a kind of spatiotemporal chaos called as a soft-mode turbulence (SMT) is observed. The SMT is caused by the nonlinear interaction between the convective modes and the Nambu--Goldstone (NG) modes. By applying an external magnetic field H, the NG mode is suppressed and an ordered pattern can be observed. By removing the suppression effect the ordered state relax to its original SMT pattern. We revealed two types of instability govern the relaxation process: the zigzag instability and the free rotation of wavevector q(r). This work is partially supported by Grant-in-Aid for Scientific Research (Nos. 20111003, 21340110, and 21540391) from the Ministry of Education, Culture, Sport, Science, and Technology of Japan and the Japan Society for the Promotion of Science (JSPS).

  2. Spatio-temporal characteristics of Trichel pulse at low pressure

    SciTech Connect

    He, Shoujie; Jing, Ha

    2014-01-15

    Trichel pulses are investigated using a needle-to-plane electrode geometry at low pressure. The evolution of current and voltage, the spatio-temporal discharge images of Trichel pulse are measured. The rising time and duration time in a pulse are about 10??s and several tens of microseconds, respectively. One period of pulse can be divided into three stages: the stage preceding cathode breakdown, cathode glow formation, and discharge decaying process. Besides a cathode glow and a dark space, an anode glow is also observed. The emission spectra mainly originate from the C{sup 3}?{sub u} ? B{sup 3}?{sub g} transition for nitrogen. In addition, the capacitances in parallel connected with the discharge cell have important influence on the pulsing frequency.

  3. Spatiotemporal dynamics of excitons in monolayer and bulk WS2

    NASA Astrophysics Data System (ADS)

    He, Jiaqi; He, Dawei; Wang, Yongsheng; Cui, Qiannan; Ceballos, Frank; Zhao, Hui

    2015-05-01

    Spatiotemporal dynamics of excitons in monolayer and bulk WS2 at room temperature is studied by transient absorption microscopy in the reflection geometry. Excitons are formed from photocarriers injected by a tightly focused 390 nm pump pulse, and monitored by detecting different reflection of a time-delayed and spatially scanned 620 nm probe pulse. We obtain exciton lifetimes of 22 +/- 1 and 110 +/- 10 ps in monolayer and bulk WS2, respectively. Both lifetimes are independent of the exciton density, showing the absence of multi-exciton recombination processes. Exciton diffusion coefficients of 60 +/- 20 and 3.5 +/- 0.5 cm2 s-1 are obtained in monolayer and bulk samples, respectively. These results provide a foundation for understanding excitons in this new material and its optoelectronic applications.

  4. Spatiotemporal dynamics of solvent-assisted lipid bilayer formation.

    PubMed

    Kim, Min Chul; Gillissen, Jurriaan J J; Tabaei, Seyed R; Zhdanov, Vladimir P; Cho, Nam-Joon

    2015-11-18

    The solvent-assisted lipid bilayer (SALB) method offers a general strategy to fabricate supported lipid bilayers on solid surfaces. In this method, lipids dissolved in alcohol are deposited on the target substrate in parallel with their aggregation during exchange with aqueous buffer solution which promotes spontaneous bilayer formation. Herein, a combination of experimental and theoretical approaches is employed in order to understand the key aspects of the SALB formation process. Epifluorescence microscopy experiments are conducted in order to measure the spatiotemporal dynamics of bilayer formation on a glass substrate in a microfluidic channel. Corresponding snapshots of bilayer formation at different stages are rationalized by a numerical simulation of solvent displacement inside the channel. Comparing simulation with experiment indicates that in close proximity to the side walls of the present setup, the bilayer formation is confined to a relatively thin region behind the moving solvent displacement front. PMID:26539669

  5. Decomposition of the complex system into nonlinear spatio-temporal modes: algorithm and application to climate data mining

    NASA Astrophysics Data System (ADS)

    Feigin, Alexander; Gavrilov, Andrey; Loskutov, Evgeny; Mukhin, Dmitry

    2015-04-01

    Proper decomposition of the complex system into well separated "modes" is a way to reveal and understand the mechanisms governing the system behaviour as well as discover essential feedbacks and nonlinearities. The decomposition is also natural procedure that provides to construct adequate and concurrently simplest models of both corresponding sub-systems, and of the system in whole. In recent works two new methods of decomposition of the Earth's climate system into well separated modes were discussed. The first method [1-3] is based on the MSSA (Multichannel Singular Spectral Analysis) [4] for linear expanding vector (space-distributed) time series and makes allowance delayed correlations of the processes recorded in spatially separated points. The second one [5-7] allows to construct nonlinear dynamic modes, but neglects delay of correlations. It was demonstrated [1-3] that first method provides effective separation of different time scales, but prevent from correct reduction of data dimension: slope of variance spectrum of spatio-temporal empirical orthogonal functions that are "structural material" for linear spatio-temporal modes, is too flat. The second method overcomes this problem: variance spectrum of nonlinear modes falls essentially sharply [5-7]. However neglecting time-lag correlations brings error of mode selection that is uncontrolled and increases with growth of mode time scale. In the report we combine these two methods in such a way that the developed algorithm allows constructing nonlinear spatio-temporal modes. The algorithm is applied for decomposition of (i) multi hundreds years globally distributed data generated by the INM RAS Coupled Climate Model [8], and (ii) 156 years time series of SST anomalies distributed over the globe [9]. We compare efficiency of different methods of decomposition and discuss the abilities of nonlinear spatio-temporal modes for construction of adequate and concurrently simplest ("optimal") models of climate systems. 1. Feigin A.M., Mukhin D., Gavrilov A., Volodin E.M., and Loskutov E.M. (2013) "Separation of spatial-temporal patterns ("climatic modes") by combined analysis of really measured and generated numerically vector time series", AGU 2013 Fall Meeting, Abstract NG33A-1574. 2. Alexander Feigin, Dmitry Mukhin, Andrey Gavrilov, Evgeny Volodin, and Evgeny Loskutov (2014) "Approach to analysis of multiscale space-distributed time series: separation of spatio-temporal modes with essentially different time scales", Geophysical Research Abstracts, Vol. 16, EGU2014-6877. 3. Dmitry Mukhin, Dmitri Kondrashov, Evgeny Loskutov, Andrey Gavrilov, Alexander Feigin, and Michael Ghil (2014) "Predicting critical transitions in ENSO models, Part II: Spatially dependent models", Journal of Climate (accepted, doi: 10.1175/JCLI-D-14-00240.1). 4. Ghil, M., R. M. Allen, M. D. Dettinger, K. Ide, D. Kondrashov, et al. (2002) "Advanced spectral methods for climatic time series", Rev. Geophys. 40(1), 3.1-3.41. 5. Dmitry Mukhin, Andrey Gavrilov, Evgeny M Loskutov and Alexander M Feigin (2014) "Nonlinear Decomposition of Climate Data: a New Method for Reconstruction of Dynamical Modes", AGU 2014 Fall Meeting, Abstract NG43A-3752. 6. Andrey Gavrilov, Dmitry Mukhin, Evgeny Loskutov, and Alexander Feigin (2015) "Empirical decomposition of climate data into nonlinear dynamic modes", Geophysical Research Abstracts, Vol. 17, EGU2015-627. 7. Dmitry Mukhin, Andrey Gavrilov, Evgeny Loskutov, Alexander Feigin, and Juergen Kurths (2015) "Reconstruction of principal dynamical modes from climatic variability: nonlinear approach", Geophysical Research Abstracts, Vol. 17, EGU2015-5729. 8. http://83.149.207.89/GCM_DATA_PLOTTING/GCM_INM_DATA_XY_en.htm. 9. http://iridl.ldeo.columbia.edu/SOURCES/.KAPLAN/.EXTENDED/.v2/.ssta/.

