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1

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

E-print Network

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

Gerstein, Mark

2

Computational prediction of the human-microbial oral interactome  

PubMed Central

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

2014-01-01

3

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

E-print Network

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

Mishra, Bud

4

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

PubMed Central

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

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

2010-01-01

5

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

PubMed Central

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

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

2014-01-01

6

A Spatiotemporal Approach to Tornado Prediction V Lakshmanan  

E-print Network

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

Lakshmanan, Valliappa

7

Spatiotemporal Signatures of Lexical-Semantic Prediction.  

PubMed

Although there is broad agreement that top-down expectations can facilitate lexical-semantic processing, the mechanisms driving these effects are still unclear. In particular, while previous electroencephalography (EEG) research has demonstrated a reduction in the N400 response to words in a supportive context, it is often challenging to dissociate facilitation due to bottom-up spreading activation from facilitation due to top-down expectations. The goal of the current study was to specifically determine the cortical areas associated with facilitation due to top-down prediction, using magnetoencephalography (MEG) recordings supplemented by EEG and functional magnetic resonance imaging (fMRI) in a semantic priming paradigm. In order to modulate expectation processes while holding context constant, we manipulated the proportion of related pairs across 2 blocks (10 and 50% related). Event-related potential results demonstrated a larger N400 reduction when a related word was predicted, and MEG source localization of activity in this time-window (350-450 ms) localized the differential responses to left anterior temporal cortex. fMRI data from the same participants support the MEG localization, showing contextual facilitation in left anterior superior temporal gyrus for the high expectation block only. Together, these results provide strong evidence that facilitatory effects of lexical-semantic prediction on the electrophysiological response 350-450 ms postonset reflect modulation of activity in left anterior temporal cortex. PMID:25316341

Lau, Ellen F; Weber, Kirsten; Gramfort, Alexandre; Hämäläinen, Matti S; Kuperberg, Gina R

2014-10-14

8

In silico prediction of physical protein interactions and characterization of interactome orphans.  

PubMed

Protein-protein interactions (PPIs) are useful for understanding signaling cascades, predicting protein function, associating proteins with disease and fathoming drug mechanism of action. Currently, only ?10% of human PPIs may be known, and about one-third of human proteins have no known interactions. We introduce FpClass, a data mining-based method for proteome-wide PPI prediction. At an estimated false discovery rate of 60%, we predicted 250,498 PPIs among 10,531 human proteins; 10,647 PPIs involved 1,089 proteins without known interactions. We experimentally tested 233 high- and medium-confidence predictions and validated 137 interactions, including seven novel putative interactors of the tumor suppressor p53. Compared to previous PPI prediction methods, FpClass achieved better agreement with experimentally detected PPIs. We provide an online database of annotated PPI predictions (http://ophid.utoronto.ca/fpclass/) and the prediction software (http://www.cs.utoronto.ca/~juris/data/fpclass/). PMID:25402006

Kotlyar, Max; Pastrello, Chiara; Pivetta, Flavia; Lo Sardo, Alessandra; Cumbaa, Christian; Li, Han; Naranian, Taline; Niu, Yun; Ding, Zhiyong; Vafaee, Fatemeh; Broackes-Carter, Fiona; Petschnigg, Julia; Mills, Gordon B; Jurisicova, Andrea; Stagljar, Igor; Maestro, Roberta; Jurisica, Igor

2015-01-01

9

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

PubMed Central

Background Every year pathogenic organisms cause billions of dollars' worth damage to crops and livestock. In agriculture, study of plant-microbe interactions is demanding a special attention to develop management strategies for the destructive pathogen induced diseases that cause huge crop losses every year worldwide. Pseudomonas syringae is a major bacterial leaf pathogen that causes diseases in a wide range of plant species. Among its various strains, pathovar tomato strain DC3000 (PstDC3000) is asserted to infect the plant host Arabidopsis thaliana and thus, has been accepted as a model system for experimental characterization of the molecular dynamics of plant-pathogen interactions. Protein-protein interactions (PPIs) play a critical role in initiating pathogenesis and maintaining infection. Understanding the PPI network between a host and pathogen is a critical step for studying the molecular basis of pathogenesis. The experimental study of PPIs at a large scale is very scarce and also the high throughput experimental results show high false positive rate. Hence, there is a need for developing efficient computational models to predict the interaction between host and pathogen in a genome scale, and find novel candidate effectors and/or their targets. Results In this study, we used two computational approaches, the interolog and the domain-based to predict the interactions between Arabidopsis and PstDC3000 in genome scale. The interolog method relies on protein sequence similarity to conduct the PPI prediction. A Pseudomonas protein and an Arabidopsis protein are predicted to interact with each other if an experimentally verified interaction exists between their respective homologous proteins in another organism. The domain-based method uses domain interaction information, which is derived from known protein 3D structures, to infer the potential PPIs. If a Pseudomonas and an Arabidopsis protein contain an interacting domain pair, one can expect the two proteins to interact with each other. The interolog-based method predicts ~0.79M PPIs involving around 7700 Arabidopsis and 1068 Pseudomonas proteins in the full genome. The domain-based method predicts 85650 PPIs comprising 11432 Arabidopsis and 887 Pseudomonas proteins. Further, around 11000 PPIs have been identified as interacting from both the methods as a consensus. Conclusion The present work predicts the protein-protein interaction network between Arabidopsis thaliana and Pseudomonas syringae pv. tomato DC3000 in a genome wide scale with a high confidence. Although the predicted PPIs may contain some false positives, the computational methods provide reasonable amount of interactions which can be further validated by high throughput experiments. This can be a useful resource to the plant community to characterize the host-pathogen interaction in Arabidopsis and Pseudomonas system. Further, these prediction models can be applied to the agriculturally relevant crops. PMID:25350354

2014-01-01

10

Hippocampal-cerebellar interaction during spatio-temporal prediction.  

PubMed

The hippocampus and cerebellum play a role in the process of temporal memory formation. The interaction between these brain regions during the prediction of motor executions nevertheless remains unclear. Using fMRI, we show here that the hippocampus and cerebellum are co-activated during a timing-dependent task that requires accurate prediction timing of finger movements following preceding visual cues, but not during 2 control tasks: a reaction task requiring identical coordination of individual and combined fingers without predicting the motor timing, or an imagery task. In addition, functional connectivity analyses reveal that the hippocampus showed increased functional connectivity with the bilateral hemispheres of the cerebellum. These results suggest that hippocampal-cerebellar interplay occurs during spatio-temporal prediction of movements on the basis of visuomotor integration. PMID:23968839

Onuki, Yoshiyuki; Van Someren, Eus J W; De Zeeuw, Chris I; Van der Werf, Ysbrand D

2015-02-01

11

Virtual Interactomics of Proteins from Biochemical Standpoint  

PubMed Central

Virtual interactomics represents a rapidly developing scientific area on the boundary line of bioinformatics and interactomics. Protein-related virtual interactomics then comprises instrumental tools for prediction, simulation, and networking of the majority of interactions important for structural and individual reproduction, differentiation, recognition, signaling, regulation, and metabolic pathways of cells and organisms. Here, we describe the main areas of virtual protein interactomics, that is, structurally based comparative analysis and prediction of functionally important interacting sites, mimotope-assisted and combined epitope prediction, molecular (protein) docking studies, and investigation of protein interaction networks. Detailed information about some interesting methodological approaches and online accessible programs or databases is displayed in our tables. Considerable part of the text deals with the searches for common conserved or functionally convergent protein regions and subgraphs of conserved interaction networks, new outstanding trends and clinically interesting results. In agreement with the presented data and relationships, virtual interactomic tools improve our scientific knowledge, help us to formulate working hypotheses, and they frequently also mediate variously important in silico simulations. PMID:22928109

Kubrycht, Jaroslav; Sigler, Karel; Sou?ek, Pavel

2012-01-01

12

Predicting BCI Subject Performance Using Probabilistic Spatio-Temporal Filters  

PubMed Central

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

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

2014-01-01

13

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

E-print Network

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 ...

Jaillet, Patrick

14

SePreSA: a server for the prediction of populations susceptible to serious adverse drug reactions implementing the methodology of a chemical-protein interactome.  

PubMed

Serious adverse drug reactions (SADRs) are caused by unexpected drug-human protein interactions, and some polymorphisms within binding pockets make the population carrying these polymorphisms susceptible to SADR. Predicting which populations are likely to be susceptible to SADR will not only strengthen drug safety, but will also assist enterprises to adjust R&D and marketing strategies. Making such predictions has recently been facilitated by the introduction of a web server named SePreSA. The server has a comprehensive collection of the structural models of nearly all the well known SADR targets. Once a drug molecule is submitted, the scale of its potential interaction with multi-SADR targets is calculated using the DOCK program. The server utilizes a 2-directional Z-transformation scoring algorithm, which computes the relative drug-protein interaction strength based on the docking-score matrix of a chemical-protein interactome, thus achieve greater accuracy in prioritizing SADR targets than simply using dock scoring functions. The server also suggests the binding pattern of the lowest docking score through 3D visualization, by highlighting and visualizing amino acid residues involved in the binding on the customer's browser. Polymorphism information for different populations for each of the interactive residues will be displayed, helping users to deduce the population-specific susceptibility of their drug molecule. The server is freely available at http://SePreSA.Bio-X.cn/. PMID:19417066

Yang, Lun; Luo, Heng; Chen, Jian; Xing, Qinghe; He, Lin

2009-07-01

15

Plant Protein-Protein Interaction Network and Interactome  

PubMed Central

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

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

2010-01-01

16

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

E-print Network

Assessing Protein Co-evolution in the Context of the Tree of Life Assists in the Prediction on the overall evolutionary histories of the species (i.e. the canonical "tree of life") in order to correct-evolution in the context of the tree of life leads to a highly significant improvement (P(N) by sign test w10E­6

Pazos, Florencio

17

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

PubMed Central

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

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

2013-01-01

18

Exploiting Spatio-Temporal Correlations in MIMO Wireless Channel Prediction  

E-print Network

minimum mean square error (2D-MMSE) narrowband MIMO channel prediction filter that maximally exploits both temporal and spatial correlations in MIMO correlated narrowband fading wireless channels. We first derive the optimal two dimensional minimum mean square error (2D-MMSE) pre- diction filter that maximally

Evans, Brian L.

19

Learned spatiotemporal sequence recognition and prediction in primary visual cortex  

PubMed Central

Learning to recognize and predict temporal sequences is fundamental to sensory perception, and is impaired in several neuropsychiatric disorders, but little is known about where and how this occurs in the brain. We discovered that repeated presentations of a visual sequence over a course of days causes evoked response potentiation in mouse V1 that is highly specific for stimulus order and timing. Remarkably, after V1 is trained to recognize a sequence, cortical activity regenerates the full sequence even when individual stimulus elements are omitted. This novel neurophysiological report of sequence learning advances the understanding of how the brain makes “intelligent guesses” based on limited information to form visual percepts and suggests that it is possible to study the mechanistic basis of this high–level cognitive ability by studying low–level sensory systems. PMID:24657967

Gavornik, Jeffrey P.; Bear, Mark F.

2014-01-01

20

Complementing the Eukaryotic Protein Interactome  

PubMed Central

Protein interaction networks are important for the understanding of regulatory mechanisms, for the explanation of experimental data and for the prediction of protein functions. Unfortunately, most interaction data is available only for model organisms. As a possible remedy, the transfer of interactions to organisms of interest is common practice, but it is not clear when interactions can be transferred from one organism to another and, thus, the confidence in the derived interactions is low. Here, we propose to use a rich set of features to train Random Forests in order to score transferred interactions. We evaluated the transfer from a range of eukaryotic organisms to S. cerevisiae using orthologs. Directly transferred interactions to S. cerevisiae are on average only 24% consistent with the current S. cerevisiae interaction network. By using commonly applied filter approaches the transfer precision can be improved, but at the cost of a large decrease in the number of transferred interactions. Our Random Forest approach uses various features derived from both the target and the source network as well as the ortholog annotations to assign confidence values to transferred interactions. Thereby, we could increase the average transfer consistency to 85%, while still transferring almost 70% of all correctly transferable interactions. We tested our approach for the transfer of interactions to other species and showed that our approach outperforms competing methods for the transfer of interactions to species where no experimental knowledge is available. Finally, we applied our predictor to score transferred interactions to 83 targets species and we were able to extend the available interactome of B. taurus, M. musculus and G. gallus with over 40,000 interactions each. Our transferred interaction networks are publicly available via our web interface, which allows to inspect and download transferred interaction sets of different sizes, for various species, and at specified expected precision levels. Availability: http://services.bio.ifi.lmu.de/coin-db/. PMID:23825550

Pesch, Robert; Zimmer, Ralf

2013-01-01

21

Towards establishment of a rice stress response interactome.  

PubMed

Rice (Oryza sativa) is a staple food for more than half the world and a model for studies of monocotyledonous species, which include cereal crops and candidate bioenergy grasses. A major limitation of crop production is imposed by a suite of abiotic and biotic stresses resulting in 30%-60% yield losses globally each year. To elucidate stress response signaling networks, we constructed an interactome of 100 proteins by yeast two-hybrid (Y2H) assays around key regulators of the rice biotic and abiotic stress responses. We validated the interactome using protein-protein interaction (PPI) assays, co-expression of transcripts, and phenotypic analyses. Using this interactome-guided prediction and phenotype validation, we identified ten novel regulators of stress tolerance, including two from protein classes not previously known to function in stress responses. Several lines of evidence support cross-talk between biotic and abiotic stress responses. The combination of focused interactome and systems analyses described here represents significant progress toward elucidating the molecular basis of traits of agronomic importance. PMID:21533176

Seo, Young-Su; Chern, Mawsheng; Bartley, Laura E; Han, Muho; Jung, Ki-Hong; Lee, Insuk; Walia, Harkamal; Richter, Todd; Xu, Xia; Cao, Peijian; Bai, Wei; Ramanan, Rajeshwari; Amonpant, Fawn; Arul, Loganathan; Canlas, Patrick E; Ruan, Randy; Park, Chang-Jin; Chen, Xuewei; Hwang, Sohyun; Jeon, Jong-Seong; Ronald, Pamela C

2011-04-01

22

Towards Establishment of a Rice Stress Response Interactome  

PubMed Central

Rice (Oryza sativa) is a staple food for more than half the world and a model for studies of monocotyledonous species, which include cereal crops and candidate bioenergy grasses. A major limitation of crop production is imposed by a suite of abiotic and biotic stresses resulting in 30%–60% yield losses globally each year. To elucidate stress response signaling networks, we constructed an interactome of 100 proteins by yeast two-hybrid (Y2H) assays around key regulators of the rice biotic and abiotic stress responses. We validated the interactome using protein–protein interaction (PPI) assays, co-expression of transcripts, and phenotypic analyses. Using this interactome-guided prediction and phenotype validation, we identified ten novel regulators of stress tolerance, including two from protein classes not previously known to function in stress responses. Several lines of evidence support cross-talk between biotic and abiotic stress responses. The combination of focused interactome and systems analyses described here represents significant progress toward elucidating the molecular basis of traits of agronomic importance. PMID:21533176

Seo, Young-Su; Chern, Mawsheng; Bartley, Laura E.; Han, Muho; Jung, Ki-Hong; Lee, Insuk; Walia, Harkamal; Richter, Todd; Xu, Xia; Cao, Peijian; Bai, Wei; Ramanan, Rajeshwari; Amonpant, Fawn; Arul, Loganathan; Canlas, Patrick E.; Ruan, Randy; Park, Chang-Jin; Chen, Xuewei; Hwang, Sohyun; Jeon, Jong-Seong; Ronald, Pamela C.

2011-01-01

23

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

PubMed Central

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

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

2014-01-01

24

Predicting Intra-Urban Variation in Air Pollution Concentrations with Complex Spatio-Temporal Dependencies  

PubMed Central

We describe a methodology for assigning individual estimates of long-term average air pollution concentrations that accounts for a complex spatio-temporal correlation structure and can accommodate spatio-temporally misaligned observations. This methodology has been developed as part of the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air), a prospective cohort study funded by the U.S. EPA to investigate the relationship between chronic exposure to air pollution and cardiovascular disease. Our hierarchical model decomposes the space-time field into a “mean” that includes dependence on covariates and spatially varying seasonal and long-term trends and a “residual” that accounts for spatially correlated deviations from the mean model. The model accommodates complex spatio-temporal patterns by characterizing the temporal trend at each location as a linear combination of empirically derived temporal basis functions, and embedding the spatial fields of coefficients for the basis functions in separate linear regression models with spatially correlated residuals (universal kriging). This approach allows us to implement a scalable single-stage estimation procedure that easily accommodates a significant number of missing observations at some monitoring locations. We apply the model to predict long-term average concentrations of oxides of nitrogen (NOx) from 2005–2007 in the Los Angeles area, based on data from 18 EPA Air Quality System regulatory monitors. The cross-validated R2 is 0.67. The MESA Air study is also collecting additional concentration data as part of a supplementary monitoring campaign. We describe the sampling plan and demonstrate in a simulation study that the additional data will contribute to improved predictions of long-term average concentrations. PMID:24860253

Szpiro, Adam A.; Sampson, Paul D.; Sheppard, Lianne; Lumley, Thomas; Adar, Sara D.; Kaufman, Joel

2014-01-01

25

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

NASA Astrophysics Data System (ADS)

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

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

2012-04-01

26

Development of Spatiotemporal Bias-Correction Techniques for Downscaling GCM Predictions  

NASA Astrophysics Data System (ADS)

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

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

2010-12-01

27

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

PubMed Central

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

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

2013-01-01

28

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

PubMed

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

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

2013-01-01

29

Spatiotemporal Neurodynamics Underlying Internally and Externally Driven Temporal Prediction: A High Spatial Resolution ERP Study.  

PubMed

Temporal prediction (TP) is a flexible and dynamic cognitive ability. Depending on the internal or external nature of information exploited to generate TP, distinct cognitive and brain mechanisms are engaged with the same final goal of reducing uncertainty about the future. In this study, we investigated the specific brain mechanisms involved in internally and externally driven TP. To this end, we employed an experimental paradigm purposely designed to elicit and compare externally and internally driven TP and a combined approach based on the application of a distributed source reconstruction modeling on a high spatial resolution electrophysiological data array. Specific spatiotemporal ERP signatures were identified, with significant modulation of contingent negative variation and frontal late sustained positivity in external and internal TP contexts, respectively. These different electrophysiological patterns were supported by the engagement of distinct neural networks, including a left sensorimotor and a prefrontal circuit for externally and internally driven TP, respectively. PMID:25203276

Mento, Giovanni; Tarantino, Vincenza; Vallesi, Antonino; Bisiacchi, Patrizia Silvia

2015-03-01

30

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

NASA Astrophysics Data System (ADS)

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.

Fu, D.; Chen, B.

2012-04-01

31

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

NASA Astrophysics Data System (ADS)

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.

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

2013-04-01

32

The HTLV-1 Tax interactome  

PubMed Central

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

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

2008-01-01

33

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

PubMed

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

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

2014-02-18

34

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

PubMed

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

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

2014-10-01

35

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

PubMed Central

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

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

2014-01-01

36

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

PubMed

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

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

2014-01-01

37

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

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

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

2014-01-01

38

Information Flow Analysis of Interactome Networks  

E-print Network

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 ...

Liu, Kesheng

39

Functional Integrative Levels in the Human Interactome Recapitulate Organ Organization  

E-print Network

Functional Integrative Levels in the Human Interactome Recapitulate Organ Organization Ouissem, Marseille, France, 3 Institut Pasteur, Tunis, Tunisia, 4 Bioinformatics and Functional Genomics Research functions are peripheral. Overall, the functional organization of the human interactome reflects several

Boyer, Edmond

40

The DAP-kinase interactome.  

PubMed

DAP-kinase (DAPK) is a Ca(2+)/calmodulin regulated Ser/Thr kinase that activates a diverse range of cellular activities. It is subject to multiple layers of regulation involving both intramolecular signaling, and interactions with additional proteins, including other kinases and phosphatases. Its protein stability is modulated by at least three distinct ubiquitin-dependent systems. Like many kinases, DAPK participates in several signaling cascades, by phosphorylating additional kinases such as ZIP-kinase and protein kinase D (PKD), or Pin1, a phospho-directed peptidyl-prolyl isomerase that regulates the function of many phosphorylated proteins. Other substrate targets have more direct cellular effects; for example, phosphorylation of the myosin II regulatory chain and tropomyosin mediate some of DAPK's cytoskeletal functions, including membrane blebbing during cell death and cell motility. DAPK induces distinct death pathways of apoptosis, autophagy and programmed necrosis. Among the substrates implicated in these processes, phosphorylation of PKD, Beclin 1, and the NMDA receptor has been reported. Interestingly, not all cellular effects are mediated by DAPK's catalytic activity. For example, by virtue of protein-protein interactions alone, DAPK activates pyruvate kinase isoform M2, the microtubule affinity regulating kinases and inflammasome protein NLRP3, to promote glycolysis, influence microtubule dynamics, and enhance interleukin-1? production, respectively. In addition, a number of other substrates and interacting proteins have been identified, the physiological significance of which has not yet been established. All of these substrates, effectors and regulators together comprise the DAPK interactome. By presenting the components of the interactome network, this review will clarify both the mechanisms by which DAPK function is regulated, and by which it mediates its various cellular effects. PMID:24220855

Bialik, Shani; Kimchi, Adi

2014-02-01

41

Spatio-temporal variability and predictability of summer monsoon onset over the Philippines  

NASA Astrophysics Data System (ADS)

The spatio-temporal variability of boreal summer monsoon onset over the Philippines is studied through the analysis of daily rainfall data across a network of 76 gauges for the period 1977 to 2004 and the pentad Merged Analysis of Precipitation from the US Climate Prediction Center from 1979 to 2006. The onset date is defined using a local agronomic definition, namely the first wet day of a 5-day period receiving at least 40 mm without any 15-day dry spell receiving <5 mm in the 30 days following the start of that period. The onset is found to occur rather abruptly across the western Philippines around mid-May on average and is associated with the set-up of a “classical” monsoonal circulation with low-level easterlies subsequently veering to southerly, and then southwesterly. The onset manifests itself merely as a seasonal increase of rainfall over the eastern Philippines, where rainfall occurs throughout most of the year. Interannual variability of the onset date is shown to consist of a spatially coherent large-scale component, rather similar over the western and eastern Philippines, with a moderate to high amount of local-scale (i.e. station scale) noise. In consequence, the large-scale signal can be easily retrieved from any sample of at least 5-6 stations across the network although the local-scale coherence and fingerprint of the large-scale signal of the onset date are found to be stronger over the central Philippines, roughly from Southern Luzon to Northern Mindanao. The seasonal predictability of local onset is analyzed through a cross-validated canonical correlation analysis using tropical Pacific and Indian Ocean sea surface temperature in March and the 850 hPa May wind field from dynamical forecast models as predictors. The regional-scale onset, defined as the average of standardized local-scale anomalies in onset date, shows good predictive skill ( r ? 0.8). Moreover, most of the stations show weak to moderate skill (median skill = 0.28-0.43 depending on the scheme) with spatial averaging across stations typically increasing skill to >0.6.

Moron, V.; Lucero, A.; Hilario, F.; Lyon, B.; Robertson, A. W.; Dewitt, D.

2009-12-01

42

A network flow approach to predict drug targets from microarray data, disease genes and interactome network - case study on prostate cancer  

PubMed Central

Background Systematic approach for drug discovery is an emerging discipline in systems biology research area. It aims at integrating interaction data and experimental data to elucidate diseases and also raises new issues in drug discovery for cancer treatment. However, drug target discovery is still at a trial-and-error experimental stage and it is a challenging task to develop a prediction model that can systematically detect possible drug targets to deal with complex diseases. Methods We integrate gene expression, disease genes and interaction networks to identify the effective drug targets which have a strong influence on disease genes using network flow approach. In the experiments, we adopt the microarray dataset containing 62 prostate cancer samples and 41 normal samples, 108 known prostate cancer genes and 322 approved drug targets treated in human extracted from DrugBank database to be candidate proteins as our test data. Using our method, we prioritize the candidate proteins and validate them to the known prostate cancer drug targets. Results We successfully identify potential drug targets which are strongly related to the well known drugs for prostate cancer treatment and also discover more potential drug targets which raise the attention to biologists at present. We denote that it is hard to discover drug targets based only on differential expression changes due to the fact that those genes used to be drug targets may not always have significant expression changes. Comparing to previous methods that depend on the network topology attributes, they turn out that the genes having potential as drug targets are weakly correlated to critical points in a network. In comparison with previous methods, our results have highest mean average precision and also rank the position of the truly drug targets higher. It thereby verifies the effectiveness of our method. Conclusions Our method does not know the real ideal routes in the disease network but it tries to find the feasible flow to give a strong influence to the disease genes through possible paths. We successfully formulate the identification of drug target prediction as a maximum flow problem on biological networks and discover potential drug targets in an accurate manner. PMID:22239822

2012-01-01

43

Surface interactome in Streptococcus pyogenes.  

PubMed

Very few studies have so far been dedicated to the systematic analysis of protein interactions occurring between surface and/or secreted proteins in bacteria. Such interactions are expected to play pivotal biological roles that deserve investigation. Taking advantage of the availability of a detailed map of surface and secreted proteins in Streptococcus pyogenes (group A Streptococcus (GAS)), we used protein array technology to define the "surface interactome" in this important human pathogen. Eighty-three proteins were spotted on glass slides in high density format, and each of the spotted proteins was probed for its capacity to interact with any of the immobilized proteins. A total of 146 interactions were identified, 25 of which classified as "reciprocal," namely, interactions that occur irrespective of which of the two partners was immobilized on the chip or in solution. Several of these interactions were validated by surface plasmon resonance and supported by confocal microscopy analysis of whole bacterial cells. By this approach, a number of interesting interactions have been discovered, including those occurring between OppA, DppA, PrsA, and TlpA, proteins known to be involved in protein folding and transport. These proteins, all localizing at the septum, might be part, together with HtrA, of the recently described ExPortal complex of GAS. Furthermore, SpeI was found to strongly interact with the metal transporters AdcA and Lmb. Because SpeI strictly requires zinc to exert its function, this finding provides evidence on how this superantigen, a major player in GAS pathogenesis, can acquire the metal in the host environment, where it is largely sequestered by carrier proteins. We believe that the approach proposed herein can lead to a deeper knowledge of the mechanisms underlying bacterial invasion, colonization, and pathogenesis. PMID:22199230

Galeotti, Cesira L; Bove, Elia; Pezzicoli, Alfredo; Nogarotto, Renzo; Norais, Nathalie; Pileri, Silvia; Lelli, Barbara; Falugi, Fabiana; Balloni, Sergio; Tedde, Vittorio; Chiarot, Emiliano; Bombaci, Mauro; Soriani, Marco; Bracci, Luisa; Grandi, Guido; Grifantini, Renata

2012-04-01

44

Subpixel Spatiotemporal Pattern Analysis Of Remote Sensing Observations For Predicting Grassland Ecological And Biophysical Parameters  

E-print Network

One of the most important limiting factors in reliable estimation of grassland ecosystem parameters from remotely sensed data is "too coarse" resolution. Areal averages obtained from readily available imagery do not match well with ecological field data. To address this discrepancy we have collected simultaneous spectral, other biophysical and ecological data with similar ground resolution between May and August 1995 in the Grassland National Park, Saskatchewan, Canada. Beyond calibration for a wide variety of conditions, the applied nested sampling design facilitates scaling of measured and estimated properties from 0.5 m to 100 m by partitioning overall variability, and by hierarchical scene simulation. Analysis of the spatiotemporal pattern reveals potential probelms with using areal averages in long-term monitoring and assessment of ecological status of grasslands. INTRODUCTION There are wide ranging arguments for the advantages of remote sensing observations in studying the spat...

Ferko Csillag Andrew; Andrew Davidson; Scott Mitchell; Bruce Wylie

1996-01-01

45

Inferring modules from human protein interactome classes  

PubMed Central

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

2010-01-01

46

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

PubMed Central

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

2014-01-01

47

Detection of driver protein complexes in breast cancer metastasis by large-scale transcriptome-interactome integration.  

PubMed

With the development of high-throughput gene expression profiling technologies came the opportunity to define genomic signatures predicting clinical condition or cancer patient outcome. However, such signatures show dependency on training set, lack of generalization, and instability, partly due to microarray data topology. Additional issues for analyzing tumor gene expression are that subtle molecular perturbations in driver genes leading to cancer and metastasis (masked in typical differential expression analysis) may provoke expression changes of greater amplitude in downstream genes (easily detected). In this chapter, we are describing an interactome-based algorithm, Interactome-Transcriptome Integration (ITI) that is used to find a generalizable signature for prediction of breast cancer relapse by superimposition of a large-scale protein-protein interaction data (human interactome) over several gene expression datasets. ITI extracts regions in the interactome whose expression is discriminating for predicting relapse-free survival in cancer and allow detection of subnetworks that constitutes a generalizable and stable genomic signature. In this chapter, we describe the practical aspects of running the full ITI pipeline (subnetwork detection and classification) on six microarray datasets. PMID:24233778

Garcia, Maxime; Finetti, Pascal; Bertucci, Francois; Birnbaum, Daniel; Bidaut, Ghislain

2014-01-01

48

Real-time road traffic prediction with spatio-temporal correlations  

Microsoft Academic Search

Real-time road traffic prediction is a fundamental capability needed to make use of advanced, smart transportation technologies. Both from the point of view of network operators as well as from the point of view of travelers wishing real-time route guidance, accurate short-term traffic prediction is a necessary first step. While techniques for short-term traffic prediction have existed for some time,

Wanli Min; Laura Wynter

2011-01-01

49

A Viral-Human Interactome Based on Structural Motif-Domain Interactions Captures the Human Infectome  

PubMed Central

Protein interactions between a pathogen and its host are fundamental in the establishment of the pathogen and underline the infection mechanism. In the present work, we developed a single predictive model for building a host-viral interactome based on the identification of structural descriptors from motif-domain interactions of protein complexes deposited in the Protein Data Bank (PDB). The structural descriptors were used for searching, in a database of protein sequences of human and five clinically important viruses; therefore, viral and human proteins sharing a descriptor were predicted as interacting proteins. The analysis of the host-viral interactome allowed to identify a set of new interactions that further explain molecular mechanism associated with viral infections and showed that it was able to capture human proteins already associated to viral infections (human infectome) and non-infectious diseases (human diseasome). The analysis of human proteins targeted by viral proteins in the context of a human interactome showed that their neighbors are enriched in proteins reported with differential expression under infection and disease conditions. It is expected that the findings of this work will contribute to the development of systems biology for infectious diseases, and help guide the rational identification and prioritization of novel drug targets. PMID:23951184

Guo, Xianwu; Rodríguez-Pérez, Mario A.

2013-01-01

50

Using Optimality Principles to Predict Spatio-Temporal Patterns of Vegetation-Atmosphere Fluxes at Leaf to Global Scales  

NASA Astrophysics Data System (ADS)

A predictive understanding of biological variation in space and time -- from spatial gradients of light within plant canopies, seasonal fluctuations in temperature and water availability during a growing season, to geographic variation in climate and soil nutrient availability across the land surface -- is a central but challenging goal in biospheric sciences. Functional attributes of vegetation, such as the capacities to exchange carbon, water and energy with the atmosphere, can be assessed based on thermodynamic and aerodynamic properties of the canopy-atmosphere system, however many of these properties cannot be directly measured at the global scale. In lieu of direct measurement, optimization methods based on simplifying theories of the underlying processes, including Maximum Entropy Production (MEP) and economic theories of plant carbon and water relations, are needed to provide sufficient constraint to estimate the required parameters. Using theories of functional coordination in which it is assumed that plants maintain a balance between the supply and demand of a variable (e.g. absorbed radiation, CO2, water) consistent with MEP in complex source-sink physiological systems, it is possible to predict spatial patterns of leaf photosynthetic capacity within plant canopies as well as their temporal variation throughout the growing season. When combined with satellite remote sensing observations of canopy light absorptance (fAPAR), these same theories can be used to predict seasonal variations in leaf and canopy photosynthesis and transpiration, and global spatio-temporal patterns of productivity and evapotranspiration. Predictions using this approach are consistent with observations at leaf to landscape scales based on leaf gas exchange and eddy covariance measurements in arctic to tropical ecosystems.

Tu, K. P.

2008-12-01

51

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

PubMed Central

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

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

2014-01-01

52

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

PubMed

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

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

2014-01-01

53

How Perfect Can Protein Interactomes Be?  

NSDL National Science Digital Library

Any engineered device should certainly not contain nonfunctional components, for this would be a waste of energy and money. In contrast, evolutionary theory tells us that biological systems need not be optimized and may very well accumulate nonfunctional elements. Mutational and demographic processes contribute to the cluttering of eukaryotic genomes and transcriptional networks with “junk” DNA and spurious DNA binding sites. Here, we question whether such a notion should be applied to protein interactomes—that is, whether these protein interactomes are expected to contain a fraction of nonselected, nonfunctional protein-protein interactions (PPIs), which we term “noisy.” We propose a simple relationship between the fraction of noisy interactions expected in a given organism and three parameters: (i) the number of mutations needed to create and destroy interactions, (ii) the size of the proteome, and (iii) the fitness cost of noisy interactions. All three parameters suggest that noisy PPIs are expected to exist. Their existence could help to explain why PPIs determined from large-scale studies often lack functional relationships between interacting proteins, why PPIs are poorly conserved across organisms, and why the PPI space appears to be immensely large. Finally, we propose experimental strategies to estimate the fraction of evolutionary noise in PPI networks.

Emmanuel D. Levy (Quebec;Universit頤e Montr顬 REV); Christian R. Landry (Quebec;Universit頤e Montr顬 REV); Stephen W. Michnick (Quebec;Universit頤e Montr顬 REV)

2009-03-03

54

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

PubMed

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

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

2015-01-01

55

Alzheimer disease: An interactome of many diseases  

PubMed Central

Alzheimer Disease (AD) is an outcome as well as source of many diseases. Alzheimer is linked with many other diseases like Diabetes type 2, cholesterolemia, hypertension and many more. But how each of these diseases affecting other is still unknown to scientific community. Signaling Pathways of one disease is interlinked with other disease. But to what extent healthy brain is affected when any signaling in human body is disturbed is the question that matters. There is a need of Pathway analysis, Protein-Protein interaction (PPI) and the conserved interactome study in AD and linked diseases. It will be helpful in finding the potent drug or vaccine target in conscious manner. In the present research the Protein-Protein interaction of all the proteins involved in Alzheimer Disease is analyzed using ViSANT and osprey tools and pathway analysis further reveals the significant genes/proteins linking AD with other diseases. PMID:24753659

Rao, Balaji S.; Gupta, Krishna Kant; Karanam, Pujitha; Peruri, Anusha

2014-01-01

56

The topology of the growing human interactome data.  

PubMed

We have long moved past the one-gene–one-function concept originally proposed by Beadle and Tatum back in 1941; but the full understanding of genotype–phenotype relations still largely relies on the analysis of static, snapshot-like, interaction data sets. Here, we look at what global patterns can be uncovered if we simply trace back the human interactome network over the last decade of protein- protein interaction (PPI) screening. We take a purely topological approach and find that as the human interactome is getting denser, it is not only gaining in structure (in terms of now being better fit by structured network models than before), but also there are patterns in the way in which it is growing: (a) newly added proteins tend to get linked to existing proteins in the interactome that are not know to interact; and (b) new proteins tend to link to already well connected proteins. Moreover, the alignment between human and yeast interactomes spanning over 40% of yeast’s proteins — that are involved in regulation of transcription, RNA splicing and other cellcycle-related processes—suggests the existence of a part of the interactome which remains topologically and functionally unaffected through evolution. Furthermore, we find a small sub-network, specific to the “core” of the human interactome and involved in regulation of transcription and cancer development, whose wiring has not changed within the human interactome over the last 10 years of interacome data acquisition. Finally, we introduce a generalisation of the clustering coefficient of a network as a new measure called the cycle coefficient, and use it to show that PPI networks of human and model organisms are wired in a tight way which forbids the occurrence large cycles. PMID:24953453

Janji?, Vuk; Pržulj, Nataša

2014-01-01

57

Quantum Interactomics and Cancer Molecular Mechanisms: I. Report Outline  

E-print Network

Single cell interactomics in simpler organisms, as well as somatic cell interactomics in multicellular organisms, involve biomolecular interactions in complex signalling pathways that were recently represented in modular terms by quantum automata with ‘reversible behavior’ representing normal cell cycling and division. Other implications of such quantum automata, modular modeling of signaling pathways and cell differentiation during development are in the fields of neural plasticity and brain development leading to quantum-weave dynamic patterns and specific molecular processes underlying extensive memory, learning, anticipation mechanisms and the emergence of human consciousness during the early brain development in children. Cell interactomics is here represented for the first time as a mixture of ‘classical’ states that determine molecular dynamics subject to Boltzmann statistics and ‘steady-state’, metabolic (multi-stable) manifolds, together with ‘configuration’ spaces of metastable quant...

