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1

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

E-print Network

Bayesian Modeling of the Yeast SH3 Domain Interactome Predicts Spatiotemporal Dynamics of America Abstract SH3 domains are peptide recognition modules that mediate the assembly of diverse of the SH3 domain family in the budding yeast, Saccharomyces cerevisiae. Although most of the SH3 domains

Gerstein, Mark

2

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

3

Integrated Prediction of the Helical Membrane Protein Interactome in Yeast  

E-print Network

boosting21 and decision tree- based methods.22,23 In addition to protein inter- action, predictions, such as subcellular locali- zation,24 protein function,25,26 and genetic inter- action.27 The membrane protein

Gerstein, Mark

4

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

PubMed Central

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

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

2014-01-01

5

Severe Hail Prediction within a Spatiotemporal Relational Data Mining Framework  

E-print Network

and Prediction of Storms, Norman, Oklahoma Email: djgagne@ou.edu Abstract--Severe hail, or spherical ice forecasts of severe hail rely on detection of hail in existing storms with radar-based methods. Predictions by incorporating output from an ensemble of storm scale numerical weather prediction models into a spatiotemporal

McGovern, Amy

6

Spatio-temporal prediction for West African monsoon Anestis Antoniadisa  

E-print Network

Spatio-temporal prediction for West African monsoon Anestis Antoniadisa , Céline Helberta in Western Africa : West African Monsoon. We are particularly interested in studying the influence of sea-temporal modeling, filtering, multivariate penalized regression 1. Introduction West African monsoon is the major

7

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

E-print Network

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

Jaillet, Patrick

8

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.

9

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

10

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.

11

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

E-print Network

Predicting 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 of disturbances to propagate across the earth's surface, such as a wildland fire burning across a landscape. We

Stambaugh, Michael C

12

Modular chemical mechanism predicts spatiotemporal dynamics of initiation in the complex network  

E-print Network

Modular chemical mechanism predicts spatiotemporal dynamics of initiation in the complex network clotting in the complex network of hemostasis. Microfluidics was used to create in vitro environments that expose both the complex network and the model system to surfaces patterned with patches presenting

Ismagilov, Rustem F.

13

On spatiotemporal series analysis and its application to predict the regional short term climate process  

NASA Astrophysics Data System (ADS)

Based on the theory of reconstructing state space, a technique for spatiotemporal series prediction is presented. By means of this technique and NCEP/NCAR data of the monthly mean geopotential height anomaly of the 500-hPa isobaric surface in the Northern Hemisphere, a regional prediction experiment is also carried out. If using the correlation coefficient R between the observed field and the prediction field to measure the prediction accuracy, the averaged R given by 48 prediction samples reaches 21%, which corresponds to the current prediction level for the short range climate process.

Wang, Geli; Yang, Peicai; Lü, Daren

2004-04-01

14

Complementing the Eukaryotic Protein Interactome  

PubMed Central

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

Pesch, Robert; Zimmer, Ralf

2013-01-01

15

Learned spatiotemporal sequence recognition and prediction in primary visual cortex  

PubMed Central

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

Gavornik, Jeffrey P.; Bear, Mark F.

2014-01-01

16

Learned spatiotemporal sequence recognition and prediction in primary visual cortex.  

PubMed

Learning to recognize and predict temporal sequences is fundamental to sensory perception and is impaired in several neuropsychiatric disorders, but little is known about where and how this occurs in the brain. We discovered that repeated presentations of a visual sequence over a course of days resulted in evoked response potentiation in mouse V1 that was highly specific for stimulus order and timing. Notably, after V1 was trained to recognize a sequence, cortical activity regenerated the full sequence even when individual stimulus elements were omitted. Our results advance the understanding of how the brain makes 'intelligent guesses' on the basis of limited information to form visual percepts and suggest that it is possible to study the mechanistic basis of this high-level cognitive ability by studying low-level sensory systems. PMID:24657967

Gavornik, Jeffrey P; Bear, Mark F

2014-05-01

17

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

18

Spatiotemporal activity patterns of rat cortical neurons predict responses in a conditioned task  

PubMed Central

Precise and repeated spike-train timings within and across neurons define spatiotemporal patterns of activity. Although the existence of these patterns in the brain is well established in several species, there has been no direct evidence of their influence on behavioral output. To address this question, up to 15 neurons were recorded simultaneously in the auditory cortex of freely moving rats while animals waited for acoustic cues in a Go/NoGo task. A total of 235 significant patterns were detected during this interval from an analysis of 13 hr of recording involving over 1 million spikes. Of particular interest were 129 (55%) patterns that were significantly associated with the type of response the animal made later, independent of whether the response was that prompted by the cue because the response occurred later and the cue was chosen randomly. Of these behavior-predicting patterns, half (59/129) were associated with an enhanced tendency to go in response to the stimulus, and for 11 patterns of this subset, trials including the pattern were followed by significantly faster reaction time than those lacking the pattern. The remaining behavior-predicting patterns were associated with an enhanced NoGo tendency. Overall mean discharge rates did not vary across trials. Hence, these data demonstrate that particular spatiotemporal patterns predict future behavioral responses. Such presignal activity could form templates for extracting specific sensory information, motor programs prespecifying preference for a particular act, and/or some intermediate, associative brain process. PMID:9927701