  6. Spatio-temporal activity of lightnings over Greece

    NASA Astrophysics Data System (ADS)

    Nastos, P. T.; Matsangouras, I. T.; Chronis, T. G.

    2012-04-01

    Extreme precipitation events are always associated with convective weather conditions driving to intense lightning activity: Cloud to Ground (CG), Ground to Cloud (GC) and Cloud to Cloud (CC). Thus, the study of lightnings, which typically occur during thunderstorms, gives evidence of the spatio-temporal variability of intense precipitation. Lightning is a natural phenomenon in the atmosphere, being a major cause of storm related with deaths and main trigger of forest fires during dry season. Lightning affects the many electrochemical systems of the body causing nerve damage, memory loss, personality change, and emotional problems. Besides, among the various nitrogen oxides sources, the contribution from lightning likely represents the largest uncertainty. An operational lightning detection network (LDN) has been established since 2007 by HNMS, consisting of eight time-of-arrival sensors (TOA), spatially distributed across Greek territory. In this study, the spatial and temporal variability of recorded lightnings (CG, GC and CC) are analyzed over Greece, during the period from January 14, 2008 to December 31, 2009, for the first time. The data for retrieving the location and time-of-occurrence of lightning were acquired from Hellenic National Meteorological Service (HNMS). In addition to the analysis of spatio-temporal activity over Greece, the HNMS-LDN characteristics are also presented. The results of the performed analysis reveal the specific geographical sub-regions associated with lightnings incidence. Lightning activity occurs mainly during the autumn season, followed by summer and spring. Higher frequencies of flashes appear over Ionian and Aegean Sea than over land during winter period against continental mountainous regions during summer period.

  7. Spatio-temporal clustering of wildfires in Portugal

    NASA Astrophysics Data System (ADS)

    Costa, R.; Pereira, M. G.; Caramelo, L.; Vega Orozco, C.; Kanevski, M.

    2012-04-01

    Several studies have shown that wildfires in Portugal presenthigh temporal as well as high spatial variability (Pereira et al., 2005, 2011). The identification and characterization of spatio-temporal clusters contributes to a comprehensivecharacterization of the fire regime and to improve the efficiency of fire prevention and combat activities. The main goalsin this studyare: (i) to detect the spatio-temporal clusters of burned area; and, (ii) to characterize these clusters along with the role of human and environmental factors. The data were supplied by the National Forest Authority(AFN, 2011) and comprises: (a)the Portuguese Rural Fire Database, PRFD, (Pereira et al., 2011) for the 1980-2007period; and, (b) the national mapping burned areas between 1990 and 2009. In this work, in order to complement the more common cluster analysis algorithms, an alternative approach based onscan statistics and on the permutation modelwas used. This statistical methodallows the detection of local excess events and to test if such an excess can reasonably have occurred by chance.Results obtained for different simulations performed for different spatial and temporal windows are presented, compared and interpreted.The influence of several fire factors such as (climate, vegetation type, etc.) is also assessed. Pereira, M.G., Trigo, R.M., DaCamara, C.C., Pereira, J.M.C., Leite, S.M., 2005:"Synoptic patterns associated with large summer forest fires in Portugal".Agricultural and Forest Meteorology. 129, 11-25. Pereira, M. G., Malamud, B. D., Trigo, R. M., and Alves, P. I.: The history and characteristics of the 1980-2005 Portuguese rural fire database, Nat. Hazards Earth Syst. Sci., 11, 3343-3358, doi:10.5194/nhess-11-3343-2011, 2011 AFN, 2011: AutoridadeFlorestalNacional (National Forest Authority). Available at http://www.afn.min-agricultura.pt/portal.