Baianu, I C

2004-01-01

58

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

PubMed

Marked spatiotemporal variabilities in mosquito infection of arboviruses require adaptive strategies for determining optimal field-sampling timeframes, pool screening, and data analyses. In particular, the error distribution and aggregation patterns of adult arboviral mosquitoes can vary significantly by species, which can statistically bias analyses of spatiotemporal-sampled predictor variables generating misinterpretation of prolific habitat surveillance locations. Currently, there is a lack of reliable and consistent measures of risk exposure based on field-sampled georeferenced explanatory covariates which can compromise quantitative predictions generated from arboviral mosquito surveillance models for implementing larval control strategies targeting productive habitats. In this research we used spatial statistics and QuickBird visible and near-infra-red data for determining trapping sites that were related to Culex quinquefasciatus and Aedes albopictus species abundance and distribution in Birmingham, Alabama. Initially, a Land Use Land Cover (LULC) model was constructed from multiple spatiotemporal-sampled georeferenced predictors and the QuickBird data. A Poisson regression model with a non-homogenous, gamma-distributed mean then decomposed the data into positive and negative spatial filter eigenvectors. An autoregressive process in the error term then was used to derive the sample distribution of the Moran's I statistic for determining latent autocorrelation components in the model. Spatial filter algorithms established means, variances, distributional functions, and pairwise correlations for the predictor variables. In doing so, the eigenfunction spatial filter quantified the residual autocorrelation error in the mean response term of the model as a linear combination of various distinct Cx. quinquefasciatus and Ae. albopictus habitat map patterns. The analyses revealed 18-27% redundant information in the data. Prolific habitats of Cx. quinquefasciatus and Ae. albopictus can be accurately spatially targeted based on georeferenced field-sampled count data using QuickBird data, LULC explanatory covariates, robust negative binomial regression estimates and space-time eigenfunctions. PMID:20969828

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

2011-02-01

59

Next-Generation Technologies for Multiomics Approaches Including Interactome Sequencing  

PubMed Central

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

Ohashi, Hiroyuki; Miyamoto-Sato, Etsuko

2015-01-01

60

Intrinsic Disorder in the BK Channel and Its Interactome  

PubMed Central

The large-conductance Ca2+-activated K+ (BK) channel is broadly expressed in various mammalian cells and tissues such as neurons, skeletal and smooth muscles, exocrine cells, and sensory cells of the inner ear. Previous studies suggest that BK channels are promiscuous binders involved in a multitude of protein-protein interactions. To gain a better understanding of the potential mechanisms underlying BK interactions, we analyzed the abundance, distribution, and potential mechanisms of intrinsic disorder in 27 BK channel variants from mouse cochlea, 104 previously reported BK-associated proteins (BKAPS) from cytoplasmic and membrane/cytoskeletal regions, plus BK ?- and ?-subunits. Disorder was evaluated using the MFDp algorithm, which is a consensus-based predictor that provides a strong and competitive predictive quality and PONDR, which can determine long intrinsically disordered regions (IDRs). Disorder-based binding sites or molecular recognition features (MoRFs) were found using MoRFpred and ANCHOR. BKAP functions were categorized based on Gene Ontology (GO) terms. The analyses revealed that the BK variants contain a number of IDRs. Intrinsic disorder is also common in BKAPs, of which ?5% are completely disordered. However, intrinsic disorder is very differently distributed within BK and its partners. Approximately 65% of the disordered segments in BK channels are long (IDRs) (>50 residues), whereas >60% of the disordered segments in BKAPs are short IDRs that range in length from 4 to 30 residues. Both ? and ? subunits showed various amounts of disorder as did hub proteins of the BK interactome. Our analyses suggest that intrinsic disorder is important for the function of BK and its BKAPs. Long IDRs in BK are engaged in protein-protein and protein-ligand interactions, contain multiple post-translational modification sites, and are subjected to alternative splicing. The disordered structure of BK and its BKAPs suggests one of the underlying mechanisms of their interaction. PMID:24727949

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

2014-01-01

61

CHARACTERIZATION OF THE ARABIDOPSIS THALIANA INTERACTOME TARGETED BY VIRUSES  

E-print Network

#12;! ! "! CHARACTERIZATION OF THE ARABIDOPSIS THALIANA INTERACTOME TARGETED BY VIRUSES Guillermo defenses in response to viruses has been a challenging problem owing to the multiplicity of factors viruses. In a first approach, we established lists of genes differentially affected by each virus

62

Exploring the protein interactome using comprehensive two-hybrid projects  

Microsoft Academic Search

Large-scale two-hybrid projects were used in an approach to examine protein–protein interactions. Despite the various limitations of this approach, these projects revealed a wealth of novel interactions, and the protein interactome may be much larger than expected.

Takashi Ito; Tomoko Chiba; Mikio Yoshida

2001-01-01

63

RESEARCH ARTICLE Open Access Curating the innate immunity interactome  

E-print Network

innate immunity interactome in rich contextual detail, and present our novel curation software system and discuss the challenges that face such curation efforts. Significantly, we provide several lines an appropriate response. Receptors of the innate immune response, known as pathogen recognition receptors (PRRs

Strynadka, Natalie

64

The Domain Landscape of Virus-Host Interactomes  

PubMed Central

Viral infections result in millions of deaths in the world today. A thorough analysis of virus-host interactomes may reveal insights into viral infection and pathogenic strategies. In this study, we presented a landscape of virus-host interactomes based on protein domain interaction. Compared to the analysis at protein level, this domain-domain interactome provided a unique abstraction of protein-protein interactome. Through comparisons among DNA, RNA, and retrotranscribing viruses, we identified a core of human domains, that viruses used to hijack the cellular machinery and evade the immune system, which might be promising antiviral drug targets. We showed that viruses preferentially interacted with host hub and bottleneck domains, and the degree and betweenness centrality among three categories of viruses are significantly different. Further analysis at functional level highlighted that different viruses perturbed the host cellular molecular network by common and unique strategies. Most importantly, we creatively proposed a viral disease network among viral domains, human domains and the corresponding diseases, which uncovered several unknown virus-disease relationships that needed further verification. Overall, it is expected that the findings will help to deeply understand the viral infection and contribute to the development of antiviral therapy. PMID:24991570

Zhou, Yanhong; Li, Yixue

2014-01-01

65

RESEARCH Open Access A human skeletal muscle interactome centered  

E-print Network

RESEARCH Open Access A human skeletal muscle interactome centered on proteins involved in muscular skeletal-muscle cDNA library to establish a proteome-scale map of protein-protein interactions centered , Marc Bartoli1,2 and Isabelle Richard1* Abstract Background: The complexity of the skeletal muscle

Paris-Sud XI, Université de

66

Identification of core T cell network based on immunome interactome  

PubMed Central

Background Data-driven studies on the dynamics of reconstructed protein-protein interaction (PPI) networks facilitate investigation and identification of proteins important for particular processes or diseases and reduces time and costs of experimental verification. Modeling the dynamics of very large PPI networks is computationally costly. Results To circumvent this problem, we created a link-weighted human immunome interactome and performed filtering. We reconstructed the immunome interactome and weighed the links using jackknife gene expression correlation of integrated, time course gene expression data. Statistical significance of the links was computed using the Global Statistical Significance (GloSS) filtering algorithm. P-values from GloSS were computed for the integrated, time course gene expression data. We filtered the immunome interactome to identify core components of the T cell PPI network (TPPIN). The interconnectedness of the major pathways for T cell survival and response, including the T cell receptor, MAPK and JAK-STAT pathways, are maintained in the TPPIN network. The obtained TPPIN network is supported both by Gene Ontology term enrichment analysis along with study of essential genes enrichment. Conclusions By integrating gene expression data to the immunome interactome and using a weighted network filtering method, we identified the T cell PPI immune response network. This network reveals the most central and crucial network in T cells. The approach is general and applicable to any dataset that contains sufficient information. PMID:24528953

2014-01-01

67

Evidence for network evolution in an arabidopsis interactome map  

Technology Transfer Automated Retrieval System (TEKTRAN)

Plants have unique features that evolved in response to their environments and ecosystems. A full account of the complex cellular networks that underlie plant-specific functions is still missing. We describe a proteome-wide binary protein-protein interaction map for the interactome network of the pl...

68

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

PubMed

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

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

2011-01-01

69

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

PubMed Central

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

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

2012-01-01

70

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

SciTech Connect

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.

Klopffleisch, Karsten [University of Cologne; Phan, Nguyen [University of North Carolina, Chapel Hill; Chen, Jay [ORNL; Panstruga, Ralph [Max-Planck Institute for Plant Breeding Research; Uhrig, Joachim [University of Cologne; Jones, Alan M [University of North Carolina, Chapel Hill

2011-01-01

71

SH3 interactome conserves general function over specific form  

PubMed Central

Src homology 3 (SH3) domains bind peptides to mediate protein–protein interactions that assemble and regulate dynamic biological processes. We surveyed the repertoire of SH3 binding specificity using peptide phage display in a metazoan, the worm Caenorhabditis elegans, and discovered that it structurally mirrors that of the budding yeast Saccharomyces cerevisiae. We then mapped the worm SH3 interactome using stringent yeast two-hybrid and compared it with the equivalent map for yeast. We found that the worm SH3 interactome resembles the analogous yeast network because it is significantly enriched for proteins with roles in endocytosis. Nevertheless, orthologous SH3 domain-mediated interactions are highly rewired. Our results suggest a model of network evolution where general function of the SH3 domain network is conserved over its specific form. PMID:23549480

Xin, Xiaofeng; Gfeller, David; Cheng, Jackie; Tonikian, Raffi; Sun, Lin; Guo, Ailan; Lopez, Lianet; Pavlenco, Alevtina; Akintobi, Adenrele; Zhang, Yingnan; Rual, Jean-François; Currell, Bridget; Seshagiri, Somasekar; Hao, Tong; Yang, Xinping; Shen, Yun A; Salehi-Ashtiani, Kourosh; Li, Jingjing; Cheng, Aaron T; Bouamalay, Dryden; Lugari, Adrien; Hill, David E; Grimes, Mark L; Drubin, David G; Grant, Barth D; Vidal, Marc; Boone, Charles; Sidhu, Sachdev S; Bader, Gary D

2013-01-01

72

A human skeletal muscle interactome centered on proteins involved in muscular dystrophies: LGMD interactome  

PubMed Central

Background The complexity of the skeletal muscle and the identification of numerous human disease-causing mutations in its constitutive proteins make it an interesting tissue for proteomic studies aimed at understanding functional relationships of interacting proteins in both health and diseases. Method We undertook a large-scale study using two-hybrid screens and a human skeletal-muscle cDNA library to establish a proteome-scale map of protein-protein interactions centered on proteins involved in limb-girdle muscular dystrophies (LGMD). LGMD is a group of more than 20 different neuromuscular disorders that principally affect the proximal pelvic and shoulder girdle muscles. Results and conclusion The interaction network we unraveled incorporates 1018 proteins connected by 1492 direct binary interactions and includes 1420 novel protein-protein interactions. Computational, experimental and literature-based analyses were performed to assess the overall quality of this network. Interestingly, LGMD proteins were shown to be highly interconnected, in particular indirectly through sarcomeric proteins. In-depth mining of the LGMD-centered interactome identified new candidate genes for orphan LGMDs and other neuromuscular disorders. The data also suggest the existence of functional links between LGMD2B/dysferlin and gene regulation, between LGMD2C/?-sarcoglycan and energy control and between LGMD2G/telethonin and maintenance of genome integrity. This dataset represents a valuable resource for future functional investigations. PMID:23414517

2013-01-01

73

Analysis of the interactome of ribosomal protein S19 mutants.  

PubMed

Diamond-Blackfan anemia, characterized by defective erythroid progenitor maturation, is caused in one-fourth of cases by mutations of ribosomal protein S19 (RPS19), which is a component of the ribosomal 40S subunit. Our previous work described proteins interacting with RPS19 with the aim to determine its functions. Here, two RPS19 mutants, R62W and R101H, have been selected to compare their interactomes versus the wild-type protein one, using the same functional proteomic approach that we employed to characterize RPS19 interactome. Mutations R62W and R101H impair RPS19 ability to associate with the ribosome. Results presented in this paper highlight the striking differences between the interactomes of wild-type and mutant RPS19 proteins. In particular, mutations abolish interactions with proteins having splicing, translational and helicase activity, thus confirming the role of RPS19 in RNA processing/metabolism and translational control. The data have been deposited to the ProteomeXchange with identifier PXD000640 (http://proteomecentral.proteomexchange.org/dataset/PXD000640). PMID:25069755

Caterino, Marianna; Aspesi, Anna; Pavesi, Elisa; Imperlini, Esther; Pagnozzi, Daniela; Ingenito, Laura; Santoro, Claudio; Dianzani, Irma; Ruoppolo, Margherita

2014-10-01

74

Charting the NF-?B pathway interactome map.  

PubMed

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

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

2012-01-01

75

Charting the NF-?B Pathway Interactome Map  

PubMed Central

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

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

2012-01-01

76

Edinburgh Research Explorer The SARS-Coronavirus-Host Interactome: Identification of  

E-print Network

Edinburgh Research Explorer The SARS-Coronavirus-Host Interactome: Identification of Cyclophilins as Target for Pan-Coronavirus Inhibitors Citation for published version: Pfefferle, S, Schoepf, J, Koegl, M Brunn, A 2011, 'The SARS-Coronavirus-Host Interactome: Identification of Cyclophilins as Target for Pan-Coronavirus

Millar, Andrew J.

77

Labeling network motifs in protein interactomes for protein function prediction  

Microsoft Academic Search

Biological networks such as the protein-protein interaction (PPI) network have been found to contain small recurring subnetworks in significantly higher frequencies than in random networks. Such network motifs are useful for uncovering structural design principles of complex biological networks. However, current network motif finding algorithms models the PPI network as a uni-labeled graph, discovering only unlabeled and thus relatively uninforma-tive

Jin Chen; Wynne Hsu; Mong-li Lee; Ng See-kiong

2007-01-01

78

Prediction of the Spatio-Temporal Extent of Groundwater Flooding in Chalk Catchments using Lumped Parameter Models  

NASA Astrophysics Data System (ADS)

In winter 2000-01 extreme rainfall resulted in anomalously high groundwater levels and groundwater flooding in many Chalk catchments of southern England and northern France. Groundwater flooding occurred in areas where it had not been recently observed and in places lasted for six months. In many of these catchments the prediction of future groundwater flood events is hindered by the lack of an appropriate predictive tool, such as a distributed groundwater model, or the inability of distributed numerical models to simulate extremes adequately. A relatively low-cost and rapidly applicable methodology for the prediction of the location and timing of groundwater flooding in Chalk catchments is developed. This involves the simulation and prediction of a subset of groundwater hydrographs using a simple lumped parameter groundwater model and the transposition of these models to observed hydrographs at other locations using quantile mapping. Time-variant groundwater level surfaces, generated using the discrete set of lumped parameter models and river elevation data, are overlain on a digital terrain model to predict the spatial extent of groundwater flooding. The number of lumped parameter models required is minimised through the classification and grouping of groundwater level time-series using principal component and cluster analysis. The approach is validated against groundwater flood extent data obtained from aerial surveys and field mapping.

Fulton, K.; Hughes, A.; Jackson, C. R.; Peach, D.; Vounaki, T.

2009-12-01

79

The cell-cycle interactome: a source of growth regulators?  

PubMed

When plants develop, cell proliferation and cell expansion are tightly controlled in order to generate organs with a determinate final size such as leaves. Several studies have demonstrated the importance of the cell proliferation phase for leaf growth, illustrating that cell-cycle regulation is crucial for correct leaf development. A large and complex set of interacting proteins that constitute the cell-cycle interactome controls the transition from one cell-cycle phase to another. Here, we review the current knowledge on cell-cycle regulators from this interactome affecting final leaf size when their expression is altered, mainly in Arabidopsis. In addition to the description of mutants of CYCLIN-DEPENDENT KINASES (CDKs), CYCLINS (CYCs), and their transcriptional and post-translational regulators, a phenotypic analysis of gain- and loss-of-function mutants for 27 genes encoding proteins that interact with cell-cycle proteins is presented. This compilation of information shows that when cell-cycle-related genes are mis-expressed, leaf growth is often altered and that, seemingly, three main trends appear to be crucial in the regulation of final organ size by cell-cycle-related genes: (i) cellular compensation; (ii) gene dosage; and (iii) correct transition through the G2/M phase by ANAPHASE PROMOTING COMPLEX/CYCLOSOME (APC/C) activation. In conclusion, this meta-analysis shows that the cell-cycle interactome is enriched in leaf growth regulators, and illustrates the potential to identify new leaf growth regulators among putative new cell-cycle regulators. PMID:24298000

Blomme, Jonas; Inzé, Dirk; Gonzalez, Nathalie

2014-06-01

80

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

NASA Astrophysics Data System (ADS)

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.

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

2013-04-01

81

Summer Rains and Dry Seasons in the Upper Blue Nile Basin: The Predictability of Half a Century of Past and Future Spatiotemporal Patterns  

PubMed Central

During the last 100 years the Ethiopian upper Blue Nile Basin (BNB) has undergone major changes in land use, and is now potentially facing changes in climate. Rainfall over BNB supplies over two-thirds of the water to the Nile and supports a large local population living mainly on subsistence agriculture. Regional food security is sensitive to both the amount and timing of rain and is already an important political challenge that will be further complicated if scenarios of climate change are realized. In this study a simple spatial model of the timing and duration of summer rains (Kiremt) and dry season (Bega), and annual rain over the upper BNB was established from observed data between 1952 and 2004. The model was used to explore potential impacts of climate change on these rains, using a down-scaled ECHAM5/MP1-OM scenario between 2050 and 2100. Over the observed period the amount, onset and duration of Kiremt rains and rain-free Bega days have exhibited a consistent spatial pattern. The spatially averaged annual rainfall was 1490 mm of which 93% was Kiremt rain. The average Kiremt rain and number of rainy days was higher in the southwest (322 days) and decreased towards the north (136 days). Under the 2050–2100 scenario, the annual mean rainfall is predicted to increase by 6% and maintain the same spatial pattern as in the past. A larger change in annual rainfall is expected in the southwest (ca. +130 mm) with a gradually smaller change towards the north (ca. +70 mm). Results highlight the need to account for the characteristic spatiotemporal zonation when planning water management and climate adaptation within the upper BNB. The presented simple spatial resolved models of the presence of Kiremt and annual total rainfall could be used as a baseline for such long-term planning. PMID:23869219

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

2013-01-01

82

STPMiner: A Highperformance Spatiotemporal Pattern Mining Toolbox  

SciTech Connect

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.

Vatsavai, Raju [ORNL] [ORNL

2011-01-01

83

A Human XPC Protein Interactome—A Resource  

PubMed Central

Global genome nucleotide excision repair (GG-NER) is responsible for identifying and removing bulky adducts from non-transcribed DNA that result from damaging agents such as UV radiation and cisplatin. Xeroderma pigmentosum complementation group C (XPC) is one of the essential damage recognition proteins of the GG-NER pathway and its dysfunction results in xeroderma pigmentosum (XP), a disorder involving photosensitivity and a predisposition to cancer. To better understand the identification of DNA damage by XPC in the context of chromatin and the role of XPC in the pathogenesis of XP, we characterized the interactome of XPC using a high throughput yeast two-hybrid screening. Our screening showed 49 novel interactors of XPC involved in DNA repair and replication, proteolysis and post-translational modifications, transcription regulation, signal transduction, and metabolism. Importantly, we validated the XPC-OTUD4 interaction by co-IP and provided evidence that OTUD4 knockdown in human cells indeed affects the levels of ubiquitinated XPC, supporting a hypothesis that the OTUD4 deubiquitinase is involved in XPC recycling by cleaving the ubiquitin moiety. This high-throughput characterization of the XPC interactome provides a resource for future exploration and suggests that XPC may have many uncharacterized cellular functions. PMID:24366067

Lubin, Abigail; Zhang, Ling; Chen, Hua; White, Victoria M.; Gong, Feng

2014-01-01

84

Dissecting noncoding and pathogen RNA–protein interactomes  

PubMed Central

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

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

85

Dissecting noncoding and pathogen RNA-protein interactomes.  

PubMed

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

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

86

Extraction de connaissances pour la modélisation tri-dimensionnelle de l'interactome structural.  

E-print Network

??L'étude structurale de l'interactome cellulaire peut conduire à des découvertes intéressantes sur les bases moléculaires de certaines pathologies. La modélisation par homologie et l'amarrage de… (more)

Ghoorah, Anisah W.

2012-01-01

87

Characterization and Interactome Study of White Spot Syndrome Virus Envelope Protein VP11  

PubMed Central

White spot syndrome virus (WSSV) is a large enveloped virus. The WSSV viral particle consists of three structural layers that surround its core DNA: an outer envelope, a tegument and a nucleocapsid. Here we characterize the WSSV structural protein VP11 (WSSV394, GenBank accession number AF440570), and use an interactome approach to analyze the possible associations between this protein and an array of other WSSV and host proteins. Temporal transcription analysis showed that vp11 is an early gene. Western blot hybridization of the intact viral particles and fractionation of the viral components, and immunoelectron microscopy showed that VP11 is an envelope protein. Membrane topology software predicted VP11 to be a type of transmembrane protein with a highly hydrophobic transmembrane domain at its N-terminal. Based on an immunofluorescence assay performed on VP11-transfected Sf9 cells and a trypsin digestion analysis of the virion, we conclude that, contrary to topology software prediction, the C-terminal of this protein is in fact inside the virion. Yeast two-hybrid screening combined with co-immunoprecipitation assays found that VP11 directly interacted with at least 12 other WSSV structural proteins as well as itself. An oligomerization assay further showed that VP11 could form dimers. VP11 is also the first reported WSSV structural protein to interact with the major nucleocapsid protein VP664. PMID:24465701

Liu, Wang-Jing; Shiung, Hui-Jui; Lo, Chu-Fang; Leu, Jiann-Horng; Lai, Ying-Jang; Lee, Tai-Lin; Huang, Wei-Tung; Kou, Guang-Hsiung; Chang, Yun-Shiang

2014-01-01

88

In vitro nuclear interactome of the HIV-1 Tat protein  

PubMed Central

Background One facet of the complexity underlying the biology of HIV-1 resides not only in its limited number of viral proteins, but in the extensive repertoire of cellular proteins they interact with and their higher-order assembly. HIV-1 encodes the regulatory protein Tat (86–101aa), which is essential for HIV-1 replication and primarily orchestrates HIV-1 provirus transcriptional regulation. Previous studies have demonstrated that Tat function is highly dependent on specific interactions with a range of cellular proteins. However they can only partially account for the intricate molecular mechanisms underlying the dynamics of proviral gene expression. To obtain a comprehensive nuclear interaction map of Tat in T-cells, we have designed a proteomic strategy based on affinity chromatography coupled with mass spectrometry. Results Our approach resulted in the identification of a total of 183 candidates as Tat nuclear partners, 90% of which have not been previously characterised. Subsequently we applied in silico analysis, to validate and characterise our dataset which revealed that the Tat nuclear interactome exhibits unique signature(s). First, motif composition analysis highlighted that our dataset is enriched for domains mediating protein, RNA and DNA interactions, and helicase and ATPase activities. Secondly, functional classification and network reconstruction clearly depicted Tat as a polyvalent protein adaptor and positioned Tat at the nexus of a densely interconnected interaction network involved in a range of biological processes which included gene expression regulation, RNA biogenesis, chromatin structure, chromosome organisation, DNA replication and nuclear architecture. Conclusion We have completed the in vitro Tat nuclear interactome and have highlighted its modular network properties and particularly those involved in the coordination of gene expression by Tat. Ultimately, the highly specialised set of molecular interactions identified will provide a framework to further advance our understanding of the mechanisms of HIV-1 proviral gene silencing and activation. PMID:19454010

Gautier, Virginie W; Gu, Lili; O'Donoghue, Niaobh; Pennington, Stephen; Sheehy, Noreen; Hall, William W

2009-01-01

89

Tools and strategies for DNA damage interactome analysis.  

PubMed

DNA is the target of multiple endogenous and exogenous agents generating chemical lesions on the double helix. Cellular DNA damage response pathways rely on a myriad of proteins interacting with DNA alterations. The cartography of this interactome currently includes well known actors of chromatin remodelling, DNA repair or proteins hijacked from their natural functions such as transcription factors. In order to go further into the characterisation of these protein networks, proteomics-based methods began to be used in the early 2000s. The strategies are diverse and include mainly (i) damaged DNA molecules used as targets on protein microarrays, (ii) damaged DNA probes used to trap within complex cellular extracts proteins that are then separated and identified by proteomics, (iii) identification of chromatin- bound proteins after a genotoxic stress, or (iv) identification of proteins associated with other proteins already known to be part of DNA damage interactome. All these approaches have already been performed to find new proteins recognizing oxidised bases, abasic sites, strand breaks or crosslinks generated by anticancer drugs such as nitrogen mustards and platinating agents. Identified interactions are generally confirmed using complementary methods such as electromobility shift assays or surface plasmon resonance. These strategies allowed, for example, demonstration of interactions between cisplatin-DNA crosslinks and PARP-1 or the protein complex PTW/PP. The next challenging step will be to understand the biological repercussions of these newly identified interactions which may help to unravel new mechanisms involved in genetic toxicology, discover new cellular responses to anticancer drugs or identify new biomarkers and therapeutic targets. PMID:23220222

Bounaix Morand du Puch, Christophe; Barbier, Ewa; Sauvaigo, Sylvie; Gasparutto, Didier; Breton, Jean

2013-01-01

90

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

PubMed

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

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

2014-01-01

91

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

PubMed

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

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

2015-02-01

92

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

PubMed Central

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

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

2015-01-01

93

Physical and in silico approaches identify DNA-PK in a Tax DNA-damage response interactome  

Microsoft Academic Search

BACKGROUND: We have initiated an effort to exhaustively map interactions between HTLV-1 Tax and host cellular proteins. The resulting Tax interactome will have significant utility toward defining new and understanding known activities of this important viral protein. In addition, the completion of a full Tax interactome will also help shed light upon the functional consequences of these myriad Tax activities.

Emad Ramadan; Michael Ward; Xin Guo; Sarah S Durkin; Adam Sawyer; Marcelo Vilela; Christopher Osgood; Alex Pothen; Oliver J Semmes

2008-01-01

94

Oncogenic nature of a novel mutant AATF and its interactome existing within human cancer cells.  

PubMed

Since apoptosis presents a natural defense in cancer development, the anti-apoptotic factor AATF/Che-1 has emerged as a crucial 'Epigenomic-Switch'. We have tried to understand the double-edged nature of AATF, showing for the first time the conspicuous existence of an aberrant AATF/Che-1 transcriptome encoding for 23?kDa mutant AATF protein, which evolves its unique interactome within human cancer cells derived from different tissue origins. This mutant AATF along with its interactome consisting of SP1, DNMT3B and Par-4 ensures cancer cell DNA methylation required for down-regulation of tumor suppressor genes. Hence, the proposed mutant AATF interactome-based pathway can have the inherent ability to ensure human cells become and remain cancerous. PMID:25231211

Sharma, Shaveta; Kaul, Deepak; Arora, Mansi; Malik, Deepti

2015-03-01

95

Examining the Interactome of Huperzine A by Magnetic Biopanning  

PubMed Central

Huperzine A is a bioactive compound derived from traditional Chinese medicine plant Qian Ceng Ta (Huperzia serrata), and was found to have multiple neuroprotective effects. In addition to being a potent acetylcholinesterase inhibitor, it was thought to act through other mechanisms such as antioxidation, antiapoptosis, etc. However, the molecular targets involved with these mechanisms were not identified. In this study, we attempted to exam the interactome of Huperzine A using a cDNA phage display library and also mammalian brain tissue extracts. The drugs were chemically linked on the surface of magnetic particles and the interactive phages or proteins were collected and analyzed. Among the various cDNA expressing phages selected, one was identified to encode the mitochondria NADH dehydrogenase subunit 1. Specific bindings between the drug and the target phages and target proteins were confirmed. Another enriched phage clone was identified as mitochondria ATP synthase, which was also panned out from the proteome of mouse brain tissue lysate. These data indicated the possible involvement of mitochondrial respiratory chain matrix enzymes in Huperzine A's pharmacological effects. Such involvement had been suggested by previous studies based on enzyme activity changes. Our data supported the new mechanism. Overall we demonstrated the feasibility of using magnetic biopanning as a simple and viable method for investigating the complex molecular mechanisms of bioactive molecules. PMID:22615909

Guo, Wei; Liu, Shupeng; Peng, Jinliang; Wei, Xiaohui; Sun, Ye; Qiu, Yangsheng; Gao, Guangwei; Wang, Peng; Xu, Yuhong

2012-01-01

96

CTCF-Mediated Functional Chromatin Interactome in Pluripotent Cells  

PubMed Central

Mammalian genomes are viewed as functional organizations that orchestrate spatial and temporal gene regulation. CTCF, the most characterized insulator-binding protein, has been implicated as a key genome organizer. Yet, little is known about CTCF-associated higher order chromatin structures at a global scale. Here, we applied Chromatin Interaction Analysis by Paired-End-Tag sequencing to elucidate the CTCF-chromatin interactome in pluripotent cells. From this analysis, 1,480 cis and 336 trans interacting loci were identified with high reproducibility and precision. Associating these chromatin interaction loci with their underlying epigenetic states, promoter activities, enhancer binding and nuclear lamina occupancy, we uncovered five distinct chromatin domains that suggest potential new models of CTCF function in chromatin organization and transcriptional control. Specifically, CTCF interactions demarcate chromatin-nuclear membrane attachments and influence proper gene expression through extensive crosstalk between promoters and regulatory elements. This highly complex nuclear organization offers insights towards the unifying principles governing genome plasticity and function. PMID:21685913

Handoko, Lusy; Xu, Han; Li, Guoliang; Ngan, Chew Yee; Chew, Elaine; Schnapp, Marie; Lee, Charlie Wah Heng; Ye, Chaopeng; Ping, Joanne Lim Hui; Mulawadi, Fabianus; Wong, Eleanor; Sheng, Jianpeng; Zhang, Yubo; Poh, Thompson; Chan, Chee Seng; Kunarso, Galih; Shahab, Atif; Bourque, Guillaume; Cacheux-Rataboul, Valere; Sung, Wing-Kin; Ruan, Yijun; Wei, Chia-Lin

2011-01-01

97

Interactome Analysis Reveals Ezrin Can Adopt Multiple Conformational States*  

PubMed Central

Ezrin, a member of the ezrin-radixin-moesin family (ERM), is an essential regulator of the structure of microvilli on the apical aspect of epithelial cells. Ezrin provides a linkage between membrane-associated proteins and F-actin, oscillating between active/open and inactive/closed states, and is regulated in part by phosphorylation of a C-terminal threonine. In the open state, ezrin can bind a number of ligands, but in the closed state the ligand-binding sites are inaccessible. In vitro analysis has proposed that there may be a third hyperactivated form of ezrin. To gain a better understanding of ezrin, we conducted an unbiased proteomic analysis of ezrin-binding proteins in an epithelial cell line, Jeg-3. We refined our list of interactors by comparing the interactomes using quantitative mass spectrometry between wild-type ezrin, closed ezrin, open ezrin, and hyperactivated ezrin. The analysis reveals several novel interactors confirmed by their localization to microvilli, as well as a significant class of proteins that bind closed ezrin. Taken together, the data indicate that ezrin can exist in three different conformational states, and different ligands “perceive” ezrin conformational states differently. PMID:24151071

Viswanatha, Raghuvir; Wayt, Jessica; Ohouo, Patrice Y.; Smolka, Marcus B.; Bretscher, Anthony

2013-01-01

98

Neurodevelopmental disorders: mechanisms and boundary definitions from genomes, interactomes and proteomes  

PubMed Central

Neurodevelopmental disorders such as intellectual disability, autism spectrum disorder and schizophrenia lack precise boundaries in their clinical definitions, epidemiology, genetics and protein–protein interactomes. This calls into question the appropriateness of current categorical disease concepts. Recently, there has been a rising tide to reformulate neurodevelopmental nosological entities from biology upward. To facilitate this developing trend, we propose that identification of unique proteomic signatures that can be strongly associated with patient's risk alleles and proteome-interactome-guided exploration of patient genomes could define biological mechanisms necessary to reformulate disorder definitions. PMID:24301647

Mullin, A P; Gokhale, A; Moreno-De-Luca, A; Sanyal, S; Waddington, J L; Faundez, V

2013-01-01

99

Spatio-temporal clustering  

NASA Astrophysics Data System (ADS)

Spatio-temporal clustering is a process of grouping objects based on their spatial and temporal similarity. It is relatively new subfield of data mining which gained high popularity especially in geographic information sciences due to the pervasiveness of all kinds of location-based or environmental devices that record position, time or/and environmental properties of an object or set of objects in real-time. As a consequence, different types and large amounts of spatio-temporal data became available that introduce new challenges to data analysis and require novel approaches to knowledge discovery. In this chapter we concentrate on the spatio-temporal clustering in geographic space. First, we provide a classification of different types of spatio-temporal data. Then, we focus on one type of spatio-temporal clustering - trajectory clustering, provide an overview of the state-of-the-art approaches and methods of spatio-temporal clustering and finally present several scenarios in different application domains such as movement, cellular networks and environmental studies.

Kisilevich, Slava; Mansmann, Florian; Nanni, Mirco; Rinzivillo, Salvatore

100

Interactome mapping suggests new mechanistic details underlying Alzheimer's disease  

PubMed Central

Recent advances toward the characterization of Alzheimer's disease (AD) have permitted the identification of a dozen of genetic risk factors, although many more remain undiscovered. In parallel, works in the field of network biology have shown a strong link between protein connectivity and disease. In this manuscript, we demonstrate that AD-related genes are indeed highly interconnected and, based on this observation, we set up an interaction discovery strategy to unveil novel AD causative and susceptibility genes. In total, we report 200 high-confidence protein–protein interactions between eight confirmed AD-related genes and 66 candidates. Of these, 31 are located in chromosomal regions containing susceptibility loci related to the etiology of late-onset AD, and 17 show dysregulated expression patterns in AD patients, which makes them very good candidates for further functional studies. Interestingly, we also identified four novel direct interactions among well-characterized AD causative/susceptibility genes (i.e., APP, A2M, APOE, PSEN1, and PSEN2), which support the suggested link between plaque formation and inflammatory processes and provide insights into the intracellular regulation of APP cleavage. Finally, we contextualize the discovered relationships, integrating them with all the interaction data reported in the literature, building the most complete interactome associated to AD. This general view facilitates the analyses of global properties of the network, such as its functional modularity, and triggers many hypotheses on the molecular mechanisms implicated in AD. For instance, our analyses suggest a putative role for PDCD4 as a neuronal death regulator and ECSIT as a molecular link between oxidative stress, inflammation, and mitochondrial dysfunction in AD. PMID:21163940

Soler-López, Montserrat; Zanzoni, Andreas; Lluís, Ricart; Stelzl, Ulrich; Aloy, Patrick

2011-01-01

101

RESEARCH Open Access Host-pathogen interactome mapping for HTLV-1  

E-print Network

RESEARCH Open Access Host-pathogen interactome mapping for HTLV-1 and -2 retroviruses Nicolas virus type 1 (HTLV-1) and type 2 both target T lymphocytes, yet induce radically different phenotypic outcomes. HTLV-1 is a causative agent of Adult T-cell leukemia (ATL), whereas HTLV-2, highly similar

Paris-Sud XI, Université de

102

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

PubMed

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

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

2013-05-21

103

The role of the interactome in the maintenance of deleterious variability in human populations  

PubMed Central

Recent genomic projects have revealed the existence of an unexpectedly large amount of deleterious variability in the human genome. Several hypotheses have been proposed to explain such an apparently high mutational load. However, the mechanisms by which deleterious mutations in some genes cause a pathological effect but are apparently innocuous in other genes remain largely unknown. This study searched for deleterious variants in the 1,000 genomes populations, as well as in a newly sequenced population of 252 healthy Spanish individuals. In addition, variants causative of monogenic diseases and somatic variants from 41 chronic lymphocytic leukaemia patients were analysed. The deleterious variants found were analysed in the context of the interactome to understand the role of network topology in the maintenance of the observed mutational load. Our results suggest that one of the mechanisms whereby the effect of these deleterious variants on the phenotype is suppressed could be related to the configuration of the protein interaction network. Most of the deleterious variants observed in healthy individuals are concentrated in peripheral regions of the interactome, in combinations that preserve their connectivity, and have a marginal effect on interactome integrity. On the contrary, likely pathogenic cancer somatic deleterious variants tend to occur in internal regions of the interactome, often with associated structural consequences. Finally, variants causative of monogenic diseases seem to occupy an intermediate position. Our observations suggest that the real pathological potential of a variant might be more a systems property rather than an intrinsic property of individual proteins. PMID:25261458

Garcia-Alonso, Luz; Jiménez-Almazán, Jorge; Carbonell-Caballero, Jose; Vela-Boza, Alicia; Santoyo-López, Javier; Antiñolo, Guillermo; Dopazo, Joaquin

2014-01-01

104

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

NASA Astrophysics Data System (ADS)

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.

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

2015-01-01

105

The Symbiosis Interactome: a computational approach reveals novel components, functional interactions and modules in Sinorhizobium meliloti  

Microsoft Academic Search

BACKGROUND: Rhizobium-Legume symbiosis is an attractive biological process that has been studied for decades because of its importance in agriculture. However, this system has undergone extensive study and although many of the major factors underpinning the process have been discovered using traditional methods, much remains to be discovered. RESULTS: Here we present an analysis of the 'Symbiosis Interactome' using novel

Ignacio Rodriguez-Llorente; Miguel A Caviedes; Mohammed Dary; Antonio J Palomares; Francisco M Cánovas; José M Peregrín-Alvarez

2009-01-01

106

Improved Microarray-Based Decision Support with Graph Encoded Interactome Data  

Microsoft Academic Search

In the past, microarray studies have been criticized due to noise and the limited overlap between gene signatures. Prior biological knowledge should therefore be incorporated as side information in models based on gene expression data to improve the accuracy of diagnosis and prognosis in cancer. As prior knowledge, we investigated interaction and pathway information from the human interactome on different

Anneleen Daemen; Marco Signoretto; Olivier Gevaert; Johan A. K. Suykens; Bart de Moor; I. King Jordan

2010-01-01

107

Next challenges in protein–protein docking: from proteome to interactome and beyond  

Microsoft Academic Search

Advances in biophysics and biochemistry have pushed back the limits for the structural characterization of biomolecular assemblies. Large efforts have been devoted to increase both resolution and accuracy of the methods, probe into the smallest biomolecules as well as the largest macromolecular machineries, unveil transient complexes along with dynamic interaction processes, and, lately, dissect whole organism interactomes using high-throughput strategies.

A. S. J. Melquiond; E. Karaca; P. Kastritis; A. M. J. J. Bonvin

2012-01-01

108

A highly efficient approach to protein interactome mapping based on collaborative filtering framework.  

