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1

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

PubMed Central

SH3 domains are peptide recognition modules that mediate the assembly of diverse biological complexes. We scanned billions of phage-displayed peptides to map the binding specificities of the SH3 domain family in the budding yeast, Saccharomyces cerevisiae. Although most of the SH3 domains fall into the canonical classes I and II, each domain utilizes distinct features of its cognate ligands to achieve binding selectivity. Furthermore, we uncovered several SH3 domains with specificity profiles that clearly deviate from the two canonical classes. In conjunction with phage display, we used yeast two-hybrid and peptide array screening to independently identify SH3 domain binding partners. The results from the three complementary techniques were integrated using a Bayesian algorithm to generate a high-confidence yeast SH3 domain interaction map. The interaction map was enriched for proteins involved in endocytosis, revealing a set of SH3-mediated interactions that underlie formation of protein complexes essential to this biological pathway. We used the SH3 domain interaction network to predict the dynamic localization of several previously uncharacterized endocytic proteins, and our analysis suggests a novel role for the SH3 domains of Lsb3p and Lsb4p as hubs that recruit and assemble several endocytic complexes. PMID:19841731

Gfeller, David; Landgraf, Christiane; Panni, Simona; Paoluzi, Serena; Castagnoli, Luisa; Currell, Bridget; Seshagiri, Somasekar; Yu, Haiyuan; Winsor, Barbara; Vidal, Marc; Gerstein, Mark B.; Bader, Gary D.; Volkmer, Rudolf; Cesareni, Gianni; Drubin, David G.; Kim, Philip M.; Sidhu, Sachdev S.; Boone, Charles

2009-01-01

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

The Predicted Arabidopsis Interactome Resource and Network Topology-Based Systems Biology Analyses[W][OA  

PubMed Central

Predicted interactions are a valuable complement to experimentally reported interactions in molecular mechanism studies, particularly for higher organisms, for which reported experimental interactions represent only a small fraction of their total interactomes. With careful engineering consideration of the lessons from previous efforts, the Predicted Arabidopsis Interactome Resource (PAIR; ) presents 149,900 potential molecular interactions, which are expected to cover ~24% of the entire interactome with ~40% precision. This study demonstrates that, although PAIR still has limited coverage, it is rich enough to capture many significant functional linkages within and between higher-order biological systems, such as pathways and biological processes. These inferred interactions can nicely power several network topology-based systems biology analyses, such as gene set linkage analysis, protein function prediction, and identification of regulatory genes demonstrating insignificant expression changes. The drastically expanded molecular network in PAIR has considerably improved the capability of these analyses to integrate existing knowledge and suggest novel insights into the function and coordination of genes and gene networks. PMID:21441435

Lin, Mingzhi; Zhou, Xi; Shen, Xueling; Mao, Chuanzao; Chen, Xin

2011-01-01

5

Cost-Based Predictive Spatiotemporal Join  

Microsoft Academic Search

Abstract—A predictive spatio-temporal join finds all pairs of moving,objects satisfying a join condition on future time and space. In this paper we present CoPST, the first and foremost algorithm for such a join using two spatio-temporal indexes. In a predictive spatio- temporal join, the bounding boxes of the outer index are used to perform window searches on the inner index,

Wook-shin Han; Jaehwa Kim; Byung Suk Lee; Yufei Tao; Ralf Rantzau; Volker Markl

2009-01-01

6

Efficient prediction of progesterone receptor interactome using a support vector machine model.  

PubMed

Protein-protein interaction (PPI) is essential for almost all cellular processes and identification of PPI is a crucial task for biomedical researchers. So far, most computational studies of PPI are intended for pair-wise prediction. Theoretically, predicting protein partners for a single protein is likely a simpler problem. Given enough data for a particular protein, the results can be more accurate than general PPI predictors. In the present study, we assessed the potential of using the support vector machine (SVM) model with selected features centered on a particular protein for PPI prediction. As a proof-of-concept study, we applied this method to identify the interactome of progesterone receptor (PR), a protein which is essential for coordinating female reproduction in mammals by mediating the actions of ovarian progesterone. We achieved an accuracy of 91.9%, sensitivity of 92.8% and specificity of 91.2%. Our method is generally applicable to any other proteins and therefore may be of help in guiding biomedical experiments. PMID:25741764

Liu, Ji-Long; Peng, Ying; Fu, Yong-Sheng

2015-01-01

7

Predicting interactome network perturbations in human cancer: application to gene fusions in acute lymphoblastic leukemia  

PubMed Central

Genomic variations such as point mutations and gene fusions are directly or indirectly associated with human diseases. They are recognized as diagnostic, prognostic markers and therapeutic targets. However, predicting the functional effect of these genetic alterations beyond affected genes and their products is challenging because diseased phenotypes are likely dependent of complex molecular interaction networks. Using as models three different chromosomal translocations—ETV6-RUNX1 (TEL-AML1), BCR-ABL1, and TCF3-PBX1 (E2A-PBX1)—frequently found in precursor-B-cell acute lymphoblastic leukemia (preB-ALL), we develop an approach to extract perturbed molecular interactions from gene expression changes. We show that the MYC and JunD transcriptional circuits are specifically deregulated after ETV6-RUNX1 and TCF3-PBX1 gene fusions, respectively. We also identified the bulk mRNA NXF1-dependent machinery as a direct target for the TCF3-PBX1 fusion protein. Through a novel approach combining gene expression and interactome data analysis, we provide new insight into TCF3-PBX1 and ETV6-RUNX1 acute lymphoblastic leukemia. PMID:25273558

Hajingabo, Leon Juvenal; Daakour, Sarah; Martin, Maud; Grausenburger, Reinhard; Panzer-Grümayer, Renate; Dequiedt, Franck; Simonis, Nicolas; Twizere, Jean-Claude

2014-01-01

8

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

PubMed

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

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

2014-07-01

9

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 Gfeller1,2 , Rudolf Volkmer4 *, Gianni Cesareni5,13 *, David G. Drubin3 *, Philip M. Kim10¤b *, Sachdev S. Sidhu14¤b Haven, Connecticut, United States of America, 13 Research Institute ``Fondazione Santa Lucia'', Rome

Gerstein, Mark

10

Support vector machines for spatiotemporal tornado prediction  

Microsoft Academic Search

The use of support vector machines (SVMs) for predicting the location and time of tornadoes is presented. In this paper, we extend the work by Lakshmanan et al. (Proceedings of 2005 IEEE international joint conference on neural networks (Montreal, Canada), 3, 2005a, 1642–1647) to use a set of 33 storm days and introduce some variations that improve the results. The

Indra Adrianto; Theodore B. Trafalis; Valliappa Lakshmanan

2009-01-01

11

A spatiotemporal approach to tornado prediction  

Microsoft Academic Search

Automated tornado detection or prediction techniques in the literature have all been based on analyzing signatures of tornadoes that appear in Doppler radar velocity data. Attributes of these signatures are derived from radar data, as well as the near-storm environment, and associated with observed tornadoes. This associated database has been used to train neural networks and support vector machines to

V. Lakshmanan; Indra Adrianto; T. Smith; Gregory Stumpf

2005-01-01

12

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

13

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

14

Prediction of Spatiotemporal Patterns of Neural Activity from Pairwise Correlations  

NASA Astrophysics Data System (ADS)

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

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

2009-04-01

15

Prediction of Spatiotemporal Patterns of Neural Activity from Pairwise Correlations  

SciTech Connect

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

Marre, O.; El Boustani, S.; Fregnac, Y.; Destexhe, A. [Unite de Neurosciences Integratives et Computationnelles (UNIC), UPR CNRS 2191, Gif-sur-Yvette (France)

2009-04-03

16

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

17

Predicting BCI subject performance using probabilistic spatio-temporal filters.  

PubMed

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

18

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

19

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

E-print Network

1 Spatio-temporal variability and predictability of summer monsoon onset over the Philippines V + International Research Institute for Climate and Society, Columbia University, USA * Philippine Atmospheric Geophysical and Astronomical Services Administration, Manila, Philippines Submitted to Climate Dynamics

Robertson, Andrew W.

20

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

21

Ozone Concentration Prediction via Spatiotemporal Autoregressive Model With Exogenous Variables  

NASA Astrophysics Data System (ADS)

Forecast of environmental variables are nowadays of main concern for public health or agricultural management. In this context a large literature is devoted to spatio-temporal modelling of these variables using different statistical approaches. However, most of studies ignored the potential contribution of local (e.g. meteorological and/or geographical) covariables as well as the dynamical characteristics of observations. In this study, we present a spatiotemporal short term forecasting model for ozone concentration based on regularly observed covariables in predefined geographical sites. Our driving system simply combines a multidimensional second order autoregressive structured process with a linear regression model over influent exogenous factors and reads as follows: ?2 ?q j Z (t) = A (Î&,cedil;D )Ã- [ ?iZ(t- i)]+ B (Î&,cedil;D )Ã- [ ?jX (t)]+ É?(t) i=1 j=1 Z(t)=(Z1(t),â?¦,Zn(t)) represents the vector of ozone concentration at time t of the n geographical sites, whereas Xj(t)=(X1j(t),â?¦,Xnj(t)) denotes the jth exogenous variable observed over these sites. The nxn matrix functions A and B account for the spatial relationships between sites through the inter site distance matrix D and a vector parameter Î&.cedil; Multidimensional white noise É? is assumed to be Gaussian and spatially correlated but temporally independent. A covariance structure of Z that takes account of noise spatial dependences is deduced under a stationary hypothesis and then included in the likelihood function. Statistical model and estimation procedure: Contrarily to the widely used choice of a {0,1}-valued neighbour matrix A, we put forward two more natural choices of exponential or power decay. Moreover, the model revealed enough stable to readily accommodate the crude observations without the usual tedious and somewhat arbitrarily variable transformations. Data set and preliminary analysis: In our case, ozone variable represents here the daily maximum ozone concentration recorded in n=42 stations during the year 2005 within a south region in France, covering an area of approximately 10565 km2. Meteorological covariates are the daily maxima of temperature, wind speed, daily maxima of humidity and atmospheric pressure. Actually, the meteorological factors are not recorded in ozone monitoring sites and thus preliminary interpolation techniques were used and compared subsequently (Gaussian conditional simulation, ordinary kriging or kriging with external drift). Concluding remarks: From the statistical point of view, both simulation study and data analysis showed a fairly robust behaviour of estimation procedures. In both cases, the analysis of residuals proved a significant improvement of error prediction within this framework. From the environmental point of view, the ability of accounting for pertinent local and dynamical meteorological covariates clearly provided a useful tool in prediction methods. Bib [1]: Pfeifer.P.E; Deutsh.S.J. (1980) "A Three-Stage Iterative Procedure for Space-Time Modelling." Technometrics 22: 35-47. Bib [2]: Raffaella Giacomini and Cliff W.J.Granger 2002 - 07 "Aggregation of Space-Time Process" Departement of Economics, University of California, San Diego.

Kamoun, W.; Senoussi, R.

2009-04-01

22

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

E-print Network

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

Mokbel, Mohamed F.

23

AtPID: Arabidopsis thaliana protein interactome database - an integrative platform for plant systems biology  

Microsoft Academic Search

Arabidopsis thaliana Protein Interactome Database (AtPID) is an object database that integrates data from several bioinformatics prediction meth- ods and manually collected information from the literature. It contains data relevant to protein- protein interaction, protein subcellular location, ortholog maps, domain attributes and gene regula- tion. The predicted protein interaction data were obtained from ortholog interactome, microarray profiles, GO annotation, and

Jian Cui; Peng Li; Guang Li; Feng Xu; Chen Zhao; Yuhua Li; Zhongnan Yang; Guang Wang; Qingbo Yu; Yi-xue Li; Tieliu Shi

2008-01-01

24

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

25

Predicting spatio-temporal variability in fire return intervals using a topographic roughness index  

E-print Network

roughness index; Surface measures; Fire history; Mean fire return interval; Disturbance; Landscape; ModelPredicting spatio-temporal variability in fire return intervals using a topographic roughness index Michael C. Stambaugh *, Richard P. Guyette Missouri Tree-Ring Laboratory, Department of Forestry, 203

Stambaugh, Michael C

26

NextPlace: A Spatio-Temporal Prediction Framework for Pervasive Systems  

E-print Network

based on nonlinear time series analysis of the arrival and residence times of users in relevant places series analysis [12] for forecasting user behavior in different locations from a spatio-temporal point to a back-end server, where analysis of the data can be per- formed at run-time in order to predict future

Hand, Steven

27

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

NASA Astrophysics Data System (ADS)

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.

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

2013-04-01

28

The current Salmonella–host interactome  

PubMed Central

Salmonella bacteria cause millions of infections and thousands of deaths every year. This pathogen has an unusually broad host range including humans, animals, and even plants. During infection, Salmonella expresses a variety of virulence factors and effectors that are delivered into the host cell triggering cellular responses through protein–protein interactions (PPIs) with host cell proteins which make the pathogen’s invasion and replication possible. To speed up proteomic efforts in elucidating Salmonella–host interactomes, we carried out a survey of the currently published Salmonella–host PPI. Such a list can serve as the gold standard for computational models aimed at predicting Salmonella–host interactomes through integration of large-scale biological data sources. Manual literature and database search of >2200 journal articles and >100 databases resulted in a gold standard list of currently 62 PPI, including primarily interactions of Salmonella proteins with human and mouse proteins. Only six of these interactions were directly retrievable from PPI databases and 16 were highlighted in databases featuring literature extracts. Thus, the literature survey resulted in the most complete interactome available to date for Salmonella. Pathway analysis using Ingenuity and Broad Gene Set Enrichment Analysis (GSEA) software revealed among general pathways such as MAPK signaling in particular those related to cell death as well as cell morphology, turnover, and interactions, in addition to response to not only Salmonella but also other pathogenic – viral and bacterial – infections. The list of interactions is available at http://www.shiprec.org/indicationslist.htm PMID:22213674

Schleker, Sylvia; Sun, Jingchun; Raghavan, Balachandran; Srnec, Matthew; Müller, Nicole; Koepfinger, Mary; Murthy, Leelavati; Zhao, Zhongming; Klein-Seetharaman, Judith

2011-01-01

29

NextPlace: A Spatio-temporal Prediction Framework for Pervasive Systems  

Microsoft Academic Search

\\u000a Accurate and fine-grained prediction of future user location and geographical profile has interesting and promising applications\\u000a including targeted content service, advertisement dissemination for mobile users, and recreational social networking tools\\u000a for smart-phones. Existing techniques based on linear and probabilistic models are not able to provide accurate prediction\\u000a of the location patterns from a spatio-temporal perspective, especially for long-term estimation. More

Salvatore Scellato; Mirco Musolesi; Cecilia Mascolo; Vito Latora; Andrew T. Campbell

30

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

PubMed

Estimating population exposure to particulate matter during wildfires can be difficult because of insufficient monitoring data to capture the spatiotemporal variability of smoke plumes. Chemical transport models (CTMs) and satellite retrievals provide spatiotemporal data that may be useful in predicting PM2.5 during wildfires. We estimated PM2.5 concentrations during the 2008 northern California wildfires using 10-fold cross-validation (CV) to select an optimal prediction model from a set of 11 statistical algorithms and 29 predictor variables. The variables included CTM output, three measures of satellite aerosol optical depth, distance to the nearest fires, meteorological data, and land use, traffic, spatial location, and temporal characteristics. The generalized boosting model (GBM) with 29 predictor variables had the lowest CV root mean squared error and a CV-R(2) of 0.803. The most important predictor variable was the Geostationary Operational Environmental Satellite Aerosol/Smoke Product (GASP) Aerosol Optical Depth (AOD), followed by the CTM output and distance to the nearest fire cluster. Parsimonious models with various combinations of fewer variables also predicted PM2.5 well. Using machine learning algorithms to combine spatiotemporal data from satellites and CTMs can reliably predict PM2.5 concentrations during a major wildfire event. PMID:25648639

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

2015-03-17

31

Meteorological factors-based spatio-temporal mapping and predicting malaria in central China.  

PubMed

Despite significant reductions in the overall burden of malaria in the 20th century, this disease still represents a significant public health problem in China, especially in central areas. Understanding the spatio-temporal distribution of malaria is essential in the planning and implementing of effective control measures. In this study, normalized meteorological factors were incorporated in spatio-temporal models. Seven models were established in WinBUGS software by using Bayesian hierarchical models and Markov Chain Monte Carlo methods. M?, M?, and M? modeled separate meteorological factors, and M?, which modeled rainfall performed better than M? and M?, which modeled average temperature and relative humidity, respectively. M? was the best fitting models on the basis of based on deviance information criterion and predicting errors. The results showed that the way rainfall influencing malaria incidence was different from other factors, which could be interpreted as rainfall having a greater influence than other factors. PMID:21896823

Huang, Fang; Zhou, Shuisen; Zhang, Shaosen; Zhang, Hongwei; Li, Weidong

2011-09-01

32

Functional organization of the yeast proteome by a yeast interactome map.  

PubMed

It is hoped that comprehensive mapping of protein physical interactions will facilitate insights regarding both fundamental cell biology processes and the pathology of diseases. To fulfill this hope, good solutions to 2 issues will be essential: (i) how to obtain reliable interaction data in a high-throughput setting and (ii) how to structure interaction data in a meaningful form, amenable to and valuable for further biological research. In this article, we structure an interactome in terms of predicted permanent protein complexes and predicted transient, nongeneric interactions between these complexes. The interactome is generated by means of an associated computational algorithm, from raw high-throughput affinity purification/mass spectrometric interaction data. We apply our technique to the construction of an interactome for Saccharomyces cerevisiae, showing that it yields reliability typical of low-throughput experiments from high-throughput data. We discuss biological insights raised by this interactome including, via homology, a few related to human disease. PMID:19164585

Valente, André X C N; Roberts, Seth B; Buck, Gregory A; Gao, Yuan

2009-02-01

33

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

34

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

35

Spatio-temporal variation and prediction of ischemic heart disease hospitalizations in Shenzhen, China.  

PubMed

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

2014-05-01

36

Predicting the rate of range expansion of an invasive alien bumblebee ( Bombus terrestris) using a stochastic spatio-temporal model  

Microsoft Academic Search

To develop effective strategies for managing biological invasions, it is important to understand and be able to predict patterns of invasion and range expansion, and particularly the rate of spread and factors controlling this rate. To predict the spatial dynamics of invasion by an alien bumblebee (Bombus terrestris) in Hokkaido, Japan, we explicitly constructed a stochastic spatio-temporal model that incorporates

Taku Kadoya; Izumi Washitani

2010-01-01

37

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

38

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

39

An adaptive mode-driven spatiotemporal motion vector prediction for wavelet video coding  

NASA Astrophysics Data System (ADS)

The three-dimensional subband/wavelet codecs use 5/3 filters rather than Haar filters for the motion compensation temporal filtering (MCTF) to improve the coding gain. In order to curb the increased motion vector rate, an adaptive motion mode driven spatiotemporal motion vector prediction (AMDST-MVP) scheme is proposed. First, by making use of the direction histograms of four motion vector fields resulting from the initial spatial motion vector prediction (SMVP), the motion mode of the current GOP is determined according to whether the fast or complex motion exists in the current GOP. Then the GOP-level MVP scheme is thereby determined by either the S-MVP or the AMDST-MVP, namely, AMDST-MVP is the combination of S-MVP and temporal-MVP (T-MVP). If the latter is adopted, the motion vector difference (MVD) between the neighboring MV fields and the S-MVP resulting MV of the current block is employed to decide whether or not the MV of co-located block in the previous frame is used for prediction the current block. Experimental results show that AMDST-MVP not only can improve the coding efficiency but also reduce the number of computation complexity.

Zhao, Fan; Liu, Guizhong; Qi, Yong

2010-07-01

40

Spatio-temporal prediction of daily temperatures using time-series of MODIS LST images  

NASA Astrophysics Data System (ADS)

A computational framework to generate daily temperature maps using time-series of publicly available MODIS MOD11A2 product Land Surface Temperature (LST) images (1 km resolution; 8-day composites) is illustrated using temperature measurements from the national network of meteorological stations (159) in Croatia. The input data set contains 57,282 ground measurements of daily temperature for the year 2008. Temperature was modeled as a function of latitude, longitude, distance from the sea, elevation, time, insolation, and the MODIS LST images. The original rasters were first converted to principal components to reduce noise and filter missing pixels in the LST images. The residual were next analyzed for spatio-temporal auto-correlation; sum-metric separable variograms were fitted to account for zonal and geometric space-time anisotropy. The final predictions were generated for time-slices of a 3D space-time cube, constructed in the R environment for statistical computing. The results show that the space-time regression model can explain a significant part of the variation in station-data (84%). MODIS LST 8-day (cloud-free) images are unbiased estimator of the daily temperature, but with relatively low precision (±4.1°C); however their added value is that they systematically improve detection of local changes in land surface temperature due to local meteorological conditions and/or active heat sources (urban areas, land cover classes). The results of 10-fold cross-validation show that use of spatio-temporal regression-kriging and incorporation of time-series of remote sensing images leads to significantly more accurate maps of temperature than if plain spatial techniques were used. The average (global) accuracy of mapping temperature was ±2.4°C. The regression-kriging explained 91% of variability in daily temperatures, compared to 44% for ordinary kriging. Further software advancement—interactive space-time variogram exploration and automated retrieval, resampling and filtering of MODIS images—are anticipated.

Hengl, Tomislav; Heuvelink, Gerard B. M.; Per?ec Tadi?, Melita; Pebesma, Edzer J.

2012-01-01

41

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

42

Comprehensive analysis of TGF-? and BMP receptor interactomes.  

PubMed

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

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

2012-04-01

43

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

44

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

45

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

NASA Astrophysics Data System (ADS)

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

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

2014-03-01

46

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

47

Predicting avian distributions to evaluate spatiotemporal overlap with locust control operations in eastern Australia.  

PubMed

Locusts and grasshoppers cause considerable economic damage to agriculture worldwide. The Australian Plague Locust Commission uses multiple pesticides to control locusts in eastern Australia. Avian exposure to agricultural pesticides is of conservation concern, especially in the case of rare and threatened species. The aim of this study was to evaluate the probability of pesticide exposure of native avian species during operational locust control based on knowledge of species occurrence in areas and times of application. Using presence-absence data provided by the Birds Australia Atlas for 1998 to 2002, we developed a series of generalized linear models to predict avian occurrences on a monthly basis in 0.5 degrees grid cells for 280 species over 2 million km2 in eastern Australia. We constructed species-specific models relating occupancy patterns to survey date and location, rainfall, and derived habitat preference. Model complexity depended on the number of observations available. Model output was the probability of occurrence for each species at times and locations of past locust control operations within the 5-year study period. Given the high spatiotemporal variability of locust control events, the variability in predicted bird species presence was high, with 108 of the total 280 species being included at least once in the top 20 predicted species for individual space-time events. The models were evaluated using field surveys collected between 2000 and 2005, at sites with and without locust outbreaks. Model strength varied among species. Some species were under- or over-predicted as times and locations of interest typically did not correspond to those in the prediction data set and certain species were likely attracted to locusts as a food source. Field surveys demonstrated the utility of the spatially explicit species lists derived from the models but also identified the presence of a number of previously unanticipated species. These results also emphasize the need for special consideration of rare and threatened species that are poorly predicted by presence-absence models. This modeling exercise was a useful a priori approach in species risk assessments to identify species present at times and locations of locust control applications, and to discover gaps in our knowledge and need for further focused data collection. PMID:20014576

Szabo, Judit K; Davy, Pamela J; Hooper, Michael J; Astheimer, Lee B

2009-12-01

48

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

49

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

NASA Astrophysics Data System (ADS)

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

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

2013-11-01

50

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

PubMed

According to the disease module hypothesis, the cellular components associated with a disease segregate in the same neighborhood of the human interactome, the map of biologically relevant molecular interactions. Yet, given the incompleteness of the interactome and the limited knowledge of disease-associated genes, it is not obvious if the available data have sufficient coverage to map out modules associated with each disease. Here we derive mathematical conditions for the identifiability of disease modules and show that the network-based location of each disease module determines its pathobiological relationship to other diseases. For example, diseases with overlapping network modules show significant coexpression patterns, symptom similarity, and comorbidity, whereas diseases residing in separated network neighborhoods are phenotypically distinct. These tools represent an interactome-based platform to predict molecular commonalities between phenotypically related diseases, even if they do not share primary disease genes. PMID:25700523

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

2015-02-20

51

Modelling the Yeast Interactome  

PubMed Central

The topology behind biological interaction networks has been studied for over a decade. Yet, there is no definite agreement on the theoretical models which best describe protein-protein interaction (PPI) networks. Such models are critical to quantifying the significance of any empirical observation regarding those networks. Here, we perform a comprehensive analysis of yeast PPI networks in order to gain insights into their topology and its dependency on interaction-screening technology. We find that: (1) interaction-detection technology has little effect on the topology of PPI networks; (2) topology of these interaction networks differs in organisms with different cellular complexity (human and yeast); (3) clear topological difference is present between PPI networks, their functional sub-modules, and their inter-functional “linkers”; (4) high confidence PPI networks have more “geometrical” topology compared to predicted, incomplete, or noisy PPI networks; and (5) inter-functional “linker” proteins serve as mediators in signal transduction, transport, regulation and organisational cellular processes. PMID:24589662

Janji?, Vuk; Sharan, Roded; Pržulj, Nataša

2014-01-01

52

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

53

Evolution of protein interactions: from interactomes to interfaces.  