  8. Spatiotemporal conceptual platform for querying archaeological information systems

    NASA Astrophysics Data System (ADS)

    Partsinevelos, Panagiotis; Sartzetaki, Mary; Sarris, Apostolos

    2015-04-01

    Spatial and temporal distribution of archaeological sites has been shown to associate with several attributes including marine, water, mineral and food resources, climate conditions, geomorphological features, etc. In this study, archeological settlement attributes are evaluated under various associations in order to provide a specialized query platform in a geographic information system (GIS). Towards this end, a spatial database is designed to include a series of archaeological findings for a secluded geographic area of Crete in Greece. The key categories of the geodatabase include the archaeological type (palace, burial site, village, etc.), temporal information of the habitation/usage period (pre Minoan, Minoan, Byzantine, etc.), and the extracted geographical attributes of the sites (distance to sea, altitude, resources, etc.). Most of the related spatial attributes are extracted with readily available GIS tools. Additionally, a series of conceptual data attributes are estimated, including: Temporal relation of an era to a future one in terms of alteration of the archaeological type, topologic relations of various types and attributes, spatial proximity relations between various types. These complex spatiotemporal relational measures reveal new attributes towards better understanding of site selection for prehistoric and/or historic cultures, yet their potential combinations can become numerous. Therefore, after the quantification of the above mentioned attributes, they are classified as of their importance for archaeological site location modeling. Under this new classification scheme, the user may select a geographic area of interest and extract only the important attributes for a specific archaeological type. These extracted attributes may then be queried against the entire spatial database and provide a location map of possible new archaeological sites. This novel type of querying is robust since the user does not have to type a standard SQL query but graphically select an area of interest. In addition, according to the application at hand, novel spatiotemporal attributes and relations can be supported, towards the understanding of historical settlement patterns.

  9. BioenergyKDF: Enabling Spatiotemporal Data Synthesis and Research Collaboration

    SciTech Connect

    Myers, Aaron T; Movva, Sunil; Karthik, Rajasekar; Bhaduri, Budhendra L; White, Devin A; Thomas, Neil; Chase, Adrian S Z

    2014-01-01

    The Bioenergy Knowledge Discovery Framework (BioenergyKDF) is a scalable, web-based collaborative environment for scientists working on bioenergy related research in which the connections between data, literature, and models can be explored and more clearly understood. The fully-operational and deployed system, built on multiple open source libraries and architectures, stores contributions from the community of practice and makes them easy to find, but that is just its base functionality. The BioenergyKDF provides a national spatiotemporal decision support capability that enables data sharing, analysis, modeling, and visualization as well as fosters the development and management of the U.S. bioenergy infrastructure, which is an essential component of the national energy infrastructure. The BioenergyKDF is built on a flexible, customizable platform that can be extended to support the requirements of any user community especially those that work with spatiotemporal data. While there are several community data-sharing software platforms available, some developed and distributed by national governments, none of them have the full suite of capabilities available in BioenergyKDF. For example, this component-based platform and database independent architecture allows it to be quickly deployed to existing infrastructure and to connect to existing data repositories (spatial or otherwise). As new data, analysis, and features are added; the BioenergyKDF will help lead research and support decisions concerning bioenergy into the future, but will also enable the development and growth of additional communities of practice both inside and outside of the Department of Energy. These communities will be able to leverage the substantial investment the agency has made in the KDF platform to quickly stand up systems that are customized to their data and research needs.

  10. Modeling directional spatio-temporal processes in island biogeography.

    PubMed

    Carvalho, José C; Cardoso, Pedro; Rigal, François; Triantis, Kostas A; Borges, Paulo A V

    2015-10-01

    A key challenge in island biogeography is to quantity the role of dispersal in shaping biodiversity patterns among the islands of a given archipelago. Here, we propose such a framework. Dispersal within oceanic archipelagos may be conceptualized as a spatio-temporal process dependent on: (1) the spatial distribution of islands, because the probability of successful dispersal is inversely related to the spatial distance between islands and (2) the chronological sequence of island formation that determines the directional asymmetry of dispersal (hypothesized to be predominantly from older to younger islands). From these premises, directional network models may be constructed, representing putative connections among islands. These models may be translated to eigenfunctions in order to be incorporated into statistical analysis. The framework was tested with 12 datasets from the Hawaii, Azores, and Canaries. The explanatory power of directional network models for explaining species composition patterns, assessed by the Jaccard dissimilarity index, was compared with simpler time-isolation models. The amount of variation explained by the network models ranged from 5.5% (for Coleoptera in Hawaii) to 60.2% (for Pteridophytes in Canary Islands). In relation to the four studied taxa, the variation explained by network models was higher for Pteridophytes in the three archipelagos. By the contrary, small fractions of explained variation were observed for Coleoptera (5.5%) and Araneae (8.6%) in Hawaii. Time-isolation models were, in general, not statistical significant and explained less variation than the equivalent directional network models for all the datasets. Directional network models provide a way for evaluating the spatio-temporal signature of species dispersal. The method allows building scenarios against which hypotheses about dispersal within archipelagos may be tested. The new framework may help to uncover the pathways via which species have colonized the islands of a given archipelago and to understand the origins of insular biodiversity. PMID:26668731

  11. SPATIO-TEMPORAL COMPLEXITY OF THE AORTIC SINUS VORTEX

    PubMed Central

    Moore, Brandon; Dasi, Lakshmi Prasad

    2014-01-01

    The aortic sinus vortex is a classical flow structure of significant importance to aortic valve dynamics and the initiation and progression of calific aortic valve disease. We characterize the spatio-temporal characteristics of aortic sinus voxtex dynamics in relation to the viscosity of blood analog solution as well as heart rate. High resolution time-resolved (2KHz) 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 time-scales as revealed using time bin averaged vectors and corresponding instantaneous streamlines. There exist small time-scale vortices and a large time-scale 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 spatio-temporal complexity of vortex dynamics is shown to be profoundly influenced by strong leaflet flutter during systole with a peak frequency of 200Hz and peak amplitude of 4 mm observed in the saline case. While fluid viscosity influences the length and time-scales 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. PMID:25067881

  12. Kinematics and spatiotemporal parameters of infant-carrying in olive baboons.

    PubMed

    Anvari, Zohreh; Berillon, Gilles; Asgari Khaneghah, Asghar; Grimaud-Herve, Dominique; Moulin, Valérie; Nicolas, Guillaume