PubMed

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

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

2015-01-01

109

Interactomics profiling of the negative regulatory function of carbon monoxide on RANKL-treated RAW 264.7 cells during osteoclastogenesis  

PubMed Central

Background During osteoclastogenesis, the maturation of osteoclast (OC) progenitors is stimulated by the receptor activator of nuclear factor-?B ligand (RANKL). Excess OC production plays a critical role in the pathogenesis of inflammatory bone disorders. Conversely, the inhibition of abnormal OC proliferation reduces inflammation-induced bone loss. Low concentrations of carbon monoxide (CO) are known to decrease inflammation and OC-mediated bone erosion but the molecular mechanism is unknown. Results To obtain insight into the biological function of CO, cultured RANKL-treated RAW 264.7 cells were used in an in vitro experimental model of osteoclastogenesis. The results showed that CO inhibited: 1) tartrate-resistant acid phosphatase (TRAP)-positive cell formation; 2) F-actin ring production; 3) c-fos pathway activation; 4) the expression of cathepsin K, TRAP, calcitonin receptor, and matrix metalloproteinase-9 mRNAs; 5) the expression of nuclear factor of activated T cells, cytoplasmic, calcineurin-dependent 1 in translation. Protein-protein interaction analysis predicted mitogen-activated protein kinase kinase kinase 4 as the controlling hub. Conclusions Low-concentrations of CO (250 ppm) may inhibit osteoclastogenesis. Data from STRING- and IPA-based interactome analyses suggested that the expression of proteins with the functions of signal transduction, enzymes, and epigenetic regulation are significantly altered by CO during RANKL-induced osteoclastogenesis. Our study provides the first interactome analysis of osteoclastogenesis, the results of which supported the negative regulation of OC differentiation by CO. PMID:24886323

2014-01-01

110

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

PubMed Central

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

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

111

Integrating the interactome and the transcriptome of Drosophila  

PubMed Central

Background Networks of interacting genes and gene products mediate most cellular and developmental processes. High throughput screening methods combined with literature curation are identifying many of the protein-protein interactions (PPI) and protein-DNA interactions (PDI) that constitute these networks. Most of the detection methods, however, fail to identify the in vivo spatial or temporal context of the interactions. Thus, the interaction data are a composite of the individual networks that may operate in specific tissues or developmental stages. Genome-wide expression data may be useful for filtering interaction data to identify the subnetworks that operate in specific spatial or temporal contexts. Here we take advantage of the extensive interaction and expression data available for Drosophila to analyze how interaction networks may be unique to specific tissues and developmental stages. Results We ranked genes on a scale from ubiquitously expressed to tissue or stage specific and examined their interaction patterns. Interestingly, ubiquitously expressed genes have many more interactions among themselves than do non-ubiquitously expressed genes both in PPI and PDI networks. While the PDI network is enriched for interactions between tissue-specific transcription factors and their tissue-specific targets, a preponderance of the PDI interactions are between ubiquitous and non-ubiquitously expressed genes and proteins. In contrast to PDI, PPI networks are depleted for interactions among tissue- or stage- specific proteins, which instead interact primarily with widely expressed proteins. In light of these findings, we present an approach to filter interaction data based on gene expression levels normalized across tissues or developmental stages. We show that this filter (the percent maximum or pmax filter) can be used to identify subnetworks that function within individual tissues or developmental stages. Conclusions These observations suggest that protein networks are frequently organized into hubs of widely expressed proteins to which are attached various tissue- or stage-specific proteins. This is consistent with earlier analyses of human PPI data and suggests a similar organization of interaction networks across species. This organization implies that tissue or stage specific networks can be best identified from interactome data by using filters designed to include both ubiquitously expressed and specifically expressed genes and proteins. PMID:24913703

2014-01-01

112

Imaging collagen type I fibrillogenesis with high spatiotemporal resolution.  

PubMed

Fibrillar collagens, such as collagen type I, belong to the most abundant extracellular matrix proteins and they have received much attention over the last five decades due to their large interactome, complex hierarchical structure and high mechanical stability. Nevertheless, the collagen self-assembly process is still incompletely understood. Determining the real-time kinetics of collagen type I formation is therefore pivotal for better understanding of collagen type I structure and function, but visualising the dynamic self-assembly process of collagen I on the molecular scale requires imaging techniques offering high spatiotemporal resolution. Fast and high-speed scanning atomic force microscopes (AFM) provide the means to study such processes on the timescale of seconds under near-physiological conditions. In this study we have applied fast AFM tip scanning to study the assembly kinetics of fibrillar collagen type I nanomatrices with a temporal resolution reaching eightseconds for a frame size of 500nm. By modifying the buffer composition and pH value, the kinetics of collagen fibrillogenesis can be adjusted for optimal analysis by fast AFM scanning. We furthermore show that amplitude-modulation imaging can be successfully applied to extract additional structural information from collagen samples even at high scan rates. Fast AFM scanning with controlled amplitude modulation therefore provides a versatile platform for studying dynamic collagen self-assembly processes at high resolution. PMID:25486377

Stamov, Dimitar R; Stock, Erik; Franz, Clemens M; Jähnke, Torsten; Haschke, Heiko

2015-02-01

113

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

PubMed

The development of models that provide accurate spatio-temporal predictions of ambient air pollution at small spatial scales is of great importance for the assessment of potential health effects of air pollution. Here we present a spatio-temporal framework that predicts ambient air pollution by combining data from several different monitoring networks and deterministic air pollution model(s) with geographic information system (GIS) covariates. The model presented in this paper has been implemented in an R package, SpatioTemporal, available on CRAN. The model is used by the EPA funded Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) to produce estimates of ambient air pollution; MESA Air uses the estimates to investigate the relationship between chronic exposure to air pollution and cardiovascular disease. In this paper we use the model to predict long-term average concentrations of NOx in the Los Angeles area during a ten year period. Predictions are based on measurements from the EPA Air Quality System, MESA Air specific monitoring, and output from a source dispersion model for traffic related air pollution (Caline3QHCR). Accuracy in predicting long-term average concentrations is evaluated using an elaborate cross-validation setup that accounts for a sparse spatio-temporal sampling pattern in the data, and adjusts for temporal effects. The predictive ability of the model is good with cross-validated R (2) of approximately 0.7 at subject sites. Replacing four geographic covariate indicators of traffic density with the Caline3QHCR dispersion model output resulted in very similar prediction accuracy from a more parsimonious and more interpretable model. Adding traffic-related geographic covariates to the model that included Caline3QHCR did not further improve the prediction accuracy. PMID:25264424

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

2014-09-01

114

Spatio-temporal variability in Ebro river basin (NE Spain): Global SST as potential source of predictability on decadal time scales  

NASA Astrophysics Data System (ADS)

SummaryThis paper investigates the spatial and temporal variability of streamflow in the Ebro river basin and its potential predictability. Principal Component Analysis applied to monthly streamflow series from 83 gauging stations distributed through the basin, reveals three homogeneous regions: Basque-Cantabrian, Pyrenees and Southern Mediterranean. Attending to this classification the main characteristic time scales of the maximum monthly streamflows are studied by Singular Spectral Analysis (SSA). Decadal variations in streamflow make particularly large contributions to year-to-year streamflow variance in stations placed in the Basque-Cantabrian and Southern Mediterranean regions, while for the Pyrenees flows the interannual contribution is more important. The predictability of the Ebro flow anomalies has been investigated using a combined methodology: at decadal time scales SST anomalies from several regions provide a significant source of predictability for the Ebro flow, while at interannual time scales autoregressive-moving-average modelling, applied to the time series previously filtered by SSA, is able to provide potential skill in forecasting. For gauging stations associated to the Basque-Cantabrian region significant correlations between the maximum monthly streamflow anomalies and a tripole-like pattern in the North Atlantic SSTs during the previous spring are found. This association is found maximum and stable for the tropical part of the pattern (approximately 0-20°N). For the gauging stations placed to the southeast of basin some influence from the Pacific Decadal Oscillation (PDO) is found. This method allows evaluating, independently, the decadal and interannual predictability of the streamflow series. In addition, the combination of both modelling techniques gives as result a methodology that has the capacity to provide basin-specific hydroclimatic predictions which vary (for the 1990-2003 validation period) between 62% for the Basque-Cantabrian region, 76% for the Southern Mediterranean and 81% for the Pyrenees. In summary, this work shows the existence of a valuable decadal and interannual predictability of the Ebro streamflow, a result which may be useful to water resources management.

Gámiz-Fortis, S. R.; Hidalgo-Muñoz, J. M.; Argüeso, D.; Esteban-Parra, M. J.; Castro-Díez, Y.

2011-11-01

115

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

PubMed Central

Omics technologies emerged as complementary strategies to genomics in the attempt to understand human illnesses. In general, proteomics technologies emerged earlier than those of metabolomics for major depressive disorder (MDD) research, but both are driven by the identification of proteins and/or metabolites that can delineate a comprehensive characterization of MDD's molecular mechanisms, as well as lead to the identification of biomarker candidates of all types—prognosis, diagnosis, treatment, and patient stratification. Also, one can explore protein and metabolite interactomes in order to pinpoint additional molecules associated with the disease that had not been picked up initially. Here, results and methodological aspects of MDD research using proteomics, metabolomics, and protein interactomics are reviewed, focusing on human samples. PMID:24733971

Martins-de-Souza, Daniel

2014-01-01

116

Roles for the Two-hybrid System in Exploration of the Yeast Protein Interactome  

Microsoft Academic Search

Comprehensive analysis of protein-protein interactions is a challenging endeavor of functional proteomics and has been best explored in the budding yeast. The yeast pro- tein interactome analysis was achieved first by using the yeast two-hybrid system in a proteome-wide scale and next by large-scale mass spectrometric analysis of affin- ity-purified protein complexes. While these interaction data have led to a

Takashi Ito; Kazuhisa Ota; Hiroyuki Kubota; Yoshihiro Yamaguchi; Tomoko Chiba; Kazumi Sakuraba; Mikio Yoshida

2002-01-01

117

A human phenome-interactome network of protein complexes implicated in genetic disorders  

Microsoft Academic Search

We performed a systematic, large-scale analysis of human protein complexes comprising gene products implicated in many different categories of human disease to create a phenome-interactome network. This was done by integrating quality-controlled interactions of human proteins with a validated, computationally derived phenotype similarity score, permitting identification of previously unknown complexes likely to be associated with disease. Using a phenomic ranking

Kasper Lage; E Olof Karlberg; Zenia M Størling; Páll Í Ólason; Anders G Pedersen; Olga Rigina; Anders M Hinsby; Zeynep Tümer; Flemming Pociot; Niels Tommerup; Yves Moreau; Søren Brunak

2007-01-01

118

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

PubMed Central

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

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

119

Hubba: hub objects analyzer--a framework of interactome hubs identification for network biology.  

PubMed

One major task in the post-genome era is to reconstruct proteomic and genomic interacting networks using high-throughput experiment data. To identify essential nodes/hubs in these interactomes is a way to decipher the critical keys inside biochemical pathways or complex networks. These essential nodes/hubs may serve as potential drug-targets for developing novel therapy of human diseases, such as cancer or infectious disease caused by emerging pathogens. Hub Objects Analyzer (Hubba) is a web-based service for exploring important nodes in an interactome network generated from specific small- or large-scale experimental methods based on graph theory. Two characteristic analysis algorithms, Maximum Neighborhood Component (MNC) and Density of Maximum Neighborhood Component (DMNC) are developed for exploring and identifying hubs/essential nodes from interactome networks. Users can submit their own interaction data in PSI format (Proteomics Standards Initiative, version 2.5 and 1.0), tab format and tab with weight values. User will get an email notification of the calculation complete in minutes or hours, depending on the size of submitted dataset. Hubba result includes a rank given by a composite index, a manifest graph of network to show the relationship amid these hubs, and links for retrieving output files. This proposed method (DMNC || MNC) can be applied to discover some unrecognized hubs from previous dataset. For example, most of the Hubba high-ranked hubs (80% in top 10 hub list, and >70% in top 40 hub list) from the yeast protein interactome data (Y2H experiment) are reported as essential proteins. Since the analysis methods of Hubba are based on topology, it can also be used on other kinds of networks to explore the essential nodes, like networks in yeast, rat, mouse and human. The website of Hubba is freely available at http://hub.iis.sinica.edu.tw/Hubba. PMID:18503085

Lin, Chung-Yen; Chin, Chia-Hao; Wu, Hsin-Hung; Chen, Shu-Hwa; Ho, Chin-Wen; Ko, Ming-Tat

2008-07-01

120

The Symbiosis Interactome: a computational approach reveals novel components, functional interactions and modules in Sinorhizobium meliloti  

PubMed Central

Background Rhizobium-Legume symbiosis is an attractive biological process that has been studied for decades because of its importance in agriculture. However, this system has undergone extensive study and although many of the major factors underpinning the process have been discovered using traditional methods, much remains to be discovered. Results Here we present an analysis of the 'Symbiosis Interactome' using novel computational methods in order to address the complex dynamic interactions between proteins involved in the symbiosis of the model bacteria Sinorhizobium meliloti with its plant hosts. Our study constitutes the first large-scale analysis attempting to reconstruct this complex biological process, and to identify novel proteins involved in establishing symbiosis. We identified 263 novel proteins potentially associated with the Symbiosis Interactome. The topology of the Symbiosis Interactome was used to guide experimental techniques attempting to validate novel proteins involved in different stages of symbiosis. The contribution of a set of novel proteins was tested analyzing the symbiotic properties of several S. meliloti mutants. We found mutants with altered symbiotic phenotypes suggesting novel proteins that provide key complementary roles for symbiosis. Conclusion Our 'systems-based model' represents a novel framework for studying host-microbe interactions, provides a theoretical basis for further experimental validations, and can also be applied to the study of other complex processes such as diseases. PMID:19531251

Rodriguez-Llorente, Ignacio; Caviedes, Miguel A; Dary, Mohammed; Palomares, Antonio J; Cánovas, Francisco M; Peregrín-Alvarez, José M

2009-01-01

121

Perturbation of the mutated EGFR interactome identifies vulnerabilities and resistance mechanisms  

PubMed Central

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

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

122

Interactome Mapping Reveals Important Pathways in Skeletal Muscle Development of Pigs  

PubMed Central

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

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

2014-01-01

123

Dynamic modularity in protein interaction networks predicts breast cancer outcome  

E-print Network

cells drives phenotypic transformations that directly affect disease outcome. Here we examineDynamic modularity in protein interaction networks predicts breast cancer outcome Ian W Taylor1 the dynamic structure of the human protein interaction network (interactome) to determine whether changes

Morris, Quaid

124

Spatiotemporal multipartite entanglement  

SciTech Connect

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

Kolobov, Mikhail I.; Patera, Giuseppe [Laboratoire de Physique des Lasers, Atomes et Molecules, Universite Lille 1, F-59655 Villeneuve d'Ascq Cedex (France)

2011-05-15

125

Assessment of spatio-temporal gait parameters from trunk accelerations during human walking  

Microsoft Academic Search

This paper studies the feasibility of an analysis of spatio-temporal gait parameters based upon accelerometry. To this purpose, acceleration patterns of the trunk and their relationships with spatio-temporal gait parameters were analysed in healthy subjects. Based on model predictions of the body's centre of mass trajectory during walking, algorithms were developed to determine spatio- temporal gait parameters from trunk acceleration

Wiebren Zijlstra

2003-01-01

126

Spatiotemporal instability of a confined capillary jet.  

PubMed

Recent experimental studies on the instability of capillary jets have revealed the suitability of a linear spatiotemporal instability analysis to ascertain the parametrical conditions for specific flow regimes such as steady jetting or dripping. In this work, an extensive analytical, numerical, and experimental description of confined capillary jets is provided, leading to an integrated picture both in terms of data and interpretation. We propose an extended, accurate analytic model in the low Reynolds number limit, and introduce a numerical scheme to predict the system response when the liquid inertia is not negligible. Theoretical predictions show remarkable accuracy when compared with the extensive experimental mapping. PMID:18999531

Herrada, M A; Gañán-Calvo, A M; Guillot, P

2008-10-01

127

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

PubMed

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

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

2013-01-01

128

Bcl2-associated Athanogene 3 Interactome Analysis Reveals a New Role in Modulating Proteasome Activity*  

PubMed Central

Bcl2-associated athanogene 3 (BAG3), a member of the BAG family of co-chaperones, plays a critical role in regulating apoptosis, development, cell motility, autophagy, and tumor metastasis and in mediating cell adaptive responses to stressful stimuli. BAG3 carries a BAG domain, a WW domain, and a proline-rich repeat (PXXP), all of which mediate binding to different partners. To elucidate BAG3's interaction network at the molecular level, we employed quantitative immunoprecipitation combined with knockdown and human proteome microarrays to comprehensively profile the BAG3 interactome in humans. We identified a total of 382 BAG3-interacting proteins with diverse functions, including transferase activity, nucleic acid binding, transcription factors, proteases, and chaperones, suggesting that BAG3 is a critical regulator of diverse cellular functions. In addition, we characterized interactions between BAG3 and some of its newly identified partners in greater detail. In particular, bioinformatic analysis revealed that the BAG3 interactome is strongly enriched in proteins functioning within the proteasome-ubiquitination process and that compose the proteasome complex itself, suggesting that a critical biological function of BAG3 is associated with the proteasome. Functional studies demonstrated that BAG3 indeed interacts with the proteasome and modulates its activity, sustaining cell survival and underlying resistance to therapy through the down-modulation of apoptosis. Taken as a whole, this study expands our knowledge of the BAG3 interactome, provides a valuable resource for understanding how BAG3 affects different cellular functions, and demonstrates that biologically relevant data can be harvested using this kind of integrated approach. PMID:23824909

Chen, Ying; Yang, Li-Na; Cheng, Li; Tu, Shun; Guo, Shu-Juan; Le, Huang-Ying; Xiong, Qian; Mo, Ran; Li, Chong-Yang; Jeong, Jun-Seop; Jiang, Lizhi; Blackshaw, Seth; Bi, Li-Jun; Zhu, Heng; Tao, Sheng-Ce; Ge, Feng

2013-01-01

129

Support Vector Machines for Spatiotemporal Tornado INDRA ADRIANTO1  

E-print Network

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

Lakshmanan, Valliappa

130

Contrast Adaptation Implies Two Spatiotemporal Channels but Three Adapting Processes  

ERIC Educational Resources Information Center

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

Langley, Keith; Bex, Peter J.

2007-01-01

131

Spatiotemporal electromagnetic soliton and spatial ring formation in nonlinear metamaterials  

Microsoft Academic Search

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.

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

2010-01-01

132

Spatial and Spatiotemporal Data Mining: Recent Advances  

SciTech Connect

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.

Shekhar, Shashi [University of Minnesota; Vatsavai, Raju [ORNL; Celik, Mete [University of Minnesota

2008-01-01

133

MitProNet: A Knowledgebase and Analysis Platform of Proteome, Interactome and Diseases for Mammalian Mitochondria  

PubMed Central

Mitochondrion plays a central role in diverse biological processes in most eukaryotes, and its dysfunctions are critically involved in a large number of diseases and the aging process. A systematic identification of mitochondrial proteomes and characterization of functional linkages among mitochondrial proteins are fundamental in understanding the mechanisms underlying biological functions and human diseases associated with mitochondria. Here we present a database MitProNet which provides a comprehensive knowledgebase for mitochondrial proteome, interactome and human diseases. First an inventory of mammalian mitochondrial proteins was compiled by widely collecting proteomic datasets, and the proteins were classified by machine learning to achieve a high-confidence list of mitochondrial proteins. The current version of MitProNet covers 1124 high-confidence proteins, and the remainders were further classified as middle- or low-confidence. An organelle-specific network of functional linkages among mitochondrial proteins was then generated by integrating genomic features encoded by a wide range of datasets including genomic context, gene expression profiles, protein-protein interactions, functional similarity and metabolic pathways. The functional-linkage network should be a valuable resource for the study of biological functions of mitochondrial proteins and human mitochondrial diseases. Furthermore, we utilized the network to predict candidate genes for mitochondrial diseases using prioritization algorithms. All proteins, functional linkages and disease candidate genes in MitProNet were annotated according to the information collected from their original sources including GO, GEO, OMIM, KEGG, MIPS, HPRD and so on. MitProNet features a user-friendly graphic visualization interface to present functional analysis of linkage networks. As an up-to-date database and analysis platform, MitProNet should be particularly helpful in comprehensive studies of complicated biological mechanisms underlying mitochondrial functions and human mitochondrial diseases. MitProNet is freely accessible at http://bio.scu.edu.cn:8085/MitProNet. PMID:25347823

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

2014-01-01

134

A hybrid spatiotemporal drought forecasting model for operational use  

NASA Astrophysics Data System (ADS)

Drought forecasting plays an important role in the planning and management of natural resources and water resource systems in a river basin. Early and timelines forecasting of a drought event can help to take proactive measures and set out drought mitigation strategies to alleviate the impacts of drought. Spatiotemporal data mining is the extraction of unknown and implicit knowledge, structures, spatiotemporal relationships, or patterns not explicitly stored in spatiotemporal databases. As one of data mining techniques, forecasting is widely used to predict the unknown future based upon the patterns hidden in the current and past data. This study develops a hybrid spatiotemporal scheme for integrated spatial and temporal forecasting. Temporal forecasting is achieved using feed-forward neural networks and the temporal forecasts are extended to the spatial dimension using a spatial recurrent neural network model. The methodology is demonstrated for an operational meteorological drought index the Standardized Precipitation Index (SPI) calculated at multiple timescales. 48 precipitation stations and 18 independent precipitation stations, located at Pinios river basin in Thessaly region, Greece, were used for the development and spatiotemporal validation of the hybrid spatiotemporal scheme. Several quantitative temporal and spatial statistical indices were considered for the performance evaluation of the models. Furthermore, qualitative statistical criteria based on contingency tables between observed and forecasted drought episodes were calculated. The results show that the lead time of forecasting for operational use depends on the SPI timescale. The hybrid spatiotemporal drought forecasting model could be operationally used for forecasting up to three months ahead for SPI short timescales (e.g. 3-6 months) up to six months ahead for large SPI timescales (e.g. 24 months). The above findings could be useful in developing a drought preparedness plan in the region.

Vasiliades, L.; Loukas, A.

2010-09-01

135

Spatiotemporal exploratory models for broad-scale survey data.  

PubMed

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

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

136

Spatiotemporal characteristics of pandemic influenza  

PubMed Central

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

2014-01-01

137

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

PubMed Central

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

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

138

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

PubMed Central

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

2013-01-01

139

Protein interactomics based on direct molecular fishing on paramagnetic particles: practical realization and further SPR validation.  

PubMed

There is increasing evidence that proteins function in the cell as integrated stable or temporally formed protein complexes, interactomes. Previously, using model systems we demonstrated applicability of direct molecular fishing on paramagnetic particles for protein interactomics (Ershov et al. Proteomics, 2012, 12, 3295). In the present study, we have used a combination of affinity-based molecular fishing and subsequent MS for investigation of human liver proteins involved in interactions with immobilized microsomal cytochrome b5 (CYB5A), and also transthyretin and BSA as alternative affinity ligands (baits). The LC-MS/MS identification of prey proteins fished on these baits revealed three sets of proteins: 98, 120, and 220, respectively. Comparison analysis of these sets revealed only three proteins common for all the baits. In the case of paired analysis, the number of common proteins varied from 2 to 9. The binding capacity of some identified proteins has been validated by a SPR-based biosensor. All the investigated proteins effectively interacted with the immobilized CYB5A (Kd values ranged from 0.07 to 1.1 ?M). Results of this study suggest that direct molecular fishing is applicable for analysis of protein-protein interactions (PPI) under normal and pathological conditions, in which altered PPIs are especially important. PMID:25044858

Ivanov, Alexis S; Medvedev, Alexei; Ershov, Pavel; Molnar, Andrey; Mezentsev, Yury; Yablokov, Evgeny; Kaluzhsky, Leonid; Gnedenko, Oksana; Buneeva, Olga; Haidukevich, Irina; Sergeev, Gennadiy; Lushchyk, Aliaksandr; Yantsevich, Alexey; Medvedeva, Marina; Kozin, Sergey; Popov, Igor; Novikova, Svetlana; Zgoda, Victor; Gilep, Andrey; Usanov, Sergey; Lisitsa, Andrey; Archakov, Alexander

2014-10-01

140

Subpixel Spatiotemporal Pattern Analysis  

E-print Network

One of the most important limiting factors in reliable estimation of grassland ecosystem parameters from remotely sensed data is "too coarse" resolution. Areal averages obtained from readily available imagery do not match well with ecological field data. To address this discrepancy we have collected simultaneous spectral, other biophysical and ecological data with similar ground resolution between May and August 1995 in the Grassland National Park, Saskatchewan, Canada. Beyond calibration for a wide variety of conditions, the applied nested sampling design facilitates scaling of measured and estimated properties from 0.5 m to 100 m by partitioning overall variability, and by hierarchical scene simulation. Analysis of the spatiotemporal pattern reveals potential problems with using areal averages in long-term monitoring and assessment of ecological status of grasslands.

Of Remote Sensing; Ferko Csillag; Andrew Davidson; Scott Mitchell; Bruce Wylie

1996-01-01

141

Shared Molecular and Functional Frameworks among Five Complex Human Disorders: A Comparative Study on Interactomes Linked to Susceptibility Genes  

PubMed Central

Background Genome-wide association studies (gwas) are invaluable in revealing the common variants predisposing to complex human diseases. Yet, until now, the large volumes of data generated from such analyses have not been explored extensively enough to identify the molecular and functional framework hosting the susceptibility genes. Methodology/Principal Findings We investigated the relationships among five neurodegenerative and/or autoimmune complex human diseases (Parkinson's disease-Park, Alzheimer's disease-Alz, multiple sclerosis-MS, rheumatoid arthritis-RA and Type 1 diabetes-T1D) by characterising the interactomes linked to their gwas-genes. An initial study on the MS interactome indicated that several genes predisposing to the other autoimmune or neurodegenerative disorders may come into contact with it, suggesting that susceptibility to distinct diseases may converge towards common molecular and biological networks. In order to test this hypothesis, we performed pathway enrichment analyses on each disease interactome independently. Several issues related to immune function and growth factor signalling pathways appeared in all autoimmune diseases, and, surprisingly, in Alzheimer's disease. Furthermore, the paired analyses of disease interactomes revealed significant molecular and functional relatedness among autoimmune diseases, and, unexpectedly, between T1D and Alz. Conclusions/Significance The systems biology approach highlighted several known pathogenic processes, indicating that changes in these functions might be driven or sustained by the framework linked to genetic susceptibility. Moreover, the comparative analyses among the five genetic interactomes revealed unexpected genetic relationships, which await further biological validation. Overall, this study outlines the potential of systems biology to uncover links between genetics and pathogenesis of complex human disorders. PMID:21533026

Menon, Ramesh; Farina, Cinthia

2011-01-01

142

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

PubMed Central

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

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

2014-01-01

143

Controlling spatiotemporal chaos in coupled nonlinear oscillators  

NASA Astrophysics Data System (ADS)

A method for controlling spatiotemporal chaos in coupled ordinary differential equations is presented. It is based on two ideas: stabilization of unstable periodic patterns embedded in spatiotemporal chaos, and perturbation of dynamical variables only at regular time intervals.

Kocarev, Ljup?o.; Parlitz, Ulrich; Stojanovski, Toni; Janji?, Predrag

1997-07-01

144

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

PubMed Central

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

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

2011-01-01

145

Spatiotemporal Gradient Modeling with Applications  

E-print Network

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 Spatiotemporal Gradients in Interval-Censored Airborne Exposures Data from the Clean-Up of the Deepwater Horizon

Carlin, Bradley P.

146

Auditory Perception of Spatiotemporal Patterns  

ERIC Educational Resources Information Center

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)

Tolkmitt, Frank J.; Brindley, Robin

1977-01-01

147

Finding Spatio-Temporal Patterns in Earth Science Data  

Microsoft Academic Search

This paper presents preliminary work in using data mining techniques to find interesting spatio-temporal patterns from Earth Science data. The data consists of time series measurements for various Earth science and climate variables (e.g. soil moisture, temperature, and precipitation), along with additional data from existing ecosystem models (e.g. Net Primary Production). The ecological patterns of interest include associations, clusters, predictive

Pang-Ning Tan; Michael Steinbach; Vipin Kumar; Christopher Potter; Steven Klooster; Alicia Torregrosa

2001-01-01

148

Prediction  

NSDL National Science Digital Library

Students must be guided to state not only what they think will happen, but also a reason or explanation for what will happen based upon their prior knowledge. Therefore, the predictions students write should activate prior knowledge, relate to their focus

Klentschy, Michael P.

2008-04-01

149

Spatio-temporal dynamics of the magnetosphere during geospace storms  

NASA Astrophysics Data System (ADS)

Nonlinear dynamical models have became powerful tools for studying and forecasting magnetospheric dynamics driven by solar wind inputs. In this thesis, the techniques of phase space reconstruction from time series data are used to develop new methods for modeling and predicting the spatio-temporal dynamics of the magnetosphere. For these studies, new databases covering the solar maximum period were compiled to enable accurate modeling of the magnetosphere during intense geospace storms. The main contributions of the thesis are: Weighted Mean Field Model and Its Application to the Intense Storms. The nonlinear dynamical models of the coupled solar wind-magnetosphere system derived from observational data yield efficient forecasts of space weather. An improved version of the mean field model, derived from a set of nearest neighbors in the phase space reconstructed from the data, was developed by assigning weights to the nearest neighbors. A new correlated database was compiled and used to model and forecast the geospace storms of October-November 2003 and April 2002, and resulted in improved forecasts of the intense storms. Mutual Information Analysis of Spatio-Temporal Dynamics. The mutual information functions enable studies of the nonlinear correlations of dynamical systems. A high resolution database for a six month period of solar wind and ground-based magnetometer data from 12 high latitude stations was used to compute the mutual information functions representing the correlations inherent in the system. Using two different window lengths of 6 and 24 hr, the spatio-temporal dynamics was analyzed using these functions for the different stations. The spreads in the average mutual information show strong correlations with the solar wind changes and the time evolution of mutual information yields a westward expansion of the disturbed region, starting from the near midnight sectors. Modeling and Predictions of Spatio-Temporal Dynamics of the Magnetosphere. The spatial structure of the magnetospheric dynamics is crucial to space weather forecasting. The database of the magnetic field perturbations at 39 magnetometers belonging to the IMAGE and CANOPUS during year 2002 was used to study the spatio-temporal structure. A longitudinal sampling process utilizing the daily rotation of Earth was used to construct a two-dimensional representation of the high latitude magnetic perturbations. The nonlinear model was used to predict the spatial structure of geomagnetic disturbances during geospace storms. Results presented in this dissetation provide a comprehensive study of the magnetosphere using nonlinear data derived models. The new weighted mean field model, mutual information analysis and spatio-temporal dynamics advance our understanding of the solar wind-magnetosphere coupling. These results can be used to develop new and more detailed space weather forecasting tools.

Chen, Jian

2007-08-01

150

Proteomic analysis of the NOS2 interactome in human airway epithelial cells  

PubMed Central

The cytokine-inducible isoform of nitric oxide synthase (NOS2) is constitutively expressed in human respiratory epithelia and is upregulated in inflammatory lung disease. Here, we sought to better define the protein interactions that may be important for NOS2 activity and stability, as well as to identify potential targets of NOS2-derived NO, in the respiratory epithelium. We overexpressed Flag-tagged, catalytically-inactive NOS2 in A549 cells and used mass spectrometry to qualitatively identify NOS2 co-immunoprecipitating proteins. Stable isotope labeling of amino acids in cell culture (SILAC) was used to quantify the coordinate effects of cytokine stimulation on NOS2-protein interactions. Multi-protein networks dominated the NOS2 interactome, and cytokine-inducible interactions with allosteric activators and with the ubiquitin-proteasome system were correlated with cytokine-dependent increases in NO metabolites and in NOS2 ubiquitination. The ubiquitin ligase scaffolding protein, FBXO45, was identified as a novel, direct NOS2 interactor. Similar to the SPRY domain-containing SOCS box (SPSB) proteins, FBXO45 requires Asn27 in the 23DINNN27 motif of NOS2 for its interaction. However, FBXO45 is unique from the SPSBs in that it recruits a distinct E3 ligase complex containing MYCBP2 and SKP1. Collectively, these findings demonstrate the general utility of interaction proteomics for defining new aspects of NOS2 physiology. PMID:23438482

Foster, Matthew W.; Thompson, J. Will; Forrester, Michael T.; Sha, Yonggang; McMahon, Timothy J.; Bowles, Dawn E.; Moseley, M. Arthur; Marshall, Harvey E.

2013-01-01

151

Characterization of the Drosophila atlastin interactome reveals VCP as a functionally related interactor.  

PubMed

At least 25 genes, many involved in trafficking, localisation or shaping of membrane organelles, have been identified as causative genes for the neurodegenerative disorder hereditary spastic paraplegia (HSP). One of the most commonly mutated HSP genes, atlastin-1, encodes a dynamin-like GTPase that mediates homotypic fusion of endoplasmic reticulum (ER) membranes. However, the molecular mechanisms of atlastin-1-related membrane fusion and axonopathy remain unclear. To better understand its mode of action, we used affinity purification coupled with mass spectrometry to identify protein interactors of atlastin in Drosophila. Analysis of 72 identified proteins revealed that the atlastin interactome contains many proteins involved in protein processing and transport, in addition to proteins with roles in mRNA binding, metabolism and mitochondrial proteins. The highest confidence interactor from mass spectrometry analysis, the ubiquitin-selective AAA-ATPase valosin-containing protein (VCP), was validated as an atlastin-interacting protein, and VCP and atlastin showed overlapping subcellular distributions. Furthermore, VCP acted as a genetic modifier of atlastin: loss of VCP partially suppressed an eye phenotype caused by atlastin overexpression, whereas overexpression of VCP enhanced this phenotype. These interactions between atlastin and VCP suggest a functional relationship between these two proteins, and point to potential shared mechanisms between HSP and other forms of neurodegeneration. PMID:23790629

O'Sullivan, Niamh C; Dräger, Nina; O'Kane, Cahir J

2013-06-20

152

Raf-interactome in tuning the complexity and diversity of Raf function.  

PubMed

Raf kinases have been intensely studied subsequent to their discovery 30 years ago. The Ras-Raf-mitogen-activated protein kinase/extracellular signal-regulated kinase kinase-extracellular signal-regulated kinase/mitogen-activated protein kinase (Ras-Raf-MEK-ERK/MAPK) signaling pathway is at the heart of the signaling networks that control many fundamental cellular processes and Raf kinases takes centre stage in the MAPK pathway, which is now appreciated to be one of the most common sources of the oncogenic mutations in cancer. The dependency of tumors on this pathway has been clearly demonstrated by targeting its key nodes; however, blockade of the central components of the MAPK pathway may have some unexpected side effects. Over recent years, the Raf-interactome or Raf-interacting proteins have emerged as promising targets for protein-directed cancer therapy. This review focuses on the diversity of Raf-interacting proteins and discusses the mechanisms by which these proteins regulate Raf function, as well as the implications of targeting Raf-interacting proteins in the treatment of human cancer. PMID:25333451

An, Su; Yang, Yang; Ward, Richard; Liu, Ying; Guo, Xiao-Xi; Xu, Tian-Rui

2015-01-01

153

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

SciTech Connect

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.

Dmitriev, Ruslan I. [Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow 117997 (Russian Federation); Korneenko, Tatyana V. [Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow 117997 (Russian Federation); Department of Physiology, Pharmacology, Metabolism, and Cardiovascular Sciences, University of Toledo College of Medicine, Toledo, OH 43614 (United States); Bessonov, Alexander A. [Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow 117997 (Russian Federation); Shakhparonov, Mikhail I. [Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow 117997 (Russian Federation); Modyanov, Nikolai N. [Department of Physiology, Pharmacology, Metabolism, and Cardiovascular Sciences, University of Toledo College of Medicine, Toledo, OH 43614 (United States); Pestov, Nikolay B. [Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow 117997 (Russian Federation); Department of Physiology, Pharmacology, Metabolism, and Cardiovascular Sciences, University of Toledo College of Medicine, Toledo, OH 43614 (United States); E-mail: korn@mail.ibch.ru

2007-04-20

154

Locus-Specific Targeting to the X Chromosome Revealed by the RNA Interactome of CTCF.  

PubMed

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

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

2015-01-22

155

Influenza virus-host interactome screen as a platform for antiviral drug development.  

PubMed

Host factors required for viral replication are ideal drug targets because they are less likely than viral proteins to mutate under drug-mediated selective pressure. Although genome-wide screens have identified host proteins involved in influenza virus replication, limited mechanistic understanding of how these factors affect influenza has hindered potential drug development. We conducted a systematic analysis to identify and validate host factors that associate with influenza virus proteins and affect viral replication. After identifying over 1,000 host factors that coimmunoprecipitate with specific viral proteins, we generated a network of virus-host protein interactions based on the stage of the viral life cycle affected upon host factor downregulation. Using compounds that inhibit these host factors, we validated several proteins, notably Golgi-specific brefeldin A-resistant guanine nucleotide exchange factor 1 (GBF1) and JAK1, as potential antiviral drug targets. Thus, virus-host interactome screens are powerful strategies to identify targetable host factors and guide antiviral drug development. PMID:25464832

Watanabe, Tokiko; Kawakami, Eiryo; Shoemaker, Jason E; Lopes, Tiago J S; Matsuoka, Yukiko; Tomita, Yuriko; Kozuka-Hata, Hiroko; Gorai, Takeo; Kuwahara, Tomoko; Takeda, Eiji; Nagata, Atsushi; Takano, Ryo; Kiso, Maki; Yamashita, Makoto; Sakai-Tagawa, Yuko; Katsura, Hiroaki; Nonaka, Naoki; Fujii, Hiroko; Fujii, Ken; Sugita, Yukihiko; Noda, Takeshi; Goto, Hideo; Fukuyama, Satoshi; Watanabe, Shinji; Neumann, Gabriele; Oyama, Masaaki; Kitano, Hiroaki; Kawaoka, Yoshihiro

2014-12-10

156

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

PubMed

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

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

2014-05-26

157

Identification of LMO2 transcriptome and interactome in diffuse large B-cell lymphoma  

PubMed Central

LMO2 regulates gene expression by facilitating the formation of multipartite DNA-binding complexes. In B cells, LMO2 is specifically up-regulated in the germinal center (GC) and is expressed in GC-derived non-Hodgkin lymphomas. LMO2 is one of the most powerful prognostic indicators in diffuse large B-cell (DLBCL) patients. However, its function in GC B cells and DLBCL is currently unknown. In this study, we characterized the LMO2 transcriptome and transcriptional complex in DLBCL cells. LMO2 regulates genes implicated in kinetochore function, chromosome assembly, and mitosis. Overexpression of LMO2 in DLBCL cell lines results in centrosome amplification. In DLBCL, the LMO2 complex contains some of the traditional partners, such as LDB1, E2A, HEB, Lyl1, ETO2, and SP1, but not TAL1 or GATA proteins. Furthermore, we identified novel LMO2 interacting partners: ELK1, nuclear factor of activated T-cells (NFATc1), and lymphoid enhancer-binding factor1 (LEF1) proteins. Reporter assays revealed that LMO2 increases transcriptional activity of NFATc1 and decreases transcriptional activity of LEF1 proteins. Overall, our studies identified a novel LMO2 transcriptome and interactome in DLBCL and provides a platform for future elucidation of LMO2 function in GC B cells and DLBCL pathogenesis. PMID:22517897

Cubedo, Elena; Gentles, Andrew J.; Huang, Chuanxin; Natkunam, Yasodha; Bhatt, Shruti; Lu, Xiaoqing; Jiang, Xiaoyu; Romero-Camarero, Isabel; Freud, Aharon; Zhao, Shuchun; Bacchi, Carlos E.; Martínez-Climent, Jose A.; Sánchez-García, Isidro; Melnick, Ari

2012-01-01

158

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

PubMed Central

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

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

159

Forecasting Confined Spatiotemporal Chaos with Genetic Algorithms  

NASA Astrophysics Data System (ADS)

A technique to forecast spatiotemporal time series is presented. It uses a proper orthogonal or Karhunen-Loève decomposition to encode large spatiotemporal data sets in a few time series, and genetic algorithms to efficiently extract dynamical rules from the data. The method works very well for confined systems displaying spatiotemporal chaos, as exemplified here by forecasting the evolution of the one-dimensional complex Ginzburg-Landau equation in a finite domain.