PubMed

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

Andreani, Jessica; Guerois, Raphael

2014-07-15

54

Surface Interactome in Streptococcus pyogenes*  

PubMed Central

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

2012-01-01

55

Mapping the functional yeast ABC transporter interactome  

PubMed Central

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

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

2013-01-01

56

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

57

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

58

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

PubMed Central

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

59

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

PubMed

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

2014-11-30

60

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

PubMed

The emergence and re-emergence of disease epidemics is a complex question that may be influenced by diverse factors, including the space-time dynamics of human populations, environmental conditions, and associated uncertainties. This study proposes a stochastic framework to integrate space-time dynamics in the form of a Susceptible-Infected-Recovered (SIR) model, together with uncertain disease observations, into a Bayesian maximum entropy (BME) framework. The resulting model (BME-SIR) can be used to predict space-time disease spread. Specifically, it was applied to obtain a space-time prediction of the dengue fever (DF) epidemic that took place in Kaohsiung City (Taiwan) during 2002. In implementing the model, the SIR parameters were continually updated and information on new cases of infection was incorporated. The results obtained show that the proposed model is rigorous to user-specified initial values of unknown model parameters, that is, transmission and recovery rates. In general, this model provides a good characterization of the spatial diffusion of the DF epidemic, especially in the city districts proximal to the location of the outbreak. Prediction performance may be affected by various factors, such as virus serotypes and human intervention, which can change the space-time dynamics of disease diffusion. The proposed BME-SIR disease prediction model can provide government agencies with a valuable reference for the timely identification, control, and prevention of DF spread in space and time. PMID:24615833

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

2014-05-01

61

Predicting the spatio-temporal distribution of Culicoides imicola in Sardinia using a discrete-time population model  

PubMed Central

Background Culicoides imicola KIEFFER, 1913 (Diptera: Ceratopogonidae) is the principal vector of Bluetongue disease in the Mediterranean basin, Africa and Asia. Previous studies have identified a range of eco-climatic variables associated with the distribution of C. imicola, and these relationships have been used to predict the large-scale distribution of the vector. However, these studies are not temporally-explicit and can not be used to predict the seasonality in C. imicola abundances. Between 2001 and 2006, longitudinal entomological surveillance was carried out throughout Italy, and provided a comprehensive spatio-temporal dataset of C. imicola catches in Onderstepoort-type black-light traps, in particular in Sardinia where the species is considered endemic. Methods We built a dynamic model that allows describing the effect of eco-climatic indicators on the monthly abundances of C. imicola in Sardinia. Model precision and accuracy were evaluated according to the influence of process and observation errors. Results A first-order autoregressive cofactor, a digital elevation model and MODIS Land Surface Temperature (LST)/or temperatures acquired from weather stations explained ~77% of the variability encountered in the samplings carried out in 9 sites during 6?years. Incorporating Normalized Difference Vegetation Index (NDVI) or rainfall did not increase the model's predictive capacity. On average, dynamics simulations showed good accuracy (predicted vs. observed r corr?=?0.9). Although the model did not always reproduce the absolute levels of monthly abundances peaks, it succeeded in reproducing the seasonality in population level and allowed identifying the periods of low abundances and with no apparent activity. On that basis, we mapped C. imicola monthly distribution over the entire Sardinian region. Conclusions This study demonstrated prospects for modelling data arising from Culicoides longitudinal entomological surveillance. The framework explicitly incorporates the influence of eco-climatic factors on population growth rates and accounts for observation and process errors. Upon validation, such a model could be used to predict monthly population abundances on the basis of environmental conditions, and hence can potentially reduce the amount of entomological surveillance. PMID:23174043

2012-01-01

62

Computational analysis of the LRRK2 interactome.  

PubMed

LRRK2 was identified in 2004 as the causative protein product of the Parkinson's disease locus designated PARK8. In the decade since then, genetic studies have revealed at least 6 dominant mutations in LRRK2 linked to Parkinson's disease, alongside one associated with cancer. It is now well established that coding changes in LRRK2 are one of the most common causes of Parkinson's. Genome-wide association studies (GWAs) have, more recently, reported single nucleotide polymorphisms (SNPs) around the LRRK2 locus to be associated with risk of developing sporadic Parkinson's disease and inflammatory bowel disorder. The functional research that has followed these genetic breakthroughs has generated an extensive literature regarding LRRK2 pathophysiology; however, there is still no consensus as to the biological function of LRRK2. To provide insight into the aspects of cell biology that are consistently related to LRRK2 activity, we analysed the plethora of candidate LRRK2 interactors available through the BioGRID and IntAct data repositories. We then performed GO terms enrichment for the LRRK2 interactome. We found that, in two different enrichment portals, the LRRK2 interactome was associated with terms referring to transport, cellular organization, vesicles and the cytoskeleton. We also verified that 21 of the LRRK2 interactors are genetically linked to risk for Parkinson's disease or inflammatory bowel disorder. The implications of these findings are discussed, with particular regard to potential novel areas of investigation. PMID:25737818

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

2015-01-01

63

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)

2009-03-03

64

Computational analysis of the LRRK2 interactome  

PubMed Central

LRRK2 was identified in 2004 as the causative protein product of the Parkinson’s disease locus designated PARK8. In the decade since then, genetic studies have revealed at least 6 dominant mutations in LRRK2 linked to Parkinson’s disease, alongside one associated with cancer. It is now well established that coding changes in LRRK2 are one of the most common causes of Parkinson’s. Genome-wide association studies (GWAs) have, more recently, reported single nucleotide polymorphisms (SNPs) around the LRRK2 locus to be associated with risk of developing sporadic Parkinson’s disease and inflammatory bowel disorder. The functional research that has followed these genetic breakthroughs has generated an extensive literature regarding LRRK2 pathophysiology; however, there is still no consensus as to the biological function of LRRK2. To provide insight into the aspects of cell biology that are consistently related to LRRK2 activity, we analysed the plethora of candidate LRRK2 interactors available through the BioGRID and IntAct data repositories. We then performed GO terms enrichment for the LRRK2 interactome. We found that, in two different enrichment portals, the LRRK2 interactome was associated with terms referring to transport, cellular organization, vesicles and the cytoskeleton. We also verified that 21 of the LRRK2 interactors are genetically linked to risk for Parkinson’s disease or inflammatory bowel disorder. The implications of these findings are discussed, with particular regard to potential novel areas of investigation. PMID:25737818

Denny, Paul; Lovering, Ruth C.; Lewis, Patrick A.

2015-01-01

65

A Unified Spatiotemporal Modeling Approach for Predicting Concentrations of Multiple Air Pollutants in the Multi-Ethnic Study of Atherosclerosis and Air Pollution  

PubMed Central

Background: Cohort studies of the relationship between air pollution exposure and chronic health effects require predictions of exposure over long periods of time. Objectives: We developed a unified modeling approach for predicting fine particulate matter, nitrogen dioxide, oxides of nitrogen, and black carbon (as measured by light absorption coefficient) in six U.S. metropolitan regions from 1999 through early 2012 as part of the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air). Methods: We obtained monitoring data from regulatory networks and supplemented those data with study-specific measurements collected from MESA Air community locations and participants’ homes. In each region, we applied a spatiotemporal model that included a long-term spatial mean, time trends with spatially varying coefficients, and a spatiotemporal residual. The mean structure was derived from a large set of geographic covariates that was reduced using partial least-squares regression. We estimated time trends from observed time series and used spatial smoothing methods to borrow strength between observations. Results: Prediction accuracy was high for most models, with cross-validation R2 (R2CV) > 0.80 at regulatory and fixed sites for most regions and pollutants. At home sites, overall R2CV ranged from 0.45 to 0.92, and temporally adjusted R2CV ranged from 0.23 to 0.92. Conclusions: This novel spatiotemporal modeling approach provides accurate fine-scale predictions in multiple regions for four pollutants. We have generated participant-specific predictions for MESA Air to investigate health effects of long-term air pollution exposures. These successes highlight modeling advances that can be adopted more widely in modern cohort studies. Citation: Keller JP, Olives C, Kim SY, Sheppard L, Sampson PD, Szpiro AA, Oron AP, Lindström J, Vedal S, Kaufman JD. 2015. A unified spatiotemporal modeling approach for predicting concentrations of multiple air pollutants in the Multi-Ethnic Study of Atherosclerosis and Air Pollution. Environ Health Perspect 123:301–309;?http://dx.doi.org/10.1289/ehp.1408145 PMID:25398188

Olives, Casey; Kim, Sun-Young; Sheppard, Lianne; Sampson, Paul D.; Szpiro, Adam A.; Oron, Assaf P.; Lindström, Johan; Vedal, Sverre; Kaufman, Joel D.

2014-01-01

66

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

67

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

NASA Astrophysics Data System (ADS)

Terrestrial biosphere models (TBMs) are used to extrapolate local observations and process-level understanding of land-atmosphere carbon exchange to larger regions, and can serve as a predictive tool for examining carbon-climate interactions and global change. Understanding and improving the performance of TBMs is thus crucial to the carbon cycle research community. In this work, we evaluate the spatiotemporal patterns of net ecosystem exchange (NEE) simulated by TBMs using atmospheric CO2 observations and a Geostatistical Inverse Modeling (GIM) framework. The evaluation methodology is based on the ability (or inability) of the spatiotemporal patterns in NEE estimates to explain the variability observed in atmospheric CO2 distribution. More simply, we examine whether the spatiotemporal patterns of NEE simulated by TBMs (including CASA-GFED, ORCHIDEE, VEGAS2 and SiB3) are consistent with the variations observed in the atmosphere. A similar GIM methodology is also applied using environmental variables (such as water availability, temperature, radiation, etc.) rather than TBMs, to explore the environmental processes associated with the variability of NEE, and determine which processes are associated with good/poor performance in TBMs. We find that NEE simulated by TBMs is consistent with that seen by atmospheric measurements more often during growing season months (Apr-Sept) than during the non-growing season. Over Temperate Broadleaf and Mixed Forests, Temperate Coniferous Forests and Temperate Grasslands, Savannas and Shrublands, atmospheric measurements are sufficiently sensitive to NEE fluxes to constrain the evaluation of model performance during the majority of the year (about 7-8 months in a year, mostly in growing season). For these regions and months, at least one of the TBMs is found to be able to reproduce the observed variability, but the most representative TBM varies by region and month. For the remaining months, none of the TBMs are able to reproduce the observed variability, whereas a linear combination of environmental variables is able to do so. By further comparing environmental processes associated with the spatiotemporal variability of NEE from the observations and from each TBM, we find that TBMs perform well when radiation-related processes are dominant; however, TBMs perform less well when water-availability (and temperature) are more important. It thus appears that the representation of water availability and its impact on fluxes within TBMs are areas of opportunity for improving TBM predictions, for example, in the seasonal transition. Further exploration of the processes associated with water availability in state-of-the-art TBMs, such as soil respiration, could therefore lead to improvements in their ability to represent the spatiotemporal variability of fluxes during the dormant season and their ability to represent phenology and carbon exchange during transition months.

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

2013-12-01

68

Spatio-temporal predictive model based on environmental factors for juvenile spotted seatrout in Texas estuaries using boosted regression trees  

Microsoft Academic Search

Long-term, fisheries-independent bag seine surveys conducted in TX, USA estuaries from 1977 to 2009 were used to develop a spatio-temporal species-environment model for juvenile spotted seatrout, Cynoscion nebulous. Relationships between environmental predictors and juvenile spotted seatrout distribution were investigated using boosted regression trees (BRTs). Results showed good model performance and suggested that, in relation to environmental factors, juvenile spotted seatrout

John T. Froeschke; Bridgette F. Froeschke

2011-01-01

69

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

70

The organelle-focused proteomes and interactomes in rice.  

PubMed

Protein subcellular localization has been a long-standing key problem in investigating proteins' function, which provides important clues for revealing their functions and aids in understanding their interactions with other biomolecules at the cellular level. Here, we systematically defined the organelle-focused proteomes and interactomes in Oryza sativa. A total of 83.42% of the whole rice proteome obtained their subcellular localizations based on manual annotation, manual adjustment and predictors' cross validation. The final organelle-focused interactomes were located in nine organelles. Furthermore, we discussed the cross talk bias between different organelles and the function organization accounting for nine organelles. Motif analysis illustrated the protein interaction bias in different organelles to implement certain biology functions. We exemplified the connection between functions and the overrepresented motifs in the organelle-focused interactomes and exemplified how to infer the functions of unknown proteins via expanding the overrepresented motifs. PMID:25059325

Liu, Lili; Jiang, Li; Chen, Ming

2014-01-01

71

Proteomic dissection of the VHL interactome  

PubMed Central

The von Hippel-Lindau (VHL) tumor suppressor gene encodes a component of a ubiquitin ligase complex containing elongin B, elongin C, cullin 2, and Rbx1, which acts as a negative regulator of hypoxia inducible factor (HIF). VHL ubiquitinates and degrades the alpha subunits of HIF and this is proposed to suppress tumorigenesis and tumor angiogenesis. Several lines of evidence also suggest important roles for HIF-independent VHL functions in maintenance of primary cilium, extracellular matrix formation, and tumor suppression. We undertook a series of proteomic analyses to gain a comprehensive picture of the VHL-interacting proteins. We found that the ARF tumor suppressor interacts with VHL30, a longer VHL isoform, but not with VHL19, a shorter VHL isoform. ARF was found to release VHL30 from the E3 ligase complex, promoting the binding of VHL30 to a protein arginine methyltransferase, PRMT3. Our analysis of the VHL19 interactome also uncovered that VHL19 displays affinity to collagens and their biosynthesis enzymes. PMID:21942715

Lai, Yanlai; Song, Meihua; Hakala, Kevin; Weintraub, Susan T.; Shiio, Yuzuru

2011-01-01

72

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

73

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

74

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

75

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

76

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

PubMed Central

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

77

A critical and Integrated View of the Yeast Interactome  

PubMed Central

Global studies of protein–protein interactions are crucial to both elucidating gene function and producing an integrated view of the workings of living cells. High-throughput studies of the yeast interactome have been performed using both genetic and biochemical screens. Despite their size, the overlap between these experimental datasets is very limited. This could be due to each approach sampling only a small fraction of the total interactome. Alternatively, a large proportion of the data from these screens may represent false-positive interactions. We have used the Genome Information Management System (GIMS) to integrate interactome datasets with transcriptome and protein annotation data and have found significant evidence that the proportion of false-positive results is high. Not all high-throughput datasets are similarly contaminated, and the tandem affinity purification (TAP) approach appears to yield a high proportion of reliable interactions for which corroborating evidence is available. From our integrative analyses, we have generated a set of verified interactome data for yeast. PMID:18629175

Paton, Norman W.; Oliver, Stephen G.

2004-01-01

78

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

79

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...

80

Kinase-two-hybrid: towards the conditional interactome  

PubMed Central

The dynamics of the protein–protein interaction network and how it responds to biological perturbations remain difficult to assay by most traditional techniques. A novel kinase-dependent yeast two-hybrid framework by Stelzl and colleagues (Grossmann et al, 2015) provides a new prism to study how tyrosine phosphorylation regulates the changes in the interactome under varying conditions. PMID:25814556

Ochoa, David; Beltrao, Pedro

2015-01-01

81

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

82

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

83

A Realistic Large-Scale Model of the Cerebellum Granular Layer Predicts Circuit Spatio-Temporal Filtering Properties  

PubMed Central

The way the cerebellar granular layer transforms incoming mossy fiber signals into new spike patterns to be related to Purkinje cells is not yet clear. Here, a realistic computational model of the granular layer was developed and used to address four main functional hypotheses: center-surround organization, time-windowing, high-pass filtering in responses to spike bursts and coherent oscillations in response to diffuse random activity. The model network was activated using patterns inspired by those recorded in vivo. Burst stimulation of a small mossy fiber bundle resulted in granule cell bursts delimited in time (time windowing) and space (center-surround) by network inhibition. This burst–burst transmission showed marked frequency-dependence configuring a high-pass filter with cut-off frequency around 100?Hz. The contrast between center and surround properties was regulated by the excitatory–inhibitory balance. The stronger excitation made the center more responsive to 10–50?Hz input frequencies and enhanced the granule cell output (with spikes occurring earlier and with higher frequency and number) compared to the surround. Finally, over a certain level of mossy fiber background activity, the circuit generated coherent oscillations in the theta-frequency band. All these processes were fine-tuned by NMDA and GABA-A receptor activation and neurotransmitter vesicle cycling in the cerebellar glomeruli. This model shows that available knowledge on cellular mechanisms is sufficient to unify the main functional hypotheses on the cerebellum granular layer and suggests that this network can behave as an adaptable spatio-temporal filter coordinated by theta-frequency oscillations. PMID:20508743

Solinas, Sergio; Nieus, Thierry; D'Angelo, Egidio

2009-01-01

84

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

85

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

86

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

87

Hierarchical modularity and the evolution of genetic interactomes across species  

PubMed Central

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

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

2012-01-01

88

Identifying protein complexes from interactome based on essential proteins and local fitness method.  

PubMed

High-throughput experimental technologies, along with computational predictions, have promoted the emergence of large-scale interactome for numerous organisms. Identification of protein complexes from these interactome networks is crucial to understand principles of cellular organization and predict protein functions. Protein complexes are generally considered as dense subgraphs. However, the real protein complexes do not always have highly connected topologies. In this paper, a novel protein complex identifying method, named EPOF, is proposed, using essential proteins and the local metric of vertex fitness. In EPOF, cliques in the subnetwork which is consisted by the essential proteins are firstly considered as seeds, which are ordered according to their size and the number of their neighbors. A protein complex is extended from a seed based on the evaluation of its neighbors' fitness value. Then, the similar procedure is applied to the cliques identified in the subnetwork which is consisted by the proteins which is not clustered in the first step. When EPOF identifies complexes by expanding essential protein cliques, the essential proteins have higher priority and lower threshold. When it identifies complexes by expanding nonessential protein cliques, the nonessential proteins have higher priority and lower threshold. Finally, the last step, we output the identified complexes set. The proposed algorithm EPOF is applied to the unweighted and weighted interaction networks of S. cerevisiae and detects many well known protein complexes. We compare the performances of EPOF to other ten previous algorithms, including EAGLE, NFC, MCODE, DPClus, IPCA, CPM, MCL, CMC, SPICi, and Core-Attachment. Experimental results show that EPOF outperforms other previous competing algorithms in terms of matching with known complexes, sensitivity, specificity, f-measure, function enrichment and accuracy. The program and related files available on https://github.com/gangchen/epof. PMID:22711784

Wang, Jianxin; Chen, Gang; Liu, Binbin; Li, Min; Pan, Yi

2012-12-01

89

Prediction of Spatiotemporal Patterns of Neural Activity from Pairwise Correlations O. Marre, S. El Boustani, Y. Fregnac, and A. Destexhe*  

E-print Network

of predictability was also observed on experimental data recorded in parietal cortex during slow-wave sleep The structure of the cortical activity and its relevance to sensory processing or motor planning are a long-standing debate [1]. There is a need to describe the structure of the spiking activity based on well

Destexhe, Alain

90

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

91

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

92

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

93

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

94

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

Technology Transfer Automated Retrieval System (TEKTRAN)

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

95

Integrating Interactome, Phenome, and Transcriptome Mapping Data for the C. elegans Germline  

Microsoft Academic Search

By integrating functional genomic and proteomic mapping approaches, biological hypotheses should be formulated with increasing levels of confidence [1–5]. For example, yeast interactome and transcriptome data can be correlated in biologically meaningful ways [6–9]. Here, we combine interactome mapping data generated for a multicellular organism with data from both large-scale phenotypic analysis (“phenome mapping”) and transcriptome profiling. First, we generated

Albertha J. M. Walhout; Jérôme Reboul; Olena Shtanko; Nicolas Bertin; Philippe Vaglio; Hui Ge; Hongmei Lee; Lynn Doucette-Stamm; Kristin C. Gunsalus; Aaron J. Schetter; Diane G. Morton; Kenneth J. Kemphues; Valerie Reinke; Stuart K. Kim; Fabio Piano; Marc Vidal

2002-01-01

96

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

97

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

98

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

PubMed Central

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

99

The Membrane- and Soluble-Protein Helix-Helix Interactome: Similar Geometry via Different Interactions.  

PubMed

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

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

2015-03-01

100

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

101

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

102

Interactomic and Pharmacological Insights on Human Sirt-1  

PubMed Central

Sirt-1 is defined as a nuclear protein involved in the molecular mechanisms of inflammation and neurodegeneration through the de-acetylation of many different substrates even if experimental data in mouse suggest both its cytoplasmatic presence and nucleo-cytoplasmic shuttling upon oxidative stress. Since the experimental structure of human Sirt-1 has not yet been reported, we have modeled its 3D structure, highlighted that it is composed by four different structural regions: N-terminal region, allosteric site, catalytic core and C-terminal region, and underlined that the two terminal regions have high intrinsic disorder propensity and numerous putative phosphorylation sites. Many different papers report experimental studies related to its functional activators because Sirt-1 is implicated in various diseases and cancers. The aim of this article is (i) to present interactomic studies based human Sirt-1 to understand its most important functional relationships in the light of the gene–protein interactions that control major metabolic pathways and (ii) to show by docking studies how this protein binds some activator molecules in order to evidence structural determinants, physico-chemical features and those residues involved in the formation of complexes. PMID:22470339

Sharma, Ankush; Gautam, Vasu; Costantini, Susan; Paladino, Antonella; Colonna, Giovanni

2012-01-01

103

Global tumor protein p53/p63 interactome  

PubMed Central

Cisplatin chemoresistance is a clinical problem that leads to treatment failure in various human epithelial cancers. Members of tumor protein (TP) p53 family play various critical roles in the multiple molecular mechanisms underlying the chemoresistance of tumor cells. However, the in-depth mechanisms of the cellular response to cisplatin-induced cell death are still under thorough investigation. We previously showed that squamous cell carcinoma (SCC) cells exposed to cisplatin display an ATM-dependent phosphorylation of ?Np63?, leading to a specific function of the phosphorylated (p)-?Np63? transcription factor in cisplatin-sensitive tumor cells. We further found that SCC cells expressing non-p-?Np63?-S385G became cisplatin-resistant. Using quantitative mass-spectrometry of protein complexes labeled with isobaric tags, we showed that TP53 and ?Np63? are involved in numerous protein-protein interactions, which are likely to be implicated in the response of tumor cells to cisplatin exposure. We found that p-?Np63? binds to the splicing complex, leading to repression of mRNA splicing and activation of ACIN1-mediated cell death pathway. In contrast to p-?Np63?, non-p-?Np63? fails to bind the critical members of the splicing complex, thereby leading to activation of RNA splicing and reduction of cell death pathway. Overall, our studies provide an integrated proteomic platform in making a case for the role of the p53/p63 interactome in cisplatin chemoresistance. PMID:22672905

Huang, Yiping; Jeong, Jun Seop; Okamura, Jun; Sook-Kim, Myoung; Zhu, Heng; Guerrero-Preston, Rafael; Ratovitski, Edward A.

2012-01-01

104

Interactome analysis reveals ezrin can adopt multiple conformational states.  

PubMed

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

2013-12-01

105

Transcriptional atlas of cardiogenesis maps congenital heart disease interactome.  