Villa, Alessandro E. P.; Tetko, Igor V.; Hyland, Brian; Najem, Abdellatif

1999-01-01

19

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

20

Electron Transfer Interactome of Cytochrome c  

PubMed Central

Lying at the heart of many vital cellular processes such as photosynthesis and respiration, biological electron transfer (ET) is mediated by transient interactions among proteins that recognize multiple binding partners. Accurate description of the ET complexes – necessary for a comprehensive understanding of the cellular signaling and metabolism – is compounded by their short lifetimes and pronounced binding promiscuity. Here, we used a computational approach relying solely on the steric properties of the individual proteins to predict the ET properties of protein complexes constituting the functional interactome of the eukaryotic cytochrome c (Cc). Cc is a small, soluble, highly-conserved electron carrier protein that coordinates the electron flow among different redox partners. In eukaryotes, Cc is a key component of the mitochondrial respiratory chain, where it shuttles electrons between its reductase and oxidase, and an essential electron donor or acceptor in a number of other redox systems. Starting from the structures of individual proteins, we performed extensive conformational sampling of the ET-competent binding geometries, which allowed mapping out functional epitopes in the Cc complexes, estimating the upper limit of the ET rate in a given system, assessing ET properties of different binding stoichiometries, and gauging the effect of domain mobility on the intermolecular ET. The resulting picture of the Cc interactome 1) reveals that most ET-competent binding geometries are located in electrostatically favorable regions, 2) indicates that the ET can take place from more than one protein-protein orientation, and 3) suggests that protein dynamics within redox complexes, and not the electron tunneling event itself, is the rate-limiting step in the intermolecular ET. Further, we show that the functional epitope size correlates with the extent of dynamics in the Cc complexes and thus can be used as a diagnostic tool for protein mobility. PMID:23236271

Volkov, Alexander N.; van Nuland, Nico A. J.

2012-01-01

21

The HTLV-1 Tax interactome  

PubMed Central

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

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

2008-01-01

22

Network Organization of the Huntingtin Proteomic Interactome in Mammalian Brain  

PubMed Central

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

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

2012-01-01

23

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

PubMed

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

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

2013-01-01

24

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

25

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

26

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

27

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

28

Spatiotemporal scale limits and roles of biogeochemical cycles in climate predictions  

NASA Astrophysics Data System (ADS)

There is much confidence in the global temperature change and its attribution to human activities. Global climate models have attained unprecedented complexity in representing the climate system and its response to external forcings. However, climate prediction remains a serious challenge and carries large uncertainty, particularly when the scale of interest becomes small. With the increasing interest in regional impact studies for decision-making, one of the urgent tasks is to make a systematic, quantitative evaluation of the expected skill of climate models over a range of spatiotemporal scales. The first part of this dissertation was devoted to this task, with focus on the predictive skill in the linear trend of surface air temperature. By evaluating the hindcasts for the last 120 year period in the form of deterministic and probabilistic predictions, it was found that the hindcasts can reproduce broad-scale changes in the surface air temperature, showing reliable skill at spatial scales larger than or equal to a few thousand kilometers (30° x 30°) and at temporal scales of 30 years or longer. However, their skill remains limited at smaller spatiotemporal scales, where we saw no significant improvement over climatology or a random guess. Over longer temporal scales, the feedbacks from the carbon cycle to atmospheric CO2 concentration become important. Therefore the rest of the dissertation attempts to find key processes in the climate-carbon cycle feedback using one of the leading land-climate models, the National Center for Atmospheric Research Community Land Model. Evaluation of site-level simulations using field observations from the Amazon forest revealed that the current formulation for drought-related mortality, which lacks the ecophysiological link between short- and long-term drought stress, prevent the model from simulating realistic forest response. Global simulations showed that such dynamics of vegetation strongly influences the control of the nitrogen cycle on vegetation productivity, which then alters the sensitivity of the terrestrial biosphere to surface air temperature. This implies that if the state of the terrestrial biosphere is inconsistent with the simulated climate, either biased or prescribed, then its feedback to anthropogenic forcing could be also inconsistent.

Sakaguchi, Koichi

29

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

PubMed

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

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

2014-02-18

30

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

31

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

32

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

33

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

34

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

35

Modelling the Yeast Interactome Vuk Janjic1  

E-print Network

Modelling the Yeast Interactome Vuk Janjic´1 , Roded Sharan2 & Natasa Przulj1 1 Department of any empirical observation regarding those networks. Here, we perform a comprehensive analysis of yeast complexity (human and yeast); (3) clear topological difference is present between PPI networks

Shamir, Ron

36

Learning Sets of Sub-Models for Spatio-Temporal Prediction  

E-print Network

a network of CCTV cameras. 1 Introduction Events over time may be described using a spatio-temporal data of CCTV cameras. Both of these approaches benefit from breaking the solution down into its component parts-model for each of the outcomes in the game. In the CCTV scenario this means learning the actions of single

Fernandez, Thomas

37

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

38

Cost-effective strategies for completing the interactome  

E-print Network

as mapping a complete genome sequence. In the case of the human and model genome projects, large, and humans5,6. Mapping a complete gene or protein network evokes similar challenges and considerations in Drosophila. RESULTS Interactome mapping: problem definition In contrast to a genome, the interactome has been

Cai, Long

39

A JOINT SPATIO-TEMPORAL FILTERING APPROACH TO EFFICIENT PREDICTION IN VIDEO COMPRESSION  

E-print Network

codecs exploit temporal and spatial redundan- cies in the format of inter and intra predictions exploiting spatial and temporal re- dundancies includes [5], where it predicts a block as a sim- ple linear combination of the inter-frame reference block and the intra predicted block. It largely ignores the variation

California at Santa Barbara, University of

40

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

41

How Perfect Can Protein Interactomes Be?  