López, Cristóbal; Álvarez, Alberto; Hernández-García, Emilio

2000-09-01

160

Forecasting confined spatiotemporal chaos with genetic algorithms.  

PubMed

A technique to forecast spatiotemporal time series is presented. It uses a proper orthogonal or Karhunen-Loève decomposition to encode large spatiotemporal data sets in a few time series, and genetic algorithms to efficiently extract dynamical rules from the data. The method works very well for confined systems displaying spatiotemporal chaos, as exemplified here by forecasting the evolution of the one-dimensional complex Ginzburg-Landau equation in a finite domain. PMID:10977996

López, C; Alvarez, A; Hernández-García, E

2000-09-11

161

Rice Mitogen-Activated Protein Kinase Interactome Analysis Using the Yeast Two-Hybrid System1[C][W  

PubMed Central

Mitogen-activated protein kinase (MAPK) cascades support the flow of extracellular signals to intracellular target molecules and ultimately drive a diverse array of physiological functions in cells, tissues, and organisms by interacting with other proteins. Yet, our knowledge of the global physical MAPK interactome in plants remains largely fragmented. Here, we utilized the yeast two-hybrid system and coimmunoprecipitation, pull-down, bimolecular fluorescence complementation, subcellular localization, and kinase assay experiments in the model crop rice (Oryza sativa) to systematically map what is to our knowledge the first plant MAPK-interacting proteins. We identified 80 nonredundant interacting protein pairs (74 nonredundant interactors) for rice MAPKs and elucidated the novel proteome-wide network of MAPK interactors. The established interactome contains four membrane-associated proteins, seven MAP2Ks (for MAPK kinase), four MAPKs, and 59 putative substrates, including 18 transcription factors. Several interactors were also validated by experimental approaches (in vivo and in vitro) and literature survey. Our results highlight the importance of OsMPK1, an ortholog of tobacco (Nicotiana benthamiana) salicyclic acid-induced protein kinase and Arabidopsis (Arabidopsis thaliana) AtMPK6, among the rice MAPKs, as it alone interacts with 41 unique proteins (51.2% of the mapped MAPK interaction network). Additionally, Gene Ontology classification of interacting proteins into 34 functional categories suggested MAPK participation in diverse physiological functions. Together, the results obtained essentially enhance our knowledge of the MAPK-interacting protein network and provide a valuable research resource for developing a nearly complete map of the rice MAPK interactome. PMID:22786887

Singh, Raksha; Lee, Mi-Ok; Lee, Jae-Eun; Choi, Jihyun; Park, Ji Hun; Kim, Eun Hye; Yoo, Ran Hee; Cho, Jung-Il; Jeon, Jong-Seong; Rakwal, Randeep; Agrawal, Ganesh Kumar; Moon, Jae Sun; Jwa, Nam-Soo

2012-01-01

162

Neural mechanisms of spatiotemporal signal processing  

NASA Astrophysics Data System (ADS)

We have studied the synaptic, dendritic, and network mechanisms of spatiotemporal signal processing underlying the computation of visual motion in the avian tectum. Such mechanisms are critical for information processing in all vertebrates, but have been difficult to elucidate in mammals because of anatomical limitations. We have therefore developed a chick tectal slice preparation, which has features that help us circumvent these limitations. Using single-electrode multi-pulse synaptic stimulation experiments we found that the SGC-I cell responds to synaptic stimulation in a binary manner and its response is phasic in a time dependent probabilistic manner over large time scales. Synaptic inputs at two locations typically interact in a mutually exclusive manner when delivered within the "interaction time" of approximately 30 ms. Then we constructed a model of SGC-I cell and the retinal inputs to examine the role of the observed non-linear cellular properties in shaping the response of SGC-I neurons to assumed retinal representations of dynamic spatiotemporal visual stimuli. We found that by these properties, SGC-I cells can classify different stimuli. Especially without the phasic synaptic signal transfer the model SGC-I cell fails to distinguish between the static stationary stimuli and dynamic spatiotemporal stimuli. Based on one-site synaptic response probability and the assumption of independent neighboring dendritic endings we predicted the response probability of SGC-I cells to multiple synaptic inputs. We tested this independence-based model prediction and found that the independency assumption is not valid. The measured SGC-I response probability to multiple synaptic inputs does not increase with the number of synaptic inputs. The presence of GABAergic horizontal cells in layer 5 suggest an inhibitory effect of these cells on the SGC-I retino-tectal synaptic responses. In our experiment we found that the measured SGC-I response probability to multiple synaptic inputs is reduced when inhibitory tectal circuits are blocked. By predicting the SGC-I response to multiple synaptic inputs based on blocked inhibitory circuitry we found that the response probability is closer to independent situation but not exactly. So there is more than just inhibitory mechanism involved. To characterize the dependency between two neighboring synapses we used 2-site stimulation experiments and measured the effect of one stimulation on a spatially separate synapse. To determine whether this inhibitory mechanism is pre-synaptic or post-synaptic we used chloride channel blocker intracellularly. We saw an increase in response probability when post-synaptic chloride channels are blocked. Finally we found a good agreement between our prediction and experimental results for Poisson spike trains which may be considered more natural stimuli. Only the early stage of SGC-I response is carrying most of the information. Analyzing the SGC-I spike timing and the accuracy of latency is the last part of the thesis.

Khanbabaie Shoub, Shaban (Reza)

163

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

SciTech Connect

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

Davidson, George S.; Brown, William Michael

2007-09-01

164

Spatio-Temporal Clustering of Monitoring Network  

NASA Astrophysics Data System (ADS)

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)

Hussain, I.; Pilz, J.

2009-04-01

165

Understanding Distal Transcriptional Regulation from Sequence Motif, Network Inference and Interactome Perspectives  

Microsoft Academic Search

Gene regulation in higher eukaryotes involves a complex interplay between the\\u000agene proximal promoter and distal genomic elements (such as enhancers) which\\u000awork in concert to drive spatio-temporal expression. The experimental\\u000acharacterization of gene regulatory elements is a very complex and\\u000aresource-intensive process. One of the major goals in computational biology is\\u000athe \\\\textit{in-silico} annotation of previously uncharacterized elements using

Arvind Rao; Alfred O. Hero III; David J. States; James Douglas Engel

2008-01-01

166

Structured reservoir computing with spatiotemporal chaotic attractors  

E-print Network

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

Lourenço, Carlos

167

Structured reservoir computing with spatiotemporal chaotic attractors  

E-print Network

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

Lourenço, Carlos

168

Phospholamban interactome in cardiac contractility and survival: A new vision of an old friend.  

PubMed

Depressed sarcoplasmic reticulum (SR) calcium cycling, reflecting impaired SR Ca-transport and Ca-release, is a key and universal characteristic of human and experimental heart failure. These SR processes are regulated by multimeric protein complexes, including protein kinases and phosphatases as well as their anchoring and regulatory subunits that fine-tune Ca-handling in specific SR sub-compartments. SR Ca-transport is mediated by the SR Ca-ATPase (SERCA2a) and its regulatory phosphoprotein, phospholamban (PLN). Dephosphorylated PLN is an inhibitor of SERCA2a and phosphorylation by protein kinase A (PKA) or calcium-calmodulin-dependent protein kinases (CAMKII) relieves these inhibitory effects. Recent studies identified additional regulatory proteins, associated with PLN, that control SR Ca-transport. These include the inhibitor-1 (I-1) of protein phosphatase 1 (PP1), the small heat shock protein 20 (Hsp20) and the HS-1 associated protein X-1 (HAX1). In addition, the intra-luminal histidine-rich calcium binding protein (HRC) has been shown to interact with both SERCA2a and triadin. Notably, there is physical and direct interaction between these protein players, mediating a fine-cross talk between SR Ca-uptake, storage and release. Importantly, regulation of SR Ca-cycling by the PLN/SERCA interactome does not only impact cardiomyocyte contractility, but also survival and remodeling. Indeed, naturally occurring variants in these Ca-cycling genes modulate their activity and interactions with other protein partners, resulting in depressed contractility and accelerated remodeling. These genetic variants may serve as potential prognostic or diagnostic markers in cardiac pathophysiology. PMID:25451386

Haghighi, Kobra; Bidwell, Philip; Kranias, Evangelia G

2014-12-01

169

Spatiotemporal behavior and nonlinear dynamics in a phase conjugate resonator  

NASA Technical Reports Server (NTRS)

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.

Liu, Siuying Raymond

1993-01-01

170

Interactome Profile of the Host Cellular Proteins and the Nonstructural Protein 2 of Porcine Reproductive and Respiratory Syndrome Virus  

PubMed Central

The nonstructural protein 2 (NSP2) is considered to be one of crucial viral proteins in the replication and pathogenesis of porcine reproductive and respiratory syndrome virus (PRRSV). In the present study, the host cellular proteins that interact with the NSP2 of PRRSV were immunoprecipitated with anti-Myc antibody from the MARC-145 cells infected by a recombinant PRRSV with 3xMyc tag insertion in its NSP2-coding region, and then 285 cellular proteins interacting with NSP2 were identified by LC-MS/MS. The Gene Ontology and enriched KEGG Pathway bioinformatics analyses indicated that the identified proteins could be assigned to different subcellular locations and functional classes. Functional analysis of the interactome profile highlighted cellular pathways associated with infectious disease, translation, immune system, nervous system and signal transduction. Two interested cellular proteins–BCL2-associated athanogene 6 (BAG6) and apoptosis-inducing factor 1 (AIF1) which may involve in transporting of NSP2 to Endoplasmic reticulum (ER) or PRRSV-driven apoptosis were validated by Western blot. The interactome data between PRRSV NSP2 and cellular proteins contribute to the understanding of the roles of NSP2 in the replication and pathogenesis of PRRSV, and also provide novel cellular target proteins for elucidating the associated molecular mechanisms of the interaction of host cellular proteins with viral proteins in regulating the viral replication. PMID:24901321

Zhang, Han; Li, Yan; Ge, Xinna; Guo, Xin; Yu, Kangzhen; Yang, Hanchun

2014-01-01

171

The Cellular Interactome of the Coronavirus Infectious Bronchitis Virus Nucleocapsid Protein and Functional Implications for Virus Biology  

PubMed Central

The coronavirus nucleocapsid (N) protein plays a multifunctional role in the virus life cycle, from regulation of replication and transcription and genome packaging to modulation of host cell processes. These functions are likely to be facilitated by interactions with host cell proteins. The potential interactome of the infectious bronchitis virus (IBV) N protein was mapped using stable isotope labeling with amino acids in cell culture (SILAC) coupled to a green fluorescent protein-nanotrap pulldown methodology and liquid chromatography-tandem mass spectrometry. The addition of the SILAC label allowed discrimination of proteins that were likely to specifically bind to the N protein over background binding. Overall, 142 cellular proteins were selected as potentially binding to the N protein, many as part of larger possible complexes. These included ribosomal proteins, nucleolar proteins, translation initiation factors, helicases, and hnRNPs. The association of selected cellular proteins with IBV N protein was confirmed by immunoblotting, cosedimentation, and confocal microscopy. Further, the localization of selected proteins in IBV-infected cells as well as their activity during virus infection was assessed by small interfering RNA-mediated depletion, demonstrating the functional importance of cellular proteins in the biology of IBV. This interactome not only confirms previous observations made with other coronavirus and IBV N proteins with both overexpressed proteins and infectious virus but also provides novel data that can be exploited to understand the interaction between the virus and the host cell. PMID:23637410

Munday, Diane; Bickerton, Erica; Britton, Paul; Rodgers, Mark A.; Whitehouse, Adrian; Zhou, En-Min

2013-01-01

172

Forecasting the Spatio-Temporal Dynamics of the Magnetosphere  

NASA Astrophysics Data System (ADS)

The spatio-temporal dynamics of the magnetosphere is a crucial component of effective space weather forecasting. The extensive data of the solar wind-magnetosphere interaction has been used to build predictive models of the magnetosphere based on nonlinear dynamical approaches. The time series data of the distributed observations are used to develop spatio-temporal dynamics of the magnetosphere. In this approach the solar wind - magnetosphere coupling is modeled as an input-output system with the solar wind variables as the input and the magnetic field variations at the ground stations as the magnetospheric response. The magnetic field perturbation at the ground and the corresponding solar wind data stations during the solar maximum period are compiled for these studies. The ground magnetometer data are from from CANOPUS, IMAGE and WDC magnetometer chain of stations. This new data set is used to study the spatio-temporal structure, including the coupling between the high and mid-latitude regions. A technique that utilizes the daily rotation of the Earth as a longitudinal sampling process is used to construct a two dimensional representation of the high latitude magnetic perturbations both in magnetic latitude and magnetic local time. This nonlinear model is used to predict the spatial structure of geomagnetic disturbances during intense geospace storms. In order to understand the predictability of space weather, the correlated database is used to study the causal relationships based on information theoretic approaches. This yields the mutual information between the solar wind variables and the ground magnetic field variations, and among the ground stations themselves. The information flow within the coupled system is analyzed by computing the transfer entropy among them.

Chen, J.; Sharma, A.; Veeramani, T.

2007-12-01

173

The Evolution of Meaning: Spatio-temporal Dynamics of Visual Object Recognition  

Microsoft Academic Search

Research on the spatio-temporal dynamics of visual object recognition suggests a recurrent, interactive model whereby an initial feedforward sweep through the ventral stream to prefrontal cortex is followed by recurrent interactions. However, critical questions remain regarding the factors that mediate the degree of recurrent interactions necessary for meaningful object recognition. The novel prediction we test here is that recurrent interactivity

Alex Clarke; Kirsten I. Taylor; Lorraine K. Tyler

2011-01-01

174

Spatio-temporal dynamics of bumblebee nest parasites (Bombus subgenus Psythirus ssp.) and their hosts  

E-print Network

Spatio-temporal dynamics of bumblebee nest parasites (Bombus subgenus Psythirus ssp in the British Isles. 2. A model of nest parasitism predicted host threshold densities and stable deterministic, parasite-free zones were evident in areas of low host abundance, but the host thresh- old for parasite

Antonovics, Janis

175

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

E-print Network

Ocean Wave Reconstruction Algorithms Based on Spatio-temporal Data Acquired by a Flash LIDAR Camera on the development of free surface reconstruction algorithms to predict ocean waves, based on spatial observationsD surface generation and reconstruction of irregular sea states using Choppy. KEY WORDS: Ocean waves

Grilli, Stéphan T.

176

A Spatiotemporal Graph Model for Rainfall Event Identification and Representation  

E-print Network

Weibo Liu Department of Geography, University of Kansas A Spatiotemporal Graph Model for Rainstorm Identification and Representation 2Introduction Geographic phenomena evolve in space and time: ? The development of a hurricane ? The evolution... divided by the area of storm cell2 at time T2; 3) the sum of two fractions. X Y T T1 T2 T3 T1 , T2 , T1 = Actual Location at T1 T1 ’= Predicted location at T2 from T1 Rainstorms’ Lifecycle Identification Rainstorm Representation ? The directed...

Liu, Weibo

2014-04-21

177

3D hybrid wound devices for spatiotemporally controlled release kinetics.  

PubMed

This paper presents localized and temporal control of release kinetics over 3-dimensional (3D) hybrid wound devices to improve wound-healing process. Imaging study is performed to extract wound bed geometry in 3D. Non-Uniform Rational B-Splines (NURBS) based surface lofting is applied to generate functionally graded regions. Diffusion-based release kinetics model is developed to predict time-based release of loaded modifiers for functionally graded regions. Multi-chamber single nozzle solid freeform dispensing system is used to fabricate wound devices with controlled dispensing concentration. Spatiotemporal control of biological modifiers thus enables a way to achieve target delivery to improve wound healing. PMID:22672934

Ozbolat, Ibrahim T; Koc, Bahattin

2012-12-01

178

Spatiotemporal fractal pattern in interfacial motion with quenched disorder  

NASA Astrophysics Data System (ADS)

We study the recently introduced Leschhorn model [H. Leschhorn, Physica A 195, 324 (1993)] for interfacial depinning with quenched disorder. The spatiotemporal intermittency observed in the system displays critical properties of fractals. By using the scaling argument, we are able to express various scaling exponents in terms of the fundamental exponents, i.e., the dynamical exponent z, the roughness exponent ?, and the correlation length exponent ?. Moreover, our simulation gives very good agreement with the prediction. The numerical values of various critical exponents show that the Leschhorn model is not in the same universality class of directed percolation.

Pang, Ning-Ning; Liang, N. Y.

1997-08-01

179

Spatiotemporal structures in aging and rejuvenating glasses  

PubMed Central

Complex spatiotemporal structures develop during the process of aging glasses after cooling and of rejuvenating glasses on heating. The key to understanding these structures is the interplay between the activated reconfiguration events that generate mobility and the transport of mobility. These effects are both accounted for by combining the random first-order transition theory of activated events with mode coupling theory in an inhomogeneous setting. The predicted modifications by mobility transport of the time course of the aging regime are modest. In contrast, the rejuvenation process is strongly affected through the propagation of fronts of enhanced mobility originating from the initial reconfiguration events. The structures in a rejuvenating glass resemble flames. An analysis along the lines of combustion theory provides an estimate of the front propagation speed. Heterogeneous rejuvenation naturally should occur for glasses with free surfaces. The analogy with combustion also provides a way of looking at the uptake of diluents by glasses described by case II and super case II diffusion. PMID:19188612

Peter G., Wolynes

2009-01-01

180

Spatiotemporal control of nanooptical excitations  

PubMed Central

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

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

181

Identification of the Hypoxia-inducible Factor 2? Nuclear Interactome in Melanoma Cells Reveals Master Proteins Involved in Melanoma Development*  

PubMed Central

Hypoxia-inducible factors (HIFs) are heterodimeric transcription factors that play a key role in cellular adaptation to hypoxia. HIF proteins are composed of an ? subunit regulated by oxygen pressure (essentially HIF1? or HIF2?) and a constitutively expressed ? subunit. These proteins are often overexpressed in cancer cells, and HIF overexpression frequently correlates with poor prognosis, making HIF proteins promising therapeutic targets. HIF proteins are involved in melanoma initiation and progression; however, the specific function of HIF2 in melanoma has not yet been studied comprehensively. Identifying protein complexes is a valuable way to uncover protein function, and affinity purification coupled with mass spectrometry and label-free quantification is a reliable method for this approach. We therefore applied quantitative interaction proteomics to identify exhaustively the nuclear complexes containing HIF2? in a human melanoma cell line, 501mel. We report, for the first time, a high-throughput analysis of the interactome of an HIF subunit. Seventy proteins were identified that interact with HIF2?, including some well-known HIF partners and some new interactors. The new HIF2? partners microphthalmia-associated transcription factor, SOX10, and AP2?, which are master actors of melanoma development, were confirmed via co-immunoprecipitation experiments. Their ability to bind to HIF1? was also tested: microphthalmia-associated transcription factor and SOX10 were confirmed as HIF1? partners, but the transcription factor AP2? was not. AP2? expression correlates with low invasive capacities. Interestingly, we demonstrated that when HIF2? was overexpressed, only cells expressing large amounts of AP2? exhibited decreased invasive capacities in hypoxia relative to normoxia. The simultaneous presence of both transcription factors therefore reduces cells' invasive properties. Knowledge of the HIF2? interactome is thus a useful resource for investigating the general mechanisms of HIF function and regulation, and here we reveal unexpected, distinct roles for the HIF1 and HIF2 isoforms in melanoma progression. PMID:23275444

Steunou, Anne-Lise; Ducoux-Petit, Manuelle; Lazar, Ikrame; Monsarrat, Bernard; Erard, Monique; Muller, Catherine; Clottes, Eric; Burlet-Schiltz, Odile; Nieto, Laurence

2013-01-01

182

Notch3 Interactome Analysis Identified WWP2 as a Negative Regulator of Notch3 Signaling in Ovarian Cancer  

PubMed Central

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

Guan, Bin; Wu, Ren-Chin; Zhu, Heng; Blackshaw, Seth; Shih, Ie-Ming; Wang, Tian-Li

2014-01-01

183

Characterization of the human NEK7 interactome suggests catalytic and regulatory properties distinct from those of NEK6.  

PubMed

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

de Souza, Edmarcia Elisa; Meirelles, Gabriela Vaz; Godoy, Bárbara Biatriz; Perez, Arina Marina; Smetana, Juliana Helena Costa; Doxsey, Stephen J; McComb, Mark E; Costello, Catherine E; Whelan, Stephen A; Kobarg, Jörg

2014-09-01

184

Spatiotemporally controlled single cell sonoporation  

PubMed Central

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

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

2012-01-01

185

Spatiotemporal control of cardiac alternans  

NASA Astrophysics Data System (ADS)

Electrical alternans are believed to be linked to the onset of life-threatening ventricular arrhythmias and sudden cardiac death. Recent studies have shown that alternans can be suppressed temporally by dynamic feedback control of the pacing interval. Here we investigate theoretically whether control can suppress alternans both temporally and spatially in homogeneous tissue paced at a single site. We first carry out ionic model simulations in a one-dimensional cable geometry which show that control is only effective up to a maximum cable length that decreases sharply away from the alternans bifurcation point. We then explain this finding by a linear stability analysis of an amplitude equation that describes the spatiotemporal evolution of alternans. This analysis reveals that control failure above a critical cable length is caused by the formation of standing wave patterns of alternans that are eigenfunctions of a forced Helmholtz equation, and therefore remarkably analogous to sound harmonics in an open pipe. We discuss the implications of these results for using control to suppress alternans in the human ventricles as well as to probe fundamental aspects of alternans morphogenesis.

Echebarria, Blas; Karma, Alain

2002-09-01

186

Spatiotemporal testing and modeling of catfish retinal neurons.  

PubMed Central

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

Krausz, H I; Naka, K

1980-01-01

187

Spatiotemporal model for the progression of transgressive dunes  

NASA Astrophysics Data System (ADS)

Transgressive dune fields, which are active sand areas surrounded by vegetation, exist on many coasts. In some regions like in Fraser Island in Australia, small dunes shrink while large ones grow, although both experience the same climatic conditions. We propose a general mathematical model for the spatiotemporal dynamics of vegetation cover on sand dunes and focus on the dynamics of transgressive dunes. Among other possibilities, the model predicts growth parallel to the wind with shrinkage perpendicular to the wind, where, depending on geometry and size, a transgressive dune can initially grow although eventually shrink. The larger is the initial area the slower its stabilization process. The model’s predictions are supported by field observations from Fraser Island in Australia.

Yizhaq, Hezi; Ashkenazy, Yosef; Levin, Noam; Tsoar, Haim

2013-10-01

188

Spatio-temporal Feature Recogntion using Randomised Ferns  

E-print Network

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

Paris-Sud XI, Université de

189

Mercury Toolset for Spatiotemporal Metadata  

NASA Astrophysics Data System (ADS)

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.

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

2010-06-01

190

Spatiotemporal electromagnetic soliton and spatial ring formation in nonlinear metamaterials  

SciTech Connect

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.

Zhang Jinggui; Wen Shuangchun; Xiang Yuanjiang; Wang Youwen; Luo Hailu [Key Laboratory for Micro/Nano Optoelectronic Devices of Ministry of Education, School of Computer and Communication, Hunan University, Changsha 410082 (China)

2010-02-15

191

Spatiotemporal electromagnetic soliton and spatial ring formation in nonlinear metamaterials  

NASA Astrophysics Data System (ADS)

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.

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

2010-02-01

192

Spatiotemporal representation of cardiac vectorcardiogram (VCG) signals  

PubMed Central

Background Vectorcardiogram (VCG) signals monitor both spatial and temporal cardiac electrical activities along three orthogonal planes of the body. However, the absence of spatiotemporal resolution in conventional VCG representations is a major impediment for medical interpretation and clinical usage of VCG. This is especially so because time-domain features of 12-lead ECG, instead of both spatial and temporal characteristics of VCG, are widely used for the automatic assessment of cardiac pathological patterns. Materials and methods We present a novel representation approach that captures critical spatiotemporal heart dynamics by displaying the real time motion of VCG cardiac vectors in a 3D space. Such a dynamic display can also be realized with only one lead ECG signal (e.g., ambulatory ECG) through an alternative lag-reconstructed ECG representation from nonlinear dynamics principles. Furthermore, the trajectories are color coded with additional dynamical properties of space-time VCG signals, e.g., the curvature, speed, octant and phase angles to enhance the information visibility. Results In this investigation, spatiotemporal VCG signal representation is used to characterize various spatiotemporal pathological patterns for healthy control (HC), myocardial infarction (MI), atrial fibrillation (AF) and bundle branch block (BBB). The proposed color coding scheme revealed that the spatial locations of the peak of T waves are in the Octant 6 for the majority (i.e., 74 out of 80) of healthy recordings in the PhysioNet PTB database. In contrast, the peak of T waves from 31.79% (117/368) of MI subjects are found to remain in Octant 6 and the rest (68.21%) spread over all other octants. The spatiotemporal VCG signal representation is shown to capture the same important heart characteristics as the 12-lead ECG plots and more. Conclusions Spatiotemporal VCG signal representation is shown to facilitate the characterization of space-time cardiac pathological patterns and enhance the automatic assessment of cardiovascular diseases. PMID:22463593

2012-01-01

193

Gestural Interaction with Spatiotemporal Linked Open Data Gestural Interaction with Spatiotemporal  

E-print Network

the Brazilian Amazon Rain- forest. Keywords: Gestural interaction, spatiotemporal phenomena, Linked Open Data. 1 of Linked Open Data about the deforestation of the Brazilian Amazon Rainforest and related ecological

Köbben, Barend

194

A Comparison of Neighbourhood Selection Techniques in Spatio-Temporal Forecasting Models  

NASA Astrophysics Data System (ADS)

Spatio-temporal neighbourhood (STN) selection is an important part of the model building procedure in spatio-temporal forecasting. The STN can be defined as the set of observations at neighbouring locations and times that are relevant for forecasting the future values of a series at a particular location at a particular time. Correct specification of the STN can enable forecasting models to capture spatio-temporal dependence, greatly improving predictive performance. In recent years, deficiencies have been revealed in models with globally fixed STN structures, which arise from the problems of heterogeneity, nonstationarity and nonlinearity in spatio-temporal processes. Using the example of a large dataset of travel times collected on London's road network, this study examines the effect of various STN selection methods drawn from the variable selection literature, varying from simple forward/backward subset selection to simultaneous shrinkage and selection operators. The results indicate that STN selection methods based on L1 penalisation are effective. In particular, the maximum concave penalty (MCP) method selects parsimonious models that produce good forecasting performance.

Haworth, J.; Cheng, T.

2014-11-01

195

Spatio-Temporal Chaos in Thermal Convection  

NASA Astrophysics Data System (ADS)

In this talk I will report on experimental and theoretical results on the pattern-formation processes occuring in Rayleigh-Benard convection (RBC). After an introduction to pattern-formation in extended systems I will introduce RBC and discuss recent andvances in the understanding of spatio-temporal chaos. more details can be found at http://milou.msc.cornell.edu/stc.html

Bodenschatz, Eberhard

1999-11-01

196

ORIGINAL PAPER Regional landslide susceptibility: spatiotemporal  

E-print Network

ORIGINAL PAPER Regional landslide susceptibility: spatiotemporal variations under dynamic soil / Accepted: 25 April 2011 Ã? 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

197

Application of kinetic theory models in spatiotemporal flows for polymer solutions, liquid crystals and polymer melts using the CONNFFESSIT approach  

Microsoft Academic Search

Three kinetic theory models are used to predict the spatiotemporal stress and velocity fields that arise in the startup of Couette flow. The models considered do not have analytic closed-form expressions for the stress tensor. Nevertheless, using a combined finite-element and Brownian dynamics technique (CONNFFESSIT), numerical solutions can be found. To describe the dynamics for dilute polymer solutions, a dumbbell

C. C. Hua; J. D. Schieber

1996-01-01

198

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

NASA Technical Reports Server (NTRS)

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.

Liu, Siuying Raymond; Indebetouw, Guy

1992-01-01

199

Spatio-temporal pattern formation on spherical surfaces: numerical simulation and application to solid tumour growth  

Microsoft Academic Search

.   In this paper we examine spatio-temporal pattern formation in reaction-diffusion systems on the surface of the unit sphere\\u000a in 3D. We first generalise the usual linear stability analysis for a two-chemical system to this geometrical context. Noting\\u000a the limitations of this approach (in terms of rigorous prediction of spatially heterogeneous steady-states) leads us to develop,\\u000a as an alternative, a

M. A. J. Chaplain; M. Ganesh; I. G. Graham

2001-01-01

200

An Integrated Framework of Spatiotemporal Dynamics of Binocular Rivalry  

PubMed Central

Fluctuations in perceptual dominance during binocular rivalry exhibit several hallmark characteristics. First, dominance switches are not periodic but, instead, stochastic: perception changes unpredictably. Second, despite being stochastic, average durations of rivalry dominance vary dependent on the strength of the rival stimuli: variations in contrast, luminance, or spatial frequency produce predictable changes in average dominance durations and, hence, in alternation rate. Third, perceptual switches originate locally and spread globally over time, sometimes as traveling waves of dominance: rivalry transitions are spatiotemporal events. This essay (1) reviews recent advances in our understanding of the bases of these three hallmark characteristics of binocular rivalry dynamics and (2) provides an integrated framework to account for those dynamics using cooperative and competitive spatial interactions among local neural circuits distributed over the visual field's retinotopic map. We close with speculations about how that framework might incorporate top-down influences on rivalry dynamics. PMID:21941473

Kang, Min-Suk; Blake, Randolph

2011-01-01

201

Working with Spatio-Temporal Data Type  

NASA Astrophysics Data System (ADS)

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.

Raza, A.

2012-07-01

202

Approach of the spatiotemporal prediction using vectorial geographic data  

Microsoft Academic Search

Spatial evolutions of the anthropized ecosystems and the progressive transformation of spaces in the course of time emerge more and more as a special interest issue in research about the environment. This evolution can present a large preoccupation in space accommodation and environmental domains, and it gives rise to a considerable problem in terms of prospective. How will be the

T. Mezzadri-Centeno; D. Saint-Joan; Jacky Desachy; F. Vidal

1996-01-01

203

Spatio-temporal prediction for adaptive optics wavefront reconstructors  

Microsoft Academic Search

By taking advantage of the spatial and temporal correlation of the phase of the atmospherically-aberrated optical wavefront, we show in extensive computer simulations that the effect of the time delay in the servo loop of an adaptive optics system can be greatly reduced. Further work based on open-loop Shack-Hartmann sensor data from a 1.6-m telescope confirms the results of the

Michael Lloyd-Hart; Patrick McGuire

1996-01-01

204

The Cellular EJC Interactome Reveals Higher Order mRNP Structure and an EJC-SR Protein Nexus  

PubMed Central

SUMMARY In addition to sculpting eukaryotic transcripts by removing introns, pre-mRNA splicing greatly impacts protein composition of the emerging mRNP. The exon junction complex (EJC), deposited upstream of exon-exon junctions after splicing, is a major constituent of spliced mRNPs. Here we report comprehensive analysis of the endogenous human EJC protein and RNA interactomes. We confirm that the major “canonical” EJC occupancy site in vivo lies 24 nucleotides upstream of exon junctions and that the majority of exon junctions carry an EJC. Unexpectedly, we find that endogenous EJCs multimerize with one another and with numerous SR proteins to form megadalton sized complexes in which SR proteins are super-stoichiometric to EJC core factors. This tight physical association may explain known functional parallels between EJCs and SR proteins. Further, their protection of long mRNA stretches from nuclease digestion suggests that endogenous EJCs and SR proteins cooperate to promote mRNA packaging and compaction. PMID:23084401

Singh, Guramrit; Kucukural, Alper; Cenik, Can; Leszyk, John D.; Shaffer, Scott A.; Weng, Zhiping; Moore, Melissa J.

2012-01-01

205

Optimal spatiotemporal reduced order modeling for nonlinear dynamical systems  

NASA Astrophysics Data System (ADS)

Proposed in this dissertation is a novel reduced order modeling (ROM) framework called optimal spatiotemporal reduced order modeling (OPSTROM) for nonlinear dynamical systems. The OPSTROM approach is a data-driven methodology for the synthesis of multiscale reduced order models (ROMs) which can be used to enhance the efficiency and reliability of under-resolved simulations for nonlinear dynamical systems. In the context of nonlinear continuum dynamics, the OPSTROM approach relies on the concept of embedding subgrid-scale models into the governing equations in order to account for the effects due to unresolved spatial and temporal scales. Traditional ROMs neglect these effects, whereas most other multiscale ROMs account for these effects in ways that are inconsistent with the underlying spatiotemporal statistical structure of the nonlinear dynamical system. The OPSTROM framework presented in this dissertation begins with a general system of partial differential equations, which are modified for an under-resolved simulation in space and time with an arbitrary discretization scheme. Basic filtering concepts are used to demonstrate the manner in which residual terms, representing subgrid-scale dynamics, arise with a coarse computational grid. Models for these residual terms are then developed by accounting for the underlying spatiotemporal statistical structure in a consistent manner. These subgrid-scale models are designed to provide closure by accounting for the dynamic interactions between spatiotemporal macroscales and microscales which are otherwise neglected in a ROM. For a given resolution, the predictions obtained with the modified system of equations are optimal (in a mean-square sense) as the subgrid-scale models are based upon principles of mean-square error minimization, conditional expectations and stochastic estimation. Methods are suggested for efficient model construction, appraisal, error measure, and implementation with a couple of well-known time-discretization schemes. Four nonlinear dynamical systems serve as testbeds to demonstrate the technique. First we consider an autonomous van der Pol oscillator for which all trajectories evolve to self-sustained limit cycle oscillations. Next we investigate a forced Duffing oscillator for which the response may be regular or chaotic. In order to demonstrate application for a problem in nonlinear wave propagation, we consider the viscous Burgers equation with large-amplitude inflow disturbances. For the fourth and final system, we analyze the nonlinear structural dynamics of a geometrically nonlinear beam under the influence of time-dependent external forcing. The practical utility of the proposed subgrid-scale models is enhanced if it can be shown that certain statistical moments amongst the subgrid-scale dynamics display to some extent the following properties: spatiotemporal homogeneity, ergodicity, smooth scaling with respect to the system parameters, and universality. To this end, we characterize the subgrid-scale dynamics for each of the four problems. The results in this dissertation indicate that temporal homogeneity and ergodicity are excellent assumptions for both regular and chaotic response types. Spatial homogeneity is found to be a very good assumption for the nonlinear beam problem with models based upon single-point but not multi-point spatial stencils. The viscous Burgers flow, however, requires spatially heterogeneous models regardless of the stencil. For each of the four problems, the required statistical moments display a functional dependence which can easily be characterized with respect to the physical parameters and the computational grid. This observed property, in particular, greatly simplifies model construction by way of moment estimation. We investigate the performance of the subgrid-scale models with under-resolved simulations (in space and time) and various discretization schemes. For the canonical Duffing and van der Pol oscillators, the subgrid-scale models are found to improve the accuracy of under-resolved time-marching and time-s

LaBryer, Allen

206

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

PubMed Central

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

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

2011-01-01

207

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

PubMed

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

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

2014-09-01

208

Spatiotemporal coupling in dispersive nonlinear planar waveguides  

NASA Astrophysics Data System (ADS)

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

Ryan, Andrew T.; Agrawal, Govind P.

1995-12-01

209

The Spatio-Temporal Structure of the Magnetosphere during Magnetic Storms  

NASA Astrophysics Data System (ADS)

Input-output analysis of geomagnetic indices and ground magnetometer measurements as the output and the solar wind as variables as the input is used to generate a spatio-temporal dynamical model of the magnetospheric dynamics. The data of magnetic field perturbation with 1-minute resolution ground stations during 2002 are used to study this spatio-temporal structure, mainly on high latitude magnetic perturbations. All of the 57 ground magnetometers are from 3 station group--CANOPUS(13), IMAGE(26) and WDC(18). A technique that utilize the daily rotation of the Earth as a longitudinal sampling mechanism is used to construct a two dimensional representation of the high latitude magnetic perturbations both in magnetic latitude and local time. The data of magnetic field perturbation at the magnetometer stations are used as the output of the nonlinear system driven by the solar wind. The model is used to predict the spatial structure of geomagnetic disturbances during intense geospace storms.

Chen, J.; Sharma, A.

2005-05-01

210

Spatio-temporal dynamics of the magnetosphere during geospace storms  

NASA Astrophysics Data System (ADS)

The magnetospheric response to strong driving by the solar wind is highly structured, and spatially resolved data are essential for the understanding of the spatio-temporal dynamics. The global features of the magnetosphere have been studied extensively using nonlinear dynamical techniques. A database of the solar wind data from ISEE3 and IMP8 spacecraft, and ground-based magnetometer data from high latitude stations [Kamide et al., JGR, 17,705, 1998] is used to study the magnetospheric response to solar wind variables by mutual information functions. A key feature of the mutual information function is its ability to bring out the linear as well as nonlinear correlations and such functions are needed to study the magnetospheric dynamics, which is inherently nonlinear. The minimum window length required for computing robust functions is found to be about 6 hrs. Another window length of 24 hrs is used in these studies to analyze the dynamics on longer time scales. The spreads in the average mutual information show strong correlations with the solar wind convective electric field and the sudden changes in the dynamic pressure. The time evolution of mutual information shows a westward expansion of the disturbed region in the night side magnetosphere, starting from near the midnight sectors. In order to study the spatial structure in more detail the magnetic field perturbation at 39 ground stations during year 2002 and the corresponding solar wind data are compiled. The ground magnetometer data are from the two chains of stations: CANOPUS (13) and IMAGE (26). This new data set, with 1-minute resolution, is used to study the spatio-temporal structure. A technique that utilizes the daily rotation of the Earth as a longitudinal sampling process is used to construct a two dimensional representation of the high latitude magnetic perturbations both in magnetic latitude and magnetic local time. This model is used to predict the spatial structure of geomagnetic disturbances during intense geospace substorms, which are important natural hazards.

Chen, J.; Sharma, A.; Edwards, J. W.; Shao, X.; Kamide, Y.