PubMed

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

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

2014-07-01

106

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

PubMed Central

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

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

2013-01-01

107

Visualisation and graph-theoretic analysis of a large-scale protein structural interactome  

Microsoft Academic Search

Background: Large-scale protein interaction maps provide a new, global perspective with which to analyse protein function. PSIMAP, the Protein Structural Interactome Map, is a database of all the structurally observed interactions between superfamilies of protein domains with known three-dimensional structure in the PDB. PSIMAP incorporates both functional and evolutionary information into a single network. Results: We present a global analysis

Dan M. Bolser; Panos Dafas; Richard Harrington; Jong Park; Michael Schroeder

2003-01-01

108

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

PubMed

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

109

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

PubMed Central

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

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

2009-01-01

110

Analysis of the human protein interactome and comparison with yeast, worm and fly interaction datasets  

Microsoft Academic Search

We present the first analysis of the human proteome with regard to interactions between proteins. We also compare the human interactome with the available interaction datasets from yeast (Saccharomyces cerevisiae), worm (Caenorhabditis elegans) and fly (Drosophila melanogaster). Of >70,000 binary interactions, only 42 were common to human, worm and fly, and only 16 were common to all four datasets. An

T K B Gandhi; Jun Zhong; Suresh Mathivanan; L Karthick; K N Chandrika; S Sujatha Mohan; Salil Sharma; Stefan Pinkert; Shilpa Nagaraju; Balamurugan Periaswamy; Goparani Mishra; Kannabiran Nandakumar; Beiyi Shen; Nandan Deshpande; Rashmi Nayak; Malabika Sarker; Jef D Boeke; Giovanni Parmigiani; Jörg Schultz; Joel S Bader; Akhilesh Pandey

2006-01-01

111

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

PubMed Central

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

112

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

113

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

114

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

PubMed

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

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

2013-01-01

115

Human transcriptional interactome of chromatin contribute to gene co-expression  

PubMed Central

Background Transcriptional interactome of chromatin is one of the important mechanisms in gene transcription regulation. By chromatin conformation capture and 3D FISH experiments, several chromatin interactions cases among sequence-distant genes or even inter-chromatin genes were reported. However, on genomics level, there is still little evidence to support these mechanisms. Recently based on Hi-C experiment, a genome-wide picture of chromatin interactions in human cells was presented. It provides a useful material for analysing whether the mechanism of transcriptional interactome is common. Results The main work here is to demonstrate whether the effects of transcriptional interactome on gene co-expression exist on genomic level. While controlling the effects of transcription factors control similarities (TCS), we tested the correlation between Hi-C interaction and the mutual ranks of gene co-expression rates (provided by COXPRESdb) of intra-chromatin gene pairs. We used 6,084 genes with both TF annotation and co-expression information, and matched them into 273,458 pairs with similar Hi-C interaction ranks in different cell types. The results illustrate that co-expression is strongly associated with chromatin interaction. Further analysis using GO annotation reveals potential correlation between gene function similarity, Hi-C interaction and their co-expression. Conclusions According to the results in this research, the intra-chromatin interactome may have relation to gene function and associate with co-expression. This study provides evidence for illustrating the effect of transcriptional interactome on transcription regulation. PMID:21156067

2010-01-01

116

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

117

Efficient Mining of Spatiotemporal Patterns  

Microsoft Academic Search

Abstract. The problem of mining spatiotemporal ,patterns is finding sequences,of events ,that occur frequently in spatiotemporal datasets. Spatiotemporal datasets store the evolution of objects over time. Examples include sequences of sensor images of a geographical region, data that describes the location and movement of individual objects over time, or data that describes the evolution of natural phenomena, such as forest

Ilias Tsoukatos; Dimitrios Gunopulos

2001-01-01

118

Spatiotemporal aggregate computation: a survey  

Microsoft Academic Search

Spatiotemporal databases are becoming increasingly more common. Typically, applications modeling spatiotemporal objects need to process vast amounts of data. In such cases, generating aggregate information from the data set is more useful than individually analyzing every entry. In this paper, we study the most relevant techniques for the evaluation of aggregate queries on spatial, temporal, and spatiotemporal data. We also

Inés Fernando Vega López; Richard T. Snodgrass; Bongki Moon

2005-01-01

119

Parabolic Resonance: A Route to Hamiltonian Spatiotemporal Chaos  

SciTech Connect

We show that initial data near an unperturbed stable plane wave can evolve into a regime of spatiotemporal chaos in the slightly forced conservative periodic one-dimensional nonlinear Schroedinger equation. Statistical measures are employed to demonstrate that this spatiotemporal chaos is intermittent: there are windows in time for which the solution gains spatial coherence. The parameters and initial profiles that lead to such intermittency are predicted by utilizing a novel geometrical description of the integrable unforced equation.

Shlizerman, Eli; Rom-Kedar, Vered [Faculty of Mathematics and Computer Science, Weizmann Institute of Science, Post Office Box 26, Rehovot 76100 (Israel)

2009-01-23

120

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 eight seconds for a frame size of 500 nm. 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

121

Integrating genomic, transcriptomic, and interactome data to improve Peptide and protein identification in shotgun proteomics.  

PubMed

Mass spectrometry (MS)-based shotgun proteomics is an effective technology for global proteome profiling. The ultimate goal is to assign tandem MS spectra to peptides and subsequently infer proteins and their abundance. In addition to database searching and protein assembly algorithms, computational approaches have been developed to integrate genomic, transcriptomic, and interactome information to improve peptide and protein identification. Earlier efforts focus primarily on making databases more comprehensive using publicly available genomic and transcriptomic data. More recently, with the increasing affordability of the Next Generation Sequencing (NGS) technologies, personalized protein databases derived from sample-specific genomic and transcriptomic data have emerged as an attractive strategy. In addition, incorporating interactome data not only improves protein identification but also puts identified proteins into their functional context and thus facilitates data interpretation. In this paper, we survey the major integrative bioinformatics approaches that have been developed during the past decade and discuss their merits and demerits. PMID:24792918

Wang, Xiaojing; Zhang, Bing

2014-06-01

122

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

PubMed Central

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

2008-01-01

123

Profiling the Human Protein-DNA Interactome Reveals MAPK1 as a Transcriptional Repressor of Interferon Signalling  

PubMed Central

SUMMARY Protein-DNA interactions (PDIs) mediate a broad range of functions essential for cellular differentiation, function, and survival. However, it is still a daunting task to comprehensively identify and profile sequence-specific PDIs in complex genomes. Here, we have used a combined bioinformatics and protein microarray-based strategy to systematically characterize the human protein-DNA interactome. We identified 17,718 PDIs between 460 DNA motifs predicted to regulate transcription and 4,191 human proteins of various functional classes. Among them, we recovered many known PDIs for transcription factors (TFs). We also identified a large number of new PDIs for known TFs, as well as for previously uncharacterized TFs. Remarkably, we found that over three hundred proteins not previously annotated as TFs also showed sequence-specific PDIs, including RNA binding proteins, mitochondrial proteins, and protein kinases. One of such unconventional DNA-binding proteins, MAPK1, acts as a transcriptional repressor for interferon gamma-induced genes. PMID:19879846

Hu, Shaohui; Xie, Zhi; Onishi, Akishi; Yu, Xueping; Jiang, Lizhi; Lin, Jimmy; Rho, Hee-sool; Woodard, Crystal; Wang, Hong; Jeong, Jun-Seop; Long, Shunyou; He, Xiaofei; Wade, Herschel; Blackshaw, Seth; Qian, Jiang; Zhu, Heng

2009-01-01

124

Label-free quantitative proteomic analysis of the YAP/TAZ interactome.  

PubMed

The function of an individual protein is typically defined by protein-protein interactions orchestrating the formation of large complexes critical for a wide variety of biological processes. Over the last decade the analysis of purified protein complexes by mass spectrometry became a key technique to identify protein-protein interactions. We present a fast and straightforward approach for analyses of interacting proteins combining a Flp-in single-copy cellular integration system and single-step affinity purification with single-shot mass spectrometry analysis. We applied this protocol to the analysis of the YAP and TAZ interactome. YAP and TAZ are the downstream effectors of the mammalian Hippo tumor suppressor pathway. Our study provides comprehensive interactomes for both YAP and TAZ and does not only confirm the majority of previously described interactors but, strikingly, revealed uncharacterized interaction partners that affect YAP/TAZ TEAD-dependent transcription. Among these newly identified candidates are Rassf8, thymopoetin, and the transcription factors CCAAT/enhancer-binding protein (C/EBP)?/? and core-binding factor subunit ? (Cbfb). In addition, our data allowed insights into complex stoichiometry and uncovered discrepancies between the YAP and TAZ interactomes. Taken together, the stringent approach presented here could help to significantly sharpen the understanding of protein-protein networks. PMID:24573087

Kohli, Priyanka; Bartram, Malte P; Habbig, Sandra; Pahmeyer, Caroline; Lamkemeyer, Tobias; Benzing, Thomas; Schermer, Bernhard; Rinschen, Markus M

2014-05-01

125

Interactome mapping reveals important pathways in skeletal muscle development of pigs.  

PubMed

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

126

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

127

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

128

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

129

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

PubMed Central

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

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

2010-01-01

130

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

PubMed

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

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

2010-06-22

131

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

132

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

133

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

NASA Astrophysics Data System (ADS)

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

Liang, Dong; Kumar, Naresh

2013-06-01

134

Reconstruction of the experimentally supported human protein interactome: what can we learn?  

PubMed Central

Background Understanding the topology and dynamics of the human protein-protein interaction (PPI) network will significantly contribute to biomedical research, therefore its systematic reconstruction is required. Several meta-databases integrate source PPI datasets, but the protein node sets of their networks vary depending on the PPI data combined. Due to this inherent heterogeneity, the way in which the human PPI network expands via multiple dataset integration has not been comprehensively analyzed. We aim at assembling the human interactome in a global structured way and exploring it to gain insights of biological relevance. Results First, we defined the UniProtKB manually reviewed human “complete” proteome as the reference protein-node set and then we mined five major source PPI datasets for direct PPIs exclusively between the reference proteins. We updated the protein and publication identifiers and normalized all PPIs to the UniProt identifier level. The reconstructed interactome covers approximately 60% of the human proteome and has a scale-free structure. No apparent differentiating gene functional classification characteristics were identified for the unrepresented proteins. The source dataset integration augments the network mainly in PPIs. Polyubiquitin emerged as the highest-degree node, but the inclusion of most of its identified PPIs may be reconsidered. The high number (>300) of connections of the subsequent fifteen proteins correlates well with their essential biological role. According to the power-law network structure, the unrepresented proteins should mainly have up to four connections with equally poorly-connected interactors. Conclusions Reconstructing the human interactome based on the a priori definition of the protein nodes enabled us to identify the currently included part of the human “complete” proteome, and discuss the role of the proteins within the network topology with respect to their function. As the network expansion has to comply with the scale-free theory, we suggest that the core of the human interactome has essentially emerged. Thus, it could be employed in systems biology and biomedical research, despite the considerable number of currently unrepresented proteins. The latter are probably involved in specialized physiological conditions, justifying the scarcity of related PPI information, and their identification can assist in designing relevant functional experiments and targeted text mining algorithms. PMID:24088582

2013-01-01

135

Intro Temporal Poisson Spatiotemporal exchangeability Discussion Are Declustered Earthquake Catalogs Poisson?  

E-print Network

Phenomenology · Earthquakes destroy and kill. Studied since ancient times. Prediction is an old goal: save livesIntro Temporal Poisson Spatiotemporal exchangeability Discussion Are Declustered Earthquake fit Poisson process models have used tests that ignore earthquake locations. They divide time

Stark, Philip B.

136

Spatio-temporal modulated polarimetry  

NASA Astrophysics Data System (ADS)

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

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

2011-10-01

137

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

138

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

139

Resolving the structure of interactomes with hierarchical agglomerative clustering  

PubMed Central

Background Graphs provide a natural framework for visualizing and analyzing networks of many types, including biological networks. Network clustering is a valuable approach for summarizing the structure in large networks, for predicting unobserved interactions, and for predicting functional annotations. Many current clustering algorithms suffer from a common set of limitations: poor resolution of top-level clusters; over-splitting of bottom-level clusters; requirements to pre-define the number of clusters prior to analysis; and an inability to jointly cluster over multiple interaction types. Results A new algorithm, Hierarchical Agglomerative Clustering (HAC), is developed for fast clustering of heterogeneous interaction networks. This algorithm uses maximum likelihood to drive the inference of a hierarchical stochastic block model for network structure. Bayesian model selection provides a principled method for collapsing the fine-structure within the smallest groups, and for identifying the top-level groups within a network. Model scores are additive over independent interaction types, providing a direct route for simultaneous analysis of multiple interaction types. In addition to inferring network structure, this algorithm generates link predictions that with cross-validation provide a quantitative assessment of performance for real-world examples. Conclusions When applied to genome-scale data sets representing several organisms and interaction types, HAC provides the overall best performance in link prediction when compared with other clustering methods and with model-free graph diffusion kernels. Investigation of performance on genome-scale yeast protein interactions reveals roughly 100 top-level clusters, with a long-tailed distribution of cluster sizes. These are in turn partitioned into 1000 fine-level clusters containing 5 proteins on average, again with a long-tailed size distribution. Top-level clusters correspond to broad biological processes, whereas fine-level clusters correspond to discrete complexes. Surprisingly, link prediction based on joint clustering of physical and genetic interactions performs worse than predictions based on individual data sets, suggesting a lack of synergy in current high-throughput data. PMID:21342576

2011-01-01

140

Oxidative status interactome map: towards novel approaches in experiment planning, data analysis, diagnostics and therapy.  

PubMed

Experimental evidence suggests an immense variety of processes associated with and aimed at producing reactive oxygen and/or nitrogen species. Clinical studies implicate an enormous range of pathologies associated with reactive oxygen/nitrogen species metabolism deregulation, particularly oxidative stress. Recent advances in biochemistry, proteomics and molecular biology/biophysics of cells suggest oxidative stress to be an endpoint of complex dysregulation events of conjugated pathways consolidated under the term, proposed here, "oxidative status". The oxidative status concept, in order to allow for novel diagnostic and therapeutic approaches, requires elaboration of a new logic system comprehending all the features, versatility and complexity of cellular pro- and antioxidative components of different nature. We have developed a curated and regularly updated interactive interactome map of human cellular-level oxidative status allowing for systematization of the related most up-to-date experimental data. A total of more than 600 papers were selected for the initial creation of the map. The map comprises more than 300 individual factors with respective interactions, all subdivided hierarchically for logical analysis purposes. The pilot application of the interactome map suggested several points for further development of oxidative status-based technologies. PMID:23698602

Zolotukhin, Peter; Kozlova, Yulia; Dovzhik, Anastasiya; Kovalenko, Konstantin; Kutsyn, Kseniya; Aleksandrova, Anzhela; Shkurat, Tatyana

2013-08-01

141

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

142

Spatiotemporal dynamics of HIV infection  

NASA Astrophysics Data System (ADS)

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

Strain, Matthew Carl

143

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

PubMed Central

The chromatin regulatory factor SIRT6 plays pivotal roles in metabolism, tumor suppression, and aging biology. Despite the fundamental roles of SIRT6 in physiology and disease, only a handful of molecular and functional interactions of SIRT6 have been reported. Here, we characterize the SIRT6 interactome and identify 80+ novel SIRT6-interacting proteins. The discovery of these SIRT6-associations considerably expands knowledge of the SIRT6 interaction network, and suggests previously unknown functional interactions of SIRT6 in fundamental cellular processes. These include chromatin remodeling, mitotic chromosome segregation, protein homeostasis, and transcriptional elongation. Extended analysis of the SIRT6 interaction with G3BP1, a master stress response factor, uncovers an unexpected role and mechanism of SIRT6 in regulating stress granule assembly and cellular stress resistance. PMID:24169447

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

2013-01-01

144

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

PubMed

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

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

2015-01-01

145

The L1TD1 Protein Interactome Reveals the Importance of Post-transcriptional Regulation in Human Pluripotency.  

PubMed

The RNA-binding protein L1TD1 is one of the most specific and abundant proteins in pluripotent stem cells and is essential for the maintenance of pluripotency in human cells. Here, we identify the protein interaction network of L1TD1 in human embryonic stem cells (hESCs) and provide insights into the interactome network constructed in human pluripotent cells. Our data reveal that L1TD1 has an important role in RNA splicing, translation, protein traffic, and degradation. L1TD1 interacts with multiple stem-cell-specific proteins, many of which are still uncharacterized in the context of development. Further, we show that L1TD1 is a part of the pluripotency interactome network of OCT4, SOX2, and NANOG, bridging nuclear and cytoplasmic regulation and highlighting the importance of RNA biology in pluripotency. PMID:25702638

Emani, Maheswara Reddy; Närvä, Elisa; Stubb, Aki; Chakroborty, Deepankar; Viitala, Miro; Rokka, Anne; Rahkonen, Nelly; Moulder, Robert; Denessiouk, Konstantin; Trokovic, Ras; Lund, Riikka; Elo, Laura L; Lahesmaa, Riitta

2015-03-10

146

The L1TD1 Protein Interactome Reveals the Importance of Post-transcriptional Regulation in Human Pluripotency  

PubMed Central

Summary The RNA-binding protein L1TD1 is one of the most specific and abundant proteins in pluripotent stem cells and is essential for the maintenance of pluripotency in human cells. Here, we identify the protein interaction network of L1TD1 in human embryonic stem cells (hESCs) and provide insights into the interactome network constructed in human pluripotent cells. Our data reveal that L1TD1 has an important role in RNA splicing, translation, protein traffic, and degradation. L1TD1 interacts with multiple stem-cell-specific proteins, many of which are still uncharacterized in the context of development. Further, we show that L1TD1 is a part of the pluripotency interactome network of OCT4, SOX2, and NANOG, bridging nuclear and cytoplasmic regulation and highlighting the importance of RNA biology in pluripotency. PMID:25702638

Emani, Maheswara Reddy; Närvä, Elisa; Stubb, Aki; Chakroborty, Deepankar; Viitala, Miro; Rokka, Anne; Rahkonen, Nelly; Moulder, Robert; Denessiouk, Konstantin; Trokovic, Ras; Lund, Riikka; Elo, Laura L.; Lahesmaa, Riitta

2015-01-01

147

Disrupted in Schizophrenia 1 Interactome: evidence for the close connectivity of risk genes and a potential synaptic basis for schizophrenia  

Microsoft Academic Search

Disrupted in Schizophrenia 1 (DISC1) is a schizophrenia risk gene associated with cognitive deficits in both schizophrenics and the normal ageing population. In this study, we have generated a network of protein–protein interactions (PPIs) around DISC1. This has been achieved by utilising iterative yeast-two hybrid (Y2H) screens, combined with detailed pathway and functional analysis. This so-called ‘DISC1 interactome’ contains many

L M Camargo; V Collura; J-C Rain; K Mizuguchi; H Hermjakob; S Kerrien; T P Bonnert; P J Whiting; N J Brandon

2007-01-01

148

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

E-print Network

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

Perez-Lopez, Aron R; Turei, Denes; Modos, Dezso; Lenti, Katalin; Korcsmaros, Tamas; Csermely, Peter

2015-01-01

149

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

150

Optical flow using spatiotemporal filters  

Microsoft Academic Search

A model is presented, consonant with current views regarding the neurophysiology and psychophysics of motion perception, that combines the outputs of a set of spatiotemporal motion-energy filters to estimate image velocity. A parallel implementation computes a distributed representation of image velocity. A measure of image-flow uncertainty is formulated; preliminary results indicate that this uncertainty measure may be used to recognize

David J. Heeger

1988-01-01

151

Spatiotemporal Reasoning about Epidemiological Data  

E-print Network

information systems. Methodology. We describe the general methods of how to (1) store epidemiolog- ical data in geographic information systems. We propose new methods to visualize and reason about epidemiological dataSpatiotemporal Reasoning about Epidemiological Data Peter Revesz , Shasha Wu Keywords Epidemiology

Revesz, Peter

152

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

153

Dynamics of Turing Patterns under Spatiotemporal Forcing  

NASA Astrophysics Data System (ADS)

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

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

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

2003-03-01

154

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

Michael P. Klentschy

2008-04-01

155

Spatiotemporal Wave Patterns: Information Dynamics  

SciTech Connect

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

Mikhail Rabinovich; Lev Tsimring

2006-01-20

156

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

PubMed

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

Kieffer-Kwon, Kyong-Rim; 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

2013-12-19

157

Dynamic evolution of the adenine nucleotide translocase interactome during chemotherapy-induced apoptosis.  

PubMed

The mitochondrial permeability transition pore complex (PTPC) is involved in the control of the mitochondrial membrane permeabilization during apoptosis, necrosis and autophagy. Indeed, the adenine nucleotide translocator (ANT) and the voltage-dependent anion channel (VDAC), two major components of PTPC, are the targets of a variety of proapoptotic inducers. Using co-immunoprecipitation and proteomic analysis, we identified some of the interacting partners of ANT in several normal tissues and human cancer cell lines. During chemotherapy-induced apoptosis, some of these interactions were constant (e.g. ANT-VDAC), whereas others changed strongly concomitantly with the dissipation of the mitochondrial transmembrane potential and until nuclear degradation occurred (e.g. Bax, Bcl-2, subunits of the respiratory chain, a subunit of the phosphatase PP2A, phospholipase PLC beta 4 and IP3 receptor). In addition, a glutathione-S-transferase (GST) interacts with ANT in normal tissue, in colon carcinoma cells and in vitro. This interaction is lost during apoptosis induction, suggesting that GST behaves as an endogenous repressor of PTPC and ANT pore opening. Thus, ANT is connected to mitochondrial proteins as well as to proteins from other organelles such as the endoplasmic reticulum forming a dynamic polyprotein complex. Changes within this ANT interactome coordinate the lethal response of cells to apoptosis induction. PMID:15377997

Verrier, Florence; Deniaud, Aurélien; Lebras, Morgane; Métivier, Didier; Kroemer, Guido; Mignotte, Bernard; Jan, Gwenaël; Brenner, Catherine

2004-10-21

158

Interactome of the negative regulator of nuclear import BRCA1-binding protein 2  

PubMed Central

Although the negative regulator of nuclear import (NRNI) BRCA1 binding protein 2 (BRAP2) is highly expressed in testis, its role is largely unknown. Here we address this question by documenting the BRAP2 interactome from human testis, using the yeast 2-hybrid system to identify BRAP2-interacting proteins with roles in diverse cellular processes, including regulation of the actin cytoskeleton, ubiquitinylation, cell cycle/apoptosis and transcription. Interaction with BRAP2 in adult mouse testis with three of these, PH domain and leucine rich repeat protein phosphatase 1 (PHLPP1), A-Kinase anchor protein (AKAP3) and DNA methyl transferase 1 (DNMT1), was confirmed by coimmunoprecipitation assays. BRAP2's ability to inhibit PHLPP1 and DNMT1 nuclear localisation was also confirmed by quantitative confocal microscopy. Importantly, the physiological relevance thereof was implied by the cytoplasmic localisation of PHLPP1, AKAP3 and DNMT1 in pachytene spermatocytes/round spermatids where BRAP2 is present at high levels, and nuclear localisation of PHLPP1 and DNMT1 in spermatogonia concomitant with lower levels of BRAP2. Interestingly, BRAP2 was also present in murine spermatozoa, in part colocalised with AKAP3. Together the results indicate for the first time that BRAP2 may play an important NRNI role in germ cells of the testis, with an additional, scaffold/structural role in mature spermatozoa. PMID:25820252

Fatima, Shadma; Wagstaff, Kylie M.; Loveland, Kate L.; Jans, David A.

2015-01-01

159

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

PubMed Central

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

2014-01-01

160

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

PubMed Central

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

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

2015-01-01

161

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

162

Determination of the heterogeneous interactome between Edwardsiella tarda and fish gills.  

PubMed

Edwardsiellosis caused by Edwardsiella tarda is a frequent occurrence throughout the world and has resulted in extensive losses in aquaculture. However, information regarding to protein-protein interaction between the pathogenic cells and host is not available although the portal of entry of the pathogen is determined. In this study, fish gill and bacterial pull-down approaches were used to isolate both bacterial outer membrane proteins that bind to gills and fish gill proteins that interact with bacterial cells, respectively. Eight interacting bacterial proteins and twelve interacting fish proteins were obtained. The genes of seven bacterial proteins were cloned and expressed for preparation of antibodies. The prepared antibodies were used to investigate protein-protein interactions between bacterial cells and fish gills. Five heterogeneous protein-protein interactions were determined. Moreover, the protective ability of three of the bacterial recombinant proteins, selected at random, was investigated in a mouse model where they showed significant protection. The gill proteins were highly homologous proteins with from humans and other animals where they are known to be involved in host immunity. These findings indicate that the heterogeneous interactome has significantly biological significance. Our results demonstrate a way to determine and understand the heterogeneous interaction between of E. tarda and gills. PMID:22079874

Liu, Yang; Zhang, Haili; Liu, Yongjun; Li, Hui; Peng, Xuanxian

2012-02-01

163

An extracellular interactome of Immunoglobulin and LRR proteins reveals receptor-ligand networks  

PubMed Central

Extracellular domains of cell-surface receptors and ligands mediate cell-cell communication, adhesion, and initiation of signaling events, but most existing protein-protein “interactome” datasets lack information for extracellular interactions. We probed interactions between receptor extracellular domains, focusing on the Immunoglobulin Superfamily (IgSF), Fibronectin type-III (FnIII) and Leucine-rich repeat (LRR) families of Drosophila, a set of 202 proteins, many of which are known to be important in neuronal and developmental functions. Out of 20503 candidate protein pairs tested, we observed 106 interactions, 83 of which were previously unknown. We ‘deorphanized’ the 20-member subfamily of defective in proboscis IgSF proteins, showing that they selectively interact with an 11-member subfamily of previously uncharacterized IgSF proteins. Both subfamilies interact with a single common ‘orphan’ LRR protein. We also observed new interactions between Hedgehog and EGFR pathway components. Several of these interactions could be visualized in live-dissected embryos, demonstrating that this approach can identify physiologically relevant receptor-ligand pairs. PMID:23827685

Özkan, Engin; Carrillo, Robert A.; Eastman, Catharine L.; Weiszmann, Richard; Waghray, Deepa; Johnson, Karl G.; Zinn, Kai; Celniker, Susan E.; Garcia, K. Christopher

2013-01-01

164

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

165

Mapping the local protein interactome of the NuA3 histone acetyltransferase  

PubMed Central

Protein–protein interactions modulate cellular functions ranging from the activity of enzymes to signal transduction cascades. A technology termed transient isotopic differentiation of interactions as random or targeted (transient I-DIRT) is described for the identification of stable and transient protein–protein interactions in vivo. The procedure combines mild in vivo chemical cross-linking and non-stringent affinity purification to isolate low abundance chromatin-associated protein complexes. Using isotopic labeling and mass spectrometric readout, purified proteins are categorized with respect to the protein ‘bait’ as stable, transient, or contaminant. Here we characterize the local interactome of the chromatin-associated NuA3 histone lysine-acetyltransferase protein complex. We describe transient associations with the yFACT nucleosome assembly complex, RSC chromatin remodeling complex and a nucleosome assembly protein. These novel, physical associations with yFACT, RSC, and Nap1 provide insight into the mechanism of NuA3-associated transcription and chromatin regulation. PMID:19621382

Smart, Sherri K; Mackintosh, Samuel G; Edmondson, Ricky D; Taverna, Sean D; Tackett, Alan J

2009-01-01

166

The Intracellular Interactome of Tetraspanin-enriched Microdomains Reveals Their Function as Sorting Machineries toward Exosomes*  

PubMed Central

Extracellular vesicles are emerging as a potent mechanism of intercellular communication because they can systemically exchange genetic and protein material between cells. Tetraspanin molecules are commonly used as protein markers of extracellular vesicles, although their role in the unexplored mechanisms of cargo selection into exosomes has not been addressed. For that purpose, we have characterized the intracellular tetraspanin-enriched microdomain (TEM) interactome by high throughput mass spectrometry, in both human lymphoblasts and their derived exosomes, revealing a clear pattern of interaction networks. Proteins interacting with TEM receptors cytoplasmic regions presented a considerable degree of overlap, although some highly specific CD81 tetraspanin ligands, such as Rac GTPase, were detected. Quantitative proteomics showed that TEM ligands account for a great proportion of the exosome proteome and that a selective repertoire of CD81-associated molecules, including Rac, is not correctly routed to exosomes in cells from CD81-deficient animals. Our data provide evidence that insertion into TEM may be necessary for protein inclusion into the exosome structure. PMID:23463506

Perez-Hernandez, Daniel; Gutiérrez-Vázquez, Cristina; Jorge, Inmaculada; López-Martín, Soraya; Ursa, Angeles; Sánchez-Madrid, Francisco; Vázquez, Jesús; Yáñez-Mó, María

2013-01-01

167

Precursor of transition to turbulence: spatiotemporal wave front.  