    2014-11-01

    In the field of biomechanics of quadrupedal locomotion in primates, infant-carrying has received little attention. This study presents the first biomechanical study of infant-carrying in captive female olive baboons (Papio anubis). We test whether females carrying infants conform 1) to the Support Polygon Model (Rollinson and Martin: Symp Zool Soc Lond 48 (1981) 377-427) of gait selection, according to which diagonality should decrease when the infant is carried cranially and increase when the infant is carried dorsally and caudally; 2) to Biewener's (Biewener: Science 245 () 45-48) theory of limb postures, according to which females should extend their hind limbs more due to infant load, especially in the later stages when the infant is not fully autonomous but relatively heavy. This study focuses on the sagittal kinematics of quadrupedal gaits (joint angles and spatiotemporal parameters) of four females with and without infant loads at the CNRS Primatology Station (France). High-speed video recordings were made using the technical platform "Motion Analysis of Primates" available in the animals' place of life. Regarding diagonality, our results do not fully conform to those predicted by the Support Polygon Model of gait selection; however, the model cannot be rejected at this stage in experiment. With regard to limb posture, our results do not support Biewener's (Biewener: Science 245 () 45-48) theory: loaded females do not extend their hind limbs more as predicted; on the contrary, the hind limbs tend to be more flexed when the infant they carry is relatively heavy. PMID:25059514

  13. Regionalised spatiotemporal rainfall and temperature models for flood studies in the Basque Country, Spain

    NASA Astrophysics Data System (ADS)

    Cowpertwait, P.; Ocio, D.; Collazos, G.; de Cos, O.; Stocker, C.

    2012-09-01

    A spatial-temporal point process model of rainfall is fitted to data taken from three homogeneous regions in the Basque Country, Spain. The model is the superposition of two spatial-temporal Neyman-Scott processes, in which rain cells are modelled as discs with radii that follow exponential distributions. In addition, the model includes a parameter for the radius of storm discs, so that rain only occurs when both a cell and a storm disc overlap a point. The model is fitted to data for each month, taken from each of the three homogeneous regions, using a modified method of moments procedure that ensures a smooth seasonal variation in the parameter estimates. Daily temperature data from twenty three sites are used to fit a stochastic temperature model. A principal component analysis of the maximum daily temperatures across the sites indicates that 92% of the variance is explained by the first component, implying that this component can be used to account for spatial variation. A harmonic equation with autoregressive error terms is fitted to the first principal component. The temperature model is obtained by regressing the maximum daily temperature on the first principal component, an indicator variable for the region, and altitude. This, together with scaling and a regression model of temperature range, enables hourly temperatures to be predicted. Rainfall is included as an explanatory variable but has only a marginal influence when predicting temperatures. A distributed model (TETIS; Francés et al., 2007) is calibrated for a selected catchment. Five hundred years of data are simulated using the rainfall and temperature models and used as input to the calibrated TETIS model to obtain simulated discharges to compare with observed discharges. Kolmogorov-Smirnov tests indicate that there is no significant difference in the distributions of observed and simulated maximum flows at the same sites, thus supporting the use of the spatiotemporal models for the intended application.

  14. Toxic Releases and Risk Disparity: A Spatiotemporal Model of Industrial Ecology and Social Empowerment

    PubMed Central

    Aoyagi, Hannah; Ogunseitan, Oladele A.

    2015-01-01

    Information-based regulations (IBRs) are founded on the theoretical premise that public participation in accomplishing policy goals is empowered by open access to information. Since its inception in 1988, the Toxics Release Inventory (TRI) has provided the framework and regulatory impetus for the compilation and distribution of data on toxic releases associated with industrial development, following the tenets of IBR. As TRI emissions are reputed to disproportionately affect low-income communities, we investigated how demographic characteristics are related to change in TRI emissions and toxicity risks between 1989 and 2002, and we sought to identify factors that predict these changes. We used local indicators of spatial association (LISA) maps and spatial regression techniques to study risk disparity in the Los Angeles urban area. We also surveyed 203 individuals in eight communities in the same region to measure the levels of awareness of TRI, attitudes towards air pollution, and general environmental risk. We discovered, through spatial lag models, that changes in gross and toxic emissions are related to community ethnic composition, poverty level, home ownership, and base 1989 emissions (R-square = 0.034–0.083). We generated a structural equation model to explain the determinants of social empowerment to act on the basis of environmental information. Hierarchical confirmatory factor analysis (HCFA) supports the theoretical model that individual empowerment is predicted by risk perception, worry, and awareness (Chi-square = 63.315, p = 0.022, df = 42). This study provides strong evidence that spatiotemporal changes in regional-scale environmental risks are influenced by individual-scale empowerment mediated by IBRs. PMID:26042368

  15. Spatiotemporal characteristics of organic contaminant concentrations and ecological risk assessment in the Songhua River, China

    EPA Science Inventory

    To control source pollution and improve water quality, an understanding of the spatiotemporal characteristics of organic contaminant concentrations in affected receiving waters is necessary. The Songhua River in northeast China is the country's third-largest domestic river and lo...

  16. Exploiting Spatiotemporal and Device Contexts for Energy-Efficient Mobile Embedded Systems

    E-print Network

    Pasricha, Sudeep

    configurations that can optimize energy consumption in mobile embedded systems. These techniques, which includeExploiting Spatiotemporal and Device Contexts for Energy-Efficient Mobile Embedded Systems Brad Engineering Department of Computer Science Colorado State University, Fort Collins, CO bdonohoo

  17. Multimodal imaging reveals the spatiotemporal dynamics of recollection Zara M. Bergstrm a,b,

    E-print Network

    Henson, Rik

    Multimodal imaging reveals the spatiotemporal dynamics of recollection Zara M. Bergström a November 2012 Available online 28 November 2012 Keywords: Episodic Recollection PFC Precuneus Multimodal of episodic information. This multimodal imaging approach revealed striking consistency between the regions

  18. Characterization of high spatiotemporal rainfall events in the upper washita river basin

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Transport phenomena at the watershed scale are driven by spatially distributed hydrological processes in which variable rainfall duration and intensity plays a fundamental role. Characterization of these rainfall phenomena using high spatiotemporal resolution is essential when using models to assess...