2007-05-01

211

Climate-mediated spatiotemporal variability in terrestrial productivity across Europe  

NASA Astrophysics Data System (ADS)

Quantifying the interannual variability (IAV) of the terrestrial ecosystem productivity and its sensitivity to climate is crucial for improving carbon budget predictions. In this context it is necessary to disentangle the influence of climate from impacts of other mechanisms underlying the spatiotemporal patterns of IAV of the ecosystem productivity. In this study we investigated the spatiotemporal patterns of IAV of historical observations of European crop yields in tandem with a set of climate variables. We further evaluated if relevant remote-sensing retrievals of NDVI (normalized difference vegetation index) and FAPAR (fraction of absorbed photosynthetically active radiation) depict a similar behaviour. Our results reveal distinct spatial patterns in the IAV of the analysed proxies linked to terrestrial productivity. In particular, we find higher IAV in water-limited regions of Europe (Mediterranean and temperate continental Europe) compared to other regions in both crop yield and remote-sensing observations. Our results further indicate that variations in the water balance during the active growing season exert a more pronounced and direct effect than variations of temperature on explaining the spatial patterns in IAV of productivity-related variables in temperate Europe. Overall, we observe a temporally increasing trend in the IAV of terrestrial productivity and an increasing sensitivity of productivity to water availability in dry regions of Europe during the 1975-2009 period. In the same regions, a simultaneous increase in the IAV of water availability was detected. These findings suggest intricate responses of carbon fluxes to climate variability in Europe and that the IAV of terrestrial productivity has become potentially more sensitive to changes in water availability in the dry regions in Europe. The changing sensitivity of terrestrial productivity accompanied by the changing IAV of climate is expected to impact carbon stocks and the net carbon balance of European ecosystems.

Wu, X.; Babst, F.; Ciais, P.; Frank, D.; Reichstein, M.; Wattenbach, M.; Zang, C.; Mahecha, M. D.

2014-06-01

212

Size-dependent diffusion promotes the emergence of spatiotemporal patterns  

NASA Astrophysics Data System (ADS)

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.

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

2014-07-01

213

Degree-adjusted algorithm for prioritisation of candidate disease genes from gene expression and protein interactome.  

PubMed

Computational methods play an important role in the disease genes prioritisation by integrating many kinds of data sources such as gene expression, functional annotations and protein-protein interactions. However, the existing methods usually perform well in predicting highly linked genes, whereas they work quite poorly for loosely linked genes. Motivated by this observation, a degree-adjusted strategy is applied to improve the algorithm that was proposed earlier for the prediction of disease genes from gene expression and protein interactions. The authors also showed that the modified method is good at identifying loosely linked disease genes and the overall performance gets enhanced accordingly. This study suggests the importance of statistically adjusting the degree distribution bias in the background network for network-based modelling of complex diseases. PMID:25014224

Wang, Yichuan; Fang, Haiyang; Yang, Tinghong; Wu, Duzhi; Zhao, Jing

2014-04-01

214

Bayesian spatiotemporal modelling for the assessment of short-term exposure to particle pollution in urban areas  

PubMed Central

This paper describes a Bayesian hierarchical approach to predict short-term concentrations of particle pollution in an urban environment, with application to inhalable particulate matter (PM10) in Greater London. We developed and compared several spatiotemporal models that differently accounted for factors affecting the spatiotemporal properties of particle concentrations. We considered two main source contributions to ambient measurements: (i) the long-range transport of the secondary fraction of particles, which temporal variability was described by a latent variable derived from rural concentrations; and (ii) the local primary component of particles (traffic- and non-traffic-related) captured by the output of the dispersion model ADMS-Urban, which site-specific effect was described by a Bayesian kriging. We also assessed the effect of spatiotemporal covariates, including type of site, daily temperature to describe the seasonal changes in chemical processes affecting local PM10 concentrations that are not considered in local-scale dispersion models and day of the week to account for time-varying emission rates not available in emissions inventories. The evaluation of the predictive ability of the models, obtained via a cross-validation approach, revealed that concentration estimates in urban areas benefit from combining the city-scale particle component and the long-range transport component with covariates that account for the residual spatiotemporal variation in the pollution process. PMID:24280683

Pirani, Monica; Gulliver, John; Fuller, Gary W; Blangiardo, Marta

2014-01-01

215

Bayesian spatiotemporal modelling for the assessment of short-term exposure to particle pollution in urban areas.  

PubMed

This paper describes a Bayesian hierarchical approach to predict short-term concentrations of particle pollution in an urban environment, with application to inhalable particulate matter (PM10) in Greater London. We developed and compared several spatiotemporal models that differently accounted for factors affecting the spatiotemporal properties of particle concentrations. We considered two main source contributions to ambient measurements: (i) the long-range transport of the secondary fraction of particles, which temporal variability was described by a latent variable derived from rural concentrations; and (ii) the local primary component of particles (traffic- and non-traffic-related) captured by the output of the dispersion model ADMS-Urban, which site-specific effect was described by a Bayesian kriging. We also assessed the effect of spatiotemporal covariates, including type of site, daily temperature to describe the seasonal changes in chemical processes affecting local PM10 concentrations that are not considered in local-scale dispersion models and day of the week to account for time-varying emission rates not available in emissions inventories. The evaluation of the predictive ability of the models, obtained via a cross-validation approach, revealed that concentration estimates in urban areas benefit from combining the city-scale particle component and the long-range transport component with covariates that account for the residual spatiotemporal variation in the pollution process. PMID:24280683

Pirani, Monica; Gulliver, John; Fuller, Gary W; Blangiardo, Marta

2014-01-01

216

Global identification of O-GlcNAc transferase (OGT) interactors by a human proteome microarray and the construction of an OGT interactome.  

PubMed

O-Linked ?-N-acetylglucosamine (O-GlcNAcylation) is an important protein PTM, which is very abundant in mammalian cells. O-GlcNAcylation is catalyzed by O-GlcNAc transferase (OGT), whose substrate specificity is believed to be regulated through interactions with other proteins. There are a handful of known human OGT interactors, which is far from enough for fully elucidating the substrate specificity of OGT. To address this challenge, we used a human proteome microarray containing ~17,000 affinity-purified human proteins to globally identify OGT interactors and identified 25 OGT-binding proteins. Bioinformatics analysis showed that these interacting proteins play a variety of roles in a wide range of cellular functions and are highly enriched in intra-Golgi vesicle-mediated transport and vitamin biosynthetic processes. Combining newly identified OGT interactors with the interactors identified prior to this study, we have constructed the first OGT interactome. Bioinformatics analysis suggests that the OGT interactome plays important roles in protein transportation/localization and transcriptional regulation. The novel OGT interactors that we identified in this study could serve as a starting point for further functional analysis. Because of its high-throughput and parallel analysis capability, we strongly believe that protein microarrays could be easily applied for the global identification of regulators for other key enzymes. PMID:24536041

Deng, Rui-Ping; He, Xiang; Guo, Shu-Juan; Liu, Wei-Feng; Tao, Yong; Tao, Sheng-Ce

2014-05-01

217

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

PubMed Central

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

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

218

Workload induced spatio-temporal distortions and safety of flight  

SciTech Connect

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.

Barrett, C.L.; Weisgerber, S.A. (Los Alamos National Lab., NM (USA); Naval Weapons Center, China Lake, CA (USA))

1989-01-01

219

Spatiotemporal Data Mining, Analysis, and Visualization of Human Activity Data  

ERIC Educational Resources Information Center

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…

Li, Xun

2012-01-01

220

Blind adaptive spatiotemporal filtering for wide-band cyclostationary signals  

NASA Astrophysics Data System (ADS)

An algorithm that blindly adapts spatiotemporal filters to extract from sensor array data one or more desired signals having known cyclostationarity properties is presented. It can perform well without knowledge of a training signal, spatiotemporal characteristics of the interference and noise, the directions of arrival of the desired signal(s), or any array calibration data.

Schell, Stephan V.; Gardner, William A.

1993-05-01

221

Online Identification of Nonlinear Spatiotemporal Systems Using Kernel Learning Approach  

Microsoft Academic Search

The identification of nonlinear spatiotemporal sys- tems is of significance to engineering practice, since it can always provide useful insight into the underlying nonlinear mechanism and physical characteristics under study. In this paper, nonlinear spatiotemporal system models are transformed into a class of multi-input-multi-output (MIMO) partially linear systems (PLSs), and an effective online identification algorithm is therefore proposed by using

Hanwen Ning; Xingjian Jing; Li Cheng

2011-01-01

222

Motion analysis and segmentation through spatio-temporal slices processing  

Microsoft Academic Search

This paper presents new approaches in characterizing and segmenting the content of video. These approaches are developed based upon the pattern analysis of spatio-temporal slices. While tradi- tional approaches to motion sequence analysis tend to formulate computational methodologies on two or three adjacent frames, spatio-temporal slices provide rich visual patterns along a larger temporal scale. In this paper, we first

Chong-Wah Ngo; Ting-Chuen Pong; Hong-Jiang Zhang

2003-01-01

223

Impulsive control and synchronization of spatiotemporal chaos q  

E-print Network

Impulsive control and synchronization of spatiotemporal chaos q Anmar Khadra a,1 , Xinzhi Liu a Accepted 10 January 2004 Communicated by Prof. Ji-Huaun He Abstract The impulsive control of spatiotemporal is determined and an estimate for the basin of attraction is given in terms of the impulse durations

Shen, Xuemin "Sherman"

224

Walking the interactome for candidate prioritization in exome sequencing studies of Mendelian diseases  

PubMed Central

Motivation: Whole-exome sequencing (WES) has opened up previously unheard of possibilities for identifying novel disease genes in Mendelian disorders, only about half of which have been elucidated to date. However, interpretation of WES data remains challenging. Results: Here, we analyze protein–protein association (PPA) networks to identify candidate genes in the vicinity of genes previously implicated in a disease. The analysis, using a random-walk with restart (RWR) method, is adapted to the setting of WES by developing a composite variant-gene relevance score based on the rarity, location and predicted pathogenicity of variants and the RWR evaluation of genes harboring the variants. Benchmarking using known disease variants from 88 disease-gene families reveals that the correct gene is ranked among the top 10 candidates in ?50% of cases, a figure which we confirmed using a prospective study of disease genes identified in 2012 and PPA data produced before that date. We implement our method in a freely available Web server, ExomeWalker, that displays a ranked list of candidates together with information on PPAs, frequency and predicted pathogenicity of the variants to allow quick and effective searches for candidates that are likely to reward closer investigation. Availability and implementation: http://compbio.charite.de/ExomeWalker Contact: peter.robinson@charite.de PMID:25078397

Smedley, Damian; Köhler, Sebastian; Czeschik, Johanna Christina; Amberger, Joanna; Bocchini, Carol; Hamosh, Ada; Veldboer, Julian; Zemojtel, Tomasz; Robinson, Peter N.

2014-01-01

225

Spatio-temporal dynamics of glycolysis in cell layers. A mathematical model.  

PubMed

Glycolytic oscillations occur in many cell types and have been intensively studied in yeast. Recent experimental and theoretical research has been focussed on the oscillatory dynamics and the synchronisation mechanism in stirred yeast cell suspensions. Here we are interested in the spatio-temporal organisation of glycolysis in cell layers. To this end we study a grid of a few thousand compartments each containing a cell. The intracellular dynamics is described by a core model of glycolysis. The compartments can exchange metabolites via diffusion. The conditions for oscillatory dynamics in a single compartment are investigated by bifurcation analysis. The spatio-temporal behaviour of the cell layer is studied by simulations. The model predicts the propagation of repetitive wave fronts induced by a substrate gradient. The formation of these waves crucially depends on the diffusive exchange of the reaction product between cells. Depending on the kinetic parameters complex spatio-temporal behaviour such as periodic termination of waves can arise. In these cases the cellular oscillation characteristics depend on the location of the cell in the array. PMID:19837130

Schütze, Jana; Wolf, Jana

2010-02-01

226

Spatiotemporal multifractal characteristics of electromagnetic radiation in response to deep coal rock bursts  

NASA Astrophysics Data System (ADS)

Dynamic collapses of deeply mined coal rocks are severe threats to miners, in order to predict the collapses more accurately using electromagnetic radiation (EMR), we investigate the spatiotemporal multifractal characteristics and formation mechanism of EMR induced by underground coal mining. Coal rock in the burst-prone zone often exchanges materials and energy with its environment and gradually transits from its original stable equilibrium structure to a non-equilibrium dissipative structure with implicit spatiotemporal complexity or multifractal structures, resulting in temporal variation in multifractal EMR. The inherent law of EMR time series during damage evolution was analyzed by using time-varying multifractal theory. Results show that the time-varying multifractal characteristics of EMR are determined by damage evolutions process, the dissipated energy caused by damage evolutions such as crack propagation, fractal sliding and shearing can be regarded as the fingerprint of various EMR micro-mechanics. Dynamic spatiotemporal multifractal spectrum of EMR considers both spatial (multiple fractures) and temporal (dynamic evolution) characteristics of coal rocks, and records the dynamic evolution processes of rock bursts. Thus, it can be used to evaluate the coal deformation and fracture process. The study is of significance for us to in-depth understand EMR mechanism and to increase the accuracy of applying the EMR method to forecast dynamic disasters.

Shaobin, H.; Enyuan, W.; Xiaofei, L.

2014-04-01

227

Impact of spatiotemporal fluctuations in airborne chemical concentration on toxic hazard assessment.  

PubMed

Models widely used to assess atmospheric chemical-dispersion hazards for emergency response rely on acute exposure guideline level (AEGL) or similar concentration guidelines to map geographic areas potentially affected by corresponding levels of toxic severity. By ignoring substantial, random variability in concentration over time and space, such standard methods routinely underestimate the size of potentially affected areas. Underestimation due to temporal fluctuation - applicable to chemicals like hydrogen cyanide (HCN) for which peak concentrations best predict acute toxicity - becomes magnified by spatial fluctuation, defined as heterogeneity in average concentration at each location relative to standard-method predictions. The combined impact of spatiotemporal fluctuation on size of assessed threat areas was studied using a statistical-simulation assessment method calibrated to Joint Urban 2003 Oklahoma City field-tracer data. For a hypothetical 60-min urban release scenario involving HCN gas, the stochastic method predicted that lethal/severe effects could occur in an area 18 or 25 times larger than was predicted by standard methods targeted to a 60-min AEGL, assuming wind speeds > or =2.0 or < or =1.5m/s, respectively. The underestimation doubled when the standard method was targeted to a 10-min AEGL. Further research and field data are needed for improved stochastic methods to assess spatiotemporal fluctuation effects. PMID:17706864

Bogen, K T; Gouveia, F J

2008-03-21

228

Spatio-temporal Transmission and Environmental Determinants of Schistosomiasis Japonica in Anhui Province, China  

PubMed Central

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

Hu, Yi; Li, Rui; Bergquist, Robert; Lynn, Henry; Gao, Fenghua; Wang, Qizhi; Zhang, Shiqing; Sun, Liqian; Zhang, Zhijie; Jiang, Qingwu

2015-01-01

229

Integrating environmental isoscapes for spatiotemporal assignment  

NASA Astrophysics Data System (ADS)

Numerous case studies in the ecological and forensic fields have illustrated the potential utility of light stable isotopes as tracers of the geographic origin of biological materials. However, a number of critical challenges continue to limit the application of these tools, among them (1) limitations to our knowledge of isotopic values expected for materials formed at particular locations and times, (2) uncertainty in our understanding of the interplay between temporal and spatial variation in the isotope 'signature' transferred to isotopic materials, and (3) lack of robust, widely used models for quantitative statistical assessment of spatiotemporal origin and associated uncertainty. In order to acknowledge and address each of these limitations, we present new models and analysis of spatiotemporal variation in the stable isotope ratios of hydrogen, oxygen, and strontium in the environment, representing three isotope systems with strong and complementary potential for provenancing applications. We demonstrate a statistical framework for the integration of these isoscapes in assignment problems and describe how this toolkit has been made broadly accessible through the IsoMAP web-GIS portal.

Bowen, G.; Bataille, C.; Kennedy, C.; Zhang, T.; West, J.

2012-04-01

230

CUTOFF: A spatio-temporal imputation method  

NASA Astrophysics Data System (ADS)

Missing values occur frequently in many different statistical applications and need to be dealt with carefully, especially when the data are collected spatio-temporally. We propose a method called CUTOFF imputation that utilizes the spatio-temporal nature of the data to accurately and efficiently impute missing values. The main feature of this method is that the estimate of a missing value is produced by incorporating similar observed temporal information from the value's nearest spatial neighbors. Extensions to this method are also developed to expand the method's ability to accommodate other data generating processes. We develop a cross-validation procedure that optimally chooses parameters for CUTOFF, which can be used by other imputation methods as well. We analyze some rainfall data from 78 gauging stations in the Murray-Darling Basin in Australia using the CUTOFF imputation method and compare its performance to four well-studied competing imputation methods, namely, k-nearest neighbors, singular value decomposition, multiple imputation and random forest. Empirical results show that our method captures the temporal patterns well and is effective at imputing large gaps in the data. Compared to the competing methods, CUTOFF is more accurate and much faster. We analyze further examples to demonstrate CUTOFF's applications to two different data sets and provide extra evidence of its validity and usefulness. We implement a simulation study based on the Murray-Darling Basin data to evaluate the method; the results show that our method performs well in both accuracy and computational efficiency.

Feng, Lingbing; Nowak, Gen; O'Neill, T. J.; Welsh, A. H.

2014-11-01

231

Bilinearity in Spatiotemporal Integration of Synaptic Inputs  

PubMed Central

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

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

2014-01-01

232

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

PubMed Central

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

2014-01-01

233

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

PubMed Central

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

Helwak, Aleksandra; Tollervey, David

2014-01-01

234

Genes involved in TGF?1-driven epithelial-mesenchymal transition of renal epithelial cells are topologically related in the human interactome map  

PubMed Central

Background Understanding how mesenchymal cells arise from epithelial cells could have a strong impact in unveiling mechanisms of epithelial cell plasticity underlying kidney regeneration and repair. In primary human tubular epithelial cells (HUTEC) under different TGF?1 concentrations we had observed epithelial-to-mesenchymal transition (EMT) but not epithelial-myofibroblast transdifferentiation. We hypothesized that the process triggered by TGF?1 could be a dedifferentiation event. The purpose of this study is to comprehensively delineate genetic programs associated with TGF?1-driven EMT in our in vitro model using gene expression profile on large-scale oligonucleotide microarrays. Results In HUTEC under TGF?1 stimulus, 977 genes were found differentially expressed. Thirty genes were identified whose expression depended directly on TGF?1 concentration. By mapping the differentially expressed genes in the Human Interactome Map using Cytoscape software, we identified a single scale-free network consisting of 2630 interacting proteins and containing 449 differentially expressed proteins. We identified 27 hub proteins in the interactome with more than 29 edges incident on them and encoded by differentially expressed genes. The Gene Ontology analysis showed an excess of up-regulated proteins involved in biological processes, such as "morphogenesis", "cell fate determination" and "regulation of development", and the most up-regulated genes belonged to these categories. In addition, 267 genes were mapped to the KEGG pathways and 14 pathways with more than nine differentially expressed genes were identified. In our model, Smad signaling was not the TGF?1 action effector; instead, the engagement of RAS/MAPK signaling pathway seems mainly to regulate genes involved in the cell cycle and proliferation/apoptosis. Conclusion Our present findings support the hypothesis that context-dependent EMT generated in our model by TGF?1 might be the outcome of a dedifferentiation. In fact: 1) the principal biological categories involved in the process concern morphogenesis and development; 2) the most up-regulated genes belong to these categories; and, finally, 3) some intracellular pathways are involved, whose engagement during kidney development and nephrogenesis is well known. These long-term effects of TGF?1 in HUTEC involve genes that are highly interconnected, thereby generating a scale-free network that we named the "TGF?1 interactome", whose hubs represent proteins that may have a crucial role for HUTEC in response to TGF?1. PMID:17953753

Campanaro, Stefano; Picelli, Simone; Torregrossa, Rossella; Colluto, Laura; Ceol, Monica; Del Prete, Dorella; D'Angelo, Angela; Valle, Giorgio; Anglani, Franca

2007-01-01

235

Characterizing configurations of fire ignition points through spatiotemporal point processes  

NASA Astrophysics Data System (ADS)

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.

Comas, C.; Costafreda-Aumedes, S.; Vega-Garcia, C.

2014-04-01

236

The use of spatio-temporal correlation to forecast critical transitions  

NASA Astrophysics Data System (ADS)

Complex dynamical systems may have critical thresholds at which the system shifts abruptly from one state to another. Such critical transitions have been observed in systems ranging from the human body system to financial markets and the Earth system. Forecasting the timing of critical transitions before they are reached is of paramount importance because critical transitions are associated with a large shift in dynamical regime of the system under consideration. However, it is hard to forecast critical transitions, because the state of the system shows relatively little change before the threshold is reached. Recently, it was shown that increased spatio-temporal autocorrelation and variance can serve as alternative early warning signal for critical transitions. However, thus far these second order statistics have not been used for forecasting in a data assimilation framework. Here we show that the use of spatio-temporal autocorrelation and variance in the state of the system reduces the uncertainty in the predicted timing of critical transitions compared to classical approaches that use the value of the system state only. This is shown by assimilating observed spatio-temporal autocorrelation and variance into a dynamical system model using a Particle Filter. We adapt a well-studied distributed model of a logistically growing resource with a fixed grazing rate. The model describes the transition from an underexploited system with high resource biomass to overexploitation as grazing pressure crosses the critical threshold, which is a fold bifurcation. To represent limited prior information, we use a large variance in the prior probability distributions of model parameters and the system driver (grazing rate). First, we show that the rate of increase in spatio-temporal autocorrelation and variance prior to reaching the critical threshold is relatively consistent across the uncertainty range of the driver and parameter values used. This indicates that an increase in spatio-temporal autocorrelation and variance are consistent predictors of a critical transition, even under the condition of a poorly defined system. Second, we perform data assimilation experiments using an artificial exhaustive data set generated by one realization of the model. To mimic real-world sampling, an observational data set is created from this exhaustive data set. This is done by sampling on a regular spatio-temporal grid, supplemented by sampling locations at a short distance. Spatial and temporal autocorrelation in this observational data set is calculated for different spatial and temporal separation (lag) distances. To assign appropriate weights to observations (here, autocorrelation values and variance) in the Particle Filter, the covariance matrix of the error in these observations is required. This covariance matrix is estimated using Monte Carlo sampling, selecting a different random position of the sampling network relative to the exhaustive data set for each realization. At each update moment in the Particle Filter, observed autocorrelation values are assimilated into the model and the state of the model is updated. Using this approach, it is shown that the use of autocorrelation reduces the uncertainty in the forecasted timing of a critical transition compared to runs without data assimilation. The performance of the use of spatial autocorrelation versus temporal autocorrelation depends on the timing and number of observational data. This study is restricted to a single model only. However, it is becoming increasingly clear that spatio-temporal autocorrelation and variance can be used as early warning signals for a large number of systems. Thus, it is expected that spatio-temporal autocorrelation and variance are valuable in data assimilation frameworks in a large number of dynamical systems.

Karssenberg, Derek; Bierkens, Marc F. P.

2010-05-01

237

A simple approach for predicting protein-protein interactions.  

PubMed

The availability of an increased number of fully sequenced genomes demands functional interpretation of the genomic information. Despite high throughput experimental techniques and in silico methods of predicting protein-protein interaction (PPI); the interactome of most organisms is far from completion. Thus, predicting the interactome of an organism is one of the major challenges in the post-genomic era. This manuscript describes Support Vector Machine (SVM) based models that have been developed for discriminating interacting and non-interacting pairs of proteins from their amino acid sequence. We have developed SVM models using various types of sequence compositions e.g. amino acid, dipeptide, biochemical property, split amino acid and pseudo amino acid composition. We also developed SVM models using evolutionary information in the form of Position Specific Scoring Matrix (PSSM) composition. We achieved maximum Matthews's correlation coefficient (MCC) of 1.00, 0.52 and 0.74 for Escherichia coli, Saccharomyces cerevisiae, and Helicobacter pylori, using dipeptide based SVM model at default threshold. It was observed that the performance of a prediction model depends on the dataset used for training and testing. In case of E. coli MCC decreased from 1.0 to 0.67 when evaluated on a new dataset. In order to understand PPI in different cellular environment, we developed species-specific and general models. It was observed that species-specific models are more accurate than general models. We conclude that the primary amino acid sequence based descriptors could be used to differentiate interacting from non-interacting protein pairs. Some amino acids tend to be favored in interacting pairs than non-interacting ones. Finally, a web server has been developed for predicting protein-protein interactions. PMID:20887258

Rashid, Mamoon; Ramasamy, Sumathy; Raghava, Gajendra P S

2010-11-01

238

A Spatio-Temporal Downscaler for Output From Numerical Models  

PubMed Central

Often, in environmental data collection, data arise from two sources: numerical models and monitoring networks. The first source provides predictions at the level of grid cells, while the second source gives measurements at points. The first is characterized by full spatial coverage of the region of interest, high temporal resolution, no missing data but consequential calibration concerns. The second tends to be sparsely collected in space with coarser temporal resolution, often with missing data but, where recorded, provides, essentially, the true value. Accommodating the spatial misalignment between the two types of data is of fundamental importance for both improved predictions of exposure as well as for evaluation and calibration of the numerical model. In this article we propose a simple, fully model-based strategy to downscale the output from numerical models to point level. The static spatial model, specified within a Bayesian framework, regresses the observed data on the numerical model output using spatially-varying coefficients which are specified through a correlated spatial Gaussian process. As an example, we apply our method to ozone concentration data for the eastern U.S. and compare it to Bayesian melding (Fuentes and Raftery 2005) and ordinary kriging (Cressie 1993; Chilès and Delfiner 1999). Our results show that our method outperforms Bayesian melding in terms of computing speed and it is superior to both Bayesian melding and ordinary kriging in terms of predictive performance; predictions obtained with our method are better calibrated and predictive intervals have empirical coverage closer to the nominal values. Moreover, our model can be easily extended to accommodate for the temporal dimension. In this regard, we consider several spatio-temporal versions of the static model. We compare them using out-of-sample predictions of ozone concentration for the eastern U.S. for the period May 1–October 15, 2001. For the best choice, we present a summary of the analysis. Supplemental material, including color versions of Figures 4, 5, 6, 7, and 8, and MCMC diagnostic plots, are available online. PMID:21113385

Berrocal, Veronica J.; Gelfand, Alan E.; Holland, David M.

2010-01-01

239

Systemic risk and spatiotemporal dynamics of the US housing market  

PubMed Central

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

Meng, Hao; Xie, Wen-Jie; Jiang, Zhi-Qiang; Podobnik, Boris; Zhou, Wei-Xing; Stanley, H. Eugene

2014-01-01

240

Systemic risk and spatiotemporal dynamics of the US housing market.  

PubMed

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

Meng, Hao; Xie, Wen-Jie; Jiang, Zhi-Qiang; Podobnik, Boris; Zhou, Wei-Xing; Stanley, H Eugene

2014-01-01

241

Systemic risk and spatiotemporal dynamics of the US housing market  

NASA Astrophysics Data System (ADS)

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.

Meng, Hao; Xie, Wen-Jie; Jiang, Zhi-Qiang; Podobnik, Boris; Zhou, Wei-Xing; Stanley, H. Eugene

2014-01-01

242

Searching for Cellular Partners of Hantaviral Nonstructural Protein NSs: Y2H Screening of Mouse cDNA Library and Analysis of Cellular Interactome  

PubMed Central

Hantaviruses (Bunyaviridae) are negative-strand RNA viruses with a tripartite genome. The small (S) segment encodes the nucleocapsid protein and, in some hantaviruses, also the nonstructural protein (NSs). The aim of this study was to find potential cellular partners for the hantaviral NSs protein. Toward this aim, yeast two-hybrid (Y2H) screening of mouse cDNA library was performed followed by a search for potential NSs protein counterparts via analyzing a cellular interactome. The resulting interaction network was shown to form logical, clustered structures. Furthermore, several potential binding partners for the NSs protein, for instance ACBD3, were identified and, to prove the principle, interaction between NSs and ACBD3 proteins was demonstrated biochemically. PMID:22506017

Parviainen, Ville; Vaheri, Antti; Renkonen, Risto; Bouloy, Michele; Plyusnin, Alexander

2012-01-01

243

Proteomic analysis of the SH2 domain-containing leukocyte protein of 76 kDa (SLP76) interactome in resting and activated primary mast cells [corrected].  

PubMed

We report the first proteomic analysis of the SLP76 interactome in resting and activated primary mouse mast cells. This was made possible by a novel genetic approach used for the first time here. It consists in generating knock-in mice that express signaling molecules bearing a C-terminal tag that has a high affinity for a streptavidin analog. Tagged molecules can be used as molecular baits to affinity-purify the molecular complex in which they are engaged, which can then be studied by mass spectrometry. We examined first SLP76 because, although this cytosolic adapter is critical for both T cell and mast cell activation, its role is well known in T cells but not in mast cells. Tagged SLP76 was expressed in physiological amounts and fully functional in mast cells. We unexpectedly found that SLP76 is exquisitely sensitive to mast cell granular proteases, that Zn(2+)-dependent metalloproteases are especially abundant in mast cells and that they were responsible for SLP76 degradation. Adding a Zn(2+) chelator fully protected SLP76 in mast cell lysates, thereby enabling an efficient affinity-purification of this adapter with its partners. Label-free quantitative mass spectrometry analysis of affinity-purified SLP76 interactomes uncovered both partners already described in T cells and novel partners seen in mast cells only. Noticeably, molecules inducibly recruited in both cell types primarily concur to activation signals, whereas molecules recruited in activated mast cells only are mostly associated with inhibition signals. The transmembrane adapter LAT2, and the serine/threonine kinase with an exchange factor activity Bcr were the most recruited molecules. Biochemical and functional validations established the unexpected finding that Bcr is recruited by SLP76 and positively regulates antigen-induced mast cell activation. Knock-in mice expressing tagged molecules with a normal tissue distribution and expression therefore provide potent novel tools to investigate signalosomes and to uncover novel signaling molecules in mast cells. PMID:23820730

Bounab, Yacine; Hesse, Anne-Marie-; Iannascoli, Bruno; Grieco, Luca; Couté, Yohann; Niarakis, Anna; Roncagalli, Romain; Lie, Eunkyung; Lam, Kong-Peng; Demangel, Caroline; Thieffry, Denis; Garin, Jérôme; Malissen, Bernard; Daëron, Marc

2013-10-01

244

Spatiotemporal complexity of the aortic sinus vortex  

NASA Astrophysics Data System (ADS)

The aortic sinus vortex is a classical flow structure of significant importance to aortic valve dynamics and the initiation and progression of calcific aortic valve disease. We characterize the spatiotemporal characteristics of aortic sinus vortex dynamics in relation to the viscosity of blood analog solution as well as heart rate. High-resolution time-resolved (2 kHz) particle image velocimetry was conducted to capture 2D particle streak videos and 2D instantaneous velocity and streamlines along the sinus midplane using a physiological but rigid aorta model fitted with a porcine bioprosthetic heart valve. Blood analog fluids used include a water-glycerin mixture and saline to elucidate the sensitivity of vortex dynamics to viscosity. Experiments were conducted to record 10 heart beats for each combination of blood analog and heart rate condition. Results show that the topological characteristics of the velocity field vary in timescales as revealed using time bin-averaged vectors and corresponding instantaneous streamlines. There exist small timescale vortices and a large timescale main vortex. A key flow structure observed is the counter vortex at the upstream end of the sinus adjacent to the base (lower half) of the leaflet. The spatiotemporal complexity of vortex dynamics is shown to be profoundly influenced by strong leaflet flutter during systole with a peak frequency of 200 Hz and peak amplitude of 4 mm observed in the saline case. While fluid viscosity influences the length and timescales as well as the introduction of leaflet flutter, heart rate influences the formation of counter vortex at the upstream end of the sinus. Higher heart rates are shown to reduce the strength of the counter vortex that can greatly influence the directionality and strength of shear stresses along the base of the leaflet. This study demonstrates the impact of heart rate and blood analog viscosity on aortic sinus hemodynamics.

Moore, Brandon; Dasi, Lakshmi Prasad

2014-07-01

245

Transient dynamics and rhythm coordination of inferior olive spatio-temporal patterns  

PubMed Central

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

Latorre, Roberto; Aguirre, Carlos; Rabinovich, Mikhail I.; Varona, Pablo

2013-01-01

246

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)...

247

Daily spatiotemporal precipitation simulation using latent and transformed Gaussian processes  

E-print Network

Daily spatiotemporal precipitation simulation using latent and transformed Gaussian processes precipitation generator that yields spatially consistent gridded quantitative precipitation realizations is described. The methodology relies on a latent Gaussian process to drive precipitation occurrence

Katz, Richard

248

Modelling pandemic influenza progression using Spatiotemporal Epidemiological Modeller (STEM)  

E-print Network

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 ...

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

2009-01-01

249

Spatiotemporal Temperature Distribution and Cancer Cell Death in Response to Extracellular Hyperthermia Induced by Gold Nanorods  

PubMed Central

Plasmonic nanoparticles have shown promise in hyperthermic cancer therapy, both in vitro and in vivo. Previous reports have described hyperthermic ablation using targeted and non-targeted nanoparticles internalized by cancer cells, but most reports do not describe a theoretical analysis for determining optimal parameters. The focus of the current research was first to evaluate the spatiotemporal temperature distribution and cell death induced by extracellular hyperthermia in which gold nanorods (GNRs) were maintained in the dispersion outside human prostate cancer cells. The nanorod dispersion was irradiated with near infrared (NIR) laser and the spatiotemporal distribution of temperature was determined experimentally. This information was employed to develop and validate theoretical models of spatiotemporal temperature profiles for gold nanorod dispersions undergoing laser irradiation, and the impact of the resulting heat generation on the viability of human prostate cancer cells. A cell injury/death model was then coupled to the heat transfer model to predict spatial and temporal variations in cell death and injury. The model predictions agreed well with experimental measurements of both, temperature and cell death profiles. Finally, the model was extended to examine the impact of selective binding of gold nanorods to cancer cells compared to non-malignant cells, coupled with a small change in cell injury activation energy. The impact of these relatively minor changes results in a dramatic change in the overall cell death rate. Taken together, extracellular hyperthermia using gold nanorods is a promising strategy and tailoring the cellular binding efficacy of nanorods can result in varying therapeutic efficacies using this approach. PMID:20387828

Huang, Huang-Chiao; Rege, Kaushal; Heys, Jeffrey J.

2010-01-01

250

Spatiotemporal phylogenetic analysis and molecular characterization of coxsackievirus A4  

Microsoft Academic Search

Coxsackievirus A4 outbreaks occurred in Taiwan in 2004 and 2006. The spatiotemporal transmission of this error-prone RNA virus involves a continuous interaction between rapid sequence variation and natural selection. To elucidate the molecular characteristics of CV-A4 and the spatiotemporal dynamic changes in CV-A4 transmission, worldwide sequences of the 3? VP1 region (420nt) obtained from GenBank were analyzed together with sequences

Pei-Yu Chu; Po-Liang Lu; Yu-Ling Tsai; Edward Hsi; Ching-Yuan Yao; Yu-Hsien Chen; Li-Ching Hsu; Sheng-Yu Wang; Ho-Sheng Wu; Yi-Ying Lin; Hui-Ju Su; Kuei-Hsiang Lin

2011-01-01

251

Mesoscopic spatiotemporal theory for quantum-dot lasers  

Microsoft Academic Search

We present a mesoscopic theory for the spatiotemporal carrier and light-field dynamics in quantum-dot lasers. Quantum-dot Maxwell-Bloch equations have been set up that mesoscopically describe the spatiotemporal light-field and interlevel\\/intralevel carrier dynamics in each quantum dot (QD) of a typical QD ensemble in quantum-dot lasers. In particular, this includes spontaneous luminescence, counterpropagation of amplified spontaneous emission, and induced recombination as

Edeltraud Gehrig; Ortwin Hess

2002-01-01

252

Spatiotemporal variation in reproductive parameters of yellow-bellied marmots  

Microsoft Academic Search

Spatiotemporal variation in reproductive rates is a common phenomenon in many wildlife populations, but the population dynamic\\u000a consequences of spatial and temporal variability in different components of reproduction remain poorly understood. We used\\u000a 43 years (1962–2004) of data from 17 locations and a capture–mark–recapture (CMR) modeling framework to investigate the spatiotemporal\\u000a variation in reproductive parameters of yellow-bellied marmots (Marmota flaviventris), and

Arpat Ozgul; Madan K. Oli; Lucretia E. Olson; Daniel T. Blumstein; Kenneth B. Armitage

2007-01-01

253

Spatiotemporal information systems in soil and environmental sciences  

Microsoft Academic Search

This work is concerned with spatiotemporal information systems and their application in soil and environmental sciences. Issues investigated in this work include developments in the space\\/time modelling of natural variations, composite spatiotemporal mapping, and the incorporation of various sources of information into space\\/time analysis. Theoretical models, simulation examples, as well as real-world case studies are discussed. The models can process

George Christakos

1998-01-01

254

Video texture indexing using spatio-temporal wavelets  

Microsoft Academic Search

In this paper, we present a new compact spatio-temporal tex- ture descriptor designed for indexing dynamic video content. Video texture provides a way to characterize spatio-temporal features such as those corresponding to splashing water, flying birds, blow- ing trees, and so forth, which are not easily characterized by static feature descriptors. The video texture descriptor measures the 3-D wavelet energy

Milind R. Naphade; Ching-yung Lin; John R. Smith

2002-01-01

255

Spatiotemporal group ICA applied to fMRI datasets  

Microsoft Academic Search

Exploratory data analysis techniques such as independent component analysis (ICA) do not depend on a priori hypotheses and are able to detect unknown, yet structured spatiotemporal processes in neuroimaging data. We present fMRI data of two different subject-groups (young and old), which performed a modified Wisconsin Card Sorting Test (WCST). Spatiotemporal ICA and SPM-generated brain maps of the subject data

Ch. Kohler; I. Keck; P. Gruber; Ch.-H. Lie; K. Specht; A. M. Tome; E. W. Lang

2008-01-01

256

APP Is Cleaved by Bace1 in Pre-Synaptic Vesicles and Establishes a Pre-Synaptic Interactome, via Its Intracellular Domain, with Molecular Complexes that Regulate Pre-Synaptic Vesicles Functions  

PubMed Central

Amyloid Precursor Protein (APP) is a type I membrane protein that undergoes extensive processing by secretases, including BACE1. Although mutations in APP and genes that regulate processing of APP, such as PSENs and BRI2/ITM2B, cause dementias, the normal function of APP in synaptic transmission, synaptic plasticity and memory formation is poorly understood. To grasp the biochemical mechanisms underlying the function of APP in the central nervous system, it is important to first define the sub-cellular localization of APP in synapses and the synaptic interactome of APP. Using biochemical and electron microscopy approaches, we have found that APP is localized in pre-synaptic vesicles, where it is processed by Bace1. By means of a proteomic approach, we have characterized the synaptic interactome of the APP intracellular domain. We focused on this region of APP because in vivo data underline the central funtional and pathological role of the intracellular domain of APP. Consistent with the expression of APP in pre-synaptic vesicles, the synaptic APP intracellular domain interactome is predominantly constituted by pre-synaptic, rather than post-synaptic, proteins. This pre-synaptic interactome of the APP intracellular domain includes proteins expressed on pre-synaptic vesicles such as the vesicular SNARE Vamp2/Vamp1 and the Ca2+ sensors Synaptotagmin-1/Synaptotagmin-2, and non-vesicular pre-synaptic proteins that regulate exocytosis, endocytosis and recycling of pre-synaptic vesicles, such as target-membrane-SNAREs (Syntaxin-1b, Syntaxin-1a, Snap25 and Snap47), Munc-18, Nsf, ?/?/?-Snaps and complexin. These data are consistent with a functional role for APP, via its carboxyl-terminal domain, in exocytosis, endocytosis and/or recycling of pre-synaptic vesicles. PMID:25247712

Del Prete, Dolores; Lombino, Franco; Liu, Xinran; D'Adamio, Luciano

2014-01-01

257

Autophagy-related gene 12 (ATG12) is a novel determinant of primary resistance to HER2-targeted therapies: Utility of transcriptome analysis of the autophagy interactome to guide breast cancer treatment  

PubMed Central

The autophagic process, which can facilitate breast cancer resistance to endocrine, cytotoxic, and molecularly targeted agents, is mainly regulated at the post-translational level. Although recent studies have suggested a possible transcriptome regulation of the autophagic genes, little is known about either the analysis tools that can be applied or the functional importance of putative candidate genes emerging from autophagy-dedicated transcriptome studies. In this context, we evaluated whether the constitutive activation of the autophagy machinery, as revealed by a transcriptome analysis using an autophagy-focused polymerase chain reaction (PCR) array, might allow for the identification of novel autophagy-specific biomarkers for intrinsic (primary) resistance to HER2-targeted therapies. Quantitative real-time PCR (qRT-PCR)-based profiling of 84 genes involved in autophagy revealed that, when compared to trastuzumab-sensitive SKBR3 cells, the positive regulator of autophagic vesicle formation ATG12 (autophagy-related gene 12) was the most differentially up-regulated gene in JIMT1 cells, a model of intrinsic cross-resistance to trastuzumab and other HER1/2-targeting drugs. An analysis of the transcriptional status of ATG12 in > 50 breast cancer cell lines suggested that the ATG12 transcript is commonly upregulated in trastuzumab-unresponsive HER2-overexpressing breast cancer cells. A lentiviral-delivered small hairpin RNA stable knockdown of the ATG12 gene fully suppressed the refractoriness of JIMT1 cells to trastuzumab, erlotinib, gefitinib, and lapatinib in vitro. ATG12 silencing significantly reduced JIMT1 tumor growth induced by subcutaneous injection in nude mice. Remarkably, the outgrowth of trastuzumab-unresponsive tumors was prevented completely when trastuzumab treatment was administered in an ATG12-silenced genetic background. We demonstrate for the first time the usefulness of low-density, autophagy-dedicated qRT-PCR-based platforms for monitoring primary resistance to HER2-targeted therapies by transcriptionally screening the autophagy interactome. The degree of predictive accuracy warrants further investigation in the clinical situation. PMID:23307622

Corominas-Faja, Bruna; Urruticoechea, Ander; Martin-Castillo, Begoña; Menendez, Javier A.