PubMed

To understand transition to turbulence via 3D disturbance growth, we report here results obtained from the solution of Navier-Stokes equation (NSE) to reproduce experimental results obtained by minimizing background disturbances and imposing deterministic excitation inside the shear layer. A similar approach was adopted in Sengupta and Bhaumik [Phys. Rev. Lett. 107, 154501 (2011)], where a route of transition from receptivity to fully developed turbulent stage was explained for 2D flow in terms of the spatio-temporal wave-front (STWF). The STWF was identified as the unit process of 2D turbulence creation for low amplitude wall excitation. Theoretical prediction of STWF for boundary layer was established earlier in Sengupta, Rao, and Venkatasubbaiah [Phys. Rev. Lett. 96, 224504 (2006)] from the Orr-Sommerfeld equation as due to spatiotemporal instability. Here, the same unit process of the STWF during transition is shown to be present for 3D disturbance field from the solution of governing NSE. PMID:24827343

Bhaumik, S; Sengupta, T K

2014-04-01

168

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)

169

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

170

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

171

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

172

Sparse Spatiotemporal Coding for Activity Recognition  

E-print Network

-squares prob- lem to be slow and perform poorly at the task of learning codes that are spatially orientedSparse Spatiotemporal Coding for Activity Recognition Thomas Dean, Rich Washington and Greg Corrado;#12;Sparse Spatiotemporal Coding for Activity Recognition Thomas Dean1 , Rich Washington1 , and Greg Corrado2

Tomkins, Andrew

173

Spatiotemporal Dynamics of Insect-Fire Interactions  

E-print Network

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

Moorcroft, Paul R.

174

Spatiotemporal change footprint pattern discovery: an  

E-print Network

Overview Spatiotemporal change footprint pattern discovery: an inter-disciplinary survey Xun Zhou, Shashi Shekhar and Reem Y. Ali Given a definition of change and a dataset about spatiotemporal (ST) phenomena, ST change footprint discovery is the process of identifying the location and/or time

Minnesota, University of

175

Noise tolerant spatiotemporal chaos computing.  

PubMed

We introduce and design a noise tolerant chaos computing system based on a coupled map lattice (CML) and the noise reduction capabilities inherent in coupled dynamical systems. The resulting spatiotemporal chaos computing system is more robust to noise than a single map chaos computing system. In this CML based approach to computing, under the coupled dynamics, the local noise from different nodes of the lattice diffuses across the lattice, and it attenuates each other's effects, resulting in a system with less noise content and a more robust chaos computing architecture. PMID:25554030

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

2014-12-01

176

Noise tolerant spatiotemporal chaos computing  

NASA Astrophysics Data System (ADS)

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

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

2014-12-01

177

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

178

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

179

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

PubMed Central

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

Carter, C. J.

2013-01-01

180

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

PubMed Central

The human kinome is gaining importance through its promising cancer therapeutic targets, yet no general model to address the kinase inhibitor resistance has emerged. Here, we constructed a systems biology-based framework to catalogue the human kinome, including 538 kinase genes, in the broader context of the human interactome. Specifically, we constructed three networks: a kinase-substrate interaction network containing 7,346 pairs connecting 379 kinases to 36,576 phosphorylation sites in 1,961 substrates, a protein-protein interaction network (PPIN) containing 92,699 pairs, and an atomic resolution PPIN containing 4,278 pairs. We identified the conserved regulatory phosphorylation motifs (e.g., Ser/Thr-Pro) using a sequence logo analysis. We found the typical anticancer target selection strategy that uses network hubs as drug targets, might lead to a high adverse drug reaction risk. Furthermore, we found the distinct network centrality of kinases creates a high anticancer drug resistance risk by feedback or crosstalk mechanisms within cellular networks. This notion is supported by the systematic network and pathway analyses that anticancer drug resistance genes are significantly enriched as hubs and heavily participate in multiple signaling pathways. Collectively, this comprehensive human kinome interactome map sheds light on anticancer drug resistance mechanisms and provides an innovative resource for rational kinase inhibitor design. PMID:25003367

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

2014-01-01

181

Spatiotemporal Thinking in the Geosciences  

NASA Astrophysics Data System (ADS)

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

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

2011-12-01

182

Risk factor analysis and spatiotemporal CART model of cryptosporidiosis in Queensland, Australia  

Microsoft Academic Search

BACKGROUND: It remains unclear whether it is possible to develop a spatiotemporal epidemic prediction model for cryptosporidiosis disease. This paper examined the impact of social economic and weather factors on cryptosporidiosis and explored the possibility of developing such a model using social economic and weather data in Queensland, Australia. METHODS: Data on weather variables, notified cryptosporidiosis cases and social economic

Wenbiao Hu; Kerrie Mengersen; Shilu Tong

2010-01-01

183

Facial Expression Recognition Using Spatiotemporal Boosted Discriminatory  

E-print Network

Facial Expression Recognition Using Spatiotemporal Boosted Discriminatory Classifiers Stephen Moore approach to facial expression recognition in video sequences. Low cost contour features are introduced information to build boosted classifiers for frontal facial expression recognition in video sequences. Facial

Bowden, Richard

184

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

PubMed

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

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

2014-01-01

185

Bayesian Spatio-Temporal Analysis and Geospatial Risk Factors of Human Monocytic Ehrlichiosis  

PubMed Central

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

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

2014-01-01

186

Spatiotemporal Semantics and Moving Objects Research  

E-print Network

SPATIOTEMPORAL?SEMANTICS?AND? MOVING?OBJECTS?RESEARCH Kathleen?Stewart?Hornsby Department?of?Geography,?The?University?of?Iowa kathleen?stewart@uiowa.edu WHO?I?AM... GIScience?faculty?in?Department?of? Geography,?The?University?of?Iowa Interested...?in?spatiotemporal? modeling,?moving?objects?research,?? geospatial?semantics,?ontologies?for? GIS THE?REAL?WORLD... Interconnected… Continuous Dynamic CONTINUANTS?VS? OCCURRENTS Continuant?entities?endure? through?some?extended? interval?of?time Houses,?roads...

Stewart, Kathleen

2009-11-18

187

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

188

Spatiotemporal features for asynchronous event-based data.  

PubMed

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

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

2015-01-01

189

Spatiotemporal features for asynchronous event-based data  

PubMed Central

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

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

2015-01-01

190

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

PubMed Central

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

2013-01-01

191

Spatiotemporal neural pattern similarity supports episodic memory.  

PubMed

Formal computational models of human memory posit a central role of feature representations in episodic memory encoding and retrieval [1-4]. Correspondingly, fMRI studies have found that, in addition to activity level [5, 6], the neural activation pattern similarity across repetitions (i.e., self-similarity) was greater for subsequently remembered than forgotten items [7-9]. This self-similarity has been suggested to reflect pattern reinstatement due to study-phase retrieval [7, 10, 11]. However, the low temporal resolution of fMRI measures could determine neither the temporal precision of study-phase reinstatement nor the processing stage at which the reinstatement supported subsequent memory [12]. Meanwhile, although self-similarity has been shown to correlate with the activity level in the left lateral prefrontal cortex (LPFC) [10, 13], a causal link between left LPFC function and pattern similarity remains to be established. Combining transcranial direct current stimulation (tDCS) and EEG, we found that greater spatiotemporal pattern similarity (STPS) across repetitions of the same item (i.e., self-STPS) during encoding predicted better subsequent memory. The self-STPS located in the right frontal electrodes occurred approximately 500 ms after stimulus onset, reflected item-specific encoding, and contributed to memory above and beyond the effects of ERP amplitude and global pattern similarity (i.e., similarity to all other items in memory space). Anodal stimulation over the left LPFC specifically enhanced memory performance and item-specific STPS in the right frontal electrodes. These results support a causal role of LPFC in enhancing STPS and memory and contribute to a mechanistic understanding of memory formation. PMID:25728695

Lu, Yi; Wang, Changming; Chen, Chuansheng; Xue, Gui

2015-03-16

192

Spatio-temporal Dynamics of Audiovisual Speech Processing  

PubMed Central

The cortical processing of auditory-alone, visual-alone, and audiovisual speech information is temporally and spatially distributed, and functional magnetic resonance imaging (fMRI) cannot adequately resolve its temporal dynamics. In order to investigate a hypothesized spatio-temporal organization for audiovisual speech processing circuits, event-related potentials (ERPs) were recorded using electroencephalography (EEG). Stimuli were congruent audiovisual /b?/, incongruent auditory /b?/ synchronized with visual /g?/, auditory-only /b?/, and visual-only /b?/ and /g?/. Current density reconstructions (CDRs) of the ERP data were computed across the latency interval of 50-250 milliseconds. The CDRs demonstrated complex spatio-temporal activation patterns that differed across stimulus conditions. The hypothesized circuit that was investigated here comprised initial integration of audiovisual speech by the middle superior temporal sulcus (STS), followed by recruitment of the intraparietal sulcus (IPS), followed by activation of Broca's area (Miller and d'Esposito, 2005). The importance of spatio-temporally sensitive measures in evaluating processing pathways was demonstrated. Results showed, strikingly, early (< 100 msec) and simultaneous activations in areas of the supramarginal and angular gyrus (SMG/AG), the IPS, the inferior frontal gyrus, and the dorsolateral prefrontal cortex. Also, emergent left hemisphere SMG/AG activation, not predicted based on the unisensory stimulus conditions was observed at approximately 160 to 220 msec. The STS was neither the earliest nor most prominent activation site, although it is frequently considered the sine qua non of audiovisual speech integration. As discussed here, the relatively late activity of the SMG/AG solely under audiovisual conditions is a possible candidate audiovisual speech integration response. PMID:17920933

Bernstein, Lynne E.; Auer, Edward T.; Wagner, Michael; Ponton, Curtis W.

2007-01-01

193

Mercury Toolset for Spatiotemporal Metadata  

NASA Technical Reports Server (NTRS)

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.

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

2010-01-01

194

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

195

Spatio-temporal statistical models with applications to atmospheric processes  

SciTech Connect

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

Wikle, C.K.

1996-12-31

196

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

PubMed Central

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

Lanan, Michele

2014-01-01

197

Spatio-temporal hybrid Anderson localization  

NASA Astrophysics Data System (ADS)

We address the localization of spatio-temporal wave packets in disordered waveguide arrays whereby temporal localization is mediated by nonlinearity while strong disorder provides Anderson statistical spatial localization. This combination of two different mechanisms allows localization to occur outside the range of parameters where diffraction, dispersion, and self-action have similar strengths, as required for the formation of standard spatio-temporal solitons. Under suitable conditions, nonlinearity is shown to weakly affect the statistically averaged spatial intensity distributions. In contrast, the temporal duration of the localized wave packets strongly depends on the level of disorder.

Lobanov, V. E.; Borovkova, O. V.; Kartashov, Y. V.; Szameit, A.

2014-12-01

198

Optimal spatiotemporal focusing through complex scattering media.  

PubMed

We present an alternative approach for spatiotemporal focusing through complex scattering media by wave front shaping. Using a nonlinear feedback signal to shape the incident pulsed wave front, we show that the limit of a spatiotemporal matched filter can be achieved; i.e., the wave amplitude at the intended time and focus position is maximized for a given input energy. It is exactly what is also achieved with time reversal. Demonstrated with ultrasound experiments, our method is generally applicable to all types of waves. PMID:22400693

Aulbach, Jochen; Bretagne, Alice; Fink, Mathias; Tanter, Mickaël; Tourin, Arnaud

2012-01-01

199

Annotating spatio-temporal datasets for meaningful analysis in the Web  

NASA Astrophysics Data System (ADS)

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

Stasch, Christoph; Pebesma, Edzer; Scheider, Simon

2014-05-01

200

An integrated environment for spatio-temporal analysis, simulation, and representation for public health research  

NASA Astrophysics Data System (ADS)

Geographic space, as the arena within which all of the natural and social processes occur, and time, have become key research components of social science for the past two decades. However, most GIS software packages lack the predictive and analytic capabilities for complex problems, such as spatial statistical methods and spatial modeling. Meanwhile, the spatio-temporally explicit representation of complex, heterogeneous and dynamic geographic data sets is a particularly challenging issue. Many efforts have been made in developing tools for effective representation of health data, spatio-temporal analysis of the data, and the dynamic process simulation of disease transmission. To meet this demand, we attempted to develop a tool for integrating spatio-temporal analysis, simulation and representation of health data and processes. In this paper, we will introduce some methods for spatial temporal data analysis and their applications in public health. We'll describe the conceptual model of spatial temporal process simulation and the process-oriented spatio-temporal data model adopted in the tool we developed. After that, we'll present the framework of our integrated research toolkit, and demonstrate how to conduct analysis, modeling, and simulation with this software. Finally, we will discuss some issues for future studies.

Hu, Haitang; Bao, Shuming; Xu, Bing; Liang, Song

2006-10-01

201

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

202

Spatiotemporal Image Analysis for Fluid Flow Measurements  

E-print Network

Spatiotemporal Image Analysis for Fluid Flow Measurements Christoph S. Garbe, Daniel Kondermann, Markus Jehle, and Bernd J¨ahne Abstract. In this chapter, a framework will be presented for measuring of the flow, a strong linkage between visualization technique, Christoph S. Garbe · Daniel Kondermann · Markus

Garbe, Christoph S.

203

Spatial and Spatio-temporal Data Mining  

Microsoft Academic Search

Summary form only given. The recent advances and price reduction of technologies for collecting spatial and spatio-temporal data like Satellite Images, Cellular Phones, Sensor Networks, and GPS devices has facilitated the collection of data referenced in space and time. These huge collections of data often hide interesting information which conventional systems and classical data mining techniques are unable to discover.

Vania Bogorny; Shashi Shekhar

2010-01-01

204

Mining Complex Spatio-Temporal Sequence Patterns  

Microsoft Academic Search

Mining sequential movement patterns describing group behaviour in potentially streaming spatio-temporal data sets is a challenging problem. Movements are typically noisy and often overlap each other. This makes a set of simple patterns difficult to interpret and sequences diffi- cult to mine. Furthermore, group behaviour is complex. Objects in a group may behave similarly for a period of time (an

Florian Verhein

2009-01-01

205

METHODS FOR SPATIOTEMPORAL DITHERING Jeffrey B. Mulligan  

E-print Network

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

Watson, Andrew B.

206

Spatiotemporal Segmentation Based on Region Merging  

Microsoft Academic Search

This paper proposes a technique for spatio-temporal segmentation to identify the objects present in the scene represented in a video sequence. This technique processes two consecutive frames at a time. A region-merging approach is used to identify the objects in the scene. Starting from an oversegmentation of the current frame, the objects are formed by iteratively merging regions together. Regions

Fabrice Moscheni; Sushil Bhattacharjee; Murat Kunt

1998-01-01

207

Spatiotemporal Features for Effective Facial Expression Recognition  

E-print Network

Spatiotemporal Features for Effective Facial Expression Recognition Hatice C¸inar Akakin and B schemes for automatic recognition of emotion related facial expressions. In one scheme facial landmark- sion database and a state-of-the-art 95.34 % recognition performance is achieved. Key words: facial

208

Spatiotemporal Reconstruction of the Breathing Function  

E-print Network

Spatiotemporal Reconstruction of the Breathing Function D. Duong1 , D. Shastri2 , P. Tsiamyrtzis3@cs.uh.edu, shastrid@uhd.edu, pt@aueb.gr, ipavlidis@uh.edu Abstract. Breathing waveform extracted via nasal thermistor profile for the breathing function via thermal imaging of the nostrils. The method models nasal airflow

209

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

210

A working spatio-temporal model of the human visual system for image restoration and quality assessment applications  

Microsoft Academic Search

This paper describes a spatio-temporal model of the human visual system (HVS) for video imaging applications, predicting the response of the neurons of the primary visual cortex. The model simulates the behavior of the HVS with a three-dimensional filter bank which decomposes the data into perceptual channels, each one being tuned to a specific spatial frequency, orientation and temporal frequency.

1996-01-01

211

Combined Spatio-Temporal Impacts of Climate and Longline Fisheries on the Survival of a Trans-Equatorial  

E-print Network

'Histoire Naturelle, Paris, France Abstract Predicting the impact of human activities and their derivable consequences relevant human impacts for the sustainability of our oceans [1,2]. Due to the complexity of theCombined Spatio-Temporal Impacts of Climate and Longline Fisheries on the Survival of a Trans

212

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

NASA Astrophysics Data System (ADS)

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

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

2001-08-01

213

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

214

A general science-based framework for dynamical spatio-temporal models  

Microsoft Academic Search

Spatio-temporal statistical models are increasingly being used across a wide variety of scientific disciplines to describe\\u000a and predict spatially-explicit processes that evolve over time. Correspondingly, in recent years there has been a significant\\u000a amount of research on new statistical methodology for such models. Although descriptive models that approach the problem from\\u000a the second-order (covariance) perspective are important, and innovative work

Christopher K. Wikle; Mevin B. Hooten

2010-01-01

215

Severe Hail Prediction within a Spatiotemporal Relational Data Mining Framework  

E-print Network

precipitation over 1 inch in diameter, has caused billions of dollars in damage to crops, buildings, automobiles, these statistics include tornado and wind reports). Physics-based [6] and neural network models [7], [8] have also

McGovern, Amy

216

Demographic Variability, Vaccination, and the Spatiotemporal Dynamics of Rotavirus Epidemics  

PubMed Central

Historically, annual rotavirus activity in the United States has started in the southwest in late fall and ended in the northeast 3 months later; this trend has diminished in recent years. Traveling waves of infection or local environmental drivers cannot account for these patterns. A transmission model calibrated against epidemiological data shows that spatiotemporal variation in birth rate can explain the timing of rotavirus epidemics. The recent large-scale introduction of rotavirus vaccination provides a natural experiment to further test the impact of susceptible recruitment on disease dynamics. The model predicts a pattern of reduced and lagged epidemics postvaccination, closely matching the observed dynamics. Armed with this validated model, we explore the relative importance of direct and indirect protection, a key issue in determining the worldwide benefits of vaccination. PMID:19608910

Pitzer, Virginia E.; Viboud, Cécile; Simonsen, Lone; Steiner, Claudia; Panozzo, Catherine A.; Alonso, Wladimir J.; Miller, Mark A.; Glass, Roger I.; Glasser, John W.; Parashar, Umesh D.; Grenfell, Bryan T.

2009-01-01

217

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

PubMed Central

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

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

2010-01-01

218

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

PubMed Central

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

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

2014-01-01

219

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

PubMed Central

The two-pore channels (TPC1 and TPC2) belong to an ancient family of intracellular ion channels expressed in the endolysosomal system. Little is known about how regulatory inputs converge to modulate TPC activity, and proposed activation mechanisms are controversial. Here, we compiled a proteomic characterization of the human TPC interactome, which revealed that TPCs complex with many proteins involved in Ca2+ homeostasis, trafficking, and membrane organization. Among these interactors, TPCs were resolved to scaffold Rab GTPases and regulate endomembrane dynamics in an isoform-specific manner. TPC2, but not TPC1, caused a proliferation of endolysosomal structures, dysregulating intracellular trafficking, and cellular pigmentation. These outcomes required both TPC2 and Rab activity, as well as their interactivity, because TPC2 mutants that were inactive, or rerouted away from their endogenous expression locale, or deficient in Rab binding, failed to replicate these outcomes. Nicotinic acid adenine dinucleotide phosphate (NAADP)-evoked Ca2+ release was also impaired using either a Rab binding-defective TPC2 mutant or a Rab inhibitor. These data suggest a fundamental role for the ancient TPC complex in trafficking that holds relevance for lysosomal proliferative scenarios observed in disease. PMID:25157141

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

2014-01-01

220

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

PubMed Central

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

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

2015-01-01

221

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

PubMed

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

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

2014-04-01

222

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

PubMed

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

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

2015-01-01

223

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

224

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

225

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

226

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

227

POINeT: protein interactome with sub-network analysis and hub prioritization  

PubMed Central

Background Protein-protein interactions (PPIs) are critical to every aspect of biological processes. Expansion of all PPIs from a set of given queries often results in a complex PPI network lacking spatiotemporal consideration. Moreover, the reliability of available PPI resources, which consist of low- and high-throughput data, for network construction remains a significant challenge. Even though a number of software tools are available to facilitate PPI network analysis, an integrated tool is crucial to alleviate the burden on querying across multiple web servers and software tools. Results We have constructed an integrated web service, POINeT, to simplify the process of PPI searching, analysis, and visualization. POINeT merges PPI and tissue-specific expression data from multiple resources. The tissue-specific PPIs and the numbers of research papers supporting the PPIs can be filtered with user-adjustable threshold values and are dynamically updated in the viewer. The network constructed in POINeT can be readily analyzed with, for example, the built-in centrality calculation module and an integrated network viewer. Nodes in global networks can also be ranked and filtered using various network analysis formulas, i.e., centralities. To prioritize the sub-network, we developed a ranking filtered method (S3) to uncover potential novel mediators in the midbody network. Several examples are provided to illustrate the functionality of POINeT. The network constructed from four schizophrenia risk markers suggests that EXOC4 might be a novel marker for this disease. Finally, a liver-specific PPI network has been filtered with adult and fetal liver expression profiles. Conclusion The functionalities provided by POINeT are highly improved compared to previous version of POINT. POINeT enables the identification and ranking of potential novel genes involved in a sub-network. Combining with tissue-specific gene expression profiles, PPIs specific to selected tissues can be revealed. The straightforward interface of POINeT makes PPI search and analysis just a few clicks away. The modular design permits further functional enhancement without hampering the simplicity. POINeT is available at . PMID:19379523

Lee, Sheng-An; Chan, Chen-Hsiung; Chen, Tzu-Chi; Yang, Chia-Ying; Huang, Kuo-Chuan; Tsai, Chi-Hung; Lai, Jin-Mei; Wang, Feng-Sheng; Kao, Cheng-Yan; Huang, Chi-Ying F

2009-01-01

228

System-Level Insights into the Cellular Interactome of a Non-Model Organism: Inferring, Modelling and Analysing Functional Gene Network of Soybean (Glycine max)  

PubMed Central

Cellular interactome, in which genes and/or their products interact on several levels, forming transcriptional regulatory-, protein interaction-, metabolic-, signal transduction networks, etc., has attracted decades of research focuses. However, such a specific type of network alone can hardly explain the various interactive activities among genes. These networks characterize different interaction relationships, implying their unique intrinsic properties and defects, and covering different slices of biological information. Functional gene network (FGN), a consolidated interaction network that models fuzzy and more generalized notion of gene-gene relations, have been proposed to combine heterogeneous networks with the goal of identifying functional modules supported by multiple interaction types. There are yet no successful precedents of FGNs on sparsely studied non-model organisms, such as soybean (Glycine max), due to the absence of sufficient heterogeneous interaction data. We present an alternative solution for inferring the FGNs of soybean (SoyFGNs), in a pioneering study on the soybean interactome, which is also applicable to other organisms. SoyFGNs exhibit the typical characteristics of biological networks: scale-free, small-world architecture and modularization. Verified by co-expression and KEGG pathways, SoyFGNs are more extensive and accurate than an orthology network derived from Arabidopsis. As a case study, network-guided disease-resistance gene discovery indicates that SoyFGNs can provide system-level studies on gene functions and interactions. This work suggests that inferring and modelling the interactome of a non-model plant are feasible. It will speed up the discovery and definition of the functions and interactions of other genes that control important functions, such as nitrogen fixation and protein or lipid synthesis. The efforts of the study are the basis of our further comprehensive studies on the soybean functional interactome at the genome and microRNome levels. Additionally, a web tool for information retrieval and analysis of SoyFGNs can be accessed at SoyFN: http://nclab.hit.edu.cn/SoyFN. PMID:25423109

Xu, Yungang; Guo, Maozu; Zou, Quan; Liu, Xiaoyan; Wang, Chunyu; Liu, Yang

2014-01-01

229

System-level insights into the cellular interactome of a non-model organism: inferring, modelling and analysing functional gene network of soybean (Glycine max).  