  19. Characterization of the spatiotemporal attributes of Sclerotinia flower blight epidemics in a perennial pyrethrum pathosystem

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Sclerotinia flower blight, caused by Sclerotinia sclerotiorum causes substantial direct crop losses from reductions in the numbers of harvestable flowers in Australian pyrethrum fields. The pathogen can also cause plant death from crown rot through myceliogenic germination. The spatiotemporal char...

  20. Behavior Recognition via Sparse Spatio-Temporal Features Piotr Dollar Vincent Rabaud Garrison Cottrell Serge Belongie

    E-print Network

    Cottrell, Garrison W.

    Behavior Recognition via Sparse Spatio-Temporal Features Piotr Doll´ar Vincent Rabaud Garrison-temporally windowed data. We present recognition results on a variety of datasets in- cluding both human and rodent

  1. Distribution and spatiotemporal variability of breeding habitat in three grassland sparrows

    E-print Network

    Dornak, Laura Lynnette

    2012-11-14

    and spatiotemporal variability of breeding habitat in three grassland sparrows L. Lynnette Dornak Geography Biodiversity Institute Objectives Henslow’s Sparrows return inconsistently to breeding areas from year to year compared to other grassland sparrows...

  2. Incremental Principal Component Analysis Based Outlier Detection Methods for Spatiotemporal Data Streams

    NASA Astrophysics Data System (ADS)

    Bhushan, A.; Sharker, M. H.; Karimi, H. A.

    2015-07-01

    In this paper, we address outliers in spatiotemporal data streams obtained from sensors placed across geographically distributed locations. Outliers may appear in such sensor data due to various reasons such as instrumental error and environmental change. Real-time detection of these outliers is essential to prevent propagation of errors in subsequent analyses and results. Incremental Principal Component Analysis (IPCA) is one possible approach for detecting outliers in such type of spatiotemporal data streams. IPCA has been widely used in many real-time applications such as credit card fraud detection, pattern recognition, and image analysis. However, the suitability of applying IPCA for outlier detection in spatiotemporal data streams is unknown and needs to be investigated. To fill this research gap, this paper contributes by presenting two new IPCA-based outlier detection methods and performing a comparative analysis with the existing IPCA-based outlier detection methods to assess their suitability for spatiotemporal sensor data streams.

  3. SPIE Proceedings Vol. 4054, Aerosense 2000, Orlando, FL (in press) Automated spatiotemporal change detection

    E-print Network

    Mountrakis, Giorgos

    SPIE Proceedings Vol. 4054, Aerosense 2000, Orlando, FL (in press) Automated spatiotemporal change/representing change. In this paper we present a novel approach for automated change detection which allows us, 04469, USA #12;GIS Library Select Preexistin

  4. Modeling the spatiotemporal cortical activity associated with the line-motion illusion

    E-print Network

    Cai, David

    Modeling the spatiotemporal cortical activity associated with the line-motion illusion in primary by investigating our model cortex response to the Hikosaka line- motion illusion (LMI) stimulus--a cue of a quickly

  5. The Human Tau Interactome: Binding to the Ribonucleoproteome, and Impaired Binding of the Proline-to-Leucine Mutant at Position 301 (P301L) to Chaperones and the Proteasome.

    PubMed

    Gunawardana, C Geeth; Mehrabian, Mohadeseh; Wang, Xinzhu; Mueller, Iris; Lubambo, Isabela B; Jonkman, James E N; Wang, Hansen; Schmitt-Ulms, Gerold

    2015-11-01

    The tau protein is central to the etiology of several neurodegenerative diseases, including Alzheimer's disease, a subset of frontotemporal dementias, progressive supranuclear palsy and dementia following traumatic brain injury, yet the proteins it interacts with have not been studied using a systematic discovery approach. Here we employed mild in vivo crosslinking, isobaric labeling, and tandem mass spectrometry to characterize molecular interactions of human tau in a neuroblastoma cell model. The study revealed a robust association of tau with the ribonucleoproteome, including major protein complexes involved in RNA processing and translation, and documented binding of tau to several heat shock proteins, the proteasome and microtubule-associated proteins. Follow-up experiments determined the relative contribution of cellular RNA to the tau interactome and mapped interactions to N- or C-terminal tau domains. We further document that expression of P301L mutant tau disrupts interactions of the C-terminal half of tau with heat shock proteins and the proteasome. The data are consistent with a model whereby a higher propensity of P301L mutant tau to aggregate may reflect a perturbation of its chaperone-assisted stabilization and proteasome-dependent degradation. Finally, using a global proteomics approach, we show that heterologous expression of a tau construct that lacks the C-terminal domain, including the microtubule binding domain, does not cause a discernible shift of the proteome except for a significant direct correlation of steady-state levels of tau and cystatin B. PMID:26269332

  6. Metabolic-Stress-Induced Rearrangement of the 14-3-3? Interactome Promotes Autophagy via a ULK1- and AMPK-Regulated 14-3-3? Interaction with Phosphorylated Atg9

    PubMed Central

    Weerasekara, Vajira K.; Panek, David J.; Broadbent, David G.; Mortenson, Jeffrey B.; Mathis, Andrew D.; Logan, Gideon N.; Prince, John T.; Thomson, David M.; Thompson, J. Will

    2014-01-01

    14-3-3? promotes cell survival via dynamic interactions with a vast network of binding partners, many of which are involved in stress regulation. We show here that hypoxia (low glucose and oxygen) triggers a rearrangement of the 14-3-3? interactome to favor an interaction with the core autophagy regulator Atg9A. Our data suggest that the localization of mammalian Atg9A to autophagosomes requires phosphorylation on the C terminus of Atg9A at S761, which creates a 14-3-3? docking site. Under basal conditions, this phosphorylation is maintained at a low level and is dependent on both ULK1 and AMPK. However, upon induction of hypoxic stress, activated AMPK bypasses the requirement for ULK1 and mediates S761 phosphorylation directly, resulting in an increase in 14-3-3? interactions, recruitment of Atg9A to LC3-positive autophagosomes, and enhanced autophagosome production. These data suggest a novel mechanism whereby the level of autophagy induction can be modulated by AMPK/ULK1-mediated phosphorylation of mammalian Atg9A. PMID:25266655