NSDL National Science Digital Library

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

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

2009-03-03

42

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

PubMed

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

Randhawa, Vinay; Bagler, Ganesh

2012-10-01

43

Spatial and Spatiotemporal Projection Pursuit Techniques to Predict the Extratropical Transition of Tropical Cyclones  

Microsoft Academic Search

A multistage projection pursuit (PP) approach is applied to the classification of tropical cyclones (TCs) during extratropical transition (ET) using 500-hPa Navy Operational Global Atmospheric Prediction System (NOGAPS) geopotential height analyses. PP algorithms reduce the dimensionality of the high-dimensional data while minimizing the loss of information that discriminates among classes of ET types. In this paper, a prediction system is

Oguz Demirci; J. Scott Tyo; Elizabeth A. Ritchie

2007-01-01

44

Predicting Chronic Fine and Coarse Particulate Exposures Using Spatiotemporal Models for the Northeastern and Midwestern United States  

PubMed Central

Background Chronic epidemiologic studies of particulate matter (PM) are limited by the lack of monitoring data, relying instead on citywide ambient concentrations to estimate exposures. This method ignores within-city spatial gradients and restricts studies to areas with nearby monitoring data. This lack of data is particularly restrictive for fine particles (PM with aerodynamic diameter < 2.5 ?m; PM2.5) and coarse particles (PM with aerodynamic diameter 2.5–10 ?m; PM10–2.5), for which monitoring is limited before 1999. To address these limitations, we developed spatiotemporal models to predict monthly outdoor PM2.5 and PM10–2.5 concentrations for the northeastern and midwestern United States. Methods For PM2.5, we developed models for two periods: 1988–1998 and 1999–2002. Both models included smooth spatial and regression terms of geographic information system-based and meteorologic predictors. To compensate for sparse monitoring data, the pre-1999 model also included predicted PM10 (PM with aerodynamic diameter < 10 ?m) and extinction coefficients (km?1). PM10–2.5 levels were estimated as the difference in monthly predicted PM10 and PM2.5, with predicted PM10 from our previously developed PM10 model. Results Predictive performance for PM2.5 was strong (cross-validation R2 = 0.77 and 0.69 for post-1999 and pre-1999 PM2.5 models, respectively) with high precision (2.2 and 2.7 ?g/m3, respectively). Models performed well irrespective of population density and season. Predictive performance for PM10–2.5 was weaker (cross-validation R2 = 0.39) with lower precision (5.5 ?g/m3). PM10–2.5 levels exhibited greater local spatial variability than PM10 or PM2.5, suggesting that PM2.5 measurements at ambient monitoring sites are more representative for surrounding populations than for PM10 and especially PM10–2.5. Conclusions We provide semiempirical models to predict spatially and temporally resolved long-term average outdoor concentrations of PM2.5 and PM10–2.5 for estimating exposures of populations living in the northeastern and midwestern United States. PMID:19440489

Yanosky, Jeff D.; Paciorek, Christopher J.; Suh, Helen H.

2009-01-01

45

Integration, visualization and analysis of human interactome.  

PubMed

Data integration and visualization are crucial to obtain meaningful hypotheses from the diversity of 'omics' fields and the large volume of heterogeneous and distributed data sets. In this review we focus on network analysis as a key technique to integrate, visualize and extrapolate relevant information from diverse data. We first describe challenges in integrating different types of data and then focus on systematically exploring network properties to gain insight into network function. We also describe the relationship between network structures and function of elements that form it. Next, we highlight the role of the interactome in connecting data derived from different experiments, and we stress the importance of network analysis to recognize interaction context-specific features. Finally, we present an example integration to demonstrate the value of the network approach in cancer research, and highlight the importance of dynamic data in the specific context of signaling pathways. PMID:24491561

Pastrello, Chiara; Pasini, Elisa; Kotlyar, Max; Otasek, David; Wong, Serene; Sangrar, Waheed; Rahmati, Sara; Jurisica, Igor

2014-03-21

46

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

47

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

E-print Network

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

Fernandez, Thomas

48

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

49

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

50

The topology of the growing human interactome data.  

PubMed

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

Janji?, Vuk; Pržulj, Nataša

2014-01-01

51

Edinburgh Research Explorer Expression of DISC1-Interactome Members Correlates with  

E-print Network

of DISC1-Interactome Members Correlates with Cognitive Phenotypes Related to Schizophrenia' PLoS One, vol. 2014 #12;Expression of DISC1-Interactome Members Correlates with Cognitive Phenotypes RelatedEdinburgh Research Explorer Expression of DISC1-Interactome Members Correlates with Cognitive

Millar, Andrew J.