PubMed

Cellular interactome, in which genes and/or their products interact on several levels, forming transcriptional regulatory-, protein interaction-, metabolic-, signal transduction networks, etc., has attracted decades of research focuses. However, such a specific type of network alone can hardly explain the various interactive activities among genes. These networks characterize different interaction relationships, implying their unique intrinsic properties and defects, and covering different slices of biological information. Functional gene network (FGN), a consolidated interaction network that models fuzzy and more generalized notion of gene-gene relations, have been proposed to combine heterogeneous networks with the goal of identifying functional modules supported by multiple interaction types. There are yet no successful precedents of FGNs on sparsely studied non-model organisms, such as soybean (Glycine max), due to the absence of sufficient heterogeneous interaction data. We present an alternative solution for inferring the FGNs of soybean (SoyFGNs), in a pioneering study on the soybean interactome, which is also applicable to other organisms. SoyFGNs exhibit the typical characteristics of biological networks: scale-free, small-world architecture and modularization. Verified by co-expression and KEGG pathways, SoyFGNs are more extensive and accurate than an orthology network derived from Arabidopsis. As a case study, network-guided disease-resistance gene discovery indicates that SoyFGNs can provide system-level studies on gene functions and interactions. This work suggests that inferring and modelling the interactome of a non-model plant are feasible. It will speed up the discovery and definition of the functions and interactions of other genes that control important functions, such as nitrogen fixation and protein or lipid synthesis. The efforts of the study are the basis of our further comprehensive studies on the soybean functional interactome at the genome and microRNome levels. Additionally, a web tool for information retrieval and analysis of SoyFGNs can be accessed at SoyFN: http://nclab.hit.edu.cn/SoyFN. PMID:25423109

Xu, Yungang; Guo, Maozu; Zou, Quan; Liu, Xiaoyan; Wang, Chunyu; Liu, Yang

2014-01-01

230

Spatiotemporal characterization of ultrabroadband Airy pulses.  

PubMed

We present experimental results of a full spatiotemporal characterization of an optical system for ultrabroadband Airy pulse generation with a liquid-crystal-on-silicon spatial light modulator. Measurements with a few micrometer spatial and almost one-wave-cycle temporal resolution were performed using a white light spatial spectral interferometry setup based on the SEA TADPOLE ultrashort pulse characterization technique. The results were compared with the theoretical model for Airy pulse propagation. PMID:23546271

Piksarv, Peeter; Valdmann, Andreas; Valtna-Lukner, Heli; Matt, Roland; Saari, Peeter

2013-04-01

231

Controlling spatiotemporal chaos via small external forces  

E-print Network

The spatiotemporal chaos in the system described by a one-dimensional nonlinear drift-wave equation is controlled by directly adding a periodic force with appropriately chosen frequencies. By dividing the solution of the system into a carrier steady wave and its perturbation, we find that the controlling mechanism can be explained by a slaving principle. The critical controlling time for a perturbation mode increases exponentially with its wave number.

Shunguang Wu; Kaifen He; Zuqia Huang

1999-08-08

232

Spatiotemporal dynamics of continuum neural fields  

NASA Astrophysics Data System (ADS)

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

Bressloff, Paul C.

2012-01-01

233

Spatio-temporal organisation of natural prehension  

Microsoft Academic Search

Bootsma, R.J. and P.C.W. van Wieringen, 1992. Spatio-temporal organisation of natural prehen- sion. Human Movement Science 11, 205-215. An information-based model of natural prehension is proposed that can account for a large number of experimental findings without taking recourse to prestructured movement plans. It is suggested that coordination of the transport and grasping components is guaranteed because both components are

Reinoud J. Bootsma; Piet C. W. van Wieringen

1992-01-01

234

Data assimilation using spatio-temporal descriptors  

NASA Astrophysics Data System (ADS)

Data assimilation is the process by which numerical model output is fused with observations in order to provide consensus estimates. In a Bayesian framework, this typically consists of constructing a 'process model prior' centred on the numerical model output and an 'observation model' which describes the relationship between the observed variable and the process of interest. This approach, while straightforward and ubiquitous in the geophysical sciences, can lead to erroneous inferences when the numerical output is biased (both spatially and temporally) in an undefined way. Here we show an alternative way in which to carry out data assimilation, whereby only the spatial and temporal properties of the numerical model are fused with the data. The method, couched in a spatio-temporal Bayesian framework, follows a two-stage approach: (i) Spatio-temporal modelling of the numerical model outputs in order to extract spectral spatio-temporal characteristics which are deemed faithful to the processes of interest (e.g. length scales and marginal variances), and (ii) Spatio-temporal modelling of the processes of interest with informative priors (based on (i)) in order to provide updated estimates. We apply this method to estimating the mass balance of Antarctic ice-sheet processes from multiple observations sources: GRACE, ICESat, ENVISat and GPS data. We show that although this problem is under-determined due to lack of observation diversity, spectral characterisation using the two-stage approach allows us to tease out the individual processes and reduce confounding between the processes whilst concurrently providing inferences which are largely data-driven.

Zammit-Mangion, Andrew; Schoen, Nana; Rougier, Jonathan; Bamber, Jonathan

2014-05-01

235

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... based on a spatiotemporal graph model; Analyze the spatiotemporal characteristics of rainstorms. Data ? NEXRAD (Next generation Radar) ? Hourly precipitation estimate ? Cover more than 2/3 of the nation Rainstorms’ Lifecycle Identification Delineate...

Liu, Weibo

2014-04-21

236

Probabilistic Spatio-Temporal Video Object Segmentation Incorporating Shape Information  

Microsoft Academic Search

From a video object segmentation perspective, using a joint spatio-temporal strategy is superior to processing with priority in either the spatial or temporal domains, as it considers a video sequence as a spatio-temporal grouping of pixels. However, existing spatio-temporal object segmentation techniques consider only pixel features, which tend to limit their performance in being able to segment arbitrary shaped objects.

Rakib Ahmed; Gour C. Karmakar; Laurence S. Dooley

2006-01-01

237

Normative spatiotemporal gait parameters in older adults.  

PubMed

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

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

2011-05-01

238

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

239

Algorithms for enhanced spatiotemporal imaging of human brain function  

E-print Network

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

Krishnaswamy, Pavitra

2014-01-01

240

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

241

Linking Proteomic and Transcriptional Data through the Interactome and Epigenome Reveals a Map of Oncogene-induced Signaling  

PubMed Central

Cellular signal transduction generally involves cascades of post-translational protein modifications that rapidly catalyze changes in protein-DNA interactions and gene expression. High-throughput measurements are improving our ability to study each of these stages individually, but do not capture the connections between them. Here we present an approach for building a network of physical links among these data that can be used to prioritize targets for pharmacological intervention. Our method recovers the critical missing links between proteomic and transcriptional data by relating changes in chromatin accessibility to changes in expression and then uses these links to connect proteomic and transcriptome data. We applied our approach to integrate epigenomic, phosphoproteomic and transcriptome changes induced by the variant III mutation of the epidermal growth factor receptor (EGFRvIII) in a cell line model of glioblastoma multiforme (GBM). To test the relevance of the network, we used small molecules to target highly connected nodes implicated by the network model that were not detected by the experimental data in isolation and we found that a large fraction of these agents alter cell viability. Among these are two compounds, ICG-001, targeting CREB binding protein (CREBBP), and PKF118–310, targeting ?-catenin (CTNNB1), which have not been tested previously for effectiveness against GBM. At the level of transcriptional regulation, we used chromatin immunoprecipitation sequencing (ChIP-Seq) to experimentally determine the genome-wide binding locations of p300, a transcriptional co-regulator highly connected in the network. Analysis of p300 target genes suggested its role in tumorigenesis. We propose that this general method, in which experimental measurements are used as constraints for building regulatory networks from the interactome while taking into account noise and missing data, should be applicable to a wide range of high-throughput datasets. PMID:23408876

Huang, Shao-shan Carol; Clarke, David C.; Gosline, Sara J. C.; Labadorf, Adam; Chouinard, Candace R.; Gordon, William; Lauffenburger, Douglas A.; Fraenkel, Ernest

2013-01-01

242

Analysis of the Bovine Intracellular Enteric Pathogen Interactome Each year the beef and dairy industries lose more than $330 million because of enteric diseases that cause the death of more than  

E-print Network

Analysis of the Bovine Intracellular Enteric Pathogen Interactome Each year the beef and dairy weight gain. Understanding how cattle respond to enteric pathogens during acute infection is crucial have developed an in vivo bovine ligated ileal loop model to study bovine response to enteric pathogens

243

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

244

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

245

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

246

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

247

Spatiotemporal modeling of monthly soil temperature using artificial neural networks  

NASA Astrophysics Data System (ADS)

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

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

2013-08-01

248

Gestural Interaction with Spatiotemporal Linked Open Data Gestural Interaction with Spatiotemporal  

E-print Network

access to simple data such as photographs, media or basic maps. Given this, our hypothesis Information Science to the pub- lic, for example in an exhibition, in a science museum or science center for complex spatiotemporal data is a contribution towards Linked Open Science [14] to support transparency

Köbben, Barend

249

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

250

A provably efficient computational model for approximate spatiotemporal retrieval  

Microsoft Academic Search

The paper is concerned with the effective and efficient processing of spatiotemporal selection queries under varying degrees of approximation. Such queries may employ operators like overlaps, north, during, etc., and their result is a set of entities standing approximately in some spatiotemporal relation with respect to a query object X. The contribution of our work is twofold: i) First we

Delis Vasilis; Makris Christos; Sioutas Spiros

1999-01-01

251

Spatiotemporal control of gene expression using microfluidics.  

PubMed

Accurate spatiotemporal regulation of genetic expression and cell microenvironment are both essential to epithelial morphogenesis during development, wound healing and cancer. In vivo, this is achieved through the interplay between intrinsic cellular properties and extrinsic signals. Amongst these, morphogen gradients induce specific concentration- and time-dependent gene expression changes that influence a target cell's fate. As systems biology attempts to understand the complex mechanisms underlying morphogenesis, the lack of experimental setup to recapitulate morphogen-induced patterning in vitro has become limiting. For this reason, we developed a versatile microfluidic-based platform to control the spatiotemporal delivery of chemical gradients to tissues grown in Petri dishes. Using this setup combined with a synthetic inducible gene expression system, we were able to restrict a target gene's expression within a confluent epithelium to bands of cells as narrow as four cell diameters with a one cell diameter accuracy. Applied to the targeted delivery of growth factor gradients to a confluent epithelium, this method further enabled the localized induction of epithelial-mesenchymal transitions and associated morphogenetic changes. Our approach paves the way for replicating in vitro the morphogen gradients observed in vivo to determine the relative contributions of known intrinsic and extrinsic factors in differential tissue patterning, during development and cancer. It could also be readily used to spatiotemporally control cell differentiation in ES/iPS cell cultures for re-engineering of complex tissues. Finally, the reversibility of the microfluidic chip assembly allows for pre- and post-treatment sample manipulations and extends the range of patternable samples to animal explants. PMID:24531367

Benedetto, Alexandre; Accetta, Giovanni; Fujita, Yasuyuki; Charras, Guillaume

2014-04-01

252

A Metascalable Computing Framework for Large Spatiotemporal-Scale Atomistic Simulations  

SciTech Connect

A metascalable (or 'design once, scale on new architectures') parallel computing framework has been developed for large spatiotemporal-scale atomistic simulations of materials based on spatiotemporal data locality principles, which is expected to scale on emerging multipetaflops architectures. The framework consists of: (1) an embedded divide-and-conquer (EDC) algorithmic framework based on spatial locality to design linear-scaling algorithms for high complexity problems; (2) a space-time-ensemble parallel (STEP) approach based on temporal locality to predict long-time dynamics, while introducing multiple parallelization axes; and (3) a tunable hierarchical cellular decomposition (HCD) parallelization framework to map these O(N) algorithms onto a multicore cluster based on hybrid implementation combining message passing and critical section-free multithreading. The EDC-STEP-HCD framework exposes maximal concurrency and data locality, thereby achieving: (1) inter-node parallel efficiency well over 0.95 for 218 billion-atom molecular-dynamics and 1.68 trillion electronic-degrees-of-freedom quantum-mechanical simulations on 212,992 IBM BlueGene/L processors (superscalability); (2) high intra-node, multithreading parallel efficiency (nanoscalability); and (3) nearly perfect time/ensemble parallel efficiency (eon-scalability). The spatiotemporal scale covered by MD simulation on a sustained petaflops computer per day (i.e. petaflops {center_dot} day of computing) is estimated as NT = 2.14 (e.g. N = 2.14 million atoms for T = 1 microseconds).

Nomura, K; Seymour, R; Wang, W; Kalia, R; Nakano, A; Vashishta, P; Shimojo, F; Yang, L H

2009-02-17

253

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

254

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

255

The spatiotemporal dynamics of scene gist recognition.  

PubMed

Viewers can rapidly extract a holistic semantic representation of a real-world scene within a single eye fixation, an ability called recognizing the gist of a scene, and operationally defined here as recognizing an image's basic-level scene category. However, it is unknown how scene gist recognition unfolds over both time and space-within a fixation and across the visual field. Thus, in 3 experiments, the current study investigated the spatiotemporal dynamics of basic-level scene categorization from central vision to peripheral vision over the time course of the critical first fixation on a novel scene. The method used a window/scotoma paradigm in which images were briefly presented and processing times were varied using visual masking. The results of Experiments 1 and 2 showed that during the first 100 ms of processing, there was an advantage for processing the scene category from central vision, with the relative contributions of peripheral vision increasing thereafter. Experiment 3 tested whether this pattern could be explained by spatiotemporal changes in selective attention. The results showed that manipulating the probability of information being presented centrally or peripherally selectively maintained or eliminated the early central vision advantage. Across the 3 experiments, the results are consistent with a zoom-out hypothesis, in which, during the first fixation on a scene, gist extraction extends from central vision to peripheral vision as covert attention expands outward. PMID:24245502

Larson, Adam M; Freeman, Tyler E; Ringer, Ryan V; Loschky, Lester C

2014-04-01

256

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

257

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

258

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

259

Model performance in spatiotemporal patterns of precipitation: New methods for identifying value added by a regional climate model  

NASA Astrophysics Data System (ADS)

Regional climate models (RCMs) are a standard tool for downscaling climate forecasts to finer spatial scales. The evaluation of RCMs against observational data is an important step in building confidence in the use of RCMs for future projection. In addition to model performance in climatological means and marginal distributions, a model's ability to capture spatiotemporal relationships is important. This study develops two approaches: (1) spatial correlation/variogram for a range of spatial lags, with total monthly precipitation and nonseasonal precipitation components used to assess the spatial variations of precipitation, and (2) spatiotemporal correlation for a wide range of distances, directions, and time lags, with daily precipitation occurrence used to detect the dynamic features of precipitation. These measures of spatial and spatiotemporal dependence are applied to a high-resolution RCM run and to the National Center for Environmental Prediction (NCEP)-U.S. Department of Energy Atmospheric Model Intercomparison Project II reanalysis data (NCEP-R2), which provide initial and lateral boundary conditions for the RCM. The RCM performs significantly better than NCEP-R2 in capturing both the spatial variations of total and nonseasonal precipitation components and the spatiotemporal correlations of daily precipitation occurrences, which are related to dynamic behavior of precipitating systems. The improvements are apparent not only at resolutions finer than that of NCEP-R2 but also when the RCM and observational data are aggregated to the resolution of NCEP-R2.

Wang, Jiali; Swati, F. N. U.; Stein, Michael L.; Kotamarthi, V. Rao

2015-02-01

260

Research on spatio-temporal ontology based on description logic  

NASA Astrophysics Data System (ADS)

DL, short for Description Logic, is aimed at getting a balance between describing ability and reasoning complexity. Users can adopt DL to write clear and formalized concept description for domain model, which makes ontology description possess well-defined syntax and semantics and helps to resolve the problem of spatio-temporal reasoning based on ontology. This paper studies on basic theory of DL and relationship between DL and OWL at first. By analyzing spatio-temporal concepts and relationship of spatio-temporal GIS, the purpose of this paper is adopting ontology language based on DL to express spatio-temporal ontology, and employing suitable ontology-building tool to build spatio-temporal ontology. With regard to existing spatio-temporal ontology based on first-order predicate logic, we need to transform it into spatio-temporal ontology based on DL so as to make the best of existing research fruits. This paper also makes a research on translating relationships between DL and first-order predicate logic.

Huang, Yongqi; Ding, Zhimin; Zhao, Zhui; Ouyang, Fucheng

2008-10-01

261

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

262

The Change-of-Feature Spatio-temporal Object Relational Model and Its implement  

Microsoft Academic Search

Now more and more application demand to spatio-temporal database is proposed and the spatio-temporal data model is the fundamental basic to spatial-temporal database. But till today the study on spatio-temporal data model still more concerned with the theory research. The article proposes a new model-the change-of-feature based spatio-temporal object relational data model by researching and analyzing the current spatio-temporal data

Xiaochun Wu; Yongqi Huang; Liyan Wang; Fengyun Mou

2009-01-01

263

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

264

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

265

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

266

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

Microsoft Academic Search

Aberrant organ development is associated with a wide spectrum of disorders, from schizophrenia to congenital heart disease, but systems-level insight into the underlying processes is very limited. Using heart morphogenesis as general model for dissecting the functional architecture of organ development, we combined detailed phenotype information from deleterious mutations in 255 genes with high-confidence experimental interactome data, and coupled the

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

2010-01-01

267

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

PubMed Central

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

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

2013-01-01

268

Ambient Air Pollution and Preeclampsia: A Spatiotemporal Analysis  

PubMed Central

Background: Available evidence concerning the association between air pollution and preeclampsia is limited, and specific associations with early- and late-onset preeclampsia have not been assessed. Objectives: We investigated the association, if any, between preeclampsia (all, early-, and late-onset) and exposure to nitrogen dioxide, nitrogen oxides, particulate matter with aerodynamic diameter ? 2.5 ?m (PM2.5; fine particles), ? 10 ?m, and 2.5–10 ?m, and PM2.5 light absorption (a proxy for elemental carbon) during the entire pregnancy and during the first, second, and third trimesters. Methods: This study was based on 8,398 pregnancies (including 103 cases of preeclampsia) among women residing in Barcelona, Spain (2000–2005). We applied a spatiotemporal exposure assessment framework using land use regression models to predict ambient pollutant levels during each week of pregnancy at the geocoded residence address of each woman at the time of birth. Logistic and conditional logistic regression models were used to estimate unadjusted and adjusted associations. Results: We found positive associations for most of our evaluated outcome–exposure pairs, with the strongest associations observed for preeclampsia and late-onset preeclampsia in relation to the third-trimester exposure to fine particulate pollutants, and for early-onset preeclampsia in relation to the first-trimester exposure to fine particulate pollutants. Among our investigated associations, those of first- and third-trimester exposures to PM2.5 and third-trimester exposure to PM2.5 absorbance and all preeclampsia, and third-trimester PM2.5 exposure and late-onset preeclampsia attained statistical significance. Conclusion: We observed increased risk of preeclampsia associated with exposure to fine particulate air pollution. Our findings, in combination with previous evidence suggesting distinct pathogenic mechanisms for early- and late-onset preeclampsia, support additional research on this topic. Citation: Dadvand P, Figueras F, Basagaña X, Beelen R, Martinez D, Cirach M, Schembari A, Hoek G, Brunekreef B, Nieuwenhuijsen MJ. 2013. Ambient air pollution and preeclampsia: a spatiotemporal analysis. Environ Health Perspect 121:1365–1371;?http://dx.doi.org/10.1289/ehp.1206430 PMID:24021707

Figueras, Francesc; Basagaña, Xavier; Beelen, Rob; Martinez, David; Cirach, Marta; Schembari, Anna; Hoek, Gerard; Brunekreef, Bert; Nieuwenhuijsen, Mark J

2013-01-01

269

Non-invertible transformations and spatiotemporal randomness  

E-print Network

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

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

2006-02-12

270

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

271

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

272

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)...

273

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

274

SVM spatio-temporal vegetation classification using HR satellite images  

Microsoft Academic Search

This paper proposes a new HR spatio-temporal vegetation classification approach based on SVM. A multi-band SVM approach is first applied on satellite images time series then a graph based SVM algorithm is used for temporal analysis.

S. Réjichi; F. Chaâbane

2011-01-01

275

SVM spatio-temporal vegetation classification using HR satellite images  

NASA Astrophysics Data System (ADS)

This paper proposes a new HR spatio-temporal vegetation classification approach based on SVM. A multi-band SVM approach is first applied on satellite images time series then a graph based SVM algorithm is used for temporal analysis.

Réjichi, S.; Chaâbane, F.

2011-11-01

276

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

277

Spatiotemporal gait parameters and recurrent falls in community-dwelling elderly women: a prospective study  

PubMed Central

BACKGROUND: Falling is a common but devastating and costly problem of aging. There is no consensus in the literature on whether the spatial and temporal gait parameters could identify elderly people at risk of recurrent falls. OBJECTIVE: To determine whether spatiotemporal gait parameters could predict recurrent falls in elderly women. METHOD: One hundred and forty-eight elderly women (65-85 years) participated in this study. Seven spatiotemporal gait parameters were collected with the GAITRite(r) system. Falls were recorded prospectively during 12 months through biweekly phone contacts. Elderly women who reported two or more falls throughout the follow-up period were considered as recurrent fallers. Principal component analysis (PCA) and discriminant analysis followed by biplot graph interpretation were applied to the gait parameters. RESULTS: After 12 months, 23 elderly women fell twice or more and comprised the recurrent fallers group and 110 with one or no falls comprised the non-recurrent fallers group. PCA resulted in three components that explained 88.3% of data variance. Discriminant analysis showed that none of the components could significantly discriminate the groups. However, visual inspection of the biplot showed a trend towards group separation in relation to gait velocity and stance time. PC1 represented gait rhythm and showed that recurrent fallers tend to walk with lower velocity and cadence and increased stance time in relation to non-recurrent fallers. CONCLUSIONS: The analyzed spatiotemporal gait parameters failed to predict recurrent falls in this sample. The PCA-biplot technique highlighted important trends or red flags that should be considered when evaluating recurrent falls in elderly females. PMID:25714603

Moreira, Bruno S.; Sampaio, Rosana F.; Kirkwood, Renata N.

2015-01-01

278

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

279

Different routes from a matter wavepacket to spatiotemporal chaos  

SciTech Connect

We investigate the dynamics of a quasi-one-dimensional Bose-Einstein condensate confined in a double-well potential with spatiotemporally modulated interaction. A variety of phenomena is identified in different frequency regimes, including the self-compression, splitting, breathing-like, and near-fidelity of the matter wavepacket, which are associated with different routes for the onset of spatiotemporal chaos. The results also reveal that chaos can retain space-inversion symmetry of the system.

Rong Shiguang [Department of Physics and Key Laboratory of Low-dimensional Quantum Structures and Quantum Control of Ministry of Education, Hunan Normal University, Changsha 410081 (China); Department of Physics, Hunan University of Science and Technology, Xiangtan 411201 (China); Hai Wenhua; Xie Qiongtao; Zhong Honghua [Department of Physics and Key Laboratory of Low-dimensional Quantum Structures and Quantum Control of Ministry of Education, Hunan Normal University, Changsha 410081 (China)

2012-09-15

280

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

281

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

282

Predictability of Conversation Partners  

NASA Astrophysics Data System (ADS)

Recent developments in sensing technologies have enabled us to examine the nature of human social behavior in greater detail. By applying an information-theoretic method to the spatiotemporal data of cell-phone locations, [C. Song , ScienceSCIEAS0036-8075 327, 1018 (2010)] found that human mobility patterns are remarkably predictable. Inspired by their work, we address a similar predictability question in a different kind of human social activity: conversation events. The predictability in the sequence of one’s conversation partners is defined as the degree to which one’s next conversation partner can be predicted given the current partner. We quantify this predictability by using the mutual information. We examine the predictability of conversation events for each individual using the longitudinal data of face-to-face interactions collected from two company offices in Japan. Each subject wears a name tag equipped with an infrared sensor node, and conversation events are marked when signals are exchanged between sensor nodes in close proximity. We find that the conversation events are predictable to a certain extent; knowing the current partner decreases the uncertainty about the next partner by 28.4% on average. Much of the predictability is explained by long-tailed distributions of interevent intervals. However, a predictability also exists in the data, apart from the contribution of their long-tailed nature. In addition, an individual’s predictability is correlated with the position of the individual in the static social network derived from the data. Individuals confined in a community—in the sense of an abundance of surrounding triangles—tend to have low predictability, and those bridging different communities tend to have high predictability.