  7. Stabilization of three-dimensional scroll waves and suppression of spatiotemporal chaos by heterogeneities.

    PubMed

    Spreckelsen, Florian; Hornung, Daniel; Steinbock, Oliver; Parlitz, Ulrich; Luther, Stefan

    2015-10-01

    Scroll waves in a three-dimensional medium with negative filament tension may break up and display spatiotemporal chaos. The presence of heterogeneities can influence the evolution of the medium, in particular scroll waves may pin to such heterogeneities. We show that as a result the medium may be stabilized by heterogeneities of a suitably chosen geometry. Thin rodlike heterogeneities suppress otherwise developing spatiotemporal chaos and additionally clear out already existing chaotic excitation patterns. PMID:26565317

  8. Ultrafast Spatiotemporal Dynamics of Terahertz Generation by Ionizing Two-Color Femtosecond Pulses in Gases

    SciTech Connect

    Babushkin, I.; Kuehn, W.; Reimann, K.; Woerner, M.; Herrmann, J.; Elsaesser, T.; Koehler, C.; Skupin, S.; Berge, L.

    2010-07-30

    We present a combined theoretical and experimental study of spatiotemporal propagation effects in terahertz (THz) generation in gases using two-color ionizing laser pulses. The observed strong broadening of the THz spectra with increasing gas pressure reveals the prominent role of spatiotemporal reshaping and of a plasma-induced blueshift of the pump pulses in the generation process. Results obtained from (3+1)-dimensional simulations are in good agreement with experimental findings and clarify the mechanisms responsible for THz emission.

  9. Numerical simulations of holographic spatiospectral traces of spatiotemporally distorted ultrashort laser pulses.

    PubMed

    Guang, Zhe; Rhodes, Michelle; Trebino, Rick

    2015-08-01

    We simulate traces for a catalog of spatiotemporally complex pulses measured using a single-shot complete spatiotemporal pulse-measurement technique we recently developed, called Spatially and Temporally Resolved Intensity and Phase Evaluation Device: Full Information from a Single Hologram (STRIPED FISH). The only such technique ever developed to our knowledge, STRIPED FISH measures the complete spatiotemporal intensity I(x,y,t) and phase ?(x,y,t) of an arbitrary laser pulse using an experimentally recorded trace consisting of multiple digital holograms, one for each frequency present in the pulse. To understand the effects of various spatiotemporal distortions on the STRIPED FISH trace, we numerically investigate STRIPED FISH trace features for a catalog of pulses, including the spatially and temporally transform-limited pulse, temporal and spatial double pulses, spherically focusing and diverging pulses, self-phase modulated and self-focusing pulses, spatiotemporally coupled pulses, and pulses with complex structures. As a practical example, we also analyze an experimentally recorded trace of a focusing pulse with spatial chirp. Overall, we find that, from STRIPED FISH's informative trace, significant spatiotemporal characteristics of the unknown pulse can be immediately recognized from the camera frame. This, coupled with its simple pulse-retrieval algorithm, makes STRIPED FISH an excellent technique for measuring and monitoring ultrafast laser sources. PMID:26368075

  10. Real-time task recognition in cataract surgery videos using adaptive spatiotemporal polynomials.

    PubMed

    Quellec, Gwénolé; Lamard, Mathieu; Cochener, Béatrice; Cazuguel, Guy

    2015-04-01

    This paper introduces a new algorithm for recognizing surgical tasks in real-time in a video stream. The goal is to communicate information to the surgeon in due time during a video-monitored surgery. The proposed algorithm is applied to cataract surgery, which is the most common eye surgery. To compensate for eye motion and zoom level variations, cataract surgery videos are first normalized. Then, the motion content of short video subsequences is characterized with spatiotemporal polynomials: a multiscale motion characterization based on adaptive spatiotemporal polynomials is presented. The proposed solution is particularly suited to characterize deformable moving objects with fuzzy borders, which are typically found in surgical videos. Given a target surgical task, the system is trained to identify which spatiotemporal polynomials are usually extracted from videos when and only when this task is being performed. These key spatiotemporal polynomials are then searched in new videos to recognize the target surgical task. For improved performances, the system jointly adapts the spatiotemporal polynomial basis and identifies the key spatiotemporal polynomials using the multiple-instance learning paradigm. The proposed system runs in real-time and outperforms the previous solution from our group, both for surgical task recognition ( Az = 0.851 on average, as opposed to Az = 0.794 previously) and for the joint segmentation and recognition of surgical tasks ( Az = 0.856 on average, as opposed to Az = 0.832 previously). PMID:25373078

  11. Global Predictions 

    E-print Network

    Swyden, Courtney

    2006-01-01

    stream_source_info Global Predictions.pdf.txt stream_content_type text/plain stream_size 7503 Content-Encoding ISO-8859-1 stream_name Global Predictions.pdf.txt Content-Type text/plain; charset=ISO-8859-1 Every morning... drought index is based on a daily water balance, where a drought factor is calculated with precipitation and soil moisture,? Srinivasan said. Global Predictions Story by Courtney Swyden Global Predictions Lab uses advanced technologies to forecast...

  12. The Influence of Weather and Lemmings on Spatiotemporal Variation in the Abundance of Multiple Avian Guilds in the Arctic

    PubMed Central

    Robinson, Barry G.; Franke, Alastair; Derocher, Andrew E.