52

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

PubMed

The ability to predict amphibian breeding across landscapes is important for informing land management decisions and helping biologists better understand and remediate factors contributing to declines in amphibian populations. We built geospatial models of likely breeding habitats for each of four amphibian species that breed in Yellowstone National Park (YNP). We used field data collected in 2000-2002 from 497 sites among 16 basins and predictor variables from geospatial models produced from remotely sensed data (e.g., digital elevation model, complex topographic index, landform data, wetland probability, and vegetative cover). Except for 31 sites in one basin that were surveyed in both 2000 and 2002, all sites were surveyed once. We used polytomous regression to build statistical models for each species of amphibian from (1) field survey site data only, (2) field data combined with data from geospatial models, and (3) data from geospatial models only. Based on measures of receiver operating characteristic (ROC) scores, models of the second type best explained likely breeding habitat because they contained the most information (ROC values ranged from 0.70 to 0.88). However, models of the third type could be applied to the entire YNP landscape and produced maps that could be verified with reserve field data. Accuracy rates for models built for single years were highly variable, ranging from 0.30 to 0.78. Accuracy rates for models built with data combined from multiple years were higher and less variable, ranging from 0.60 to 0.80. Combining results from the geospatial multiyear models yielded maps of "core" breeding areas (areas with high probability values for all three years) surrounded by areas that scored high for only one or two years, providing an estimate of variability among years. Such information can highlight landscape options for amphibian conservation. For example, our models identify alternative areas that could be protected for each species, including 6828-10 764 ha for tiger salamanders, 971-3017 ha for western toads, 4732-16 696 ha for boreal chorus frogs, and 4940-19 690 ha for Columbia spotted frogs. PMID:22073642

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

2011-10-01

53

Evidence for network evolution in an Arabidopsis interactome map.  

PubMed

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 plant Arabidopsis thaliana containing about 6200 highly reliable interactions between about 2700 proteins. A global organization of plant biological processes emerges from community analyses of the resulting network, together with large numbers of novel hypothetical functional links between proteins and pathways. We observe a dynamic rewiring of interactions following gene duplication events, providing evidence for a model of evolution acting upon interactome networks. This and future plant interactome maps should facilitate systems approaches to better understand plant biology and improve crops. PMID:21798944

2011-07-29

54

Hierarchical modularity and the evolution of genetic interactomes across species.  

PubMed

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

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

2012-06-01

55

A proteome-scale map of the human interactome network.  

PubMed

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

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

2014-11-20

56

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

57

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

58

Dynamic Zebrafish Interactome Reveals Transcriptional Mechanisms of Dioxin Toxicity  

PubMed Central

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

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

2010-01-01

59

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

60

Improved Microarray-Based Decision Support with Graph Encoded Interactome Data  

PubMed Central

In the past, microarray studies have been criticized due to noise and the limited overlap between gene signatures. Prior biological knowledge should therefore be incorporated as side information in models based on gene expression data to improve the accuracy of diagnosis and prognosis in cancer. As prior knowledge, we investigated interaction and pathway information from the human interactome on different aspects of biological systems. By exploiting the properties of kernel methods, relations between genes with similar functions but active in alternative pathways could be incorporated in a support vector machine classifier based on spectral graph theory. Using 10 microarray data sets, we first reduced the number of data sources relevant for multiple cancer types and outcomes. Three sources on metabolic pathway information (KEGG), protein-protein interactions (OPHID) and miRNA-gene targeting (microRNA.org) outperformed the other sources with regard to the considered class of models. Both fixed and adaptive approaches were subsequently considered to combine the three corresponding classifiers. Averaging the predictions of these classifiers performed best and was significantly better than the model based on microarray data only. These results were confirmed on 6 validation microarray sets, with a significantly improved performance in 4 of them. Integrating interactome data thus improves classification of cancer outcome for the investigated microarray technologies and cancer types. Moreover, this strategy can be incorporated in any kernel method or non-linear version of a non-kernel method. PMID:20419106

Daemen, Anneleen; Signoretto, Marco; Gevaert, Olivier; Suykens, Johan A. K.; De Moor, Bart

2010-01-01

61

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

62

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

63

Identification of Human Disease Genes from Interactome Network Using Graphlet Interaction  

PubMed Central

Identifying genes related to human diseases, such as cancer and cardiovascular disease, etc., is an important task in biomedical research because of its applications in disease diagnosis and treatment. Interactome networks, especially protein-protein interaction networks, had been used to disease genes identification based on the hypothesis that strong candidate genes tend to closely relate to each other in some kinds of measure on the network. We proposed a new measure to analyze the relationship between network nodes which was called graphlet interaction. The graphlet interaction contained 28 different isomers. The results showed that the numbers of the graphlet interaction isomers between disease genes in interactome networks were significantly larger than random picked genes, while graphlet signatures were not. Then, we designed a new type of score, based on the network properties, to identify disease genes using graphlet interaction. The genes with higher scores were more likely to be disease genes, and all candidate genes were ranked according to their scores. Then the approach was evaluated by leave-one-out cross-validation. The precision of the current approach achieved 90% at about 10% recall, which was apparently higher than the previous three predominant algorithms, random walk, Endeavour and neighborhood based method. Finally, the approach was applied to predict new disease genes related to 4 common diseases, most of which were identified by other independent experimental researches. In conclusion, we demonstrate that the graphlet interaction is an effective tool to analyze the network properties of disease genes, and the scores calculated by graphlet interaction is more precise in identifying disease genes. PMID:24465923