2012-01-01

258

Sex & vision I: Spatio-temporal resolution  

PubMed Central

Background Cerebral cortex has a very large number of testosterone receptors, which could be a basis for sex differences in sensory functions. For example, audition has clear sex differences, which are related to serum testosterone levels. Of all major sensory systems only vision has not been examined for sex differences, which is surprising because occipital lobe (primary visual projection area) may have the highest density of testosterone receptors in the cortex. We have examined a basic visual function: spatial and temporal pattern resolution and acuity. Methods We tested large groups of young adults with normal vision. They were screened with a battery of standard tests that examined acuity, color vision, and stereopsis. We sampled the visual system’s contrast-sensitivity function (CSF) across the entire spatio-temporal space: 6 spatial frequencies at each of 5 temporal rates. Stimuli were gratings with sinusoidal luminance profiles generated on a special-purpose computer screen; their contrast was also sinusoidally modulated in time. We measured threshold contrasts using a criterion-free (forced-choice), adaptive psychophysical method (QUEST algorithm). Also, each individual’s acuity limit was estimated by fitting his or her data with a model and extrapolating to find the spatial frequency corresponding to 100% contrast. Results At a very low temporal rate, the spatial CSF was the canonical inverted-U; but for higher temporal rates, the maxima of the spatial CSFs shifted: Observers lost sensitivity at high spatial frequencies and gained sensitivity at low frequencies; also, all the maxima of the CSFs shifted by about the same amount in spatial frequency. Main effect: there was a significant (ANOVA) sex difference. Across the entire spatio-temporal domain, males were more sensitive, especially at higher spatial frequencies; similarly males had significantly better acuity at all temporal rates. Conclusion As with other sensory systems, there are marked sex differences in vision. The CSFs we measure are largely determined by inputs from specific sets of thalamic neurons to individual neurons in primary visual cortex. This convergence from thalamus to cortex is guided by cortex during embryogenesis. We suggest that testosterone plays a major role, leading to different connectivities in males and in females. But, for whatever reasons, we find that males have significantly greater sensitivity for fine detail and for rapidly moving stimuli. One interpretation is that this is consistent with sex roles in hunter-gatherer societies. PMID:22943466

2012-01-01

259

Spatiotemporal directional analysis of 4D echocardiography  

NASA Astrophysics Data System (ADS)

Speckle noise corrupts ultrasonic data by introducing sharp changes in an echocardiographic image intensity profile, while attenuation alters the intensity of equally significant cardiac structures. These properties introduce inhomogeneity in the spatial domain and suggests that measures based on phase information rather than intensity are more appropriate for denoising and cardiac border detection. The present analysis method relies on the expansion of temporal ultrasonic volume data on complex exponential wavelet-like basis functions called Brushlets. These basis functions decompose a signal into distinct patterns of oriented textures. Projected coefficients are associated with distinct 'brush strokes' of a particular size and orientation. 4D overcomplete brushlet analysis is applied to temporal echocardiographic values. We show that adding the time dimension in the analysis dramatically improves the quality and robustness of the method without adding complexity in the design of a segmentation tool. We have investigated mathematical and empirical methods for identifying the most 'efficient' brush stroke sizes and orientations for decomposition and reconstruction on both phantom and clinical data. In order to determine the 'best tiling' or equivalently, the 'best brushlet basis', we use an entorpy-based information cost metric function. Quantitative validation and clinical applications of this new spatio-temporal analysis tool are reported for balloon phantoms and clinical data sets.

Angelini-Casadevall, Elsa D.; Laine, Andrew F.; Takuma, Shin; Homma, Shunichi

2000-12-01

260

Spatiotemporal pattern of bacterioplankton in Donghu Lake  

NASA Astrophysics Data System (ADS)

Bacterioplankton play key roles in the biogeochemical cycle and in organic contaminant degradation. The species richness and abundance of bacterial subgroups are generally distinct from each other, and this is attributed to their different functions in aquatic ecosystems. The spatiotemporal variations of eight phylogenetic subgroups (Actinobacteria, Bacteroidetes, Cyanobacteria, Firmicutes, Planctomycetes, alpha-, beta-, and gamma-Proteobacteria) derived from Donghu Lake were investigated using PCR-DGGE fingerprinting, to explore their responses to environmental factors. Results indicate that Actinobacteria and beta-Proteobacteria were the two largest bacterial subgroups detected. These two groups and Bacteroidetes showed clear seasonal patterns in composition of the operational taxonomic unit. Results also suggest that the bacterioplankton subgroups in Donghu Lake were significantly correlated with different environmental factors. In brief, the total nitrogen was one of the major factors regulating all the bacterioplankton except for Actinobacteria. However, total phosphorus, another important eutrophication factor, contributed to the two largest bacterial groups (Actinobacteria and beta-Proteobacteria), as well as to the Cyanobacteria and Firmicutes. Therefore, the responses of bacterioplankton subgroups to environmental factors were different, and this should be attributed to the differences in the functions of different groups.

Zhang, Xiang; Yan, Qingyun; Yu, Yuhe; Dai, Lili

2014-05-01

261

Automatic spatiotemporal matching of detected pleural thickenings  

NASA Astrophysics Data System (ADS)

Pleural thickenings can be found in asbestos exposed patient's lung. Non-invasive diagnosis including CT imaging can detect aggressive malignant pleural mesothelioma in its early stage. In order to create a quantitative documentation of automatic detected pleural thickenings over time, the differences in volume and thickness of the detected thickenings have to be calculated. Physicians usually estimate the change of each thickening via visual comparison which provides neither quantitative nor qualitative measures. In this work, automatic spatiotemporal matching techniques of the detected pleural thickenings at two points of time based on the semi-automatic registration have been developed, implemented, and tested so that the same thickening can be compared fully automatically. As result, the application of the mapping technique using the principal components analysis turns out to be advantageous than the feature-based mapping using centroid and mean Hounsfield Units of each thickening, since the resulting sensitivity was improved to 98.46% from 42.19%, while the accuracy of feature-based mapping is only slightly higher (84.38% to 76.19%).

Chaisaowong, Kraisorn; Keller, Simon Kai; Kraus, Thomas

2014-01-01

262

Spatiotemporal vortices in optical fiber bundles  

NASA Astrophysics Data System (ADS)

We analyze complex spatiotemporal semidiscrete solitons in a model of a set of nonlinear optical fibers which form a square lattice in the cross section. The medium was recently realized as a set of parallel waveguides written in fused silica. The model also applies to a self-attracting Bose-Einstein condensate trapped in a very strong quasi-two-dimensional optical lattice. By means of the variational approximation (VA) and using numerical methods, we construct several species of the semidiscrete solitons, including vortices of rhombus (alias cross) and square types, with vorticity S=1 and 2, and quadrupoles. The VA is developed for narrow cross vortices with S=1 and quadrupoles, which turn out to be the most stable species. Two finite stability intervals are also found for the square-shaped vortices with S=1 , while all the vortices with S=2 are unstable. For the unstable solitons, several scenarios of the instability development are identified, such as fusion of the entire complex into a single fundamental soliton, or splitting into coherent soliton pairs.

Leblond, Hervé; Malomed, Boris A.; Mihalache, Dumitru

2008-06-01

263

Deformation localization in orogens: Spatiotemporal expression and thermodynamic constraint  

NASA Astrophysics Data System (ADS)

Orogens are spatiotemporal expressions of instabilities in materials under load, constrained by thermodynamics, and preserved in the cold outer shell of the planet. Their pressure-temperature-time histories are consistent with the predictions of differential grade-2 (DG-2) materials in pure shear. We place the statistically invariant shear localization mechanism of these materials in a coherent thermodynamic context using an analysis of strained elastic materials. This prototype system exhibits non-classical thermodynamic symmetry-breaking, where the potentials are all functions of a single variable and the distinction between heat and work fades from view. Consequently, internal energy must be described by a monotonically decreasing function of the entropy in order for heat capacity and absolute temperature to be positive. The entropy itself exhibits an inverse dependence on length. These constraints are satisfied by the overall shape and slope of the distributed deformation threshold ?D for DG-2 materials, and its noted 1/length correlation with naturally observed folds as a function of thermomechanical competence ?/?. We predict that temperature in this non-linear elastic material will vary in proportion to the slope of ?D, being high at low competence, and low at high competence. Similar constraints apply to a self-gravitating body, where the energy function varies inversely with radius. Assigning zero pressure at the surface of the body, we also predict that pressure, the tensor trace of its stress-energy density, will vary inversely with radius. Thus, the body force of gravity will be expressed in this elastic self-gravitating system through the interplay of elastic and thermal lengths. Deformation localization in DG-2 materials arises due to the dynamic rescaling of lengths in response to a spike in the intrinsic energy ?I at ?/? = ½. While the intrinsic ?I and localization ?L thresholds are monotonically decreasing for ?/? > ½, they exhibit positive slopes at lower competence, signaling a return to classical thermodynamics and Joule heating in this transitional domain. Numerous structural and tectonic observations can be correlated using this remarkably simple model, beginning with the thickness and mechanical character of the brittle crust and oceanic lithosphere. In effect, this model projects the kinematic theory of plate tectonics into four-dimensional spacetime.

Patton, R. L.; Watkinson, A. John

2013-05-01

264

Modeling sediment transport as a spatio-temporal Markov process.  

NASA Astrophysics Data System (ADS)

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.

Heyman, Joris; Ancey, Christophe

2014-05-01

265

Ultrashort relativistic electron bunches and spatio-temporal radiation biology  

NASA Astrophysics Data System (ADS)

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.

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

2008-08-01

266

PhotoScope: Visualizing Spatiotemporal Coverage of Photos for Construction Management  

E-print Network

PhotoScope specifically to address challenges in the construction management industry, where large photoPhotoScope: Visualizing Spatiotemporal Coverage of Photos for Construction Management Fuqu Wu Visualization, photo browser, construction management, spatiotemporal coverage. ACM Classification Keywords H1

Tory, Melanie

267

Spatio-temporal chaos in a chemotaxis model  

NASA Astrophysics Data System (ADS)

In this paper we explore the dynamics of a one-dimensional Keller-Segel type model for chemotaxis incorporating a logistic cell growth term. We demonstrate the capacity of the model to self-organise into multiple cellular aggregations which, according to position in parameter space, either form a stationary pattern or undergo a sustained spatio-temporal sequence of merging (two aggregations coalesce) and emerging (a new aggregation appears). This spatio-temporal patterning can be further subdivided into either a time-periodic or time-irregular fashion. Numerical explorations into the latter indicate a positive Lyapunov exponent (sensitive dependence to initial conditions) together with a rich bifurcation structure. In particular, we find stationary patterns that bifurcate onto a path of periodic patterns which, prior to the onset of spatio-temporal irregularity, undergo a “periodic-doubling” sequence. Based on these results and comparisons with other systems, we argue that the spatio-temporal irregularity observed here describes a form of spatio-temporal chaos. We discuss briefly our results in the context of previous applications of chemotaxis models, including tumour invasion, embryonic development and ecology.

Painter, Kevin J.; Hillen, Thomas

2011-02-01

268

Experimental study of spatiotemporally localized surface gravity water waves.  

PubMed

We present experimental results on the study of spatiotemporally localized surface wave events on deep water that can be modeled using the Peregrine breather solution of the nonlinear Schrödinger equation. These are often considered as prototypes of oceanic rogue waves that can focus wave energy into a single wave packet. For small steepness values of the carrier gravity waves the Peregrine breathers are relatively wide, thus providing an excellent agreement between the theory and experimental results. For larger steepnesses the focusing leads to temporally and spatially shorter events. Nevertheless, agreement between measurements and the Peregrine breather theory remains reasonably good, with discrepancies of modulation gradients and spatiotemporal symmetries being tolerable. Lifetimes and travel distances of the spatiotemporally localized wave events determined from the experiment are in good agreement with the theory. PMID:23005529

Chabchoub, A; Akhmediev, N; Hoffmann, N P

2012-07-01

269

Characterizations of spatio-temporal complex systems  

NASA Astrophysics Data System (ADS)

The thesis develops two characterizations of spatio-temporal complex patterns. While these are developed for the patterns of fluid flow in experiments on Rayleigh-Benard Convection (RBC), they are adaptable to a wide range of spatially extended systems. The characterizations may be especially useful in cases where one does not have good models describing the dynamics, making numerical and analytic studies difficult. In Spiral Defect Chaos (SDC), a weakly turbulent regime of RBC, the convective rolls exhibit complex spatial and temporal dynamics. We study the dynamics of SDC through local defect formations between convective rolls as well as the topological rearrangements of these rolls at a global scale. A laser based thermal actuation system is developed to reproducibly impose initial states for the fluid flow and construct ensembles of trajectories in the neighborhood of defect nucleation. This is used to extract the modes and their growth rates, characterizing the linear manifold corresponding to defect nucleation. The linear manifold corresponding to instabilities resulting in defect formation is key to building efficient schemes to control the dynamics exhibited. We also develop the use of computational homology as a tool to study spatially extended dynamical systems. A quantitative measure of the topological features of patterns is shown to provide insights into the underlying dynamics not easily uncovered otherwise. In the case of RBC, the homology of the patterns is seen to indicate asymmetries between hot and cold regions of the flow, stochastic evolution at a global scale as well as bifurcations occurring well into the turbulent regime of the flow.

Krishan, Kapilanjan

2005-11-01

270

Moment analysis for spatiotemporal fractional dispersion  

NASA Astrophysics Data System (ADS)

The evolution of the first five nonnegative integer-order spatial moments (corresponding to the mass, mean, variance, skewness, and kurtosis) are investigated systematically for spatiotemporal nonlocal, fractional dispersion. Three commonly used fractional-order transport equations, including the time fractional advection-dispersion equation (Time-FADE), the fractal mobile-immobile (MIM) equation, and the fully fractional advection-dispersion equation (FFADE), are considered. Analytical solutions verify our numerical results and reveal the anomalous evolution of the moments. Following Adams and Gelhar's (1992) work on the classical ADE, we find that a simultaneous analysis of all moments is critical in discriminating between different nonlocal models. The evolution of dispersion among the subdiffusive to superdiffusive rates is then further explored numerically by a non-Markovian random walk particle-tracking method that can be used for any heterogeneous boundary or initial value problem in three dimensions. Both the analytical and the numerical results also show the similarity (at the early time) and the difference (at the late time) of moment growth for solutes in different phases (mobile versus total) described by the MIM models. Further simulations of the 1-D bromide snapshots measured at the MADE experiments, using all three models with parameters fitted by the observed zeroth to fourth moments, indicate that (1) both the time and space nonlocality strongly affect the solute transport at the MADE site, (2) all five spatial moments should be considered in transport model selection and calibration because those up to the variance cannot effectively discriminate between nonlocal models, and (3) the log concentration should be used when evaluating the plume leading edge and the effects of space nonlocality.

Zhang, Yong; Benson, David A.; Baeumer, Boris

2008-04-01

271

Spatiotemporal SNP analysis reveals pronounced biocomplexity at the northern range margin of Atlantic cod Gadus morhua.  

PubMed

Accurate prediction of species distribution shifts in the face of climate change requires a sound understanding of population diversity and local adaptations. Previous modeling has suggested that global warming will lead to increased abundance of Atlantic cod (Gadus morhua) in the ocean around Greenland, but the dynamics of earlier abundance fluctuations are not well understood. We applied a retrospective spatiotemporal population genomics approach to examine the temporal stability of cod population structure in this region and to search for signatures of divergent selection over a 78-year period spanning major demographic changes. Analyzing >900 gene-associated single nucleotide polymorphisms in 847 individuals, we identified four genetically distinct groups that exhibited varying spatial distributions with considerable overlap and mixture. The genetic composition had remained stable over decades at some spawning grounds, whereas complete population replacement was evident at others. Observations of elevated differentiation in certain genomic regions are consistent with adaptive divergence between the groups, indicating that they may respond differently to environmental variation. Significantly increased temporal changes at a subset of loci also suggest that adaptation may be ongoing. These findings illustrate the power of spatiotemporal population genomics for revealing biocomplexity in both space and time and for informing future fisheries management and conservation efforts. PMID:23789034

Therkildsen, Nina Overgaard; Hemmer-Hansen, Jakob; Hedeholm, Rasmus Berg; Wisz, Mary S; Pampoulie, Christophe; Meldrup, Dorte; Bonanomi, Sara; Retzel, Anja; Olsen, Steffen Malskær; Nielsen, Einar Eg

2013-06-01

272

Spatio-temporal evolution of biogeochemical processes at a landfill site  

NASA Astrophysics Data System (ADS)

Predictions of fate and transport of contaminants are strongly dependent on spatio-temporal variability of soil hydraulic and geochemical properties. This study focuses on time-series signatures of hydrological and geochemical properties at different locations within the Norman landfill site. Norman Landfill is a closed municipal landfill site with prevalent organic contamination. Monthly data at the site include specific conductance, ?18O, ?2H, dissolved organic carbon (DOC) and anions (chloride, sulfate, nitrate) from 1998-2006. Column scale data on chemical concentrations, redox gradients, and flow parameters are also available on daily and hydrological event (infiltration, drainage, etc.) scales. Since high-resolution datasets of contaminant concentrations are usually unavailable, Wavelet and Fourier analyses were used to infer the dominance of different biogeochemical processes at different spatio-temporal scales and to extract linkages between transport and reaction processes. Results indicate that time variability controls the progression of reactions affecting biodegradation of contaminants. Wavelet analysis suggests that iron-sulfide reduction reactions had high seasonal variability at the site, while fermentation processes dominated at the annual time scale. Findings also suggest the dominance of small spatial features such as layered interfaces and clay lenses in driving biogeochemical reactions at both column and landfill scales. A conceptual model that caters to increased understanding and remediating structurally heterogeneous variably-saturated media is developed from the study.

Arora, B.; Mohanty, B. P.; McGuire, J. T.

2011-12-01

273

Hierarchical Bayesian spatio-temporal modeling and entropy-based network design  

NASA Astrophysics Data System (ADS)

Typical spatio-temporal data include temperature, precipitation, atmospheric pressure, ozone concentration, personal income, infection prevalence, mosquito populations, among others. To model such data in a given region by hierarchical Bayesian kriging is undertaken in this paper. In addition, an environmental network design problem is also explored. For demonstration, we consider the ozone concentrations in the Toronto region of Ontario, Canada. There are many missing observations in the data. To proceed, we first formulate the hierarchical spatio-temporal model in terms of observed data. We then fill in some missing observations such that the data has the staircase structure. Thus, in light of Le and Zidek (2006), we model the ozone concentrations in Toronto region by hierarchical Bayesian kriging and derive a conditional predictive distribution of the ozone concentrations over unknown locations. To decide if a new monitoring station needs to be added or an existing station can be closed down, we solve this environmental network design problem by using the principle of maximum entropy.

Wu, Y.; Jin, B.; Chan, E.

2012-12-01

274

Bioimage informatics for understanding spatiotemporal dynamics of cellular processes.  

PubMed

The inner environment of the cell is highly dynamic and heterogeneous yet exquisitely organized. Successful completion of cellular processes within this environment depends on the right molecules or molecular complexes to function at the right place at the right time. Understanding spatiotemporal behaviors of cellular processes is therefore essential to understanding their molecular mechanisms at the systems level. These behaviors are usually visualized and recorded using imaging techniques. However, to infer from them systems-level molecular mechanisms, computational analysis and understanding of recorded image data is crucial, not only for acquiring quantitative behavior measurements but also for comprehending complex interactions among the molecules or molecular complexes involved. The technology of computational analysis and understanding of biological images is often referred to simply as bioimage informatics. This article introduces fundamentals of bioimage informatics for understanding spatiotemporal dynamics of cellular processes and reviews recent advances on this topic. Basic bioimage informatics concepts and techniques for characterizing spatiotemporal cell dynamics are introduced first. Studies on specific cellular processes such as cell migration and signal transduction are then used as examples to analyze and summarize recent advances, with the focus on transforming quantitative measurements of spatiotemporal cellular behaviors into knowledge of underlying molecular mechanisms. Despite the advances made, substantial technological challenges remain, especially in representation of spatiotemporal cellular behaviors and inference of systems-level molecular mechanisms. These challenges are briefly discussed. Overall, understanding spatiotemporal cell dynamics will provide critical insights into how specific cellular processes as well as the entire inner cellular environment are dynamically organized and regulated. PMID:23408597

Yang, Ge

2013-01-01

275

Longitudinal changes in poststroke spatiotemporal gait asymmetry over inpatient rehabilitation.  

PubMed

Background. Little information exists about longitudinal changes in spatiotemporal gait asymmetry during rehabilitation, despite it being a common goal. Objectives. To describe longitudinal changes in spatiotemporal gait asymmetry over rehabilitation and examine relationships with changes in other poststroke impairments. Methods. Retrospective chart reviews were conducted for 71 stroke rehabilitation inpatients. Admission and discharge measures of spatiotemporal symmetry, velocity, motor impairment, mobility and balance were extracted and change scores were calculated. Relationships between changes in spatiotemporal symmetry and other change scores were investigated with Spearman correlations. Individuals were divided into four groups (worse, no change-symmetric, no change-asymmetric, improved) based on (1) symmetry/asymmetry at admission and (2) symmetry change scores >minimal detectable change. Differences in change scores between groups were investigated with analyses of covariance using the admission value as a covariate. Results. At admission, 59% and 49% of individuals were asymmetric in swing time and step length, respectively. Of these individuals, 21% and 14% improved swing symmetry or step symmetry, respectively. In contrast, 30% improved gait velocity, 62% improved functional balance and 73% improved functional mobility. Associations between change in swing symmetry and change in paretic limb weight bearing in standing and change in step symmetry and change in velocity were significant. There were no significant differences in change scores between the symmetry groups. Conclusions. The majority of asymmetric stroke patients did not improve spatiotemporal asymmetry during rehabilitation despite the fact that velocity, balance and functional mobility improved. Future work should investigate other factors associated with improved spatiotemporal symmetry and interventions to specifically improve it. PMID:24826888

Patterson, Kara K; Mansfield, Avril; Biasin, Louis; Brunton, Karen; Inness, Elizabeth L; McIlroy, William E

2015-02-01

276

Adaptive spatio-temporal filtering for movement related potentials in EEG-based brain-computer interfaces.  

PubMed

Movement related potentials (MRPs) are used as features in many brain-computer interfaces (BCIs) based on electroencephalogram (EEG). MRP feature extraction is challenging since EEG is noisy and varies between subjects. Previous studies used spatial and spatio-temporal filtering methods to deal with these problems. However, they did not optimize temporal information or may have been susceptible to overfitting when training data are limited and the feature space is of high dimension. Furthermore, most of these studies manually select data windows and low-pass frequencies. We propose an adaptive spatio-temporal (AST) filtering method to model MRPs more accurately in lower dimensional space. AST automatically optimizes all parameters by employing a Gaussian kernel to construct a low-pass time-frequency filter and a linear ridge regression (LRR) algorithm to compute a spatial filter. Optimal parameters are simultaneously sought by minimizing leave-one-out cross-validation error through gradient descent. Using four BCI datasets from 12 individuals, we compare the performances of AST filter to two popular methods: the discriminant spatial pattern filter and regularized spatio-temporal filter. The results demonstrate that our AST filter can make more accurate predictions and is computationally feasible. PMID:24723632

Lu, Jun; Xie, Kan; McFarland, Dennis J

2014-07-01

277

Male reproductive strategy explains spatiotemporal segregation in brown bears  

PubMed Central

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

Steyaert, Sam MJG; Kindberg, Jonas; Swenson, Jon E; Zedrosser, Andreas

2013-01-01

278

Spatiotemporal evolution of dielectric driven cogenerated dust density waves  

SciTech Connect

An experimental observation of spatiotemporal evolution of dust density waves (DDWs) in cogenerated dusty plasma in the presence of modified field induced by glass plate is reported. Various DDWs, such as vertical, oblique, and stationary, were detected simultaneously for the first time. Evolution of spatiotemporal complexity like bifurcation in propagating wavefronts is also observed. As dust concentration reaches extremely high value, the DDW collapses. Also, the oblique and nonpropagating mode vanishes when we increase the number of glass plates, while dust particles were trapped above each glass plates showing only vertical DDWs.

Sarkar, Sanjib; Bose, M. [Department of Physics, Jadavpur University, Kolkata 700032 (India)] [Department of Physics, Jadavpur University, Kolkata 700032 (India); Mukherjee, S. [FCIPT, Institute for Plasma Research, Gandhinagar 382428 (India)] [FCIPT, Institute for Plasma Research, Gandhinagar 382428 (India); Pramanik, J. [Kharagpur College, Kharagpur 721305, West Bengal (India)] [Kharagpur College, Kharagpur 721305, West Bengal (India)

2013-06-15

279

Proteomic Analysis of the EWS-Fli-1 Interactome Reveals the Role of the Lysosome in EWS-Fli-1 Turnover.  

PubMed

Ewing sarcoma is a cancer of bone and soft tissue in children that is characterized by a chromosomal translocation involving EWS and an Ets family transcription factor, most commonly Fli-1. EWS-Fli-1 fusion accounts for 85% of cases. The growth and survival of Ewing sarcoma cells are critically dependent on EWS-Fli-1. A large body of evidence has established that EWS-Fli-1 functions as a DNA-binding transcription factor that regulates the expression of a number of genes important for cell proliferation and transformation. However, little is known about the biochemical properties of the EWS-Fli-1 protein. We undertook a series of proteomic analyses to dissect the EWS-Fli-1 interactome. Employing a proximity-dependent biotinylation technique, BioID, we identified cation-independent mannose 6-phosphate receptor (CIMPR) as a protein located in the vicinity of EWS-Fli-1 within a cell. CIMPR is a cargo that mediates the delivery of lysosomal hydrolases from the trans-Golgi network to the endosome, which are subsequently transferred to the lysosomes. Further molecular cell biological analyses uncovered a role for lysosomes in the turnover of the EWS-Fli-1 protein. We demonstrate that an mTORC1 active-site inhibitor, torin 1, which stimulates the TFEB-lysosome pathway, can induce the degradation of EWS-Fli-1, suggesting a potential therapeutic approach to target EWS-Fli-1 for degradation. PMID:24999758

Elzi, David J; Song, Meihua; Hakala, Kevin; Weintraub, Susan T; Shiio, Yuzuru

2014-07-14

280

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

PubMed Central

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

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

2014-01-01

281

Diffusion of Information throughout the Host Interactome Reveals Gene Expression Variations in Network Proximity to Target Proteins of Hepatitis C Virus  

PubMed Central

Hepatitis C virus infection is one of the most common and chronic in the world, and hepatitis associated with HCV infection is a major risk factor for the development of cirrhosis and hepatocellular carcinoma (HCC). The rapidly growing number of viral-host and host protein-protein interactions is enabling more and more reliable network-based analyses of viral infection supported by omics data. The study of molecular interaction networks helps to elucidate the mechanistic pathways linking HCV molecular activities and the host response that modulates the stepwise hepatocarcinogenic process from preneoplastic lesions (cirrhosis and dysplasia) to HCC. Simulating the impact of HCV-host molecular interactions throughout the host protein-protein interaction (PPI) network, we ranked the host proteins in relation to their network proximity to viral targets. We observed that the set of proteins in the neighborhood of HCV targets in the host interactome is enriched in key players of the host response to HCV infection. In opposition to HCV targets, subnetworks of proteins in network proximity to HCV targets are significantly enriched in proteins reported as differentially expressed in preneoplastic and neoplastic liver samples by two independent studies. Using multi-objective optimization, we extracted subnetworks that are simultaneously “guilt-by-association” with HCV proteins and enriched in proteins differentially expressed. These subnetworks contain established, recently proposed and novel candidate proteins for the regulation of the mechanisms of liver cells response to chronic HCV infection. PMID:25461596

Milanesi, Luciano

2014-01-01

282

SRC Homology 2 Domain Binding Sites in Insulin, IGF-1 and FGF receptor mediated signaling networks reveal an extensive potential interactome  

PubMed Central

Specific peptide ligand recognition by modular interaction domains is essential for the fidelity of information flow through the signal transduction networks that control cell behavior in response to extrinsic and intrinsic stimuli. Src homology 2 (SH2) domains recognize distinct phosphotyrosine peptide motifs, but the specific sites that are phosphorylated and the complement of available SH2 domains varies considerably in individual cell types. Such differences are the basis for a wide range of available protein interaction microstates from which signaling can evolve in highly divergent ways. This underlying complexity suggests the need to broadly map the signaling potential of systems as a prerequisite for understanding signaling in specific cell types as well as various pathologies that involve signal transduction such as cancer, developmental defects and metabolic disorders. This report describes interactions between SH2 domains and potential binding partners that comprise initial signaling downstream of activated fibroblast growth factor (FGF), insulin (Ins), and insulin-like growth factor-1 (IGF-1) receptors. A panel of 50 SH2 domains screened against a set of 192 phosphotyrosine peptides defines an extensive potential interactome while demonstrating the selectivity of individual SH2 domains. The interactions described confirm virtually all previously reported associations while describing a large set of potential novel interactions that imply additional complexity in the signaling networks initiated from activated receptors. This study of pTyr ligand binding by SH2 domains provides valuable insight into the selectivity that underpins complex signaling networks that are assembled using modular protein interaction domains. PMID:22974441

2012-01-01

283

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

PubMed Central

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. PMID:19123612

Zhang, Yu; Jiang, Jack J.

2008-01-01

284

The Truncated Tornado in TMBB: A Spatiotemporal Uncertainty Model for  

E-print Network

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

Bae, Wan

285

The GLIMS Glacier Database: a spatio-temporal database  

E-print Network

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

Raup, Bruce H.

286

Discriminability limits in spatio-temporal stereo block matching.  

PubMed

Disparity estimation is a fundamental task in stereo imaging and is a well-studied problem. Recently, methods have been adapted to the video domain where motion is used as a matching criterion to help disambiguate spatially similar candidates. In this paper, we analyze the validity of the underlying assumptions of spatio-temporal disparity estimation, and determine the extent to which motion aids the matching process. By analyzing the error signal for spatio-temporal block matching under the sum of squared differences criterion and treating motion as a stochastic process, we determine the probability of a false match as a function of image features, motion distribution, image noise, and number of frames in the spatio-temporal patch. This performance quantification provides insight into when spatio-temporal matching is most beneficial in terms of the scene and motion, and can be used as a guide to select parameters for stereo matching algorithms. We validate our results through simulation and experiments on stereo video. PMID:24733012

Jain, Ankit K; Nguyen, Truong Q

2014-05-01

287

Locally Regularized Spatiotemporal Modeling and Model Comparison for Functional MRI  

E-print Network

Locally Regularized Spatiotemporal Modeling and Model Comparison for Functional MRI Patrick L fMRI data analysis as a spatio- temporal system identification problem and address issues of model to iden- tifying appropriate statistical models for fMRI studies. © 2001 Academic Press Key Words

Rotstein, Horacio G.

288

Topological Edge Cost Estimation through Spatio-Temporal Integration of  

E-print Network

Topological Edge Cost Estimation through Spatio-Temporal Integration of Low-level Behaviour that increasingly accurate cost estimates can indeed be derived using this strategy. This allows the use terrain, where consistent edge traversal cost estimates are indispensable for efficient path computation

Berns, Karsten

289

Cubic map algebra functions for spatio-temporal analysis  

USGS Publications Warehouse

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.

Mennis, J.; Viger, R.; Tomlin, C.D.

2005-01-01

290

Algebraic Properties of Qualitative Spatio-Temporal Calculi  

E-print Network

Algebraic Properties of Qualitative Spatio-Temporal Calculi Frank Dylla1 , Till Mossakowski1,2 , Thomas Schneider3 , and Diedrich Wolter1 1 Collaborative Research Center on Spatial Cognition (SFB/TR 8@informatik.uni-bremen.de Abstract Qualitative spatial and temporal reasoning is based on so- called qualitative calculi. Algebraic

Lutz, Carsten

291

Spatio-temporal video segmentation using a joint similarity measure  

Microsoft Academic Search

This paper presents a new morphological spatio-temporal segmentation algorithm. The algorithm incorporates luminance and motion information simultaneously and uses morphological tools such as morphological filters and watershed algorithm. The procedure toward complete segmentation consists of three steps: joint marker extraction, boundary decision, and motion-based region fusion. First, the joint marker extraction identifies the presence of homogeneous regions in both motion

Jae Gark Choi; Si-Woong Lee; Seong-Dae Kim

1997-01-01

292

Spatio-temporal evaluation matrices for geospatial data  

NASA Astrophysics Data System (ADS)

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.