    2014-01-01

    Climate change is occurring more rapidly in the Arctic than other places in the world, which is likely to alter the distribution and abundance of migratory birds breeding there. A warming climate can provide benefits to birds by decreasing spring snow cover, but increases in the frequency of summer rainstorms, another product of climate change, may reduce foraging opportunities for insectivorous birds. Cyclic lemming populations in the Arctic also influence bird abundance because Arctic foxes begin consuming bird eggs when lemmings decline. The complex interaction between summer temperature, precipitation, and the lemming cycle hinder our ability to predict how Arctic-breeding birds will respond to climate change. The main objective of this study was to investigate the relationship between annual variation in weather, spring snow cover, lemming abundance and spatiotemporal variation in the abundance of multiple avian guilds in a tundra ecosystem in central Nunavut, Canada: songbirds, shorebirds, gulls, loons, and geese. We spatially stratified our study area based on vegetation productivity, terrain ruggedness, and freshwater abundance, and conducted distance sampling to estimate strata-specific densities of each guild during the summers of 2010–2012. We also monitored temperature, rainfall, spring snow cover, and lemming abundance each year. Spatial variation in bird abundance matched what was expected based on previous ecological knowledge, but weather and lemming abundance also significantly influenced the abundance of some guilds. In particular, songbirds were less abundant during the cool, wet summer with moderate snow cover, and shorebirds and gulls declined with lemming abundance. The abundance of geese did not vary over time, possibly because benefits created by moderate spring snow cover were offset by increased fox predation when lemmings were scarce. Our study provides an example of a simple way to monitor the correlation between weather, spring snow cover, lemming abundance, and spatiotemporal variations in Arctic-breeding birds. PMID:24983471

  13. Spatiotemporal Variability of NDVI Over Indian Region and its Relationship with Rainfall, Temperature, Soil moisture, and Sea Surface Temperature

    NASA Astrophysics Data System (ADS)

    Akarsh, A.; Mishra, V.

    2014-12-01

    The Normalized difference Vegetation Index (NDVI) is considered as a proxy for vegetation health. Worldwide it is used as an effective tool to monitor spatiotemporal variations in land use practices and vegetation vigor. The forecast of NDVI can be effectively utilized as an early warning system for the better planning and management, especially in agricultural sector. Here, in this study, we evaluated the spatiotemporal variability of NDVI over Indian region and how it is affected by various factors such as rain fall, temperature, sea surface temperature (SST) and soil moisture. First, we evaluated the seasonal (Pre monsoon, Monsoon, Post Monsoon, Kharif and Rabi) NDVI trend from 1982-2013 and it is found that there is a significant increase in NDVI over the Indian region in land use land cover (LULC) classes. Further the correlation analysis of NDVI with above mention parameters were performed at various lags to evaluate better predictor of NDVI and it is observed that all the parameters exhibit significantly high correlations at various lags. It is well known that over the Indian region vegetation growth/crop growth is largely dependent on climate parameters especially rainfall, and Indian region rainfall is highly correlated with El Nino/Southern Oscillation (ENSO). Thus the relationship of NDVI with SST one of the proxies of ENSO can be utilized to predict vegetation health over Indian region. To evaluate that we performed Maximum Covariance Analysis (MCA) of SST departure field and NDVI time series and found that there exists a decline in vegetation health or NDVI if the equatorial eastern pacific SST is anomalously high.

  14. Multivariate spatio-temporal modelling for assessing Antarctica's present-day contribution to sea-level rise

    PubMed Central

    Zammit-Mangion, Andrew; Rougier, Jonathan; Schön, Nana; Lindgren, Finn; Bamber, Jonathan

    2015-01-01

    Antarctica is the world's largest fresh-water reservoir, with the potential to raise sea levels by about 60 m. An ice sheet contributes to sea-level rise (SLR) when its rate of ice discharge and/or surface melting exceeds accumulation through snowfall. Constraining the contribution of the ice sheets to present-day SLR is vital both for coastal development and planning, and climate projections. Information on various ice sheet processes is available from several remote sensing data sets, as well as in situ data such as global positioning system data. These data have differing coverage, spatial support, temporal sampling and sensing characteristics, and thus, it is advantageous to combine them all in a single framework for estimation of the SLR contribution and the assessment of processes controlling mass exchange with the ocean. In this paper, we predict the rate of height change due to salient geophysical processes in Antarctica and use these to provide estimates of SLR contribution with associated uncertainties. We employ a multivariate spatio-temporal model, approximated as a Gaussian Markov random field, to take advantage of differing spatio-temporal properties of the processes to separate the causes of the observed change. The process parameters are estimated from geophysical models, while the remaining parameters are estimated using a Markov chain Monte Carlo scheme, designed to operate in a high-performance computing environment across multiple nodes. We validate our methods against a separate data set and compare the results to those from studies that invariably employ numerical model outputs directly. We conclude that it is possible, and insightful, to assess Antarctica's contribution without explicit use of numerical models. Further, the results obtained here can be used to test the geophysical numerical models for which in situ data are hard to obtain. © 2015 The Authors. Environmetrics published by John Wiley & Sons Ltd. PMID:25937792

  15. Predictive Evaluation

    ERIC Educational Resources Information Center

    Scriven, Michael

    2007-01-01

    Noting that there has been extensive discussion of the relation of evaluation to: (1) research; (2) explanations (a.k.a. theory-driven, logic model, or realistic evaluation); and (3) recommendations, the author introduces: (4) prediction. He advocates that unlike the first three concepts, prediction is necessarily part of most kinds of evaluation,…

  16. Graphing Predictions

    ERIC Educational Resources Information Center

    Connery, Keely Flynn

    2007-01-01

    Graphing predictions is especially important in classes where relationships between variables need to be explored and derived. In this article, the author describes how his students sketch the graphs of their predictions before they begin their investigations on two laboratory activities: Distance Versus Time Cart Race Lab and Resistance; and…

  17. Tossing the Earth: How to Reliably Test Earthquake Prediction Methods

    NASA Astrophysics Data System (ADS)

    Zaliapin, I.; Molchan, G.