Yang, Lun; Wei, Dong-Qing; Qi, Ying-Xin; Jiang, Zong-Lai

2014-01-01

64

A Human XPC Protein Interactome--A Resource  

PubMed Central

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

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

2014-01-01

65

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

66

A Map of the Interactome Network of the Metazoan C. elegans  

Microsoft Academic Search

To initiate studies on how protein-protein interaction (or ``interactome'') networks relate to multicellular functions, we have mapped a large fraction of the Caenorhabditis elegans interactome network. Starting with a subset of metazoan-specific proteins, more than 4000 interactions were identified from high-throughput, yeast two-hybrid (HT=Y2H) screens. Independent coaffinity purification assays experimentally validated the overall quality of this Y2H data set. Together

Siming Li; Christopher M. Armstrong; Nicolas Bertin; Hui Ge; Stuart Milstein; Mike Boxem; Pierre-Olivier Vidalain; Jing-Dong J. Han; Alban Chesneau; Tong Hao; Debra S. Goldberg; Ning Li; Monica Martinez; Jean-François Rual; Philippe Lamesch; Lai Xu; Muneesh Tewari; Sharyl L. Wong; Lan V. Zhang; Gabriel F. Berriz; Laurent Jacotot; Philippe Vaglio; Jérôme Reboul; Tomoko Hirozane-Kishikawa; Qianru Li; Harrison W. Gabel; Ahmed Elewa; Bridget Baumgartner; Debra J. Rose; Haiyuan Yu; Stephanie Bosak; Reynaldo Sequerra; Andrew Fraser; Susan E. Mango; William M. Saxton; Susan Strome; Sander van den Heuvel; Fabio Piano; Jean Vandenhaute; Claude Sardet; Mark Gerstein; Lynn Doucette-Stamm; Kristin C. Gunsalus; J. Wade Harper; Michael E. Cusick; Frederick P. Roth; David E. Hill; Marc Vidal

2004-01-01

67

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, Fabio; Murugesan, Gavuthami; Hoxhaj, Gerta; Toth, Rachel; MacKintosh, Carol

2014-01-01

68

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

69

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

70

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

71

M-Finder: Uncovering functionally associated proteins from interactome data integrated with GO annotations  

PubMed Central

Background Protein-protein interactions (PPIs) play a key role in understanding the mechanisms of cellular processes. The availability of interactome data has catalyzed the development of computational approaches to elucidate functional behaviors of proteins on a system level. Gene Ontology (GO) and its annotations are a significant resource for functional characterization of proteins. Because of wide coverage, GO data have often been adopted as a benchmark for protein function prediction on the genomic scale. Results We propose a computational approach, called M-Finder, for functional association pattern mining. This method employs semantic analytics to integrate the genome-wide PPIs with GO data. We also introduce an interactive web application tool that visualizes a functional association network linked to a protein specified by a user. The proposed approach comprises two major components. First, the PPIs that have been generated by high-throughput methods are weighted in terms of their functional consistency using GO and its annotations. We assess two advanced semantic similarity metrics which quantify the functional association level of each interacting protein pair. We demonstrate that these measures outperform the other existing methods by evaluating their agreement to other biological features, such as sequence similarity, the presence of common Pfam domains, and core PPIs. Second, the information flow-based algorithm is employed to discover a set of proteins functionally associated with the protein in a query and their links efficiently. This algorithm reconstructs a functional association network of the query protein. The output network size can be flexibly determined by parameters. Conclusions M-Finder provides a useful framework to investigate functional association patterns with any protein. This software will also allow users to perform further systematic analysis of a set of proteins for any specific function. It is available online at http://bionet.ecs.baylor.edu/mfinder PMID:24565382

2013-01-01

72

High-quality binary protein interaction map of the yeast interactome network.  

PubMed

Current yeast interactome network maps contain several hundred molecular complexes with limited and somewhat controversial representation of direct binary interactions. We carried out a comparative quality assessment of current yeast interactome data sets, demonstrating that high-throughput yeast two-hybrid (Y2H) screening provides high-quality binary interaction information. Because a large fraction of the yeast binary interactome remains to be mapped, we developed an empirically controlled mapping framework to produce a "second-generation" high-quality, high-throughput Y2H data set covering approximately 20% of all yeast binary interactions. Both Y2H and affinity purification followed by mass spectrometry (AP/MS) data are of equally high quality but of a fundamentally different and complementary nature, resulting in networks with different topological and biological properties. Compared to co-complex interactome models, this binary map is enriched for transient signaling interactions and intercomplex connections with a highly significant clustering between essential proteins. Rather than correlating with essentiality, protein connectivity correlates with genetic pleiotropy. PMID:18719252