Takaguchi, Taro; Nakamura, Mitsuhiro; Sato, Nobuo; Yano, Kazuo; Masuda, Naoki

2011-08-01

283

Multisensory control of hippocampal spatiotemporal selectivity.  

PubMed

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

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

2013-06-14

284

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

285

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

286

Spatiotemporal characteristics of drought in Serbia  

NASA Astrophysics Data System (ADS)

The evaluation of spatiotemporal characteristics of drought was based on monthly precipitation data from 29 synoptic stations for the period of 1948-2012. The percent of normal precipitation was applied to illustrate the driest years in Serbia (1990, 2000, and 2011). The Standardized Precipitation Index (SPI) and S-mode principal component analysis (PCA) were used to capture the drought patterns. Agglomerative hierarchical cluster analysis was applied to identify three different drought sub-regions: (1) region R1 includes the north and the northeast part of Serbia; (2) region R2 includes the western part of Central Serbia and southwestern part of Serbia; and (3) region R3 includes central, east, south and southeast part of Serbia. The R2 had the monthly precipitation values above average, while R1 and R3 had the precipitation values under average of Serbia. The year 2000 was the driest and 1955 was the wettest during the observed period. The characteristics of drought were analyzed in terms of the temporal evolution of the SPI-12 values and the frequency of drought for the three identified regions. The percentage of years characterized by drought was 44.62% for R1, 50.77% for R2 and 46.15% for R3. Approximately 70% of the frequency of drought belongs to the near normal drought category.

Gocic, Milan; Trajkovic, Slavisa

2014-03-01

287

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

288

Assessment of soil organic carbon distribution in Europe scale by spatio-temporal data and geostatistics  

NASA Astrophysics Data System (ADS)

Accuracy in assessing the distribution of soil organic carbon (SOC) is an important issue because SOC is an important soil component that plays key roles in the functions of both natural ecosystems and agricultural systems. The SOC content varies from place to place and it is strongly related with climate variables (temperature and rainfall), terrain features, soil texture, parent material, vegetation, land-use types, and human management (management and degradation) at different spatial scales. Geostatistical techniques allow for the prediction of soil properties using soil information and environmental covariates. In this study, assessment of SOC distribution has been predicted using combination of LUCAS soil samples with local soil data and ten spatio-temporal predictors (slope, aspect, elevation, CTI, CORINE land-cover classification, parent material, texture, WRB soil classification, average temperature and precipitation) with Regression-Kriging method in Europe scale. Significant correlation between the covariates and the organic carbon dependent variable was found.

Aksoy, Ece; Panagos, Panos; Montanarella, Luca

2013-04-01

289

Spatiotemporal nutrient loading to Cultus Lake: Context for eutrophication and implications for  

E-print Network

Spatiotemporal nutrient loading to Cultus Lake: Context for eutrophication and implications of Thesis: Spatiotemporal nutrient loading to Cultus Lake: Context for eutrophication and implications Cultus Lake, British Columbia experiences significant anthropogenic nutrient loadings and eutrophication

290

Spatiotemporal Analysis of Hepatitis C Virus Infection  

PubMed Central

Hepatitis C virus (HCV) entry, translation, replication, and assembly occur with defined kinetics in distinct subcellular compartments. It is unclear how HCV spatially and temporally regulates these events within the host cell to coordinate its infection. We have developed a single molecule RNA detection assay that facilitates the simultaneous visualization of HCV (+) and (?) RNA strands at the single cell level using high-resolution confocal microscopy. We detect (+) strand RNAs as early as 2 hours post-infection and (?) strand RNAs as early as 4 hours post-infection. Single cell levels of (+) and (?) RNA vary considerably with an average (+):(?) RNA ratio of 10 and a range from 1–35. We next developed microscopic assays to identify HCV (+) and (?) RNAs associated with actively translating ribosomes, replication, virion assembly and intracellular virions. (+) RNAs display a defined temporal kinetics, with the majority of (+) RNAs associated with actively translating ribosomes at early times of infection, followed by a shift to replication and then virion assembly. (?) RNAs have a strong colocalization with NS5A, but not NS3, at early time points that correlate with replication compartment formation. At later times, only ~30% of the replication complexes appear to be active at a given time, as defined by (?) strand colocalization with either (+) RNA, NS3, or NS5A. While both (+) and (?) RNAs colocalize with the viral proteins NS3 and NS5A, only the plus strand preferentially colocalizes with the viral envelope E2 protein. These results suggest a defined spatiotemporal regulation of HCV infection with highly varied replication efficiencies at the single cell level. This approach can be applicable to all plus strand RNA viruses and enables unprecedented sensitivity for studying early events in the viral life cycle. PMID:25822891

Shulla, Ana; Randall, Glenn

2015-01-01

291

Spatio-temporal topological relationships between land parcels in cadastral database  

NASA Astrophysics Data System (ADS)

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

Song, W.; Zhang, F.

2014-04-01

292

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

293

Control of spatiotemporal patterns in the Gray-Scott model  

NASA Astrophysics Data System (ADS)

This paper studies the effects of a time-delayed feedback control on the appearance and development of spatiotemporal patterns in a reaction-diffusion system. Different types of control schemes are investigated, including single-species, diagonal, and mixed control. This approach helps to unveil different dynamical regimes, which arise from chaotic state or from traveling waves. In the case of spatiotemporal chaos, the control can either stabilize uniform steady states or lead to bistability between a trivial steady state and a propagating traveling wave. Furthermore, when the basic state is a stable traveling pulse, the control is able to advance stationary Turing patterns or yield the above-mentioned bistability regime. In each case, the stability boundary is found in the parameter space of the control strength and the time delay, and numerical simulations suggest that diagonal control fails to control the spatiotemporal chaos.

Kyrychko, Y. N.; Blyuss, K. B.; Hogan, S. J.; Schöll, E.

2009-12-01

294

A general science-based framework for dynamical spatio-temporal models  

USGS Publications Warehouse

Spatio-temporal statistical models are increasingly being used across a wide variety of scientific disciplines to describe and predict spatially-explicit processes that evolve over time. Correspondingly, in recent years there has been a significant amount of research on new statistical methodology for such models. Although descriptive models that approach the problem from the second-order (covariance) perspective are important, and innovative work is being done in this regard, many real-world processes are dynamic, and it can be more efficient in some cases to characterize the associated spatio-temporal dependence by the use of dynamical models. The chief challenge with the specification of such dynamical models has been related to the curse of dimensionality. Even in fairly simple linear, first-order Markovian, Gaussian error settings, statistical models are often over parameterized. Hierarchical models have proven invaluable in their ability to deal to some extent with this issue by allowing dependency among groups of parameters. In addition, this framework has allowed for the specification of science based parameterizations (and associated prior distributions) in which classes of deterministic dynamical models (e. g., partial differential equations (PDEs), integro-difference equations (IDEs), matrix models, and agent-based models) are used to guide specific parameterizations. Most of the focus for the application of such models in statistics has been in the linear case. The problems mentioned above with linear dynamic models are compounded in the case of nonlinear models. In this sense, the need for coherent and sensible model parameterizations is not only helpful, it is essential. Here, we present an overview of a framework for incorporating scientific information to motivate dynamical spatio-temporal models. First, we illustrate the methodology with the linear case. We then develop a general nonlinear spatio-temporal framework that we call general quadratic nonlinearity and demonstrate that it accommodates many different classes of scientific-based parameterizations as special cases. The model is presented in a hierarchical Bayesian framework and is illustrated with examples from ecology and oceanography. ?? 2010 Sociedad de Estad??stica e Investigaci??n Operativa.

Wikle, C.K.; Hooten, M.B.

2010-01-01

295

Spatiotemporal monthly rainfall forecasting for south-eastern and eastern Australia using climatic indices  

NASA Astrophysics Data System (ADS)

Knowledge about future rainfall would significantly benefit land, water resources and agriculture management, as this assists with planning and management decisions. Forecasting spatiotemporal monthly rainfall is difficult, especially in Australia where there is a complex interaction between topography and the effect of Indian and Pacific Ocean. This study describes a method for spatiotemporal monthly rainfall forecasting in south-eastern and eastern part of Australia using climatic and non-climatic variables. Rainfall data were obtained from Bureau of Meteorology (BoM) from 136 high quality weather stations from the south-eastern and eastern part of Australia with monthly rainfall records from 1879 to 2012. To reduce spatial complexity of the area and improve model accuracy, spatial classification (regionalization) was considered as first step. Significant predictors for each sub-region among lagged climatic input variables were selected using Fuzzy Ranking Algorithm (FRA). Climate classification: 1) discovered homogenous sub-regions with a similar rainfall patterns and investigated spatiotemporal rainfall variations in the area, 2) allowed selection of significant predictors with a fine resolution for each area, 3) improved the prediction model and increased model accuracy. PCA was used to reduce the dimensions of the dataset and to remove the rainfall time series correlation. K-means clustering was used on the loadings of PCs describing 93% of long-term monthly rainfall variations. The analysis was repeated for different numbers of sub-regions (3 - 8) to identify the best number of clusters to improve the forecast model performance. Subsequently, a Fuzzy Ranking Algorithm (FRA) was applied to the lagged climatic predictors and monthly rainfall in each sub-region to identify the best predictors. After these two stages of pre-processing, a Neural Network model was developed and optimized for each of the sub-regions as well as for the entire area. It is concluded from the result of this study that climate classification can improve the result of monthly spatiotemporal rainfall forecast models in South-eastern and eastern Australia. Also, the number of sub-regions is one of the important parameters in ranking predictors at the modeling stage, and allows elucidation of climate influences for different sub regions. Classification of stations helps FRA to capture variations in Australian rainfall in space without influence of the rainfall seasonal cycle and regimes.

Montazerolghaem, Maryam; Vervoort, Willem; Minasny, Budiman; McBratney, Alex

2014-05-01

296

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

297

Spatio-temporal heterogeneity of riparian soil morphology in a restored floodplain  

NASA Astrophysics Data System (ADS)

Floodplains have been intensively altered in industrialized countries, but are now increasingly being restored and it is therefore important to assess the effect of these restoration projects on the aquatic and terrestrial components of ecosystems. Soils are a functionally crucial component of terrestrial ecosystems but are generally overlooked in floodplain restoration assessment. We studied the spatio-temporal heterogeneity of soil morphology in a restored (riverbed widening) river reach along River Thur (Switzerland) using three criteria (soil diversity, dynamism and typicality) and their associated indicators. We hypothesized that these criteria would correctly discriminate the post-restoration changes in soil morphology within the study site, and that these changes correspond to patterns of vascular plant diversity. Soil diversity and dynamism increased five years after the restoration, but typical soils of braided rivers were still missing. Soil typicality and dynamism correlated to vegetation changes. These results suggest a limited success of the project in agreement with evaluations carried out at the same site using other, more resource demanding methods (e.g. soil fauna, fish, ecosystem functioning). Soil morphology provides structural and functional information on floodplain ecosystems and allows predicting broad changes in plant diversity. The spatio-temporal heterogeneity of soil morphology represents a cost-efficient ecological indicator that could easily be integrated into rapid assessment protocols of floodplain and river restoration projects.

Fournier, B.; Guenat, C.; Bullinger-Weber, G.; Mitchell, E. A. D.

2013-04-01

298

Intrinsic islet heterogeneity and gap junction coupling determine spatiotemporal Ca²? wave dynamics.  

PubMed

Insulin is released from the islets of Langerhans in discrete pulses that are linked to synchronized oscillations of intracellular free calcium ([Ca(2+)]i). Associated with each synchronized oscillation is a propagating calcium wave mediated by Connexin36 (Cx36) gap junctions. A computational islet model predicted that waves emerge due to heterogeneity in ?-cell function throughout the islet. To test this, we applied defined patterns of glucose stimulation across the islet using a microfluidic device and measured how these perturbations affect calcium wave propagation. We further investigated how gap junction coupling regulates spatiotemporal [Ca(2+)]i dynamics in the face of heterogeneous glucose stimulation. Calcium waves were found to originate in regions of the islet having elevated excitability, and this heterogeneity is an intrinsic property of islet ?-cells. The extent of [Ca(2+)]i elevation across the islet in the presence of heterogeneity is gap-junction dependent, which reveals a glucose dependence of gap junction coupling. To better describe these observations, we had to modify the computational islet model to consider the electrochemical gradient between neighboring ?-cells. These results reveal how the spatiotemporal [Ca(2+)]i dynamics of the islet depend on ?-cell heterogeneity and cell-cell coupling, and are important for understanding the regulation of coordinated insulin release across the islet. PMID:25468351

Benninger, Richard K P; Hutchens, Troy; Head, W Steven; McCaughey, Michael J; Zhang, Min; Le Marchand, Sylvain J; Satin, Leslie S; Piston, David W

2014-12-01

299

Disclosing the spatio-temporal structure of PDC entanglement through frequency up-conversion  

E-print Network

In this work we propose and analyse a scheme where the full spatio-temporal correlation of twin photons/beams generated by parametric down-conversion is detected by using its inverse process, i.e. sum frequency generation. Our main result is that, by imposing independently a temporal delay \\Delta t and a transverse spatial shift \\Delta x between two twin components of PDC light, the up-converted light intensity provides information on the correlation of the PDC light in the full spatio-temporal domain, and should enable the reconstruction of the peculiar X-shaped structure of the correlation predicted in [gatti2009,caspani2010,brambilla2010]. Through both a semi-analytical and a numerical modeling of the proposed optical system, we analyse the feasibility of the experiment and identify the best conditions to implement it. In particular, the tolerance of the phase-sensitive measurement against the presence of dispersive elements, imperfect imaging conditions and possible misalignments of the two crystals is evaluated.

Enrico Brambilla; Ottavia Jedrkiewicz; Luigi Lugiato; Alessandra Gatti

2012-05-09

300

Disclosing the spatio-temporal structure of PDC entanglement through frequency  

E-print Network

In this work we propose and analyse a scheme where the full spatio-temporal correlation of twin photons/beams generated by parametric down-conversion is detected by using its inverse process, i.e. sum frequency generation. Our main result is that, by imposing independently a temporal delay \\Delta t and a transverse spatial shift \\Delta x between two twin components of PDC light, the up-converted light intensity provides information on the correlation of the PDC light in the full spatio-temporal domain, and should enable the reconstruction of the peculiar X-shaped structure of the correlation predicted in [gatti2009,caspani2010,brambilla2010]. Through both a semi-analytical and a numerical modeling of the proposed optical system, we analyse the feasibility of the experiment and identify the best conditions to implement it. In particular, the tolerance of the phase-sensitive measurement against the presence of dispersive elements, imperfect imaging conditions and possible misalignments of the two crystals is ev...

Brambilla, Enrico; Lugiato, Luigi; Gatti, Alessandra

2012-01-01

301

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

PubMed Central

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

2013-01-01

302

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

303

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

SciTech Connect

The present study was performed to develop a robust gene-based prediction model for early assessment of potential hepatocarcinogenicity of chemicals in rats by using our toxicogenomics database, TG-GATEs (Genomics-Assisted Toxicity Evaluation System developed by the Toxicogenomics Project in Japan). The positive training set consisted of high- or middle-dose groups that received 6 different non-genotoxic hepatocarcinogens during a 28-day period. The negative training set consisted of high- or middle-dose groups of 54 non-carcinogens. Support vector machine combined with wrapper-type gene selection algorithms was used for modeling. Consequently, our best classifier yielded prediction accuracies for hepatocarcinogenicity of 99% sensitivity and 97% specificity in the training data set, and false positive prediction was almost completely eliminated. Pathway analysis of feature genes revealed that the mitogen-activated protein kinase p38- and phosphatidylinositol-3-kinase-centered interactome and the v-myc myelocytomatosis viral oncogene homolog-centered interactome were the 2 most significant networks. The usefulness and robustness of our predictor were further confirmed in an independent validation data set obtained from the public database. Interestingly, similar positive predictions were obtained in several genotoxic hepatocarcinogens as well as non-genotoxic hepatocarcinogens. These results indicate that the expression profiles of our newly selected candidate biomarker genes might be common characteristics in the early stage of carcinogenesis for both genotoxic and non-genotoxic carcinogens in the rat liver. Our toxicogenomic model might be useful for the prospective screening of hepatocarcinogenicity of compounds and prioritization of compounds for carcinogenicity testing. - Highlights: >We developed a toxicogenomic model to predict hepatocarcinogenicity of chemicals. >The optimized model consisting of 9 probes had 99% sensitivity and 97% specificity. >This model enables us to detect genotoxic as well as non-genotoxic hepatocarcinogens.

Uehara, Takeki, E-mail: takeki.uehara@shionogi.co.jp [Drug Developmental Research Laboratories, Shionogi and Co., Ltd., 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825 (Japan); Toxicogenomics Informatics Project, National Institute of Biomedical Innovation, 7-6-8 Asagi, Ibaraki, Osaka 567-0085 (Japan); Minowa, Yohsuke; Morikawa, Yuji [Toxicogenomics Informatics Project, National Institute of Biomedical Innovation, 7-6-8 Asagi, Ibaraki, Osaka 567-0085 (Japan); Kondo, Chiaki; Maruyama, Toshiyuki; Kato, Ikuo [Drug Developmental Research Laboratories, Shionogi and Co., Ltd., 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825 (Japan); Nakatsu, Noriyuki; Igarashi, Yoshinobu; Ono, Atsushi [Toxicogenomics Informatics Project, National Institute of Biomedical Innovation, 7-6-8 Asagi, Ibaraki, Osaka 567-0085 (Japan); Hayashi, Hitomi [Laboratory of Veterinary Pathology, Tokyo University of Agriculture and Technology, 3-5-8 Harumi-cho, Fuchu, Tokyo 183-8509 (Japan); Pathogenetic Veterinary Science, United Graduate School of Veterinary Sciences, Gifu University, 1-1 Yanagido, Gifu, 501-1193 Gifu (Japan); Mitsumori, Kunitoshi [Laboratory of Veterinary Pathology, Tokyo University of Agriculture and Technology, 3-5-8 Harumi-cho, Fuchu, Tokyo 183-8509 (Japan); Yamada, Hiroshi [Toxicogenomics Informatics Project, National Institute of Biomedical Innovation, 7-6-8 Asagi, Ibaraki, Osaka 567-0085 (Japan); Ohno, Yasuo [National Institute of Health Sciences, 1-18-1 Kamiyoga, Setagaya-ku, Tokyo 158-8501 (Japan); Urushidani, Tetsuro [Toxicogenomics Informatics Project, National Institute of Biomedical Innovation, 7-6-8 Asagi, Ibaraki, Osaka 567-0085 (Japan); Department of Pathophysiology, Faculty of Pharmaceutical Sciences, Doshisha Women's College of Liberal Arts, Kodo, Kyotanabe, Kyoto 610-0395 (Japan)

2011-09-15

304

Quantitative macroscopic treatment of the spatiotemporal properties of spin crossover solids based on a reaction diffusion equation  

NASA Astrophysics Data System (ADS)

We propose here a new theoretical treatment of the spatiotemporal properties in spin-crosser solids, based on the expansion of the free energy taking into account the spatial fluctuations of the high-spin (HS) fraction. This leads to an equation of motion on the HS fraction following a reaction diffusion equation (RDE), in which most of the parameters can be derived from the experiments. This equation involves the true temporal and spatial scales at variance from the previous stochastic microscopic models, which were based on a homogeneous treatment of the crystal's properties. We have illustrated this new treatment for a two-dimensional rectangularly shaped system with a square symmetry and we could reproduce quantitatively the process of nucleation, growth, and propagation of the HS fraction inside the thermal hysteresis loop, accompanying a first-order transition. The computed spatiotemporal evolution of the system allowed one to follow the propagation of a well-defined macroscopic HS:LS interface, which was found in excellent quantitative agreement with the experimental observations of optical microscopy on the switchable spin crossover crystal [{Fe(NCSe)(py)2}2(m-bpypz)]. The RDE treatment should generate predictive models for novel spatiotemporal effects in spin crossover solids and more generally for all kinds of switchable molecular solids.

Paez-Espejo, Miguel; Sy, Mouhamadou; Varret, François; Boukheddaden, Kamel

2014-01-01

305

Male reproductive strategy explains spatiotemporal segregation in brown bears.  

PubMed

Spatiotemporal segregation is often explained by the risk for offspring predation or by differences in physiology, predation risk vulnerability or competitive abilities related to size dimorphism. Most large carnivores are size dimorphic and offspring predation is often intraspecific and related to nonparental infanticide (NPI). NPI can be a foraging strategy, a strategy to reduce competition, or a male reproductive strategy. Spatiotemporal segregation is widespread among large carnivores, but its nature remains poorly understood. We evaluated three hypotheses to explain spatiotemporal segregation in the brown bear, a size-dimorphic large carnivore in which NPI is common; the 'NPI - foraging/competition hypothesis', i.e. NPI as a foraging strategy or a strategy to reduce competition, the 'NPI - sexual selection hypothesis', i.e. infanticide as a male reproductive strategy and the 'body size hypothesis', i.e. body-size-related differences in physiology, predation risk vulnerability or competitive ability causes spatiotemporal segregation. To test these hypotheses, we quantified spatiotemporal segregation among adult males, lone adult females and females with cubs-of-the-year, based on GPS-relocation data (2006-2010) and resource selection functions in a Scandinavian population. We found that spatiotemporal segregation was strongest between females with cubs-of-the-year and adult males during the mating season. During the mating season, females with cubs-of-the-year selected their resources, in contrast to adult males, in less rugged landscapes in relative close proximity to certain human-related variables, and in more open habitat types. After the mating season, females with cubs-of-the-year markedly shifted their resource selection towards a pattern more similar to that of their conspecifics. No strong spatiotemporal segregation was apparent between females with cubs-of-the-year and conspecifics during the mating and the postmating season. The 'NPI - sexual 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 M J G; Kindberg, Jonas; Swenson, Jon E; Zedrosser, Andreas

2013-07-01

306

Time reversal and the spatio-temporal matched filter  

SciTech Connect

It is known that focusing of an acoustic field by a time-reversal mirror (TRM) is equivalent to a spatio-temporal matched filter under conditions where the Green's function of the field satisfies reciprocity and is time invariant, i.e. the Green's function is independent of the choice of time origin. In this letter, it is shown that both reciprocity and time invariance can be replaced by a more general constraint on the Green's function that allows a TRM to implement the spatio-temporal matched filter even when conditions are time varying.

Lehman, S K; Poggio, A J; Kallman, J S; Meyer, A W; Candy, J V

2004-03-08

307

Routes to spatiotemporal chaos in Kerr optical frequency combs  

SciTech Connect

We investigate the various routes to spatiotemporal chaos in Kerr optical frequency combs, obtained through pumping an ultra-high Q-factor whispering-gallery mode resonator with a continuous-wave laser. The Lugiato–Lefever model is used to build bifurcation diagrams with regards to the parameters that are externally controllable, namely, the frequency and the power of the pumping laser. We show that the spatiotemporal chaos emerging from Turing patterns and solitons display distinctive dynamical features. Experimental spectra of chaotic Kerr combs are also presented for both cases, in excellent agreement with theoretical spectra.

Coillet, Aurélien; Chembo, Yanne K., E-mail: yanne.chembo@femto-st.fr [Optics Department, FEMTO-ST Institute CNRS UMR6174, 16 Route de Gray, 25030 Besançon cedex (France)

2014-03-15

308

Spatiotemporal focusing dynamics in plasmas at X-ray wavelength  

SciTech Connect

Using a finite curvature beam, we investigate here the spatiotemporal focusing dynamics of a laser pulse in plasmas at X-ray wavelength. We trace the dependence of curvature parameter on the focusing of laser pulse and recognize that the self-focusing in plasma is more intense for the X-ray laser pulse with curved wavefront than with flat wavefront. The simulation results demonstrate that spatiotemporal focusing dynamics in plasmas can be controlled with the appropriate choice of beam-plasma parameters to explore the high intensity effects in X-ray regime.

Sharma, A., E-mail: a-physics2001@yahoo.com; Tibai, Z. [Institute of Physics, University of Pecs, Pecs–7624 (Hungary)] [Institute of Physics, University of Pecs, Pecs–7624 (Hungary); Hebling, J. [Institute of Physics, University of Pecs, Pecs–7624 (Hungary) [Institute of Physics, University of Pecs, Pecs–7624 (Hungary); Szentagothai Research Centre, University of Pecs, Pecs-7624 (Hungary); Mishra, S. K. [Institute for Plasma Research, Gandhinagar (India)] [Institute for Plasma Research, Gandhinagar (India)

2014-03-15

309

Routes to spatiotemporal chaos in Kerr optical frequency combs  

NASA Astrophysics Data System (ADS)

We investigate the various routes to spatiotemporal chaos in Kerr optical frequency combs, obtained through pumping an ultra-high Q-factor whispering-gallery mode resonator with a continuous-wave laser. The Lugiato-Lefever model is used to build bifurcation diagrams with regards to the parameters that are externally controllable, namely, the frequency and the power of the pumping laser. We show that the spatiotemporal chaos emerging from Turing patterns and solitons display distinctive dynamical features. Experimental spectra of chaotic Kerr combs are also presented for both cases, in excellent agreement with theoretical spectra.