    2004-12-01

    One of the most consequential issues of the earthquake prediction problem is reliable testing of hypothetical prediction methods. The danger of self-deception by data overfitting here is especially high due to both the scarceness of large earthquakes and the absence of a conventional wide-reaching theoretical framework. This talk gives an overview of the methods currently employed to test prediction algorithms and bridges the commonly accepted approaches to the problem. The main focus is on the two most widely used approaches to assessing prediction methods. Both of them evaluate the amount of new information revealed by the prediction method about the impending earthquake activity. The first one starts by estimating the expected spatio-temporal distribution of seismicity, and uses the classical likelihood paradigm to evaluate the prediction power. Accordingly, it uses the nomenclature of statistical estimation. The second one applies results of G. Molchan [Pure Appl. Geophys., 149: 233-247, 1997] that can be considered as a time-dependent analog of the Neyman-Pearson lemma to make a decision whether or not to expect an earthquake within a given spatio-temporal region. Accordingly, it uses the nomenclature of hypothesis testing. Importantly, this approach does not require the explicit knowledge of the earthquake hazard rate; in other words, the correct decision can be made with the realistically imprecise data. We discuss how the choice of the assessment method depends on a specific prediction situation using the outcomes of real-time prediction experiments. The best choice happened to depend crucially on the specifics of the prediction problem: set of target earthquakes; prediction time-span, resolution, etc.

  18. Modelling spatiotemporal distribution patterns of earthworms in order to indicate hydrological soil processes

    NASA Astrophysics Data System (ADS)

    Palm, Juliane; Klaus, Julian; van Schaik, Loes; Zehe, Erwin; Schröder, Boris

    2010-05-01

    Soils provide central ecosystem functions in recycling nutrients, detoxifying harmful chemicals as well as regulating microclimate and local hydrological processes. The internal regulation of these functions and therefore the development of healthy and fertile soils mainly depend on the functional diversity of plants and animals. Soil organisms drive essential processes such as litter decomposition, nutrient cycling, water dynamics, and soil structure formation. Disturbances by different soil management practices (e.g., soil tillage, fertilization, pesticide application) affect the distribution and abundance of soil organisms and hence influence regulating processes. The strong relationship between environmental conditions and soil organisms gives us the opportunity to link spatiotemporal distribution patterns of indicator species with the potential provision of essential soil processes on different scales. Earthworms are key organisms for soil function and affect, among other things, water dynamics and solute transport in soils. Through their burrowing activity, earthworms increase the number of macropores by building semi-permanent burrow systems. In the unsaturated zone, earthworm burrows act as preferential flow pathways and affect water infiltration, surface-, subsurface- and matrix flow as well as the transport of water and solutes into deeper soil layers. Thereby different ecological earthworm types have different importance. Deep burrowing anecic earthworm species (e.g., Lumbricus terrestris) affect the vertical flow and thus increase the risk of potential contamination of ground water with agrochemicals. In contrast, horizontal burrowing endogeic (e.g., Aporrectodea caliginosa) and epigeic species (e.g., Lumbricus rubellus) increase water conductivity and the diffuse distribution of water and solutes in the upper soil layers. The question which processes are more relevant is pivotal for soil management and risk assessment. Thus, finding relevant environmental predictors which explain the distribution and dynamics of different ecological earthworm types can help us to understand where or when these processes are relevant in the landscape. Therefore, we develop species distribution models which are a useful tool to predict spatiotemporal distributions of earthworm occurrence and abundance under changing environmental conditions. On field scale, geostatistical distribution maps have shown that the spatial distribution of earthworms depends on soil parameters such as food supply, soil moisture, bulk density but with different patterns for earthworm stages (adult, juvenile) and ecological types (anecic, endogeic, epigeic). On landscape scales, earthworm distribution seems to be strongly controlled by management/disturbance-related factors. Our study shows different modelling approaches for predicting distribution patterns of earthworms in the Weiherbach area, an agricultural site in Kraichtal (Baden-Württemberg, Germany). We carried out field studies on arable fields differing in soil management practices (conventional, conservational), soil properties (organic matter content, texture, soil moisture), and topography (slope, elevation) in order to identify predictors for earthworm occurrence, abundance and biomass. Our earthworm distribution models consider all ecological groups as well as different life stages, accounting for the fact that the activity of juveniles is sometimes different from those of adults. Within our BIOPORE-project it is our final goal to couple our distribution models with population dynamic models and a preferential flow model to an integrated ecohydrological model to analyse feedbacks between earthworm engineering and transport characteristics affecting the functioning of (agro-) ecosystems.

  19. Global Compartmental Pharmacokinetic Models for Spatiotemporal SPECT and PET Imaging*

    PubMed Central

    Clarkson, Eric; Kupinski, Matthew A.

    2010-01-01

    A new mathematical framework is introduced for combining the linear compartmental models used in pharmacokinetics with the spatiotemporal distributions of activity that are measured in single photon emission computed tomography (SPECT) and PET imaging. This approach is global in the sense that the compartmental differential equations involve only the overall spatially integrated activity in each compartment. The kinetics for the local compartmental activities are not specified by the model and would be determined from data. It is shown that an increase in information about the spatial distribution of the local compartmental activities leads to an increase in the number of identifiable quantities associated with the compartmental matrix. These identifiable quantities, which are important kinetic parameters in applications, are determined by computing the invariants of a symmetry group. This group generates the space of compartmental matrices that are compatible with a given activity distribution, input function, and set of support constraints. An example is provided where all of the compartmental spatial supports have been separated, except that of the vascular compartment. The question of estimating the identifiable parameters from SPECT and PET data is also discussed. PMID:20648238

  20. Spatio-temporal distribution of human lifespan in China.

    PubMed

    Wang, Shaobin; Luo, Kunli; Liu, Yonglin

    2015-01-01

    Based on the data of latest three Chinese population censuses (1990-2010), four lifespan indicators were calculated: centenarians per one hundred thousand inhabitants (CH); longevity index (LI); the percentage of the population aged at least 80 years (ultra-octogenarian index, UOI) and life expectancy at birth (LEB). The spatio-temporal distributions of data at Chinese county level show that high-longevity areas (high values of CH and LI) and low-longevity areas (low CH and LI values) both exhibit clear non-uniformity of spatial distribution and relative immobility through time. Contrarily, the distribution of UOI and LEB shows a decline from the east to the west. The spatial autocorrelation analyses indicate less spatial dependency and several discontinuous clusters regions of high-CH and LI areas. The factors of temperature, topography and wet/dry climate lack of significant influence on CH and LI. It can be inferred that, in addition to genetic factor and living custom, some unique and long-term environmental effects may be related with high or low values of CH and LI. PMID:26346713