Yu, Haiyuan; Braun, Pascal; Yildirim, Muhammed A; Lemmens, Irma; Venkatesan, Kavitha; Sahalie, Julie; Hirozane-Kishikawa, Tomoko; Gebreab, Fana; Li, Na; Simonis, Nicolas; Hao, Tong; Rual, Jean-François; Dricot, Amélie; Vazquez, Alexei; Murray, Ryan R; Simon, Christophe; Tardivo, Leah; Tam, Stanley; Svrzikapa, Nenad; Fan, Changyu; de Smet, Anne-Sophie; Motyl, Adriana; Hudson, Michael E; Park, Juyong; Xin, Xiaofeng; Cusick, Michael E; Moore, Troy; Boone, Charlie; Snyder, Michael; Roth, Frederick P; Barabási, Albert-László; Tavernier, Jan; Hill, David E; Vidal, Marc

2008-10-01

73

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

PubMed

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

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

2013-05-21

74

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

75

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

76

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

77

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

PubMed Central

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

2014-01-01

78

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

PubMed Central

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

Martins-de-Souza, Daniel

2014-01-01

79

Resolving the structure of interactomes with hierarchical agglomerative clustering  

Microsoft Academic Search

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

Yongjin Park; Joel S Bader

2011-01-01

80

Spatiotemporal multipartite entanglement  

NASA Astrophysics Data System (ADS)

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 (??,t) and (??',t'), with ?? 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

2011-05-01

81

Interactive Spatiotemporal Reasoning  

Microsoft Academic Search

\\u000a Spatiotemporal reasoning involves pattern recognition in space and time. It is a complex process that has been dominated by\\u000a manual analytics. In this chapter, we explore the new method that combines computer vision, multi-physics simulation and human-computer\\u000a interaction. The objective is to bridge the gap among the three with visual transformation algorithms for mapping the data\\u000a from an abstract space

Yang Cai; Richard Stumpf; Michelle Tomlinson; Timothy Wynne; Sai Ho Chung; Xavier Boutonnier

82

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

83

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

84

A Y2H-seq approach defines the human protein methyltransferase interactome.  

PubMed

To accelerate high-density interactome mapping, we developed a yeast two-hybrid interaction screening approach involving short-read second-generation sequencing (Y2H-seq) with improved sensitivity and a quantitative scoring readout allowing rapid interaction validation. We applied Y2H-seq to investigate enzymes involved in protein methylation, a largely unexplored post-translational modification. The reported network of 523 interactions involving 22 methyltransferases or demethylases is comprehensively annotated and validated through coimmunoprecipitation experiments and defines previously undiscovered cellular roles of nonhistone protein methylation. PMID:23455924

Weimann, Mareike; Grossmann, Arndt; Woodsmith, Jonathan; Özkan, Ziya; Birth, Petra; Meierhofer, David; Benlasfer, Nouhad; Valovka, Taras; Timmermann, Bernd; Wanker, Erich E; Sauer, Sascha; Stelzl, Ulrich

2013-04-01

85

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

PubMed Central

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

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

2014-01-01

86

Embryonic stem cell interactomics: the beginning of a long road to biological function.  

PubMed

Embryonic stem cells (ESCs) are capable of unlimited self-renewal while maintaining pluripotency. They are of great interest in regenerative medicine due to their ability to differentiate into all cell types of the three embryonic germ layers. Recently, induced pluripotent stem cells (iPSCs) have shown similarities to ESCs and thus promise great therapeutic potential in regenerative medicine. Despite progress in stem cell biology, our understanding of the exact mechanisms by which pluripotency and self-renewal are established and maintained is largely unknown. A better understanding of these processes may lead to discovery of alternative ways for reprogramming, differentiation and more reliable applications of stem cells in therapies. It has become evident that proteins generally function as members of large complexes that are part of a more complex network. Therefore, the identification of protein-protein interactions (PPI) is an efficient strategy for understanding protein function and regulation. Systematic genome-wide and pathway-specific PPI analysis of ESCs has generated a network of ESC proteins, including major transcription factors. These PPI networks of ESCs may contribute to a mechanistic understanding of self-renewal and pluripotency. In this review we describe different experimental approaches for the identification of PPIs along with various databases. We discuss biological findings and technical challenges encountered with interactome studies of pluripotent stem cells, and provide insight into how interactomics is likely to develop. PMID:22847281

Yousefi, Maram; Hajihoseini, Vahid; Jung, Woojin; Hosseinpour, Batol; Rassouli, Hassan; Lee, Bonghee; Baharvand, Hossein; Lee, KiYoung; Salekdeh, Ghasem Hosseini

2012-12-01

87

Grouping annotations on the subcellular layered interactome demonstrates enhanced autophagy activity in a recurrent experimental autoimmune uveitis T cell line.  