Triglav, Joc; Petrovi?, Dušan; Stopar, Bojan

2011-02-01

293

Spatiotemporal controlled delivery of nanoparticles to injured vasculature  

E-print Network

importance. peptides | collagen | nanoparticle | paclitaxel | angioplasty The field of nanotechnology has a nanoparticle (NP) system that fundamentally changes the way we control spatiotemporal delivery of therapeutic as a model therapeutic agent (8), made by a modified drug-alkoxide ring-opening strategy (9, 10

Cheng, Jianjun

294

SPATIO-TEMPORAL REGISTRATION OF EMBRYO IMAGES L. Guignard  

E-print Network

SPATIO-TEMPORAL REGISTRATION OF EMBRYO IMAGES L. Guignard C. Godin U.-M. Fiuza L. Hufnagel P. Stitching together sequences captured from different embryos may help producing a sequence covering is to describe cell and/or embryo shapes through development, to analyze their dy- namics and variability within

Paris-Sud XI, Université de

295

Football analysis using spatio-temporal tools Joachim Gudmundsson  

E-print Network

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

Wolle, Thomas

296

Spatio-Temporal Signal Recovery from Political Tweets in Indonesia  

E-print Network

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

Davulcu, Hasan

297

Spatiotemporal Background Subtraction Using Minimum Spanning Tree and Optical Flow  

E-print Network

Spatiotemporal Background Subtraction Using Minimum Spanning Tree and Optical Flow Mingliang Chen1. Background modeling and subtraction is a fundamental re- search topic in computer vision. Pixel and integrated with a temporal M-smoother to ensure temporally-consistent background subtraction

Yang, Ming-Hsuan

298

BACKGROUND SUBTRACTION WITH ADAPTIVE SPATIO-TEMPORAL NEIGHBORHOOD ANALYSIS  

E-print Network

BACKGROUND SUBTRACTION WITH ADAPTIVE SPATIO-TEMPORAL NEIGHBORHOOD ANALYSIS Marco Cristani, Vittorio- ground subtraction are proven to be effective in discovering foreground objects in cluttered scenes of quality of the detection with respect to the frame rate achieved. 1 Introduction Background subtraction

Cristani, Marco

299

Spatiotemporal modeling of irregularly spaced Aerosol Optical Depth data  

PubMed Central

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

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

2012-01-01

300

Spatio-Temporal Saliency Perception via Hypercomplex Frequency Spectral Contrast  

PubMed Central

Salient object perception is the process of sensing the salient information from the spatio-temporal visual scenes, which is a rapid pre-attention mechanism for the target location in a visual smart sensor. In recent decades, many successful models of visual saliency perception have been proposed to simulate the pre-attention behavior. Since most of the methods usually need some ad hoc parameters or high-cost preprocessing, they are difficult to rapidly detect salient object or be implemented by computing parallelism in a smart sensor. In this paper, we propose a novel spatio-temporal saliency perception method based on spatio-temporal hypercomplex spectral contrast (HSC). Firstly, the proposed HSC algorithm represent the features in the HSV (hue, saturation and value) color space and features of motion by a hypercomplex number. Secondly, the spatio-temporal salient objects are efficiently detected by hypercomplex Fourier spectral contrast in parallel. Finally, our saliency perception model also incorporates with the non-uniform sampling, which is a common phenomenon of human vision that directs visual attention to the logarithmic center of the image/video in natural scenes. The experimental results on the public saliency perception datasets demonstrate the effectiveness of the proposed approach compared to eleven state-of-the-art approaches. In addition, we extend the proposed model to moving object extraction in dynamic scenes, and the proposed algorithm is superior to the traditional algorithms. PMID:23482090

Li, Ce; Xue, Jianru; Zheng, Nanning; Lan, Xuguang; Tian, Zhiqiang

2013-01-01

301

A Case Study: Ordinal Responses With Spatio-Temporal Dependencies  

Microsoft Academic Search

Data structures with spatial and temporal dependencies are not uncom- mon in environmental and agronomic flelds. We consider the modeling and estima- tion problem for these type of structures, in particular we consider proportional odds models with spatio-temporal covariables with estimation via maximum pseudlikeli- hood. We end by presenting a testing problem on treatment efiects on data from a fleld

Rogelio Ramos-Quiroga; Graciela Gonzalez-Far

302

Efficient Spatio-temporal Edge Descriptor Claudiu Tanase1  

E-print Network

by comparing to the initial edge histogram descriptor and the potential of feature fusion with other classifiers. Keywords: spatio-temporal, descriptor, content-based video retrieval, high-level feature extraction, classification, concept, edge histogram 1 Introduction High-level feature extraction

Paris-Sud XI, Université de

303

Spatiotemporal Coupling of the Tongue in Amyotrophic Lateral Sclerosis  

ERIC Educational Resources Information Center

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…

Kuruvilla, Mili S.; Green, Jordan R.; Yunusova, Yana; Hanford, Kathy

2012-01-01

304

VIDEO SALIENCY INCORPORATING SPATIOTEMPORAL CUES AND UNCERTAINTY WEIGHTING  

E-print Network

VIDEO SALIENCY INCORPORATING SPATIOTEMPORAL CUES AND UNCERTAINTY WEIGHTING Yuming Fang1 , Zhou Wang from video signals by combing both spatial and temporal information and statistical uncertainty-of-the-art video saliency detection models. Index Terms-- visual attention, video saliency, spa- tiotemporal

Wang, Zhou

305

Spatio-Temporal Querying in Video Databases Mesru Kprl1  

E-print Network

. Objects, events, activities performed by objects are main interests of the model. The model supports fuzzy various spatio-temporal queries along with the fuzzy ones and it is prone to implement compound queries technology, which have made the storage and processing capabilities increase while the costs decrease

�içekli, Nihan Kesim

306

Environmental heterogeneity and spatiotemporal variability in plant defense traits  

E-print Network

452 Environmental heterogeneity and spatiotemporal variability in plant defense traits Alyssa S of plant defenses. If environmental heterogeneity is an important mechanism influ- encing plant defense in our system. This study highlights the context dependence of plant defense trait levels, which may

Cronin, James T.

307

Video Dissolve and Wipe Detection via Spatio-Temporal  

E-print Network

-temporal approach has been developed by Ngo et al. [Ngo99] which uses one horizontal, one vertical, and one diagonal) then the spatio-temporal image formed by contiguous frames, for that row, may roughly show a diagonal edge [Ngo99

Drew, Mark S.

308

Spatio-Temporal Patterns for a Generalized Innovation Diffusion Model  

E-print Network

Spatio-Temporal Patterns for a Generalized Innovation Diffusion Model Fariba Hashemi Ecole and Mobility Laboratory (Transp-OR) August 31, 2010 Abstract We construct a model of innovation diffusion;Keywords: Diffusion of innovation - Bass' model - interactive multi- agent systems - local interactions

Bierlaire, Michel

309

Spatio-temporal spectral analysis by eigenstructure methods  

Microsoft Academic Search

This paper presents new algorithms for estimating the spatio-temporal spectrum of the signals received by a passive array. The algorithms are based on the eigenstructure of the covariance and spectral density matrices of the received signals. They allow partial correlation between the sources and thus are applicable to certain kinds of multipath problems. Simulation results that illustrate the performance of

M. Wax; Tie-Jun Shan; T. Kailath

1984-01-01

310

Spatiotemporal model for the progression of transgressive dunes  

E-print Network

Spatiotemporal model for the progression of transgressive dunes H. Yizhaqa, , Y. Ashkenazya , N Transgressive dunes, which are active sand areas surrounded by vegetation, exist on many coasts. In some regions like in Fraser Island in Australia, small dunes shrink while large ones grow, although both experience

Ashkenazy, Yossi "Yosef"

311

SPATIOTEMPORAL MODELS IN THE ESTIMATION OF AREA PRECIPITATION  

E-print Network

SPATIOTEMPORAL MODELS IN THE ESTIMATION OF AREA PRECIPITATION Eduardo Severino and Teresa Alpuim University of Lisbon, Portugal SUMMARY Since area precipitation measurements are difficult to obtain because of the large spatial and time variability of the precipitation field, the development of statistical methods

Lisbon, University of

312

Globally optimal spatio-temporal reconstruction from cluttered videos  

E-print Network

Globally optimal spatio-temporal reconstruction from cluttered videos Ehsan Aganj1 , Jean Abstract. We propose a method for multi-view reconstruction from videos adapted to dynamic cluttered scenes-view reconstruction from videos adapted to dynamic cluttered scenes under uncontrolled imaging conditions. Taking

Paris-Sud XI, Université de

313

Fast Spatio-Temporal Data Mining from Large Geophysical Datasets  

NASA Technical Reports Server (NTRS)

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.

Stolorz, P.; Mesrobian, E.; Muntz, R.; Santos, J. R.; Shek, E.; Yi, J.; Mechoso, C.; Farrara, J.

1995-01-01

314

Spatiotemporal Transition to Conduction Block in Canine Ventricle  

E-print Network

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

Bailey-Kellogg, Chris

315

Neuronal spatiotemporal pattern discrimination: The dynamical evolution of seizures  

Microsoft Academic Search

We developed a modern numerical approach to the multivariate linear discrimination of Fisher from 1936 based upon singular value decomposition that is sufficiently stable to permit widespread application to spatiotemporal neuronal patterns. We demonstrate this approach on an old problem in neuroscience—whether seizures have distinct dynamical states as they evolve with time. A practical result was the first demonstration that

Steven J. Schiff; Tim Sauer; Rohit Kumar; Steven L. Weinstein

2005-01-01

316

Spatiotemporal Relational Probability Trees: An Introduction Amy McGovern  

E-print Network

we believe that spatiotemporal knowledge discovery methods can have a significant impact]. On the regional scale, drought, has one of the highest costs of any natural event in terms of socioeconomic (a scientists to better understand the evolu- tion of severe weather by creating human readable models that can

McGovern, Amy

317

Discovering SpatioTemporal Mobility Profiles of Cellphone Users  

E-print Network

Discovering SpatioTemporal Mobility Profiles of Cellphone Users Murat Ali Bayir Computer Sci. & Eng: nathan@mit.edu Abstract-- Mobility path information of cellphone users play a crucial role in a wide range of cellphone applications, including context-based search and advertising, early warning systems

Demirbas, Murat

318

Online identification of nonlinear spatiotemporal systems using kernel learning approach.  

PubMed

The identification of nonlinear spatiotemporal systems is of significance to engineering practice, since it can always provide useful insight into the underlying nonlinear mechanism and physical characteristics under study. In this paper, nonlinear spatiotemporal system models are transformed into a class of multi-input-multi-output (MIMO) partially linear systems (PLSs), and an effective online identification algorithm is therefore proposed by using a pruning error minimization principle and least square support vector machines. It is shown that many benchmark physical and engineering systems can be transformed into MIMO-PLSs which keep some important physical spatiotemporal relationships and are very helpful in the identification and analysis of the underlying system. Compared with several existing methods, the advantages of the proposed method are that it can make full use of some prior structural information about system physical models, can realize online estimation of the system dynamics, and achieve accurate characterization of some important nonlinear physical characteristics of the system. This would provide an important basis for state estimation, control, optimal analysis, and design of nonlinear distributed parameter systems. The proposed algorithm can also be applied to identification problems of stochastic spatiotemporal dynamical systems. Numeral examples and comparisons are given to demonstrate our results. PMID:21788186

Ning, Hanwen; Jing, Xingjian; Cheng, Li

2011-09-01

319

Spatio-temporal development of the pairing instability in an infinite array of vortex rings  

NASA Astrophysics Data System (ADS)

In this paper, we study the linear stability of an infinite vortex ring array with respect to the pairing instability, using a spectral code. The base flow solution, obtained after a short relaxation process, is composed of rings with a Gaussian azimuthal vorticity profile. The temporal stability properties are first obtained and compared to the theoretical predictions obtained by Levy and Forsedyke (1927 Proc. R. Soc. Lond. A 114 594–604). The spatio-temporal evolution of a localized perturbation is then computed. The growth rate ? ?ft( v \\right) of the perturbation in the frame moving at the speed v is obtained for all v. The variation of ? ?ft( v \\right) with respect to the parameters of the flow is provided.

Bolnot, H.; Le Dizès, S.; Leweke, T.

2014-12-01

320

Challenges for modelling spatio-temporal variations of malaria risk in Malawi  

NASA Astrophysics Data System (ADS)

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.

Lowe, R.; Chirombo, J.; Tompkins, A. M.

2012-04-01

321

Spatio-temporal dynamics of the magnetosphere during intense geospace storms  

NASA Astrophysics Data System (ADS)

During geomagnetically active periods the magnetosphere exhibits global, regional and local features. The global features are in general captured by the geomagnetic indices and the regional and local features are measured by spacecraft-based imagers and ground-based instruments. The global features of the magnetosphere have been studied extensively using nonlinear dynamical techniques, such as phase space reconstruction from observational data. The time series data of the distributed observations are used to develop spatio-temporal dynamics of the magnetosphere using phase space reconstruction techniques. In this approach the solar wind - magnetosphere coupling is modeled as an input-output system with the solar wind variables as the input and the ground-based magnetic field variations as the magnetospheric response. The magnetic field perturbation at 57 ground stations during year 2002 and the corresponding solar wind data are compiled for this study. The ground magnetometer data are from the three chains of stations: CANOPUS (13), IMAGE (26) and WDC (18). This new data set, with 1-minute resolution, is used to study the spatio-temporal structure, including the coupling between the high and mid-latitude regions. A technique that utilizes the daily rotation of the Earth as a longitudinal sampling process is used to construct a two dimensional representation of the high latitude magnetic perturbations both in magnetic latitude and magnetic local time. This model is used to predict the spatial structure of geomagnetic disturbances during intense geospace storms. From the point of view of space weather the predictions of the spatial structure are crucial, as it is important to identify the regions of strong disturbances during intense geospace storms

Chen, J.; Sharma, A.

2005-12-01

322

Spatio-temporal dynamics of the magnetosphere during intense geospace storms  

NASA Astrophysics Data System (ADS)

During geomagnetically active periods the magnetosphere exhibits global, regional and local features. The global features are in general captured by the geomagnetic indices and the regional and local features are measured by spacecraft-based imagers and ground-based instruments. The global features of the magnetosphere have been studied extensively using nonlinear dynamical techniques, such as phase space reconstruction from observational data. The time series data of the distributed observations are used to develop spatio-temporal dynamics of the magnetosphere using phase space reconstruction techniques. In this approach the solar wind - magnetosphere coupling is modeled as an input-output system with the solar wind variables as the input and the ground-based magnetic field variations as the magnetospheric response. The magnetic field perturbation at 57 ground stations during year 2002 and the corresponding solar wind data are compiled for this study. The ground magnetometer data are from the three chains of stations: CANOPUS (13), IMAGE (26) and WDC (18). This new data set, with 1-minute resolution, is used to study the spatio-temporal structure, including the coupling between the high and mid-latitude regions. A technique that utilizes the daily rotation of the Earth as a longitudinal sampling process is used to construct a two dimensional representation of the high latitude magnetic perturbations both in magnetic latitude and magnetic local time. This linear and nonlinear model is used to predict the spatial structure of geomagnetic disturbances during intense geospace storms. From the point of view of space weather the predictions of the spatial structure are crucial, as it is important to identify the regions of strong disturbances during intense geospace storms

Chen, J.; Sharma, A.

2006-05-01

323

Phosphoinositide-specific Phospholipase C ? 1b (PI-PLC?1b) Interactome: Affinity Purification-Mass Spectrometry Analysis of PI-PLC?1b with Nuclear Protein*  

PubMed Central

Two isoforms of inositide-dependent phospholipase C ?1 (PI-PLC?1) are generated by alternative splicing (PLC?1a and PLC?1b). Both isoforms are present within the nucleus, but in contrast to PLC?1a, the vast majority of PLC?1b is nuclear. In mouse erythroid leukemia cells, PI-PLC?1 is involved in the regulation of cell division and the balance between cell proliferation and differentiation. It has been demonstrated that nuclear localization is crucial for the enzymatic function of PI-PLC?1, although the mechanism by which this nuclear import occurs has never been fully characterized. The aim of this study was to characterize both the mechanism of nuclear localization and the molecular function of nuclear PI-PLC?1 by identifying its interactome in Friend's erythroleukemia isolated nuclei, utilizing a procedure that coupled immuno-affinity purification with tandem mass spectrometry analysis. Using this procedure, 160 proteins were demonstrated to be in association with PI-PLC?1b, some of which have been previously characterized, such as the splicing factor SRp20 (Srsf3) and Lamin B (Lmnb1). Co-immunoprecipitation analysis of selected proteins confirmed the data obtained via mass spectrometry. Of particular interest was the identification of the nuclear import proteins Kpna2, Kpna4, Kpnb1, Ran, and Rangap1, as well as factors involved in hematological malignancies and several anti-apoptotic proteins. These data give new insight into possible mechanisms of nuclear trafficking and functioning of this critical signaling molecule. PMID:23665500

Piazzi, Manuela; Blalock, William L.; Bavelloni, Alberto; Faenza, Irene; D'Angelo, Antonietta; Maraldi, Nadir M.; Cocco, Lucio

2013-01-01

324

Stereo matching using belief propagation with spatiotemporal consistency  

NASA Astrophysics Data System (ADS)

In this paper, we propose a stereo matching approach using belief propagation for video disparity estimation by establishing a novel spatiotemporal belief propagation model. The proposed model extends 2D belief propagation algorithm to 3D mode by propagating the belief of preceding frame to the following frame. Additionally, the propagating messages of the preceding frame are translated through referring to motion vector and then used as the initial values of message for the current frame. Meanwhile, the consistency of the motion vector is incorporated to the smoothness constraint for the current frame. The proposed spatiotemporal model of belief propagation has more systematic and comprehensive combination of temporal correlation compared to previous works. The experimental results show that it outperforms the algorithms based on 2D belief propagation especially for non-deformation motion in middle-low speed.

Yang, Yingyun; Song, Xie; Zhang, Qin

2013-12-01

325

Broadband spatiotemporal Gaussian Schell-model pulse trains.  

PubMed

A new class of partially coherent model sources is introduced on the basis of the second-order coherence theory of nonstationary optical fields. These model sources are spatially fully coherent at each frequency but can have broadband spectra and variable spectral coherence properties, which lead to reduced spatiotemporal coherence in the time domain. The source model is motivated by the spectral coherence properties of supercontinuum pulse trains generated in single-spatial-mode optical fibers. We demonstrate that such broadband light is highly (but not completely) spatially coherent, even though the spectral and temporal coherence properties may vary over a wide range. The model sources introduced here are convenient in assessing the spatiotemporal coherence of broadband pulses in optical systems. PMID:24690663

Dutta, Rahul; Korhonen, Minna; Friberg, Ari T; Genty, Göery; Turunen, Jari

2014-03-01

326

Nature of Spatiotemporal Light Bullets in Bulk Kerr Media  

NASA Astrophysics Data System (ADS)

We present a detailed experimental investigation which uncovers the nature of light bullets generated from self-focusing in a bulk dielectric medium with Kerr nonlinearity in the anomalous group velocity dispersion regime. By high dynamic range measurements of three-dimensional intensity profiles, we demonstrate that the light bullets consist of a sharply localized high-intensity core, which carries the self-compressed pulse and contains approximately 25% of the total energy, and a ring-shaped spatiotemporal periphery. Subdiffractive propagation along with dispersive broadening of the light bullets in free space after they exit the nonlinear medium indicate a strong space-time coupling within the bullet. This finding is confirmed by measurements of a spatiotemporal energy density flux that exhibits the same features as a stationary, polychromatic Bessel beam, thus highlighting the nature of the light bullets.

Majus, D.; Tamošauskas, G.; Gražulevi?iÅ«tÄ--, I.; Garejev, N.; Lotti, A.; Couairon, A.; Faccio, D.; Dubietis, A.

2014-05-01

327

Nature of spatiotemporal light bullets in bulk Kerr media.  

PubMed

We present a detailed experimental investigation which uncovers the nature of light bullets generated from self-focusing in a bulk dielectric medium with Kerr nonlinearity in the anomalous group velocity dispersion regime. By high dynamic range measurements of three-dimensional intensity profiles, we demonstrate that the light bullets consist of a sharply localized high-intensity core, which carries the self-compressed pulse and contains approximately 25% of the total energy, and a ring-shaped spatiotemporal periphery. Subdiffractive propagation along with dispersive broadening of the light bullets in free space after they exit the nonlinear medium indicate a strong space-time coupling within the bullet. This finding is confirmed by measurements of a spatiotemporal energy density flux that exhibits the same features as a stationary, polychromatic Bessel beam, thus highlighting the nature of the light bullets. PMID:24877940

Majus, D; Tamošauskas, G; Gražulevi?i?t?, I; Garejev, N; Lotti, A; Couairon, A; Faccio, D; Dubietis, A

2014-05-16

328

A spatiotemporal coding mechanism for background-invariant odor recognition.  

PubMed

Sensory stimuli evoke neural activity that evolves over time. What features of these spatiotemporal responses allow the robust encoding of stimulus identity in a multistimulus environment? Here we examined this issue in the locust (Schistocerca americana) olfactory system. We found that sensory responses evoked by an odorant (foreground) varied when presented atop or after an ongoing stimulus (background). These inconsistent sensory inputs triggered dynamic reorganization of ensemble activity in the downstream antennal lobe. As a result, partial pattern matches between neural representations encoding the same foreground stimulus across conditions were achieved. The degree and segments of response overlaps varied; however, any overlap observed was sufficient to drive background-independent responses in the downstream neural population. Notably, recognition performance of locusts in behavioral assays correlated well with our physiological findings. Hence, our results reveal how background-independent recognition of odors can be achieved using spatiotemporal patterns of neural activity. PMID:24185426

Saha, Debajit; Leong, Kevin; Li, Chao; Peterson, Steven; Siegel, Gregory; Raman, Baranidharan

2013-12-01

329

Automatic validation of computational models using pseudo-3D spatio-temporal model checking.  

PubMed

BackgroundComputational models play an increasingly important role in systems biology for generating predictions and in synthetic biology as executable prototypes/designs. For real life (clinical) applications there is a need to scale up and build more complex spatio-temporal multiscale models; these could enable investigating how changes at small scales reflect at large scales and viceversa. Results generated by computational models can be applied to real life applications only if the models have been validated first. Traditional in silico model checking techniques only capture how non-dimensional properties (e.g. concentrations) evolve over time and are suitable for small scale systems (e.g. metabolic pathways). The validation of larger scale systems (e.g. multicellular populations) additionally requires capturing how spatial patterns and their properties change over time, which are not considered by traditional non-spatial approaches.ResultsWe developed and implemented a methodology for the automatic validation of computational models with respect to both their spatial and temporal properties. Stochastic biological systems are represented by abstract models which assume a linear structure of time and a pseudo-3D representation of space (2D space plus a density measure). Time series data generated by such models is provided as input to parameterised image processing modules which automatically detect and analyse spatial patterns (e.g. cell) and clusters of such patterns (e.g. cellular population). For capturing how spatial and numeric properties change over time the Probabilistic Bounded Linear Spatial Temporal Logic is introduced. Given a collection of time series data and a formal spatio-temporal specification the model checker Mudi (http://mudi.modelchecking.org) determines probabilistically if the formal specification holds for the computational model or not. Mudi is an approximate probabilistic model checking platform which enables users to choose between frequentist and Bayesian, estimate and statistical hypothesis testing based validation approaches. We illustrate the expressivity and efficiency of our approach based on two biological case studies namely phase variation patterning in bacterial colony growth and the chemotactic aggregation of cells.ConclusionsThe formal methodology implemented in Mudi enables the validation of computational models against spatio-temporal logic properties and is a precursor to the development and validation of more complex multidimensional and multiscale models. PMID:25440773

Pârvu, Ovidiu; Gilbert, David

2014-12-01

330

Spatiotemporal dynamics of landscape pattern and hydrologic process in watershed systems  

NASA Astrophysics Data System (ADS)

SummaryLand use change is influenced by spatial and temporal factors that interact with watershed resources. Modeling these changes is critical to evaluate emerging land use patterns and to predict variation in water quantity and quality. The objective of this study is to model the nature and emergence of spatial patterns in land use and water resource impacts using a spatially explicit and dynamic landscape simulation. Temporal changes are predicted using a probabilistic Markovian process and spatial interaction through cellular automation. The MCMC (Monte Carlo Markov Chain) analysis with cellular automation is linked to hydrologic equations to simulate landscape patterns and processes. The spatiotemporal watershed dynamics (SWD) model is applied to a subwatershed in the Blackstone River watershed of Massachusetts to predict potential land use changes and expected runoff and sediment loading. Changes in watershed land use and water resources are evaluated over 100 years at a yearly time step. Results show high potential for rapid urbanization that could result in lowering of groundwater recharge and increased storm water peaks. The watershed faces potential decreases in agricultural and forest area that affect open space and pervious cover of the watershed system. Water quality deteriorated due to increased runoff which can also impact stream morphology. While overland erosion decreased, instream erosion increased from increased runoff from urban areas. Use of urban best management practices (BMPs) in sensitive locations, preventive strategies, and long-term conservation planning will be useful in sustaining the watershed system.

Randhir, Timothy O.; Tsvetkova, Olga

2011-06-01

331

Spatiotemporal energy models for the perception of motion  

Microsoft Academic Search

A motion sequence may be represented as a single pattern in x-y-t space; a velocity of motion corresponds to a three-dimensional orientation in this space. Motion sinformation can be extracted by a system that responds to the oriented spatiotemporal energy. We discuss a class of models for human motion mechanisms in which the first stage consists of linear filters that

Edward H. Adelson; James R. Bergen

2002-01-01

332

Spatiotemporal energy models for the perception of motion  

Microsoft Academic Search

A motion sequence may be represented as a single pattern in x-y-t space; a velocity of motion corresponds to a three-dimensional orientation in this space. Motion information can be extracted by a system that responds to the oriented spatiotemporal energy. We discuss a class of models for human motion mechanisms in which the first stage consists of linear filters that

E. H. Adelson; J. R. Bergen

1985-01-01

333

Cell Population Tracking and Lineage Construction with Spatiotemporal Context  

Microsoft Academic Search

Automated visual-tracking of cell populations in vitro using time-lapse phase contrast microscopy enables quantitative, systematic, and high-throughput measurements of cell behaviors. These measure- ments include the spatiotemporal quantification of cell migration, mitosis, apoptosis, and the reconstruc- tion of cell lineages. The combination of low signal-to-noise ratio of phase contrast microscopy images, high and varying densities of the cell cultures, topological

Kang Li; Mei Chen; Takeo Kanade

2008-01-01

334

Considering Correlation between Variables to Improve Spatiotemporal Forecasting  

Microsoft Academic Search

The importance of forecasting cannot be overemphasized in modern environment surveillance applications, including flood control,\\u000a rainfall analysis, pollution study, nuclear leakage prevention and so on. That is why we proposed STIFF (SpatioTemporal Integrated\\u000a Forecasting Framework) in previous work [11], trying to answer such a challenging problem of doing forecasting in natural environment with both spatial and temporal\\u000a characteristics involved. However,

Zhigang Li; Liangang Liu; Margaret H. Dunham

2003-01-01

335

Modeling spatio-temporal wildfire ignition point patterns  

Microsoft Academic Search

We analyze and model the structure of spatio-temporal wildfire ignitions in the St. Johns River Water Management District\\u000a in northeastern Florida. Previous studies, based on the K-function and an assumption of homogeneity, have shown that wildfire events occur in clusters. We revisit this analysis based\\u000a on an inhomogeneous K-function and argue that clustering is less important than initially thought. We

Amanda S. Hering; Cynthia L. Bell; Marc G. Genton

2009-01-01

336

Interactive Information Visualization for Exploratory Analysis of Spatiotemporal Trend Information  

NASA Astrophysics Data System (ADS)

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.

Takama, Yasufumi; Yamada, Takashi

337

Western Antarctic Peninsula physical oceanography and spatio–temporal variability  

Microsoft Academic Search

This study focuses on 12 years of physical oceanography data, collected during the Palmer, Antarctica, Long-Term Ecological Research program (PAL LTER) over the continental margin of the western Antarctic Peninsula (WAP). The dataset offers the most long-lived consistent CTD-gridded observations of Antarctic waters collected anywhere in the Southern Ocean. The physical characteristics, water column structure and spatio–temporal variability of the

Douglas G. Martinson; Sharon E. Stammerjohn; Richard A. Iannuzzi; Raymond C. Smith; Maria Vernet

2008-01-01

338

Three dimensional electromagnetic wavepackets in a plasma: Spatiotemporal modulational instability  

SciTech Connect

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.

Borhanian, J.; Hosseini Faradonbe, F. [Department of Physics, Faculty of Science, University of Mohaghegh Ardabili, P. O. Box 179, Ardabil (Iran, Islamic Republic of)] [Department of Physics, Faculty of Science, University of Mohaghegh Ardabili, P. O. Box 179, Ardabil (Iran, Islamic Republic of)

2014-04-15

339

A Comparison Between Complexity and Temporal GIS Models for Spatio-temporal Urban Applications  

Microsoft Academic Search

Spatio-temporal modeling for urban applications has received special attention lately. Due to the recent advances in computer\\u000a and geospatial technologies, the temporal aspect of urban applications which was ignored in conventional systems, is under\\u000a consideration nowadays. This new interest in spatio-temporal modeling, in spite of all its deficiencies, has brought about\\u000a great advances in spatio-temporal modeling and will enhance the

Majeed Pooyandeh; Saadi Mesgari; Abbas Alimohammadi; Rouzbeh Shad

2007-01-01

340

Spatiotemporal cGMP Dynamics in Living Mouse Rods  

PubMed Central

Signaling of single photons in rod photoreceptors decreases the concentration of the second messenger, cyclic GMP (cGMP), causing closure of cGMP-sensitive channels located in the plasma membrane. Whether the spatiotemporal profiles of the fall in cGMP are narrow and deep, or broad and shallow, has important consequences for the amplification and the fidelity of signaling. The factors that determine the cGMP profiles include the diffusion coefficient for cGMP, the spontaneous rate of cGMP hydrolysis, and the rate of cGMP synthesis, which is powerfully regulated by calcium feedback mechanisms. Here, using suction electrodes to record light-dependent changes in cGMP-activated current in living mouse rods lacking calcium feedback, we have determined the rate constant of spontaneous cGMP hydrolysis and the longitudinal cGMP diffusion coefficient. These measurements result in a fully constrained spatiotemporal model of phototransduction, which we used to determine the effect of feedback to cGMP synthesis in spatially constricting the fall of cGMP during the single-photon response of normal rods. We find that the spatiotemporal cGMP profiles during the single-photon response are optimized for maximal amplification and preservation of signal linearity, effectively operating within an axial signaling domain of ?2 ?m. PMID:22768933

Gross, Owen P.; Pugh, Edward N.; Burns, Marie E.

2012-01-01

341

Spatiotemporal distributions of tsunami sources and discovered periodicities  

NASA Astrophysics Data System (ADS)

Both spatial and spatiotemporal distributions of the sources of tsunamigenic earthquakes of tectonic origin over the last 112 years have been analyzed. This analysis has been made using tsunami databases published by the Institute of Computational Mathematics and Mathematical Geophysics (Siberian Branch, Russian Academy of Sciences) and the National Aeronautics and Space Administration (United States), as well as earthquake catalogs published by the National Earthquake Information Center (United States). It has been found that the pronounced activation of seismic processes and an increase in the total energy of tsunamigenic earthquakes were observed at the beginning of both the 20th (1905-1920) and 21st (2004-2011) centuries. Studying the spatiotemporal periodicity of such events on the basis of an analysis of the two-dimensional distributions of the sources of tectonic tsunamis has made it possible to determine localized latitudinal zones with a total lack of such events (90°-75° N, 45°-90° S, and 35°-25° N) and regions with a periodic occurrence of tsunamis mainly within the middle (65°-35° N and 25°-40° S) and subequatorial (15° N-20° S) latitudes of the Northern and Southern hemispheres. The objective of this work is to analyze the spatiotemporal distributions of sources of tsunamigenic earthquakes and the effect of the periodic occurrence of such events on the basis of data taken from global tsunami catalogs.

Levin, B. W.; Sasorova, E. V.

2014-09-01

342

Visual memory performance for color depends on spatiotemporal context.  

PubMed

Performance on visual short-term memory for features has been known to depend on stimulus complexity, spatial layout, and feature context. However, with few exceptions, memory capacity has been measured for abruptly appearing, single-instance displays. In everyday life, objects often have a spatiotemporal history as they or the observer move around. In three experiments, we investigated the effect of spatiotemporal history on explicit memory for color. Observers saw a memory display emerge from behind a wall, after which it disappeared again. The test display then emerged from either the same side as the memory display or the opposite side. In the first two experiments, memory improved for intermediate set sizes when the test display emerged in the same way as the memory display. A third experiment then showed that the benefit was tied to the original motion trajectory and not to the display object per se. The results indicate that memory for color is embedded in a richer episodic context that includes the spatiotemporal history of the display. PMID:25073612

Olivers, Christian N L; Schreij, Daniel

2014-10-01

343

Spatio-temporal simulation of first pass drug perfusion in the liver.  

PubMed

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

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

2014-03-01

344

Spatio-Temporal Variability of the North Sea Cod Recruitment in Relation to Temperature and Zooplankton  

PubMed Central

The North Sea cod (Gadus morhua, L.) stock has continuously declined over the past four decades linked with overfishing and climate change. Changes in stock structure due to overfishing have made the stock largely dependent on its recruitment success, which greatly relies on environmental conditions. Here we focus on the spatio-temporal variability of cod recruitment in an effort to detect changes during the critical early life stages. Using International Bottom Trawl Survey (IBTS) data from 1974 to 2011, a major spatio-temporal change in the distribution of cod recruits was identified in the late 1990s, characterized by a pronounced decrease in the central and southeastern North Sea stock. Other minor spatial changes were also recorded in the mid-1980s and early 1990s. We tested whether the observed changes in recruits distribution could be related with direct (i.e. temperature) and/or indirect (i.e. changes in the quantity and quality of zooplankton prey) effects of climate variability. The analyses were based on spatially-resolved time series, i.e. sea surface temperature (SST) from the Hadley Center and zooplankton records from the Continuous Plankton Recorder Survey. We showed that spring SST increase was the main driver for the most recent decrease in cod recruitment. The late 1990s were also characterized by relatively low total zooplankton biomass, particularly of energy-rich zooplankton such as the copepod Calanus finmarchicus, which have further contributed to the decline of North Sea cod recruitment. Long-term spatially-resolved observations were used to produce regional distribution models that could further be used to predict the abundance of North Sea cod recruits based on temperature and zooplankton food availability. PMID:24551103

Nicolas, Delphine; Rochette, Sébastien; Llope, Marcos; Licandro, Priscilla

2014-01-01

345

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

PubMed Central

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

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

2014-01-01

346

Dim moving target detection algorithm based on spatio-temporal classification sparse representation  

NASA Astrophysics Data System (ADS)

A dim moving target detection algorithm based on spatio-temporal classification sparse representation, which can characterize the motion information and morphological feature of target and background clutter, is proposed to enhance the performance of target detection. A spatio-temporal redundant dictionary is trained according to the content of infrared image sequence, and then is subdivided into target spatio-temporal redundant dictionary describing moving target, and background spatio-temporal redundant dictionary embedding background by the criterion that the target spatio-temporal atom could be decomposed more sparsely over Gaussian spatio-temporal redundant dictionary. The target and background clutter can be sparsely decomposed over their corresponding spatio-temporal redundant dictionary, yet could not be sparsely decomposed on their opposite spatio-temporal redundant dictionary, and so their residuals after reconstruction by the prescribed number of target and background spatio-temporal atoms would differ very visibly. Some experimental results show this proposed approach could not only improve the sparsity more efficiently, but also enhance the target detection performance more effectively.

Li, Zhengzhou; Dai, Zhen; Fu, Hongxia; Hou, Qian; Wang, Zhen; Yang, Lijiao; Jin, Gang; Liu, Changju; Li, Ruzhang

2014-11-01

347

Spatiotemporal Variations in the Fire Regimes of Whitebark Pine (Pinus albicaulis Engelm.) Forests, Western Montana, USA,  

E-print Network

Spatiotemporal Variations in the Fire Regimes of Whitebark Pine (Pinus albicaulis Engelm.) Forests Change Research Group at the University of Tennessee. #12;v Abstract Whitebark pine (Pinus albicaulis

Grissino-Mayer, Henri D.

348

Spatiotemporal fuzzy based climate forecasting for Australia  

NASA Astrophysics Data System (ADS)

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.

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

2012-12-01

349

Spatiotemporal Dynamics of Dengue Epidemics, Southern Vietnam  

PubMed Central

An improved understanding of heterogeneities in dengue virus transmission might provide insights into biological and ecologic drivers and facilitate predictions of the magnitude, timing, and location of future dengue epidemics. To investigate dengue dynamics in urban Ho Chi Minh City and neighboring rural provinces in Vietnam, we analyzed a 10-year monthly time series of dengue surveillance data from southern Vietnam. The per capita incidence of dengue was lower in Ho Chi Minh City than in most rural provinces; annual epidemics occurred 1–3 months later in Ho Chi Minh City than elsewhere. The timing and the magnitude of annual epidemics were significantly more correlated in nearby districts than in remote districts, suggesting that local biological and ecologic drivers operate at a scale of 50–100 km. Dengue incidence during the dry season accounted for 63% of variability in epidemic magnitude. These findings can aid the targeting of vector-control interventions and the planning for dengue vaccine implementation. PMID:23735713

Cuong, Hoang Quoc; Vu, Nguyen Thanh; Cazelles, Bernard; Boni, Maciej F.; Thai, Khoa T.D.; Rabaa, Maia A.; Quang, Luong Chan; Simmons, Cameron P.; Huu, Tran Ngoc

2013-01-01

350

Spatiotemporal dynamics of dengue epidemics, southern Vietnam.  

PubMed

An improved understanding of heterogeneities in dengue virus transmission might provide insights into biological and ecologic drivers and facilitate predictions of the magnitude, timing, and location of future dengue epidemics. To investigate dengue dynamics in urban Ho Chi Minh City and neighboring rural provinces in Vietnam, we analyzed a 10-year monthly time series of dengue surveillance data from southern Vietnam. The per capita incidence of dengue was lower in Ho Chi Minh City than in most rural provinces; annual epidemics occurred 1-3 months later in Ho Chi Minh City than elsewhere. The timing and the magnitude of annual epidemics were significantly more correlated in nearby districts than in remote districts, suggesting that local biological and ecologic drivers operate at a scale of 50-100 km. Dengue incidence during the dry season accounted for 63% of variability in epidemic magnitude. These findings can aid the targeting of vector-control interventions and the planning for dengue vaccine implementation. PMID:23735713

Cuong, Hoang Quoc; Vu, Nguyen Thanh; Cazelles, Bernard; Boni, Maciej F; Thai, Khoa T D; Rabaa, Maia A; Quang, Luong Chan; Simmons, Cameron P; Huu, Tran Ngoc; Anders, Katherine L

2013-06-01

351

Sniffing and Spatiotemporal Coding in Olfaction  

PubMed Central

The act of sniffing increases the air velocity and changes the duration of air flow in the nose. It is not yet clear how these changes interact with the intrinsic timing within the olfactory bulb, but this is a matter of current research activity. An action of sniffing in generating a high velocity that alters the sorption of odorants onto the lining of the nasal cavity is expected from the established work on odorant properties and sorption in the frog nose. Recent work indicates that the receptor properties in the olfactory epithelium and olfactory bulb are correlated with the receptor gene expression zones. The responses in both the epithelium and the olfactory bulb are predictable to a considerable extent by the hydrophobicity of odorants. Furthermore receptor expression in both that rodent and salamander nose interacts with the shapes of the nasal cavity to place the receptor sensitivity to odorants in optimal places according to the aerodynamic properties of the nose. PMID:16354743

Scott, John W.

2008-01-01

352

Structure-based algorithms for protein-protein interaction prediction  

E-print Network

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 ...

Hosur, Raghavendra

2012-01-01

353

Spatio-temporal modelling of climate-sensitive disease risk: Towards an early warning system for dengue in Brazil  

NASA Astrophysics Data System (ADS)

This paper considers the potential for using seasonal climate forecasts in developing an early warning system for dengue fever epidemics in Brazil. In the first instance, a generalised linear model (GLM) is used to select climate and other covariates which are both readily available and prove significant in prediction of confirmed monthly dengue cases based on data collected across the whole of Brazil for the period January 2001 to December 2008 at the microregion level (typically consisting of one large city and several smaller municipalities). The covariates explored include temperature and precipitation data on a 2.5°×2.5° longitude-latitude grid with time lags relevant to dengue transmission, an El Niño Southern Oscillation index and other relevant socio-economic and environmental variables. A negative binomial model formulation is adopted in this model selection to allow for extra-Poisson variation (overdispersion) in the observed dengue counts caused by unknown/unobserved confounding factors and possible correlations in these effects in both time and space. Subsequently, the selected global model is refined in the context of the South East region of Brazil, where dengue predominates, by reverting to a Poisson framework and explicitly modelling the overdispersion through a combination of unstructured and spatio-temporal structured random effects. The resulting spatio-temporal hierarchical model (or GLMM—generalised linear mixed model) is implemented via a Bayesian framework using Markov Chain Monte Carlo (MCMC). Dengue predictions are found to be enhanced both spatially and temporally when using the GLMM and the Bayesian framework allows posterior predictive distributions for dengue cases to be derived, which can be useful for developing a dengue alert system. Using this model, we conclude that seasonal climate forecasts could have potential value in helping to predict dengue incidence months in advance of an epidemic in South East Brazil.