Coillet, Aurélien; Chembo, Yanne K.

2014-03-01

310

Stabilization of spatiotemporal solitons in Kerr media by dispersive coupling.  

PubMed

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

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

2015-03-15

311

Identification of the Low Density Lipoprotein (LDL) Receptor-related Protein-1 Interactome in Central Nervous System Myelin Suggests a Role in the Clearance of Necrotic Cell Debris*  

PubMed Central

In the central nervous system (CNS), fast neuronal signals are facilitated by the oligodendrocyte-produced myelin sheath. Oligodendrocyte turnover or injury generates myelin debris that is usually promptly cleared by phagocytic cells. Failure to remove dying oligodendrocytes leads to accumulation of degraded myelin, which, if recognized by the immune system, may contribute to the development of autoimmunity in diseases such as multiple sclerosis. We recently identified low density lipoprotein receptor-related protein-1 (LRP1) as a novel phagocytic receptor for myelin debris. Here, we report characterization of the LRP1 interactome in CNS myelin. Fusion proteins were designed corresponding to the extracellular ligand-binding domains of LRP1. LRP1 partners were isolated by affinity purification and characterized by mass spectrometry. We report that LRP1 binds intracellular proteins via its extracellular domain and functions as a receptor for necrotic cells. Peptidyl arginine deiminase-2 and cyclic nucleotide phosphodiesterase are novel LRP1 ligands identified in our screen, which interact with full-length LRP1. Furthermore, the extracellular domain of LRP1 is a target of peptidyl arginine deiminase-2-mediated deimination in vitro. We propose that LRP1 functions as a receptor for endocytosis of intracellular components released during cellular damage and necrosis. PMID:23264627

Fernandez-Castaneda, Anthony; Arandjelovic, Sanja; Stiles, Travis L.; Schlobach, Ryan K.; Mowen, Kerri A.; Gonias, Steven L.; Gaultier, Alban

2013-01-01

312

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

313

Exploring Off-Targets and Off-Systems for Adverse Drug Reactions via Chemical-Protein Interactome — Clozapine-Induced Agranulocytosis as a Case Study  

PubMed Central

In the era of personalized medical practice, understanding the genetic basis of patient-specific adverse drug reaction (ADR) is a major challenge. Clozapine provides effective treatments for schizophrenia but its usage is limited because of life-threatening agranulocytosis. A recent high impact study showed the necessity of moving clozapine to a first line drug, thus identifying the biomarkers for drug-induced agranulocytosis has become important. Here we report a methodology termed as antithesis chemical-protein interactome (CPI), which utilizes the docking method to mimic the differences in the drug-protein interactions across a panel of human proteins. Using this method, we identified HSPA1A, a known susceptibility gene for CIA, to be the off-target of clozapine. Furthermore, the mRNA expression of HSPA1A-related genes (off-target associated systems) was also found to be differentially expressed in clozapine treated leukemia cell line. Apart from identifying the CIA causal genes we identified several novel candidate genes which could be responsible for agranulocytosis. Proteins related to reactive oxygen clearance system, such as oxidoreductases and glutathione metabolite enzymes, were significantly enriched in the antithesis CPI. This methodology conducted a multi-dimensional analysis of drugs' perturbation to the biological system, investigating both the off-targets and the associated off-systems to explore the molecular basis of an adverse event or the new uses for old drugs. PMID:21483481

Chen, Jian; Jegga, Anil G.; Luo, Heng; Shi, Leming; Wan, Chunling; Guo, Xizhi; Qin, Shengying; He, Guang; Feng, Guoyin; He, Lin

2011-01-01

314

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

315

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

PubMed

Nuclei of Xenopus laevis oocytes grow 100?000-fold larger in volume than a typical somatic nucleus and require an unusual intranuclear F-actin scaffold for mechanical stability. We now developed a method for mapping F-actin interactomes and identified a comprehensive set of F-actin binders from the oocyte nuclei. Unexpectedly, the most prominent interactor was a novel kinesin termed NabKin (Nuclear and meiotic actin-bundling Kinesin). NabKin not only binds microtubules but also F-actin structures, such as the intranuclear actin bundles in prophase and the contractile actomyosin ring during cytokinesis. The interaction between NabKin and F-actin is negatively regulated by Importin-? and is responsive to spatial information provided by RanGTP. Disconnecting NabKin from F-actin during meiosis caused cytokinesis failure and egg polyploidy. We also found actin-bundling activity in Nabkin's somatic paralogue KIF14, which was previously shown to be essential for somatic cell division. Our data are consistent with the notion that NabKin/KIF14 directly link microtubules with F-actin and that such link is essential for cytokinesis. PMID:23727888

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

2013-07-01

316

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

PubMed Central

Nuclei of Xenopus laevis oocytes grow 100?000-fold larger in volume than a typical somatic nucleus and require an unusual intranuclear F-actin scaffold for mechanical stability. We now developed a method for mapping F-actin interactomes and identified a comprehensive set of F-actin binders from the oocyte nuclei. Unexpectedly, the most prominent interactor was a novel kinesin termed NabKin (Nuclear and meiotic actin-bundling Kinesin). NabKin not only binds microtubules but also F-actin structures, such as the intranuclear actin bundles in prophase and the contractile actomyosin ring during cytokinesis. The interaction between NabKin and F-actin is negatively regulated by Importin-? and is responsive to spatial information provided by RanGTP. Disconnecting NabKin from F-actin during meiosis caused cytokinesis failure and egg polyploidy. We also found actin-bundling activity in Nabkin's somatic paralogue KIF14, which was previously shown to be essential for somatic cell division. Our data are consistent with the notion that NabKin/KIF14 directly link microtubules with F-actin and that such link is essential for cytokinesis. PMID:23727888

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

2013-01-01

317

Drafting the CLN3 protein interactome in SH-SY5Y human neuroblastoma cells: a label-free quantitative proteomics approach.  

PubMed

Neuronal ceroid lipofuscinoses (NCL) are the most common inherited progressive encephalopathies of childhood. One of the most prevalent forms of NCL, Juvenile neuronal ceroid lipofuscinosis (JNCL) or CLN3 disease (OMIM: 204200), is caused by mutations in the CLN3 gene on chromosome 16p12.1. Despite progress in the NCL field, the primary function of ceroid-lipofuscinosis neuronal protein 3 (CLN3) remains elusive. In this study, we aimed to clarify the role of human CLN3 in the brain by identifying CLN3-associated proteins using a Tandem Affinity Purification coupled to Mass Spectrometry (TAP-MS) strategy combined with Significance Analysis of Interactome (SAINT). Human SH-SY5Y-NTAP-CLN3 stable cells were used to isolate native protein complexes for subsequent TAP-MS. Bioinformatic analyses of isolated complexes yielded 58 CLN3 interacting partners (IP) including 42 novel CLN3 IP, as well as 16 CLN3 high confidence interacting partners (HCIP) previously identified in another high-throughput study by Behrends et al., 2010. Moreover, 31 IP of ceroid-lipofuscinosis neuronal protein 5 (CLN5) were identified (18 of which were in common with the CLN3 bait). Our findings support previously suggested involvement of CLN3 in transmembrane transport, lipid homeostasis and neuronal excitability, as well as link it to G-protein signaling and protein folding/sorting in the ER. PMID:23464991

Scifo, Enzo; Szwajda, Agnieszka; D?bski, Janusz; Uusi-Rauva, Kristiina; Kesti, Tapio; Dadlez, Micha?; Gingras, Anne-Claude; Tyynelä, Jaana; Baumann, Marc H; Jalanko, Anu; Lalowski, Maciej

2013-05-01

318

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

NASA Astrophysics Data System (ADS)

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

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

2014-06-01

319

Spatio-temporal dynamics before population collapse  

E-print Network

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

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

2014-01-01

320

Spatiotemporal Dynamics of a Photorefractive Phase - Resonator  

NASA Astrophysics Data System (ADS)

The spatiotemporal dynamics of a photorefractive phase-conjugate resonator (PPCR) is studied both experimentally and analytically. The resonator is a confocal cavity bounded by a dielectric mirror and a phase-conjugate mirror in a four wave mixing geometry. The effect of the Bragg mismatch, which is caused by the misalignment of the pump fields, is experimentally shown to break the cylindrical symmetry of the system and to increase the speed of the dynamics. By studying the first non stationary state at a cavity Fresnel number of F ~ 2.0, the effect of the transverse component of the mismatch is shown to add a transverse phase to the wavefront of the phase-conjugate field, leading to the periodic nucleation of a pair of phase defects. A model of this state is developed in terms of the competition of a few transverse patterns. The model is experimentally verified using a holographic optical correlator designed to identify the modes presumed by the model. The dynamics are also studied using a Karhunen -Loeve decomposition in which the eigenvectors of the covariance matrix are calculated. The covariance matrix is obtained from the transverse intensity fluctuations of the cavity field and the eigenvectors are interpreted as the active cavity modes of the resonator. The results of the application of this experimental method to the F ~ 2.0 state match those obtained by the correlator. This demonstrates its validity as a useful tool for studying the system. Application of the decomposition to states at higher F reveal that aperiodic and periodic states can have very similar active mode structures. An analytical model of the PPCR is then developed using a plane wave decomposition of the cavity field and the material variables contained in Kukhtarev's equations. Numerical simulations using the model demonstrate its accuracy. In addition, the different effects of the longitudinal and transverse components of the Bragg mismatch on the dynamics and defect nucleation are revealed. The relevant assumptions involved in the development of the model are discussed in detail.

Korwan, Daniel Richard

321

Mapping and spatiotemporal analysis tool for hydrological data: Spellmap  

Technology Transfer Automated Retrieval System (TEKTRAN)

Lack of data management and analyses tools is one of the major limitations to effectively evaluate and use large datasets of high-resolution atmospheric, surface, and subsurface observations. High spatial and temporal resolution datasets better represent the spatiotemporal variability of hydrologica...

322

Reference Canopy Stomatal Conductance Explains Spatiotemporal Patterns of Tree Transpiration  

Microsoft Academic Search

Increased heterogeneity in patterns of whole tree transpiration (EC) with increasing atmospheric vapor pressure deficit (D) suggests a dynamic response of sap flow velocity (JS) to environmental drivers. We hypothesized that differences in reference stomatal conductance (GSref), stomatal conductance at D = 1kPa, would explain the spatiotemporal dynamics of JS. Using a coupled model of plant hydraulic and biochemical processes

M. M. Loranty; D. S. Mackay; B. E. Ewers; E. L. Kruger; E. Traver

2007-01-01

323

358 04/2011 Group Spatiotemporal Pattern Queries  

E-print Network

crosses a snow storm, and delay of train >= 30 min. The pattern can be completely evaluated for every consistently express and evaluate a wide range of group spatiotemporal pattern queries. We formally define the language operators, illustrate the evaluation algorithms, and dis- cuss the optimization methods. Several

Güting, Ralf Hartmut

324

Location, Location, Location: Development of Spatiotemporal Sequence Learning in Infancy  

ERIC Educational Resources Information Center

We investigated infants' sensitivity to spatiotemporal structure. In Experiment 1, circles appeared in a statistically defined spatial pattern. At test 11-month-olds, but not 8-month-olds, looked longer at a novel spatial sequence. Experiment 2 presented different color/shape stimuli, but only the location sequence was violated during test;…

Kirkham, Natasha Z.; Slemmer, Jonathan A.; Richardson, Daniel C.; Johnson, Scott P.

2007-01-01

325

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

326

Visual Experience Modulates Spatio-Temporal Dynamics of Circuit Activation  

PubMed Central

Persistent reduction in sensory drive in early development results in multiple plastic changes of different cortical synapses. How these experience-dependent modifications affect the spatio-temporal dynamics of signal propagation in neocortical circuits is poorly understood. Here we demonstrate that brief visual deprivation significantly affects the propagation of electrical signals in the primary visual cortex. The spatio-temporal spread of circuit activation upon direct stimulation of its input layer (Layer 4) is reduced, as is the activation of L2/3 – the main recipient of the output from L4. Our data suggest that the decrease in spatio-temporal activation of L2/3 depends on reduced L4 output, and is not intrinsically generated within L2/3. The data shown here suggest that changes in the synaptic components of the visual cortical circuit result not only in alteration of local integration of excitatory and inhibitory inputs, but also in a significant decrease in overall circuit activation. Furthermore, our data indicate a differential effect of visual deprivation on L4 and L2/3, suggesting that while feedforward activation of L2/3 is reduced, its activation by long range, within layer inputs is unaltered. Thus, brief visual deprivation induces experience-dependent circuit re-organization by modulating not only circuit excitability, but also the spatio-temporal patterns of cortical activation within and between layers. PMID:21743804

Wang, Lang; Fontanini, Alfredo; Maffei, Arianna

2011-01-01

327

Spatiotemporal electrohysterography patterns in normal and arrested labor  

E-print Network

OBSTETRICS Spatiotemporal electrohysterography patterns in normal and arrested labor Tammy Y patterns of uterine electrical activity in normal and arrested labors. STUDY DESIGN: From a database of electrohysterograms, 12 sub- jects who underwent cesarean delivery for active-phase arrest were each matched with 2

Slatton, Clint

328

UNDERSTANDING SEVERE WEATHER PROCESSES THROUGH SPATIOTEMPORAL RELATIONAL RANDOM FORESTS  

E-print Network

, JEFFREY BASARA5, AND JOHN K. WILLIAMS6 Abstract. Major severe weather events can cause a significant loss the formation of tornadoes near strong frontal boundaries, and understanding the translation of drought across. For example, a thunderstorm evolves over time and may eventually produce a tornado through the spatiotemporal

McGovern, Amy

329

Spatio-temporal Spike Pattern Classification in Neuromorphic Systems  

E-print Network

architectures offer an attractive solution for implementing compact efficient sensory-motor neural processing, classify the spatio-temporal information contained in the data, and pro- duce appropriate motor outputs and asynchronous streams of spikes, and spiking multi-neuron chips [5, 6, 7] for implementing state dependent

330

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 efficient minimum spanning tree based aggregation technique is used to enable robust estimators like M- tion. Efficient minimum spanning tree (MST) based aggregation technique [30] is then integrated

Yang, Ming-Hsuan

331

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

332

Kernel Averaged Predictors for Spatio-Temporal Regression Models  

PubMed Central

In applications where covariates and responses are observed across space and time, a common goal is to quantify the effect of a change in the covariates on the response while adequately accounting for the spatio-temporal structure of the observations. The most common approach for building such a model is to confine the relationship between a covariate and response variable to a single spatio-temporal location. However, oftentimes the relationship between the response and predictors may extend across space and time. In other words, the response may be affected by levels of predictors in spatio-temporal proximity to the response location. Here, a flexible modeling framework is proposed to capture such spatial and temporal lagged effects between a predictor and a response. Specifically, kernel functions are used to weight a spatio-temporal covariate surface in a regression model for the response. The kernels are assumed to be parametric and non-stationary with the data informing the parameter values of the kernel. The methodology is illustrated on simulated data as well as a physical data set of ozone concentrations to be explained by temperature. PMID:24010051

Gelfand, Alan E.

2013-01-01

333

Finding Spatio-Temporal Patterns in Large Sensor Datasets  

ERIC Educational Resources Information Center

Spatial or temporal data mining tasks are performed in the context of the relevant space, defined by a spatial neighborhood, and the relevant time period, defined by a specific time interval. Furthermore, when mining large spatio-temporal datasets, interesting patterns typically emerge where the dataset is most dynamic. This dissertation is…

McGuire, Michael Patrick

2010-01-01

334

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

335

Spatio-temporal Information Ranking in VANET Applications  

E-print Network

Spatio-temporal Information Ranking in VANET Applications PIOTR SZCZUREK, BO XU, JIE LIN, AND OURI WOLFSON University of Illinois at Chicago Vehicular ad-hoc networks (VANETs) is a promising approach ranking in VANETs. In this method, mobile nodes such as vehicles judge the relevance of incoming

Wolfson, Ouri E.

336

A Probabilistic Framework for Spatio-Temporal Video Representation & Indexing  

E-print Network

. A key feature of the system is the analysis of video input as a single entity as opposed to a sequenceA Probabilistic Framework for Spatio-Temporal Video Representation & Indexing Hayit Greenspan1, Israel 2 CUTe Ltd., Tel-Aviv, Israel Abstract. In this work we describe a novel statistical video

Goldberger, Jacob

337

Intelligence and Spatiotemporal Patterns of Event-Related Desynchronization (ERD).  

ERIC Educational Resources Information Center

The relationship between psychometric intelligence, determined by Raven's Advanced Progressive Matrices, and spatiotemporal patterns of cortical activation, determined by quantifying event-related desynchronization, was studied in 17 college students. Findings support the hypothesis of a more efficient use of the brain in higher IQ individuals.…

Neubauer, Aljoscha; And Others

1995-01-01

338

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

339

Early Spatiotemporal Grouping with a Distributed Oriented Energy Representation  

E-print Network

, delineated groupings serve to define support regions that can be processed as wholes for compactEarly Spatiotemporal Grouping with a Distributed Oriented Energy Representation Konstantinos G. In this paper, a new represen- tation for grouping raw image data into a set of coherent spacetime regions

Wildes, Richard P.

340

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"

341

Recovering metric properties of objects through spatiotemporal interpolation.  

PubMed

Spatiotemporal interpolation (STI) refers to perception of complete objects from fragmentary information across gaps in both space and time. It differs from static interpolation in that requirements for interpolation are not met in any static frame. It has been found that STI produced objective performance advantages in a shape discrimination paradigm for both illusory and occluded objects when contours met conditions of spatiotemporal relatability. Here we report psychophysical studies testing whether spatiotemporal interpolation allows recovery of metric properties of objects. Observers viewed virtual triangles specified only by sequential partial occlusions of background elements by their vertices (the STI condition) and made forced choice judgments of the object's size relative to a reference standard. We found that length could often be accurately recovered for conditions where fragments were relatable and formed illusory triangles. In the first control condition, three moving dots located at the vertices provided the same spatial and timing information as the virtual object in the STI condition but did not induce perception of interpolated contours or a coherent object. In the second control condition oriented line segments were added to the dots and mid-points between the dots in a way that did not induce perception of interpolated contours. Control stimuli did not lead to accurate size judgments. We conclude that spatiotemporal interpolation can produce representations, from fragmentary information, of metric properties in addition to shape. PMID:25111311

Ghose, Tandra; Liu, Janelle; Kellman, Philip J

2014-09-01

342

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

343

Itk Controls the Spatiotemporal Organization of T Cell Activation  

PubMed Central

During T cell activation by antigen-presenting cells (APCs), the diverse spatiotemporal organization of components of T cell signaling pathways modulates the efficiency of activation. Here, we found that loss of the tyrosine kinase interleukin-2 (IL-2)–inducible T cell kinase (Itk) in mice altered the spatiotemporal distributions of 14 of 16 sensors of T cell signaling molecules in the region of the interface between the T cell and the APC, which reduced the segregation of signaling intermediates into distinct spatiotemporal patterns. Activation of the Rho family guanosine triphosphatase Cdc42 at the center of the cell-cell interface was impaired, although the total cellular amount of active Cdc42 remained intact. The defect in Cdc42 localization resulted in impaired actin accumulation at the T cell–APC interface in Itk-deficient T cells. Reconstitution of cells with active Cdc42 that was specifically directed to the center of the interface restored actin accumulation in Itk-deficient T cells. Itk also controlled the central localization of the guanine nucleotide exchange factor SLAT [Switch-associated protein 70 (SWAP-70)–like adaptor of T cells], which may contribute to the activation of Cdc42 at the center of the interface. Together, these data illustrate how control of the spatiotemporal organization of T cell signaling controls critical aspects of T cell function. PMID:21971040

Singleton, Kentner L.; Gosh, Monica; Dandekar, Radhika D.; Au-Yeung, Byron B.; Ksionda, Olga; Tybulewicz, Victor L. J.; Altman, Amnon; Fowell, Deborah J.; Wülfing, Christoph

2011-01-01

344

Itk controls the spatiotemporal organization of T cell activation.  

PubMed

During T cell activation by antigen-presenting cells (APCs), the diverse spatiotemporal organization of components of T cell signaling pathways modulates the efficiency of activation. Here, we found that loss of the tyrosine kinase interleukin-2 (IL-2)-inducible T cell kinase (Itk) in mice altered the spatiotemporal distributions of 14 of 16 sensors of T cell signaling molecules in the region of the interface between the T cell and the APC, which reduced the segregation of signaling intermediates into distinct spatiotemporal patterns. Activation of the Rho family guanosine triphosphatase Cdc42 at the center of the cell-cell interface was impaired, although the total cellular amount of active Cdc42 remained intact. The defect in Cdc42 localization resulted in impaired actin accumulation at the T cell-APC interface in Itk-deficient T cells. Reconstitution of cells with active Cdc42 that was specifically directed to the center of the interface restored actin accumulation in Itk-deficient T cells. Itk also controlled the central localization of the guanine nucleotide exchange factor SLAT [Switch-associated protein 70 (SWAP-70)-like adaptor of T cells], which may contribute to the activation of Cdc42 at the center of the interface. Together, these data illustrate how control of the spatiotemporal organization of T cell signaling controls critical aspects of T cell function. PMID:21971040

Singleton, Kentner L; Gosh, Monica; Dandekar, Radhika D; Au-Yeung, Byron B; Ksionda, Olga; Tybulewicz, Victor L J; Altman, Amnon; Fowell, Deborah J; Wülfing, Christoph

2011-10-01

345

INTRODUCTION The retina evolved to report spatiotemporal and chromatic  

E-print Network

, cell form, and cell patterning in the retina. THE EVOLUTIONARY CONTEXT INTRODUCTION Molecular biologyINTRODUCTION The retina evolved to report spatiotemporal and chromatic patterns of photons imaged by the eye.1 The plan of the human neurosensory retina is generically vertebrate in form and development

Marc, Robert E.

346

Efficient Probabilistic Spatio-Temporal Video Object Segmentation  

Microsoft Academic Search

One of the major objectives in multimedia technology is to be able to segment objects automatically from a video sequence, for a diverse range of applications from video surveillance and object tracking through to content-based video retrieval, coding and medical imaging. Probabilistic spatio-temporal (PST) video object segmentation has been shown to be of pivotal importance in achieving better segmentation, because

Rakib Ahmed; Gour C. Karmakar; Laurence S. Dooley

2007-01-01

347

Rapidly switched random links enhance spatiotemporal regularity Arghya Mondal,1  

E-print Network

Rapidly switched random links enhance spatiotemporal regularity Arghya Mondal,1 Sudeshna Sinha,2, we change the random links at different frequencies in order to discern the effect if any of the time dependence of the links. We observe two different regimes in this network: i when the network is rewired

Sinha, Sudeshna

348

PSO2004/FU5766 Improved wind power prediction  

E-print Network

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

349

MVL spatiotemporal analysis for model intercomparison in EPS: application to the DEMETER multi-model ensemble  

NASA Astrophysics Data System (ADS)

In a recent paper, Gutiérrez et al. (Nonlinear Process Geophys 15(1):109-114, 2008) introduced a new characterization of spatiotemporal error growth—the so called mean-variance logarithmic (MVL) diagram—and applied it to study ensemble prediction systems (EPS); in particular, they analyzed single-model ensembles obtained by perturbing the initial conditions. In the present work, the MVL diagram is applied to multi-model ensembles analyzing also the effect of model formulation differences. To this aim, the MVL diagram is systematically applied to the multi-model ensemble produced in the EU-funded DEMETER project. It is shown that the shared building blocks (atmospheric and ocean components) impose similar dynamics among different models and, thus, contribute to poorly sampling the model formulation uncertainty. This dynamical similarity should be taken into account, at least as a pre-screening process, before applying any objective weighting method.

Fernández, J.; Primo, C.; Cofiño, A. S.; Gutiérrez, J. M.; Rodríguez, M. A.

2009-08-01

350

Spatiotemporal Analysis of Normal and Pathological Human Vocal Fold Vibrations  

PubMed Central

Purpose In order for spatiotemporal analysis to become a relevant clinical tool, it must be applied to human vocal fold vibration. Receiver operating characteristic (ROC) analysis will help assess the ability of spatiotemporal parameters to detect pathological vibration. Materials and Methods Spatiotemporal parameters of correlation length and entropy were extracted from high speed videos of 124 subjects, 67 without vocal fold pathology and 57 with either vocal fold polyps or nodules. Mann-Whitney rank sum tests were performed to compare normal vocal fold vibrations to pathological vibrations, and ROC analysis was used to assess the diagnostic value of spatiotemporal analysis. Results A statistically significant difference was found between the normal and pathological groups in both correlation length (P < 0.001) and entropy (P < 0.001). ROC analysis showed area under the curve (AUC) of 0.85 for correlation length, 0.87 for entropy, and 0.92 when the two parameters were combined. A statistically significant difference was not found between the nodules and polyps groups in either correlation length (P = 0.227) or entropy (P = 0.943). ROC analysis showed AUC of 0.63 for correlation length and 0.51 for entropy. Conclusions Although they could not effectively distinguish vibration of vocal folds with nodules from those with polyps, the spatiotemporal parameters correlation length and entropy exhibit the ability to differentiate normal and pathological vocal fold vibration, and may represent a diagnostic tool for objectively detecting abnormal vibration in the future, especially in neurological voice disorders and vocal folds without a visible lesion. PMID:22841342

Krausert, Christopher R.; Liang, Yufang; Zhang, Yu; Rieves, Adam L.; Geurink, Kyle R.; Jiang, Jack J.