PubMed

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

Jia, Xiuzhi; Li, Jingbo; Shi, Dejing; Zhao, Yu; Dong, Yucui; Ju, Huanyu; Yang, Jinfeng; Sun, Jianhua; Li, Xia; Ren, Huan

2014-01-01

88

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

PubMed Central

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

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

2014-01-01

89

Spatio-temporal properties of multipartite entanglement  

NASA Astrophysics Data System (ADS)

Quantum multipartite entanglement is a striking phenomenon predicted by quantum mechanics when several parts of a physical system share the same quantum state that cannot be factorized into the states of individual subsystems. The Gaussian quantum states are usually characterized by the covariance matrix of the quadrature components. A powerful formalism for treating the Gaussian states is that of the symplectic eigenvalues. In particular, a quantitative measure of multipartite entanglement is the so-called logarithmic negativity, related to the symplectic eigenvalues of the partially transposed covariance matrix. Considering only global variances of the field quadratures one completely neglects the spatiotemporal properties of the electromagnetic field. We propose, following the spirit of quantum imaging, to generalize the theory of multipartite entanglement for the continuous variable Gaussian states by considering the local correlation matrix at two different spatiotemporal points [see manuscript for characters] and [see manuscript for characters] with [see manuscript for characters] being the transverse coordinate. For stationary and homogeneous systems one can also introduce the spatiotemporal Fourier components of the correlation matrix. The formalism of the global symplectic eigenvalues can be straightforwardly generalized to the frequency-dependent symplectic eigenvalues. This generalized theory allows, in particular, to introduce the characteristic spatial area and time of the multipartite entanglement, which in general depend on the number of "parties" in the system. As an example we consider multipartite entanglement in spontaneous parametric down-conversion with spatially-structured pump. We investigate spatial properties of such entanglement and calculate its characteristic spatial length.

Patera, Giuseppe; Kolobov, Mikhail I.

2010-06-01

90

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

91

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

PubMed Central

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. PMID:24039539

Liang, Dong; Kumar, Naresh

2013-01-01

92

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

93

Contrast Adaptation Implies Two Spatiotemporal Channels but Three Adapting Processes  

ERIC Educational Resources Information Center

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

Langley, Keith; Bex, Peter J.

2007-01-01

94

Modelling spatio-temporal variation in black smoke pollutant concentrations  

E-print Network

encompassing air pollution, socio-economic and meteorological data. Location Newcastle-upon-Tyne, 1961-1992 AimModelling spatio-temporal variation in black smoke pollutant concentrations T.R. Fanshawe, P To predict black smoke level for any location in the study region, for any time in the study period

Diggle, Peter J.

95

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

96

Emergence of patterns in driven and in autonomous spatiotemporal systems  

E-print Network

The relationship between a driven extended system and an autonomous spatiotemporal system is investigated in the context of coupled map lattice models. Specifically, a locally coupled map lattice subjected to an external drive is compared to a coupled map system with similar local couplings plus a global interaction. It is shown that, under some conditions, the emergent patterns in both systems are analogous. Based on the knowledge of the dynamical responses of the driven lattice, we present a method that allows the prediction of parameter values for the emergence of ordered spatiotemporal patterns in a class of coupled map systems having local coupling and general forms of global interactions.

M. G. Cosenza; M. Pineda; A. Parravano

2002-11-22

97

Spatiotemporal correlations of aftershock sequences  

E-print Network

Aftershock sequences are of particular interest in seismic research since they may condition seismic activity in a given region over long time spans. While they are typically identified with periods of enhanced seismic activity after a large earthquake as characterized by the Omori law, our knowledge of the spatiotemporal correlations between events in an aftershock sequence is limited. Here, we study the spatiotemporal correlations of two aftershock sequences form California (Parkfield and Hector Mine) using the recently introduced concept of "recurrent" events. We find that both sequences have very similar properties and that most of them are captured by the space-time epidemic-type aftershock sequence (ETAS) model if one takes into account catalog incompleteness. However, the stochastic model does not capture the spatiotemporal correlations leading to the observed structure of seismicity on small spatial scales.

Tiago P. Peixoto; Katharina Doblhoff-Dier; Jörn Davidsen

2010-04-12

98

The bovine milk proteome: cherishing, nourishing and fostering molecular complexity. An interactomics and functional overview.  

PubMed

Bovine milk represents an essential source of nutrients for lactating calves and a key raw material for human food preparations. A wealth of data are present in the literature dealing with massive proteomic analyses of milk fractions and independent targeted studies on specific groups of proteins, such as caseins, globulins, hormones and cytokines. In this study, we merged data from previous investigations to compile an exhaustive list of 573 non-redundant annotated protein entries. This inventory was exploited for integrated in silico studies, including functional GO term enrichment (FatiGO/Babelomics), multiple pathway and network analyses. As expected, most of the milk proteins were grouped under pathways/networks/ontologies referring to nutrient transport, lipid metabolism and objectification of the immune system response. Notably enough, another functional family was observed as the most statistically significant one, which included proteins involved in the induction of cellular proliferation processes as well as in anatomical and haematological system development. Although the latter function for bovine milk proteins has long been postulated, studies reported so far mainly focused on a handful of molecules and missed the whole overview resulting from an integrated holistic analysis. A preliminary map of the bovine milk proteins interactome was also built up, which will be refined in future as result of the widespread use of quantitative methods in protein interaction studies and consequent reduction of false-positives within associated databases. PMID:20877905

D'Alessandro, Angelo; Zolla, Lello; Scaloni, Andrea

2011-03-01

99

Genome-wide bimolecular fluorescence complementation analysis of SUMO interactome in yeast  