Lowe, Rachel; Bailey, Trevor C.; Stephenson, David B.; Graham, Richard J.; Coelho, Caio A. S.; Sá Carvalho, Marilia; Barcellos, Christovam

2011-03-01

354

New insights into schizophrenia disease genes interactome in the human brain: emerging targets and therapeutic implications in the postgenomics era.  

PubMed

Abstract Schizophrenia, a complex neurological disorder, is comprised of interactions between multiple genetic and environmental factors wherein each of the factors individually exhibits a small effect. In this regard a network-based strategy is best suited to capture the combined effect of multiple genes with their definite pattern of interactions. Given that schizophrenia affects multiple regions of the brain, we postulated that instead of any single specific tissue, a mutual set of interactions occurs between different regions of brain in a well-defined pattern responsible for the disease phenotype. To validate, we constructed and compared tissue specific co-expression networks of schizophrenia candidate genes in twenty diverse brain tissues. As predicted, we observed a common interaction network of certain genes in all the studied brain tissues. We examined fundamental network topologies of the common network to sequester essential common candidates for schizophrenia. We also performed a gene set analysis to identify the essential biological pathways enriched by the common candidates in the network. Finally, the candidate drug targets were prioritized and scored against known available schizophrenic drugs by molecular docking studies. We distinctively identified protein kinases as the top candidates in the network that can serve as probable drug targets for the disease. Conclusively, we propose that a comprehensive study of the connectivity amongst the disease genes themselves may turn out to be more informative to understand schizophrenia disease etiology and the underlying complexity. PMID:25454513

Podder, Avijit; Latha, Narayanan

2014-12-01

355

Spatiotemporal Patterns of Urban Human Mobility  

NASA Astrophysics Data System (ADS)

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.

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

2013-04-01

356

An ontology-based spatio-temporal data model and query language for use in GIS-type applications  

Microsoft Academic Search

In this paper, we present a Web Ontology language (OWL) -based spatio-temporal data model that introduces the 'spatio-temporal coordinate' concept and makes use of 'temporal lifting'. The ontology-based data model captures application data features. A process for application data model development that incorporates spatio-temporal dependencies is presented. Standardized spatial concepts can be utilized. Spatio-temporal querying is supported; it makes use

M. Lyell; D. Voyadgis; M. Song; P. Ketha; P. Dibner

2011-01-01

357

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

SciTech Connect

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.

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

2013-04-25

358

Methods for ad-hoc delineation and analysis of categories of spatio-temporal events  

Microsoft Academic Search

Analysts are faced with increasing volume and complexity of spatially and spatio-temporally referenced events to analyze. One means of taming this volume and complexity is to develop methods and tools that can identify patterns, including spatio-temporal structure like clusters, in event data. To understand these methods and tools, we first present some of the motivation for the work, and then

Frank Hardisty; Donna Peuquet; Sen Xu; Anthony Robinson

2011-01-01

359

Soliton ``molecules'': Robust clusters of spatiotemporal optical solitons Lucian-Cornel Crasovan,* Yaroslav V. Kartashov,  

E-print Network

Soliton ``molecules'': Robust clusters of spatiotemporal optical solitons Lucian-Cornel Crasovan 21 April 2003 We show how to generate robust self-sustained clusters of soliton bullets--spatiotemporal optical or matter- wave solitons. The clusters carry an orbital angular momentum being supported

360

Enhancement of peak intensity in a filament core with spatiotemporally focused femtosecond laser pulses  

SciTech Connect

We demonstrate that the peak intensity in the filament core, which is inherently limited by the intensity clamping effect during femtosecond laser filamentation, can be significantly enhanced using spatiotemporally focused femtosecond laser pulses. In addition, the filament length obtained by spatiotemporally focused femtosecond laser pulses is {approx}25 times shorter than that obtained by a conventional focusing scheme, resulting in improved high spatial resolution.

Zeng Bin; Chu Wei; Li Guihua; Zhang Haisu; Ni Jielei [State Key Laboratory of High Field Laser Physics, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai 201800 (China); Graduate School of Chinese Academy of Sciences, Beijing 100080 (China); Gao Hui; Liu Weiwei [Institute of Modern Optics, Nankai University, Tianjin, 300071 (China); Yao Jinping; Cheng Ya; Xu Zhizhan [State Key Laboratory of High Field Laser Physics, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai 201800 (China); Chin, See Leang [Center for Optics, Photonics and Laser (COPL) and Department of Physics, Engineering Physics and Optics, Universite Laval, Quebec City, QC, G1V 0A6 (Canada)

2011-12-15

361

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

E-print Network

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

Bernstein, Phil

362

A 3-D spatio-temporal deconvolution approach for MR perfusion in the brain  

E-print Network

A 3-D spatio-temporal deconvolution approach for MR perfusion in the brain Carole Frindel , Marc C al., 1998), in con- trast-enhanced MRI for spatio-temporal reconstruction (Schmid et al., 2006), the cere- bral blood flow (CBF), the mean transit time (MTT) and the time- to-peak of the residue function

Robini, Marc - Pôle de Mathématiques, Institut National des Sciences Appliquées de Lyon

363

VIDEO REGION SEGMENTATION BY SPATIO-TEMPORAL WATERSHEDS M. A. El Saban and B. S. Manjunath  

E-print Network

VIDEO REGION SEGMENTATION BY SPATIO-TEMPORAL WATERSHEDS M. A. El Saban and B. S. Manjunath}@ece.ucsb.edu Abstract We propose a video region segmentation scheme combin- ing spatio-temporal edges and watershed is used as a topological surface for a watershed grouping stage. Considering the video as a 3-D volume

California at Santa Barbara, University of

364

LETTER Communicated by Terrence Sejnowski The Dynamic Neural Filter: A Binary Model of Spatiotemporal  

E-print Network

of spatiotemporal data. This measure is applied to experimental observations in the locust olfactory system, whose on supervised learning, in order to construct feedback attractor networks (Hop eld, 1982) for associative memory of spatiotemporal coding. Its existence has been demonstrated (Wehr & Laurent, 1996) in the locust olfactory system

Horn, David

365

A SPATIO-TEMPORAL MODEL OF HOUSING PRICES BASED ON INDIVIDUAL  

E-print Network

A SPATIO-TEMPORAL MODEL OF HOUSING PRICES BASED ON INDIVIDUAL SALES TRANSACTIONS OVER TIME Tony E price trends is developed that focuses on individual housing sales over time. The model allows for both in the Philadelphia area. Key Words: Housing Prices, Spatio-temporal models, Autocorrelation We owe special thanks

Smith, Tony E.

366

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

E-print Network

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

Kumar, Vipin

367

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

E-print Network

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

Bookhagen, Bodo

368

Thinking and computing spatiotemporally to enable cloud computing and science discoveries  

Microsoft Academic Search

We live in space time dimensions and all physical and social sciences are based on the dimensions. The representation and digitization of scientific phenomena into data and computation of the digitized data greatly depends on the spatiotemporal principles that govern the relationships of phenomena. The latest advancement of cloud computing is not an exception. Conducting cloud computing in a spatiotemporal

Chaowei Yang

2011-01-01

369

Self-Healing Spatio-Temporal Data Streams Using Error Signatures  

E-print Network

Self-Healing Spatio-Temporal Data Streams Using Error Signatures Shigeru Imai, Richard Klockowski, NY 12180, USA Email: {imais,klockr,cvarela}@cs.rpi.edu Abstract--Self-healing spatio-temporal data streaming systems enable error detection and data correction based on error signatures. Error signatures

Bystroff, Chris

370

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

E-print Network

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

Tse, Chi K. "Michael"

371

Spatiotemporal analysis of ERP during chinese idiom comprehension.  

PubMed

The objective of the present study was to elucidate the neural underpinning of Chinese idiom comprehension with spatiotemporal patterns of ERP. Thirteen subjects were required to decide whether the last character of each viewed Chinese four-character idiom was correct or not. Fuzzy c-means algorithm based on shape similarity was applied to segmenting spatiotemporal patterns of ERP. Statistical parametric map of t-statistic (SPM(t)) was performed after realignment according to the referential frame provided by fuzzy clustering in order to overcome temporal mismatch. Within 540 ms post-stimulus onset, the spatiotemporal patterns of ERP under both conditions could be segmented into 7 stages optimally and both share the first four microstates with variant membership functions and durations. SPM(t) presented significant differences in multiple regions in 3 stages: (1) during 120-150 ms, the early right hemispheric negativities (ERHN) inboth frontal and temporoparietal areas were likely to reflect both initial syntactic processing and visual word-form mismatch; (2) during 320-380 ms (the N400 stage), negative deflections in left frontal, left anterior temporal, centrofrontal regions might coordinate and integrate both syntactic and semantic analysis in extensive right hemisphere; (3) during 480-540 ms (the P600 stage), positive deflections in left temporoparietal and occipital regions seemed to reflect the reanalysis and the integration of word meanings to obtain the over all meaning of idioms. Our study has implicated the brain mechanism of language comprehension common to alphabetic language as well as that specialized in logographic language. PMID:15669753

Zhou, S; Zhou, W; Chen, X

2004-01-01

372

Spatiotemporal Patterns of Japanese Encephalitis in China, 2002–2010  

PubMed Central

Objective The aim of the study is to examine the spatiotemporal pattern of Japanese Encephalitis (JE) in mainland China during 2002–2010. Specific objectives of the study were to quantify the temporal variation in incidence of JE cases, to determine if clustering of JE cases exists, to detect high risk spatiotemporal clusters of JE cases and to provide evidence-based preventive suggestions to relevant stakeholders. Methods Monthly JE cases at the county level in mainland China during 2002–2010 were obtained from the China Information System for Diseases Control and Prevention (CISDCP). For the purpose of the analysis, JE case counts for nine years were aggregated into four temporal periods (2002; 2003–2005; 2006; and 2007–2010). Local Indicators of Spatial Association and spatial scan statistics were performed to detect and evaluate local high risk space-time clusters. Results JE incidence showed a decreasing trend from 2002 to 2005 but peaked in 2006, then fluctuated over the study period. Spatial cluster analysis detected high value clusters, mainly located in Southwestern China. Similarly, we identified a primary spatiotemporal cluster of JE in Southwestern China between July and August, with the geographical range of JE transmission increasing over the past years. Conclusion JE in China is geographically clustered and its spatial extent dynamically changed during the last nine years in mainland China. This indicates that risk factors for JE infection are likely to be spatially heterogeneous. The results may assist national and local health authorities in the development/refinement of a better preventive strategy and increase the effectiveness of public health interventions against JE transmission. PMID:23819000

Sun, Hai-Long; Li, Yi-Xing; Zou, Wen; Wang, Yong; Liu, Qi-Yong; Li, Shen-Long; Yin, Wen-Wu; Huang, Liu-Yu; Clements, Archie C. A.; Bi, Peng; Li, Cheng-Yi

2013-01-01

373

Spatiotemporal quantile regression for detecting distributional changes in environmental processes  

PubMed Central

Climate change may lead to changes in several aspects of the distribution of climate variables, including changes in the mean, increased variability, and severity of extreme events. In this paper, we propose using spatiotemporal quantile regression as a flexible and interpretable method for simultaneously detecting changes in several features of the distribution of climate variables. The spatiotemporal quantile regression model assumes that each quantile level changes linearly in time, permitting straight-forward inference on the time trend for each quantile level. Unlike classical quantile regression which uses model-free methods to analyze a single quantile or several quantiles separately, we take a model-based approach which jointly models all quantiles, and thus the entire response distribution. In the spatiotemporal quantile regression model, each spatial location has its own quantile function that evolves over time, and the quantile functions are smoothed spatially using Gaussian process priors. We propose a basis expansion for the quantile function that permits a closed-form for the likelihood, and allows for residual correlation modeling via a Gaussian spatial copula. We illustrate the methods using temperature data for the southeast US from the years 1931–2009. For these data, borrowing information across space identifies more significant time trends than classical non-spatial quantile regression. We find a decreasing time trend for much of the spatial domain for monthly mean and maximum temperatures. For the lower quantiles of monthly minimum temperature, we find a decrease in Georgia and Florida, and an increase in Virginia and the Carolinas. PMID:23861555

Reich, Brian J

2013-01-01

374

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

SciTech Connect

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.

Destexhe, A. (Universite Libre de Bruxelles, Code Postal 231, Campus Plaine, Boulevard du Triomphe, B-1050 Bruxelles (Belgium))

1994-08-01

375

Multi-Scale Locality-Constrained Spatiotemporal Coding for Local Feature Based Human Action Recognition  

PubMed Central

We propose a Multiscale Locality-Constrained Spatiotemporal Coding (MLSC) method to improve the traditional bag of features (BoF) algorithm which ignores the spatiotemporal relationship of local features for human action recognition in video. To model this spatiotemporal relationship, MLSC involves the spatiotemporal position of local feature into feature coding processing. It projects local features into a sub space-time-volume (sub-STV) and encodes them with a locality-constrained linear coding. A group of sub-STV features obtained from one video with MLSC and max-pooling are used to classify this video. In classification stage, the Locality-Constrained Group Sparse Representation (LGSR) is adopted to utilize the intrinsic group information of these sub-STV features. The experimental results on KTH, Weizmann, and UCF sports datasets show that our method achieves better performance than the competing local spatiotemporal feature-based human action recognition methods. PMID:24194681

Liu, Yu; Wang, Wei; Xu, Wei; Zhang, Maojun

2013-01-01

376

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

PubMed Central

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

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

2014-01-01

377

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

PubMed

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

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

2014-01-01

378

Spatio-temporal dynamics in the origin of genetic information  

NASA Astrophysics Data System (ADS)

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.

Kim, Pan-Jun; Jeong, Hawoong

2005-04-01

379

Moving target detection in thermal infrared imagery using spatiotemporal information.  

PubMed

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

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

2013-08-01

380

Instability and Spatiotemporal Dynamics of Alternans in Paced Cardiac Tissue  

E-print Network

We derive an equation that governs the spatiotemporal dynamics of small amplitude alternans in paced cardiac tissue. We show that a pattern-forming linear instability leads to the spontaneous formation of stationary or traveling waves whose nodes divide the tissue into regions with opposite phase of oscillation of action potential duration. This instability is important because it creates dynamically an heterogeneous electrical substrate for inducing fibrillation if the tissue size exceeds a fraction of the pattern wavelength. We compute this wavelength analytically as a function of three basic length scales characterizing dispersion and inter-cellular electrical coupling.

Blas Echebarria; Alain Karma

2001-11-29

381

Instability and Spatiotemporal Dynamics of Alternans in Paced Cardiac Tissue  

NASA Astrophysics Data System (ADS)

We derive an equation that governs the spatiotemporal dynamics of small amplitude alternans in paced cardiac tissue. We show that a pattern-forming linear instability leads to the spontaneous formation of stationary or traveling waves whose nodes divide the tissue into regions with opposite phase of oscillation of action potential duration. This instability is important because it creates dynamically a heterogeneous electrical substrate for the formation of conduction blocks and the induction of fibrillation if the tissue size exceeds a fraction of the pattern wavelength. We derive an analytical expression for this wavelength as a function of three basic length scales related to dispersion and intercellular electrical coupling.

Echebarria, Blas; Karma, Alain

2002-05-01

382

Spatiotemporal flow instabilities of wormlike micellar solutions in rectangular microchannels  

NASA Astrophysics Data System (ADS)

Flow velocimetry measurements are made on a non-shear-banding wormlike micellar solution within high-aspect-ratio rectilinear microchannels over a wide range of imposed steady flow rates. At the lowest and highest flow rates tested, Newtonian-like velocity profiles are measured. However, at intermediate flow rates the velocity field never stabilizes on the timescale of the experiments (up to several hours). Here, spatiotemporally dependent "jets" of high velocity fluid are observed to fluctuate within regions of essentially stagnant fluid. The reason for this flow instability remains undetermined, but it has significant consequences for many industrial applications and also for microfluidic rheometry of complex fluids.

Haward, S. J.; Galindo-Rosales, F. J.; Ballesta, P.; Alves, M. A.

2014-03-01

383

Large scale stochastic spatio-temporal modelling with PCRaster  

NASA Astrophysics Data System (ADS)

PCRaster is a software framework for building spatio-temporal models of land surface processes (http://www.pcraster.eu). Building blocks of models are spatial operations on raster maps, including a large suite of operations for water and sediment routing. These operations are available to model builders as Python functions. The software comes with Python framework classes providing control flow for spatio-temporal modelling, Monte Carlo simulation, and data assimilation (Ensemble Kalman Filter and Particle Filter). Models are built by combining the spatial operations in these framework classes. This approach enables modellers without specialist programming experience to construct large, rather complicated models, as many technical details of modelling (e.g., data storage, solving spatial operations, data assimilation algorithms) are taken care of by the PCRaster toolbox. Exploratory modelling is supported by routines for prompt, interactive visualisation of stochastic spatio-temporal data generated by the models. The high computational requirements for stochastic spatio-temporal modelling, and an increasing demand to run models over large areas at high resolution, e.g. in global hydrological modelling, require an optimal use of available, heterogeneous computing resources by the modelling framework. Current work in the context of the eWaterCycle project is on a parallel implementation of the modelling engine, capable of running on a high-performance computing infrastructure such as clusters and supercomputers. Model runs will be distributed over multiple compute nodes and multiple processors (GPUs and CPUs). Parallelization will be done by parallel execution of Monte Carlo realizations and sub regions of the modelling domain. In our approach we use multiple levels of parallelism, improving scalability considerably. On the node level we will use OpenCL, the industry standard for low-level high performance computing kernels. To combine multiple nodes we will use software from the eScience Technology Platform (eSTeP), developed at the Netherlands eScience Center. This will allow us to scale up to hundreds of machines, with thousands of compute cores. A key requirement is not to change the user experience of the software. PCRaster operations and the use of the Python framework classes should work in a similar manner on machines ranging from a laptop to a supercomputer. This enables a seamless transfer of models from small machines, where model development is done, to large machines used for large-scale model runs. Domain specialists from a large range of disciplines, including hydrology, ecology, sedimentology, and land use change studies, currently use the PCRaster Python software within research projects. Applications include global scale hydrological modelling and error propagation in large-scale land use change models. The software runs on MS Windows, Linux operating systems, and OS X.

Karssenberg, Derek; Drost, Niels; Schmitz, Oliver; de Jong, Kor; Bierkens, Marc F. P.

2013-04-01

384

Spatiotemporal distribution of malaria and the association between its epidemic and climate factors in Hainan, China  

PubMed Central

Background Hainan is one of the provinces most severely affected by malaria epidemics in China. The distribution pattern and major determinant climate factors of malaria in this region have remained obscure, making it difficult to target countermeasures for malaria surveillance and control. This study detected the spatiotemporal distribution of malaria and explored the association between malaria epidemics and climate factors in Hainan. Methods The cumulative and annual malaria incidences of each county were calculated and mapped from 1995 to 2008 to show the spatial distribution of malaria in Hainan. The annual and monthly cumulative malaria incidences of the province between 1995 and 2008 were calculated and plotted to observe the annual and seasonal fluctuation. The Cochran-Armitage trend test was employed to explore the temporal trends in the annual malaria incidences. Cross correlation and autocorrelation analyses were performed to detect the lagged effect of climate factors on malaria transmission and the auto correlation of malaria incidence. A multivariate time series analysis was conducted to construct a model of climate factors to explore the association between malaria epidemics and climate factors. Results The highest malaria incidences were mainly distributed in the central-south counties of the province. A fluctuating but distinctly declining temporal trend of annual malaria incidences was identified (Cochran-Armitage trend test Z = -25.14, P < 0.05). The peak incidence period was May to October when nearly 70% of annual malaria cases were reported. The mean temperature of the previous month, of the previous two months and the number of cases during the previous month were included in the model. The model effectively explained the association between malaria epidemics and climate factors (F = 85.06, P < 0.05, adjusted R 2 = 0.81). The autocorrelations of the fitting residuals were not significant (P > 0.05), indicating that the model extracted information sufficiently. There was no significant difference between the monthly predicted value and the actual value (t = -1.91, P = 0.08). The R 2 for predicting was 0.70, and the autocorrelations of the predictive residuals were not significant (P > 0.05), indicating that the model had a good predictive ability. Discussion Public health resource allocations should focus on the areas and months with the highest malaria risk in Hainan. Malaria epidemics can be accurately predicted by monitoring the fluctuations of the mean temperature of the previous month and of the previous two months in the area. Therefore, targeted countermeasures can be taken ahead of time, which will make malaria surveillance and control in Hainan more effective and simpler. This model was constructed using relatively long-term data and had a good fit and predictive validity, making the results more reliable than the previous report. Conclusions The spatiotemporal distribution of malaria in Hainan varied in different areas and during different years. The monthly trends in the malaria epidemics in Hainan could be predicted effectively by using the multivariate time series model. This model will make malaria surveillance simpler and the control of malaria more targeted in Hainan. PMID:20579365

2010-01-01

385

Agent-based modeling of autophagy reveals emergent regulatory behavior of spatio-temporal autophagy dynamics.  

PubMed

BackgroundAutophagy is a vesicle-mediated pathway for lysosomal degradation, essential under basal and stressed conditions. Various cellular components, including specific proteins, protein aggregates, organelles and intracellular pathogens, are targets for autophagic degradation. Thereby, autophagy controls numerous vital physiological and pathophysiological functions, including cell signaling, differentiation, turnover of cellular components and pathogen defense. Moreover, autophagy enables the cell to recycle cellular components to metabolic substrates, thereby permitting prolonged survival under low nutrient conditions. Due to the multi-faceted roles for autophagy in maintaining cellular and organismal homeostasis and responding to diverse stresses, malfunction of autophagy contributes to both chronic and acute pathologies.ResultsWe applied a systems biology approach to improve the understanding of this complex cellular process of autophagy. All autophagy pathway vesicle activities, i.e. creation, movement, fusion and degradation, are highly dynamic, temporally and spatially, and under various forms of regulation. We therefore developed an agent-based model (ABM) to represent individual components of the autophagy pathway, subcellular vesicle dynamics and metabolic feedback with the cellular environment, thereby providing a framework to investigate spatio-temporal aspects of autophagy regulation and dynamic behavior. The rules defining our ABM were derived from literature and from high-resolution images of autophagy markers under basal and activated conditions. Key model parameters were fit with an iterative method using a genetic algorithm and a predefined fitness function. From this approach, we found that accurate prediction of spatio-temporal behavior required increasing model complexity by implementing functional integration of autophagy with the cellular nutrient state. The resulting model is able to reproduce short-term autophagic flux measurements (up to 3 hours) under basal and activated autophagy conditions, and to measure the degree of cell-to-cell variability. Moreover, we experimentally confirmed two model predictions, namely (i) peri-nuclear concentration of autophagosomes and (ii) inhibitory lysosomal feedback on mTOR signaling.ConclusionAgent-based modeling represents a novel approach to investigate autophagy dynamics, function and dysfunction with high biological realism. Our model accurately recapitulates short-term behavior and cell-to-cell variability under basal and activated conditions of autophagy. Further, this approach also allows investigation of long-term behaviors emerging from biologically-relevant alterations to vesicle trafficking and metabolic state. PMID:25214434

Börlin, Christoph S; Lang, Verena; Hamacher-Brady, Anne; Brady, Nathan R

2014-09-10

386

Deep Spatiotemporal Feature Learning with Application to Image Classification  

SciTech Connect

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.

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

2010-01-01

387

Spatiotemporal chaotic unjamming and jamming in granular avalanches.  

PubMed

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

Wang, Ziwei; Zhang, Jie

2015-01-01

388

Spatiotemporal variations of reference crop evapotranspiration in Northern Xinjiang, China.  

PubMed

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

Wang, Jian; Lv, Xin; Wang, Jiang-li; Lin, Hai-rong

2014-01-01

389

Spatio-temporal processing of tactile stimuli in autistic children.  

PubMed

Altered multisensory integration has been reported in autism; however, little is known concerning how the autistic brain processes spatio-temporal information concerning tactile stimuli. We report a study in which a crossed-hands illusion was investigated in autistic children. Neurotypical individuals often experience a subjective reversal of temporal order judgments when their hands are stimulated while crossed, and the illusion is known to be acquired in early childhood. However, under those conditions where the somatotopic representation is given priority over the actual spatial location of the hands, such reversals may not occur. Here, we showed that a significantly smaller illusory reversal was demonstrated in autistic children than in neurotypical children. Furthermore, in an additional experiment, the young boys who had higher Autism Spectrum Quotient (AQ) scores generally showed a smaller crossed hands deficit. These results suggest that rudimentary spatio-temporal processing of tactile stimuli exists in autistic children, and the altered processing may interfere with the development of an external frame of reference in real-life situations. PMID:25100146

Wada, Makoto; Suzuki, Mayuko; Takaki, Akiko; Miyao, Masutomo; Spence, Charles; Kansaku, Kenji

2014-01-01

390

Spatio-temporal Granger causality: a new framework  

PubMed Central

That physiological oscillations of various frequencies are present in fMRI signals is the rule, not the exception. Herein, we propose a novel theoretical framework, spatio-temporal Granger causality, which allows us to more reliably and precisely estimate the Granger causality from experimental datasets possessing time-varying properties caused by physiological oscillations. Within this framework, Granger causality is redefined as a global index measuring the directed information flow between two time series with time-varying properties. Both theoretical analyses and numerical examples demonstrate that Granger causality is a monotonically increasing function of the temporal resolution used in the estimation. This is consistent with the general principle of coarse graining, which causes information loss by smoothing out very fine-scale details in time and space. Our results confirm that the Granger causality at the finer spatio-temporal scales considerably outperforms the traditional approach in terms of an improved consistency between two resting-state scans of the same subject. To optimally estimate the Granger causality, the proposed theoretical framework is implemented through a combination of several approaches, such as dividing the optimal time window and estimating the parameters at the fine temporal and spatial scales. Taken together, our approach provides a novel and robust framework for estimating the Granger causality from fMRI, EEG, and other related data. PMID:23643924

Luo, Qiang; Lu, Wenlian; Cheng, Wei; Valdes-Sosa, Pedro A.; Wen, Xiaotong; Ding, Mingzhou; Feng, Jianfeng

2015-01-01

391

Event Detection using Twitter: A Spatio-Temporal Approach  

PubMed Central

Background Every day, around 400 million tweets are sent worldwide, which has become a rich source for detecting, monitoring and analysing news stories and special (disaster) events. Existing research within this field follows key words attributed to an event, monitoring temporal changes in word usage. However, this method requires prior knowledge of the event in order to know which words to follow, and does not guarantee that the words chosen will be the most appropriate to monitor. Methods This paper suggests an alternative methodology for event detection using space-time scan statistics (STSS). This technique looks for clusters within the dataset across both space and time, regardless of tweet content. It is expected that clusters of tweets will emerge during spatio-temporally relevant events, as people will tweet more than expected in order to describe the event and spread information. The special event used as a case study is the 2013 London helicopter crash. Results and Conclusion A spatio-temporally significant cluster is found relating to the London helicopter crash. Although the cluster only remains significant for a relatively short time, it is rich in information, such as important key words and photographs. The method also detects other special events such as football matches, as well as train and flight delays from Twitter data. These findings demonstrate that STSS is an effective approach to analysing Twitter data for event detection. PMID:24893168

Cheng, Tao; Wicks, Thomas

2014-01-01

392

Cell Population Tracking and Lineage Construction with Spatiotemporal Context 1  

PubMed Central

Automated visual-tracking of cell populations in vitro using phase contrast time-lapse microscopy enables quantitative, systematic and high-throughput measurements of cell behaviors. These measurements include the spatiotemporal quantification of cell migration, mitosis, apoptosis, and the construction of cell lineages. The combination of low signal-to-noise ratio of phase contrast microscopy images, high and varying densities of the cell cultures, topological complexities of cell shapes, and wide range of cell behaviors pose many challenges to existing tracking techniques. This paper presents a fully-automated multi-target tracking system that can efficiently cope with these challenges while simultaneously tracking and analyzing thousands of cells observed using time-lapse phase contrast microscopy. The system combines bottom-up and top-down image analysis by integrating multiple collaborative modules, which exploit a fast geometric active contour tracker in conjunction with adaptive interacting multiple models (IMM) motion filtering and spatiotemporal trajectory optimization. The system, which was tested using a variety of cell populations, achieved tracking accuracy in the range of 86.9%–92.5%. PMID:18656418

Li, Kang; Chen, Mei; Kanade, Takeo; Miller, Eric D.; Weiss, Lee E.; Campbell, Phil G.

2008-01-01

393

BICAR: A New Algorithm for Multiresolution Spatiotemporal Data Fusion  

PubMed Central

We introduce a method for spatiotemporal data fusion and demonstrate its performance on three constructed data sets: one entirely simulated, one with temporal speech signals and simulated spatial images, and another with recorded music time series and astronomical images defining the spatial patterns. Each case study is constructed to present specific challenges to test the method and demonstrate its capabilities. Our algorithm, BICAR (Bidirectional Independent Component Averaged Representation), is based on independent component analysis (ICA) and extracts pairs of temporal and spatial sources from two data matrices with arbitrarily different spatiotemporal resolution. We pair the temporal and spatial sources using a physical transfer function that connects the dynamics of the two. BICAR produces a hierarchy of sources ranked according to reproducibility; we show that sources which are more reproducible are more similar to true (known) sources. BICAR is robust to added noise, even in a “worst case” scenario where all physical sources are equally noisy. BICAR is also relatively robust to misspecification of the transfer function. BICAR holds promise as a useful data-driven assimilation method in neuroscience, earth science, astronomy, and other signal processing domains. PMID:23209693

Brown, Kevin S.; Grafton, Scott T.; Carlson, Jean M.

2012-01-01

394

Gait recognition using spatio-temporal silhouette-based features  

NASA Astrophysics Data System (ADS)

This paper presents a new algorithm for human gait recognition based on Spatio-temporal body biometric features using wavelet transforms. The proposed algorithm extracts the Gait cycle depending on the width of boundary box from a sequence of Silhouette images. Gait recognition is based on feature level fusion of three feature vectors: the gait spatio-temporal feature represented by the distances between (feet, knees, hands, shoulders, and height); binary difference between consecutive frames of the silhouette for each leg detected separately based on hamming distance; a vector of statistical parameters captured from the wavelet low frequency domain. The fused feature vector is subjected to dimension reduction using linear discriminate analysis. The Nearest Neighbour with a certain threshold used for classification. The threshold is obtained by experiment from a set of data captured from the CASIA database. We shall demonstrate that our method provides a non-traditional identification based on certain threshold to classify the outsider members as non-classified members.

Sabir, Azhin; Al-jawad, Naseer; Jassim, Sabah

2013-05-01

395

Spatiotemporal chaotic unjamming and jamming in granular avalanches  

PubMed Central

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

Wang, Ziwei; Zhang, Jie

2015-01-01

396

Spatiotemporal variation in reproductive parameters of yellow-bellied marmots.  

PubMed

Spatiotemporal variation in reproductive rates is a common phenomenon in many wildlife populations, but the population dynamic consequences of spatial and temporal variability in different components of reproduction remain poorly understood. We used 43 years (1962-2004) of data from 17 locations and a capture-mark-recapture (CMR) modeling framework to investigate the spatiotemporal variation in reproductive parameters of yellow-bellied marmots (Marmota flaviventris), and its influence on the realized population growth rate. Specifically, we estimated and modeled breeding probabilities of two-year-old females (earliest age of first reproduction), >2-year-old females that have not reproduced before (subadults), and >2-year-old females that have reproduced before (adults), as well as the litter sizes of two-year old and >2-year-old females. Most reproductive parameters exhibited spatial and/or temporal variation. However, reproductive parameters differed with respect to their relative influence on the realized population growth rate (lambda). Litter size had a stronger influence than did breeding probabilities on both spatial and temporal variations in lambda. Our analysis indicated that lambda was proportionately more sensitive to survival than recruitment. However, the annual fluctuation in litter size, abetted by the breeding probabilities, accounted for most of the temporal variation in lambda. PMID:17687571

Ozgul, Arpat; Oli, Madan K; Olson, Lucretia E; Blumstein, Daniel T; Armitage, Kenneth B

2007-11-01

397

Spatio-Temporal Updating in the Left Posterior Parietal Cortex  

PubMed Central

Adopting an unusual posture can sometimes give rise to paradoxical experiences. For example, the subjective ordering of successive unseen tactile stimuli delivered to the two arms can be affected when people cross them. A growing body of evidence now highlights the role played by the parietal cortex in spatio-temporal information processing when sensory stimuli are delivered to the body or when actions are executed; however, little is known about the neural basis of such paradoxical feelings resulting from such unusual limb positions. Here, we demonstrate increased fMRI activation in the left posterior parietal cortex when human participants adopted a crossed hands posture with their eyes closed. Furthermore, by assessing tactile temporal order judgments (TOJs) in the same individuals, we observed a positive association between activity in this area and the degree of reversal in TOJs resulting from crossing arms. The strongest positive association was observed in the left intraparietal sulcus. This result implies that the left posterior parietal cortex may be critically involved in monitoring limb position and in spatio-temporal binding when serial events are delivered to the limbs. PMID:22768126

Wada, Makoto; Takano, Kouji; Ikegami, Shiro; Ora, Hiroki; Spence, Charles; Kansaku, Kenji

2012-01-01

398

Spatio-temporal processing of tactile stimuli in autistic children  

PubMed Central

Altered multisensory integration has been reported in autism; however, little is known concerning how the autistic brain processes spatio-temporal information concerning tactile stimuli. We report a study in which a crossed-hands illusion was investigated in autistic children. Neurotypical individuals often experience a subjective reversal of temporal order judgments when their hands are stimulated while crossed, and the illusion is known to be acquired in early childhood. However, under those conditions where the somatotopic representation is given priority over the actual spatial location of the hands, such reversals may not occur. Here, we showed that a significantly smaller illusory reversal was demonstrated in autistic children than in neurotypical children. Furthermore, in an additional experiment, the young boys who had higher Autism Spectrum Quotient (AQ) scores generally showed a smaller crossed hands deficit. These results suggest that rudimentary spatio-temporal processing of tactile stimuli exists in autistic children, and the altered processing may interfere with the development of an external frame of reference in real-life situations. PMID:25100146

Wada, Makoto; Suzuki, Mayuko; Takaki, Akiko; Miyao, Masutomo; Spence, Charles; Kansaku, Kenji

2014-01-01

399

Spatiotemporal Variations of Reference Crop Evapotranspiration in Northern Xinjiang, China  

PubMed Central

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

Lv, Xin; Lin, Hai-rong

2014-01-01

400

Stochastic spatio-temporal modelling with PCRaster Python  

NASA Astrophysics Data System (ADS)

PCRaster Python is a software framework for building spatio-temporal models of land surface processes (Karssenberg, Schmitz, Salamon, De Jong, & Bierkens, 2010; PCRaster, 2012). Building blocks of models are spatial operations on raster maps, including a large suite of operations for water and sediment routing. These operations, developed in C++, are available to model builders as Python functions. Users create models by combining these functions in a Python script. As construction of large iterative models is often difficult and time consuming for non-specialists in programming, the software comes with a set of Python framework classes that provide control flow for static modelling, temporal modelling, stochastic modelling using Monte Carlo simulation, and data assimilation techniques including the Ensemble Kalman filter and the Particle Filter. A framework for integrating model components with different time steps and spatial discretization is currently available as a prototype (Schmitz, de Jong, & Karssenberg, in review). The software includes routines for visualisation of stochastic spatio-temporal data for prompt, interactive, visualisation of model inputs and outputs. Visualisation techniques include animated maps, time series, probability distributions, and animated maps with exceedance probabilities. The PCRaster Python software is used by researchers from a large range of disciplines, including hydrology, ecology, sedimentology, and land use change studies. Applications include global scale hydrological modelling and error propagation in large-scale land use change models. The software runs on MS Windows and Linux operating systems, and OS X (under development).

Karssenberg, D.; Schmitz, O.; de Jong, K.

2012-04-01

401

Small effects of smoking on visual spatiotemporal processing  

PubMed Central

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

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

2014-01-01

402

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

PubMed

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

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

2014-01-01

403

Under what kind of parametric fluctuations is spatiotemporal regularity the most robust?  

E-print Network

It was observed that the spatiotemporal chaos in lattices of coupled chaotic maps was suppressed to a spatiotemporal fixed point when some fraction of the regular coupling connections were replaced by random links. Here we investigate the effects of different kinds of parametric fluctuations on the robustness of this spatiotemporal fixed point regime. In particular we study the spatiotemporal dynamics of the network with noisy interaction parameters, namely fluctuating fraction of random links and fluctuating coupling strengths. We consider three types of fluctuations: (i) noisy in time, but homogeneous in space; (ii) noisy in space, but fixed in time; (iii) noisy in both space and time. We find that the effect of different kinds of parameteric noise on the dy- namics is quite distinct: quenched spatial fluctuations are the most detrimental to spatiotemporal regularity; spatiotemporal fluctuations yield phenomena similar to that observed when parameters are held constant at the mean-value; and interestingly, spatiotemporal regularity is most robust under spatially uniform temporal fluctuations, which in fact yields a larger fixed point range than that obtained under constant mean-value parameters.

Manish Dev Shrimali; Swarup Poria; Sudeshna Sinha

2008-07-05

404

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

SciTech Connect

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.

Banerjee, Tanmoy, E-mail: tbanerjee@phys.buruniv.ac.in; Paul, Bishwajit; Sarkar, B. C. [Department of Physics, University of Burdwan, Burdwan, West Bengal 713 104 (India)] [Department of Physics, University of Burdwan, Burdwan, West Bengal 713 104 (India)

2014-03-15

405

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

PubMed

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. PMID:24697378

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

2014-03-01

406

A Hybrid Spatio-Temporal Data Indexing Method for Trajectory Databases  

PubMed Central

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

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

2014-01-01

407

Predictive Modeling-Based Data Collection in Wireless Sensor Networks  

Microsoft Academic Search

We address the problem of designing practical, energy-efficient protocols for data collection in wireless sensor networks\\u000a using predictive modeling. Prior work has suggested several approaches to capture and exploit the rich spatio-temporal correlations\\u000a prevalent in WSNs during data collection. Although shown to be effective in reducing the data collection cost, those approaches\\u000a use simplistic corelation models and further, ignore many

Lidan Wang; Amol Deshpande

2008-01-01