2012-01-01

351

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

352

Computational analysis of interactomes: current and future perspectives for bioinformatics approaches to model the host-pathogen interaction space.  

PubMed

Bacterial and viral pathogens affect their eukaryotic host partly by interacting with proteins of the host cell. Hence, to investigate infection from a systems' perspective we need to construct complete and accurate host-pathogen protein-protein interaction networks. Because of the paucity of available data and the cost associated with experimental approaches, any construction and analysis of such a network in the near future has to rely on computational predictions. Specifically, this challenge consists of a number of sub-problems: First, prediction of possible pathogen interactors (e.g. effector proteins) is necessary for bacteria and protozoa. Second, the prospective host binding partners have to be determined and finally, the impact on the host cell analyzed. This review gives an overview of current bioinformatics approaches to obtain and understand host-pathogen interactions. As an application example of the methods covered, we predict host-pathogen interactions of Salmonella and discuss the value of these predictions as a prospective for further research. PMID:22750305

Arnold, Roland; Boonen, Kurt; Sun, Mark G F; Kim, Philip M

2012-08-01

353

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

354

Spatiotemporal Modeling of Ozone Levels in Quebec (Canada): A Comparison of Kriging, Land-Use Regression (LUR), and Combined Bayesian Maximum Entropy–LUR Approaches  

PubMed Central

Background: Ambient air ozone (O3) is a pulmonary irritant that has been associated with respiratory health effects including increased lung inflammation and permeability, airway hyperreactivity, respiratory symptoms, and decreased lung function. Estimation of O3 exposure is a complex task because the pollutant exhibits complex spatiotemporal patterns. To refine the quality of exposure estimation, various spatiotemporal methods have been developed worldwide. Objectives: We sought to compare the accuracy of three spatiotemporal models to predict summer ground-level O3 in Quebec, Canada. Methods: We developed a land-use mixed-effects regression (LUR) model based on readily available data (air quality and meteorological monitoring data, road networks information, latitude), a Bayesian maximum entropy (BME) model incorporating both O3 monitoring station data and the land-use mixed model outputs (BME-LUR), and a kriging method model based only on available O3 monitoring station data (BME kriging). We performed leave-one-station-out cross-validation and visually assessed the predictive capability of each model by examining the mean temporal and spatial distributions of the average estimated errors. Results: The BME-LUR was the best predictive model (R2 = 0.653) with the lowest root mean-square error (RMSE ;7.06 ppb), followed by the LUR model (R2 = 0.466, RMSE = 8.747) and the BME kriging model (R2 = 0.414, RMSE = 9.164). Conclusions: Our findings suggest that errors of estimation in the interpolation of O3 concentrations with BME can be greatly reduced by incorporating outputs from a LUR model developed with readily available data. Citation: Adam-Poupart A, Brand A, Fournier M, Jerrett M, Smargiassi A. 2014. Spatiotemporal modeling of ozone levels in Quebec (Canada): a comparison of kriging, land-use regression (LUR), and combined Bayesian maximum entropy–LUR approaches. Environ Health Perspect 122:970–976;?http://dx.doi.org/10.1289/ehp.1306566 PMID:24879650

Adam-Poupart, Ariane; Brand, Allan; Fournier, Michel; Jerrett, Michael

2014-01-01

355

Ordering spatiotemporal chaos in complex thermosensitive neuron networks  

NASA Astrophysics Data System (ADS)

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

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

2006-04-01

356

An autoregressive approach to spatio-temporal disease mapping.  

PubMed

Disease mapping has been a very active research field during recent years. Nevertheless, time trends in risks have been ignored in most of these studies, yet they can provide information with a very high epidemiological value. Lately, several spatio-temporal models have been proposed, either based on a parametric description of time trends, on independent risk estimates for every period, or on the definition of the joint covariance matrix for all the periods as a Kronecker product of matrices. The following paper offers an autoregressive approach to spatio-temporal disease mapping by fusing ideas from autoregressive time series in order to link information in time and by spatial modelling to link information in space. Our proposal can be easily implemented in Bayesian simulation software packages, for example WinBUGS. As a result, risk estimates are obtained for every region related to those in their neighbours and to those in the same region in adjacent periods. PMID:17979141

Martínez-Beneito, M A; López-Quilez, A; Botella-Rocamora, P

2008-07-10

357

Spatiotemporal Chaotic unjamming and jamming in granular avalanches  

E-print Network

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

Ziwei Wang; Jie Zhang

2014-10-23

358

A new perspective on the spatio-temporal variability of soil moisture  

NASA Astrophysics Data System (ADS)

One of the key components controlling both the water and energy balance, is soil moisture. The characterization of its spatio-temporal variability is crucial to understand and predict processes in climate science and hydrology. A number of studies characterized the spatial variability and the rank stability (also called temporal stability) of the absolute soil moisture within a given network. These studies were generally based on short-term measurement campaigns and did not distinguish between the time invariant and time varying contributors of the absolute soil moisture. In the current study (Mittelbach and Seneviratne, 2012), we investigate this issue using measurements from 14 grassland sites of the SwissSMEX soil moisture network over a spatial extent of about 150x210 km and for the time period May 2010 to July 2011. The spatial variance of the absolute column soil moisture (integrated over 50 cm) is thereby decomposed over time in contributions from the spatial variance of the mean soil moisture at all sites (which is time invariant), and components that are related to soil moisture dynamics (which are time varying). These include the spatial variance of the temporal soil moisture anomalies at all sites and the covariance between the sites' anomalies to the spatial mean at a given time step and those for the temporal mean values. The analysis illustrates that the spatial variance of the time invariant term contributes 50-160% of the overall spatial soil moisture variance at any point in time. On the other hand the spatial variance of the temporal anomalies, which is most relevant for climate and hydrological applications as it is directly related to the soil moisture dynamics, contributes at most 2-30% to the overall variance. This result suggests that a large fraction of the spatial variability of soil moisture assessed from short-term campaigns is time invariant and that the rank (or "temporal") stability concept when applied to absolute soil moisture, mostly characterizes the time-invariant patterns. Indeed, sites that best represent the mean soil moisture dynamics of the network are not the same as those that best reflect mean soil moisture at any point in time. Overall this study indicates that conclusions derived from the analysis of the spatio-temporal variability of absolute soil moisture do not necessary apply to temporal soil moisture anomalies, and hence to soil moisture dynamics. Reference: Mittelbach, H. and S.I. Seneviratne, 2012: A new perspective on the spatio-temporal variability of soil moisture: Temporal dynamics versus time invariant contributions. Submitted to HESS.

Mittelbach, H.; Seneviratne, S. I.

2012-04-01

359

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

360

Bayesian spatio-temporal discard model in a demersal trawl fishery  

NASA Astrophysics Data System (ADS)

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

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

2014-07-01

361

Free-carrier-driven spatiotemporal dynamics in amplifying silicon waveguides  

NASA Astrophysics Data System (ADS)

We theoretically investigate the free-carrier-induced spatiotemporal dynamics of continuous waves in silicon waveguides embedded in an amplifying medium. Optical propagation is governed by a cubic Ginzburg-Landau equation coupled with an ordinary differential equation accounting for the free-carrier dynamics. We find that, owing to free-carrier dispersion, continuous waves are modulationally unstable in both anomalous and normal dispersion regimes and chaotically generate unstable accelerating pulses.

Roy, Samudra; Marini, Andrea; Biancalana, Fabio

2014-05-01

362

Spatiotemporal Bayesian inference dipole analysis for MEG neuroimaging data.  

PubMed

Recently, we described a Bayesian inference approach to the MEG/EEG inverse problem that used numerical techniques to estimate the full posterior probability distributions of likely solutions upon which all inferences were based [Schmidt, D.M., George, J.S., Wood, C.C., 1999. Bayesian inference applied to the electromagnetic inverse problem. Human Brain Mapping 7, 195; Schmidt, D.M., George, J.S., Ranken, D.M., Wood, C.C., 2001. Spatial-temporal bayesian inference for MEG/EEG. In: Nenonen, J., Ilmoniemi, R. J., Katila, T. (Eds.), Biomag 2000: 12th International Conference on Biomagnetism. Espoo, Norway, p. 671]. Schmidt et al. (1999) focused on the analysis of data at a single point in time employing an extended region source model. They subsequently extended their work to a spatiotemporal Bayesian inference analysis of the full spatiotemporal MEG/EEG data set. Here, we formulate spatiotemporal Bayesian inference analysis using a multi-dipole model of neural activity. This approach is faster than the extended region model, does not require use of the subject's anatomical information, does not require prior determination of the number of dipoles, and yields quantitative probabilistic inferences. In addition, we have incorporated the ability to handle much more complex and realistic estimates of the background noise, which may be represented as a sum of Kronecker products of temporal and spatial noise covariance components. This reduces the effects of undermodeling noise. In order to reduce the rigidity of the multi-dipole formulation which commonly causes problems due to multiple local minima, we treat the given covariance of the background as uncertain and marginalize over it in the analysis. Markov Chain Monte Carlo (MCMC) was used to sample the many possible likely solutions. The spatiotemporal Bayesian dipole analysis is demonstrated using simulated and empirical whole-head MEG data. PMID:16023866

Jun, Sung C; George, John S; Paré-Blagoev, Juliana; Plis, Sergey M; Ranken, Doug M; Schmidt, David M; Wood, C C

2005-10-15

363

The spatiotemporal structure of population in the Muskrat ( Ondatra zibethicus )  

Microsoft Academic Search

The spatiotemporal structure of the muskrat population has been studied by means of the prenatal radioactive marking of juveniles\\u000a with 45 Ca and their subsequent recapture in the test area. The muskrat population is characterized by a cyclic type of spatial\\u000a structure, with seasonal transition from a mosaic type of settling to a diffuse type and, after the breeding season,

Yu. A. Gorshkov

2006-01-01

364

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

365

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

366

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

367

Spatiotemporal nonlinear optics in arrays of subwavelength waveguides  

SciTech Connect

We report numerical and experimental investigations of spatiotemporal nonlinear optical effects leading to spectral broadening in an array of subwavelength silicon waveguides pumped with infrared femtosecond pulses. Adjusting an input pulse position across the array, we observe different patterns in the output spectra. We explain these observations using a theory of the resonant (Cherenkov) radiation emitted by temporal solitons belonging to different spatial supermodes of the array. We also demonstrate strong nonperturbative coupling of temporal dispersion and discrete diffraction in the subwavelength arrays.

Gorbach, A. V.; Ding, W.; Staines, O. K.; Nobriga, C. E. de; Hobbs, G. D.; Wadsworth, W. J.; Knight, J. C.; Skryabin, D. V.; Samarelli, A.; Sorel, M.; De La Rue, R. M. [Centre for Photonics and Photonic Materials, Department of Physics, University of Bath, Bath BA2 7AY (United Kingdom); Department of Electronics and Electrical Engineering, University of Glasgow, Glasgow G12 8LT (United Kingdom)

2010-10-15

368

Small GTPases and Spatiotemporal Regulation of Pollen Tube Growth  

Microsoft Academic Search

During in vivo growth, pollen tubes make a long journey toward the ovule, responding to\\u000a long- and short-distance guidance cues and elongating through different female tissues. Thus, pollen\\u000a tube growth and guidance require complicated inter- and intracellular signaling, integration of multiple\\u000a signals, and spatiotemporal coordination of the downstream responses necessary for targeted exocytosis.\\u000a ROP, a plant-unique family of Rho small G proteins,

Jae-Ung Hwang; Zhenbiao Yang

369

An image blocks encryption algorithm based on spatiotemporal chaos  

Microsoft Academic Search

In this paper, the CML-based spatiotemporal chaos system is used for image blocks encryption, which gets higher security.\\u000a The basic idea is to divide the image into blocks, and then use the block numbers as the spatial parameter of CML to iterate\\u000a the chaos system. Each lattice generates a chaos sequence, and the number of chaos sequence values is equal

Xingyuan Wang; Lin Teng

370

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

371

SINA: scalable incremental processing of continuous queries in spatio-temporal databases  

Microsoft Academic Search

This paper intoduces the Scalable INcremental hash-based Algorithm (SINA, for short); a new algorithm for evaluting a set of concurrent continuous spatio-temporal queries. SINA is designed with two goals in mind: (1) Scalability in terms of the number of concurrent continuous spatio-temporal queries, and (2) Incremental evaluation of continyous spatio-temporal queries. SINA achieves scalability by empolying a shared execution paradigm

Mohamed F. Mokbel; Xiaopeing Xiong; Walid G. Aref

2004-01-01

372

Conceptual data modeling on the evolution of the spatiotemporal object  

NASA Astrophysics Data System (ADS)

A framework to express the changes and the causalities within the object's evolution is proposed based on a general inspection of the interactions among the Spatiotemporal Objects (STOs). Why the STOs can evolve is that they can exchange the material, the energy and the information mutually. The result of their evolution is the changes of their features and mechanism. Feature changes can be categorized into 2 levels: the changes of the feature statuses and the changes of the feature structures. The former result in just the increment of the data quantity of the database, the later can furthermore result in the increment of data structures defined in the database. Any a change of a STO is caused directly by a behavior of either itself or another STO. Feature changes can be directly expressed by spatiotemporal data or data structure, but the mechanism changes of a STO can only be indirectly reflected by its feature and behavior description. The proposed framework consists of five key elements: the essence, the features, and the behaviors of the STO, the information flow and the material flow within the spatiotemporal interactive process.

She, Jiangfeng; Feng, Xuezhi; Liu, Bo; Xiao, Pengfeng; Wang, Peifa

2007-06-01

373

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

PubMed

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

Tran, Du; Yuan, Junsong; Forsyth, David

2014-02-01

374

Spatiotemporal Distribution of Chinavia hilaris (Hemiptera: Pentatomidae) in Corn Farmscapes.  

PubMed

The green stink bug, Chinavia hilaris (Say) (Hemiptera: Pentatomidae), is a pest of cotton in the southeastern United States but little is known concerning its spatiotemporal distribution in corn cropping systems. Therefore, the spatiotemporal distribution of C. hilaris in farmscapes, when corn was adjacent to cotton, peanut, or both, was examined weekly. The spatial patterns of C. hilaris counts were analyzed using Spatial Analysis by Distance Indices methodology. Interpolated maps of C. hilaris density were used to visualize abundance and distribution of C. hilaris in crops in corn-peanut-cotton farmscapes. This stink bug was detected in six of seven corn-cotton farmscapes, four of six corn-peanut farmscapes, and in both corn-peanut-cotton farmscapes. The frequency of C. hilaris in cotton (89.47%) was significantly higher than in peanut (7.02%) or corn (3.51%). This stink bug fed on noncrop hosts that grew in field borders adjacent to crops. The spatial distribution of C. hilaris in crops and the capture of C. hilaris adults and nymphs in pheromone-baited traps near noncrop hosts indicated that these hosts were sources of this stink bug dispersing into crops, primarily cotton. Significant aggregated spatial distributions were detected in cotton on some dates within corn-peanut-cotton farmscapes. Maps of local clustering indices depicted small patches of C. hilaris in cotton or cotton-sorghum at the peanut-cotton interface. Factors affecting the spatiotemporal dynamics of C. hilaris in corn farmscapes are discussed. PMID:25843581

Cottrell, Ted E; Tillman, P Glynn

2015-01-01

375

Spatio-temporal patterns in simple models of marine systems  

NASA Astrophysics Data System (ADS)

Spatio-temporal patterns in marine systems are a result of the interaction of population dynamics with physical transport processes. These physical transport processes can be either diffusion processes in marine sediments or in the water column. We study the dynamics of one population of bacteria and its nutrient in in a simplified model of a marine sediments, taking into account that the considered bacteria possess an active as well as an inactive state, where activation is processed by signal molecules. Furthermore the nutrients are transported actively by bioirrigation and passively by diffusion. It is shown that under certain conditions Turing patterns can occur which yield heterogeneous spatial patterns of the species. The influence of bioirrigation on Turing patterns leads to the emergence of ''hot spots``, i.e. localized regions of enhanced bacterial activity. All obtained patterns fit quite well to observed patterns in laboratory experiments. Spatio-temporal patterns appear in a predator-prey model, used to describe plankton dynamics. These patterns appear due to the simultaneous emergence of Turing patterns and oscillations in the species abundance in the neighborhood of a Turing-Hopf bifurcation. We observe a large variety of different patterns where i) stationary heterogeneous patterns (e.g. hot and cold spots) compete with spatio-temporal patterns ii) slowly moving patterns are embedded in an oscillatory background iii) moving fronts and spiral waves appear.

Feudel, U.; Baurmann, M.; Gross, T.

2009-04-01

376

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

377

Plasticity of recurring spatiotemporal activity patterns in cortical networks  

PubMed Central

How do neurons encode and store information for long periods of time? Recurring patterns of activity have been reported in various cortical structures and were suggested to play a role in information processing and memory. To study the potential role of bursts of action potentials in memory mechanisms, we investigated patterns of spontaneous multi-single-unit activity in dissociated rat cortical cultures in vitro. Spontaneous spikes were recorded from networks of approximately 50 000 neurons and glia cultured on a grid of 60 extracellular substrate-embedded electrodes (multi-electrode arrays). These networks expressed spontaneous culture-wide bursting from approximately one week in vitro. During bursts, a large portion of the active electrodes showed elevated levels of firing. Spatiotemporal activity patterns within spontaneous bursts were clustered using a correlation-based clustering algorithm, and the occurrences of these burst clusters were tracked over several hours. This analysis revealed spatiotemporally diverse bursts occurring in well-defined patterns, which remained stable for several hours. Activity evoked by strong local tetanic stimulation resulted in significant changes in the occurrences of spontaneous bursts belonging to different clusters, indicating that the dynamical flow of information in the neuronal network had been altered. The diversity of spatiotemporal structure and long-term stability of spontaneous bursts together with their plastic nature strongly suggests that such network patterns could be used as codes for information transfer and the expression of memories stored in cortical networks. PMID:17928657

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

2008-01-01

378

Neural computations governing spatiotemporal pooling of visual motion signals in humans  

PubMed Central

The brain estimates visual motion by decoding the responses of populations of neurons. Extracting unbiased motion estimates from early visual cortical neurons is challenging because each neuron contributes an ambiguous (local) representation of the visual environment and inherently variable neural response. To mitigate these sources of noise, the brain can pool across large populations of neurons, pool each neuron’s response over time, or a combination of the two. Recent psychophysical and physiological work points to a flexible motion pooling system which arrives at different computational solutions over time and for different stimuli. Here we ask whether a single, likelihood-based computation can accommodate the flexible nature of spatiotemporal motion pooling in humans. We examined the contribution of different computations to human observers’ performance on two global visual motion discriminations tasks, one requiring the combination of motion directions over time, another requiring their combination in different relative proportions over space and time. Observers’ perceived direction of global motion was accurately predicted by a vector average read-out of direction signals accumulated over time and a maximum likelihood read-out of direction signals combined over space, consistent with the notion of a flexible motion pooling system that uses different computations over space and time. Further simulations of observers’ performance with a population decoding model revealed a more parsimonious solution: flexible spatiotemporal pooling could be accommodated by a single computation that optimally pools motion signals across a population of neurons which accumulate local motion signals on their receptive fields at a fixed rate over time. PMID:21451030

Webb, Ben S.; Ledgeway, Timothy; Rocchi, Francesca

2012-01-01

379

Spatio-temporal variability of the North Sea cod recruitment in relation to temperature and zooplankton.  

PubMed

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

380

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

381

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

382

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

383

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.

384

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

PubMed Central

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

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

2013-01-01

385

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

386

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

387

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

388

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

389

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

390

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

391

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"

392

A new spatio-temporal equalization method based on estimated channel response  

Microsoft Academic Search

This paper proposes a new spatio-temporal equalization method, which simultaneously utilizes an adaptive antenna array and a decision feedback equalizer (DFE). For effective spatio-temporal equalization with less computational cost, how to split equalization functionality into spatial processing, and temporal processing is quite important. One of the answers which we have given is “incoming signals with larger time delays should be

Kazunori Hayashi; Shinsuke Hara

2001-01-01

393

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

394

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

395

The Complex Spatio-Temporal Regulation of the Drosophila Myoblast Attractant Gene duf/kirre  

E-print Network

The Complex Spatio-Temporal Regulation of the Drosophila Myoblast Attractant Gene duf/kirre K. GRaghavan K (2009) The Complex Spatio-Temporal Regulation of the Drosophila Myoblast Attractant Gene duf number of FCs are chosen from a pool of equivalent myoblasts and serve to attract fusion

396

AN ITERATIVE SPATIO-TEMPORAL SPEECH ENHANCEMENT ALGORITHM FOR MICROPHONE ARRAYS  

E-print Network

AN ITERATIVE SPATIO-TEMPORAL SPEECH ENHANCEMENT ALGORITHM FOR MICROPHONE ARRAYS !"#"$ %&'t" "nd +c ABSTRACT We present a new spatio-temporal algorithm for speech enhancement using microphone arrays. Our-dependent parameter settings. Index Terms4 Speech enhancement, acoustic arrays, adaptive arrays, eigenvalues

Douglas, Scott C.

397

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

398

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

E-print Network

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

Foufoula-Georgiou, Efi

399

Spatio-temporal analysis of nucleate pool boiling: identi cation of nucleation sites using  

E-print Network

Spatio-temporal analysis of nucleate pool boiling: identi#12;cation of nucleation sites using non are often limited by the available techniques. These limitations are especially evident in nucleate boiling boiling experiment. Spatio-temporal data for the wall temperature in pool nu- cleate boiling of water

McSharry, Patrick E.

400

Spatio-temporal response of maize yield to edaphic and meteorological conditions in a saline farmland  

Technology Transfer Automated Retrieval System (TEKTRAN)

Spatio-temporal variability of crop production strongly depends on soil heterogeneity, meteorological conditions, and their interaction. Canopy reflectance can be used to describe crop status and yield spatial variability. The objectives of this work were to understand the spatio-temporal variabilit...

401

Spatiotemporal analysis of vocal fold vibrations between children and adults  

PubMed Central

Objectives/Hypothesis Aim of the study is to quantify differences in spatiotemporal features of vibratory motion in typically developing pre-pubertal children and adults with use of high speed digital imaging. Study Design Prospective case-control study. Methods Vocal fold oscillations of 31 children and 35 adults were analysed. Endoscopic high-speed imaging was performed during sustained phonation at typical pitch and loudness. Quantitative technique of Phonovibrogram was used to compute spatiotemporal features. Spatial features are represented by opening and closing angles along the anterior and posterior parts of the vocal folds, as well as by left-right symmetry ratio. Temporal features are represented by the cycle-to-cycle variability of the spatial features. Group differences (adult females, adult males, and children) were statistically investigated. Results Statistical differences were more pronounced in the temporal behavior compared to the spatial behavior. Children demonstrated greater cycle-to-cycle variability in oscillations compared to adults. Most differences between children and adults were found for temporal characteristics along the anterior parts during closing phase. The spatiotemporal features differed more between children and males than between children and females. Both adults and children showed equally high left-right symmetry. Conclusions Results suggest a more unstable phonation in children than in adults yielding increased perturbation in periodicity. Children demonstrated longer phase delay in the anterior/posterior and medio-lateral parts during the opening phase compared to adults. The data presented may provide the bases for differentiating normal vibratory characteristics from the disordered in the pediatric population and eventually assist in aiding the clinical utility of high speed imaging. PMID:22965771

Döllinger, Michael; Dubrovskiy, Denis; Patel, Rita

2012-01-01

402

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

403

Refined estimate of China's CO2 emissions in spatiotemporal distributions  

NASA Astrophysics Data System (ADS)

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

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

2013-11-01

404

The Spatiotemporal Land use/cover Change of Adana City  

NASA Astrophysics Data System (ADS)

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

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

2013-10-01

405

Spatiotemporal Dynamics of Word Processing in the Human Brain  

PubMed Central

We examined the spatiotemporal dynamics of word processing by recording the electrocorticogram (ECoG) from the lateral frontotemporal cortex of neurosurgical patients chronically implanted with subdural electrode grids. Subjects engaged in a target detection task where proper names served as infrequent targets embedded in a stream of task-irrelevant verbs and nonwords. Verbs described actions related to the hand (e.g, throw) or mouth (e.g., blow), while unintelligible nonwords were sounds which matched the verbs in duration, intensity, temporal modulation, and power spectrum. Complex oscillatory dynamics were observed in the delta, theta, alpha, beta, low, and high gamma (HG) bands in response to presentation of all stimulus types. HG activity (80–200?Hz) in the ECoG tracked the spatiotemporal dynamics of word processing and identified a network of cortical structures involved in early word processing. HG was used to determine the relative onset, peak, and offset times of local cortical activation during word processing. Listening to verbs compared to nonwords sequentially activates first the