PubMed Central

The definition of protein–protein interactions (PPIs) in the natural cellular context is essential for properly understanding various biological processes. So far, however, most large-scale PPI analyses have not been performed in the natural cellular context. Here, we describe the construction of a Saccharomyces cerevisiae fusion library in which each endogenous gene is C-terminally tagged with the N-terminal fragment of Venus (VN) for a genome-wide bimolecular fluorescence complementation assay, a powerful technique for identifying PPIs in living cells. We illustrate the utility of the VN fusion library by systematically analyzing the interactome of the small ubiquitin-related modifier (SUMO) and provide previously unavailable information on the subcellular localization, types, and protease dependence of SUMO interactions. Our data set is highly complementary to the existing data sets and represents a useful resource for expanding the understanding of the physiological roles of SUMO. In addition, the VN fusion library provides a useful research tool that makes it feasible to systematically analyze PPIs in the natural cellular context. PMID:23403034

Sung, Min-Kyung; Lim, Gyubum; Yi, Dae-Gwan; Chang, Yeon Ji; Yang, Eun Bin; Lee, KiYoung; Huh, Won-Ki

2013-01-01

100

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

PubMed

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

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

2012-06-01

101

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

102

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

PubMed

Genome-wide association studies have identified a number of genes associated with human body weight. While some of these genes are large fields within obesity research, such as MC4R, POMC, FTO and BDNF, the majority do not have a clearly defined functional role explaining why they may affect body weight. Here, we searched biological databases and discovered 33 additional genes associated with human obesity (CADM2, GIPR, GPCR5B, LRP1B, NEGR1, NRXN3, SH2B1, FANCL, GNPDA2, HMGCR, MAP2K5, NUDT3, PRKD1, QPCTL, TNNI3K, MTCH2, DNAJC27, SLC39A8, MTIF3, RPL27A, SEC16B, ETV5, HMGA1, TFAP2B, TUB, ZNF608, FAIM2, KCTD15, LINGO2, POC5, PTBP2, TMEM18, TMEM160). We find that the majority have orthologues in distant species, such as D. melanogaster and C. elegans, suggesting that they are important for the biology of most bilateral species. Intriguingly, signalling cascade genes and transcription factors are enriched among these obesity genes, and several of the genes show properties that could be useful for potential drug discovery. In this review, we demonstrate how information from several distant model species, interactomics and signalling pathway analysis represents an important way to better understand the functional diversity of the surprisingly high number of molecules that seem to be important for human obesity. PMID:22618246

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

2012-11-01

103

A synthetic coiled-coil interactome provides heterospecific modules for molecular engineering  

PubMed Central

The versatile coiled-coil protein motif is widely used to induce and control macromolecular interactions in biology and materials science. Yet the types of interaction patterns that can be constructed using known coiled coils are limited. Here we greatly expand the coiled-coil toolkit by measuring the complete pair-wise interactions of 48 synthetic coiled coils and 7 human bZIP coiled coils using peptide microarrays. The resulting 55-member protein ‘interactome’ includes 27 pairs of interacting peptides that preferentially hetero-associate. The 27 pairs can be used in combinations to assemble sets of 3 to 6 proteins that compose networks of varying topologies. Of special interest are heterospecific peptide pairs that participate in mutually orthogonal interactions. Such pairs provide the opportunity to dimerize two separate molecular systems without undesired crosstalk. Solution and structural characterization of two such sets of orthogonal heterodimers provide details of their interaction geometries. The orthogonal pair, along with the many other network motifs discovered in our screen, provide new capabilities for synthetic biology and other applications. PMID:20387835

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

2010-01-01

104

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

105

Spatiotemporal network analysis and visualization  

E-print Network

Mellon University, U.S.A. ABSTRACT Spatiotemporal social network analysis shows relationships among intervals, may be visualized by third-party social network analysis software in the form of standard network analysis, social network analysis, data mining, text mining knowledge discovery, visualization INTRODUCTION

Shamos, Michael I.

106

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

107

Detecting Disease Outbreaks Using Local Spatiotemporal Methods  

PubMed Central

Summary A real-time surveillance method is developed with emphasis on rapid and accurate detection of emerging outbreaks. We develop a model with relatively weak assumptions regarding the latent processes generating the observed data, ensuring a robust prediction of the spatiotemporal incidence surface. Estimation occurs via a local linear fitting combined with day-of-week effects, where spatial smoothing is handled by a novel distance metric that adjusts for population density. Detection of emerging outbreaks is carried out via residual analysis. Both daily residuals and AR model-based de-trended residuals are used for detecting abnormalities in the data given that either a large daily residual or an increasing temporal trend in the residuals signals a potential outbreak, with the threshold for statistical significance determined using a resampling approach. PMID:21418049

Zhao, Yingqi; Zeng, Donglin; Herring, Amy H.; Ising, Amy; Waller, Anna; Richardson, David; Kosorok, Michael R.

2013-01-01

108

PREDICTS  

NASA Technical Reports Server (NTRS)

PREDICTS is a computer program that predicts the frequencies, as functions of time, of signals to be received by a radio science receiver in this case, a special-purpose digital receiver dedicated to analysis of signals received by an antenna in NASA s Deep Space Network (DSN). Unlike other software used in the DSN, PREDICTS does not use interpolation early in the calculations; as a consequence, PREDICTS is more precise and more stable. The precision afforded by the other DSN software is sufficient for telemetry; the greater precision afforded by PREDICTS is needed for radio-science experiments. In addition to frequencies as a function of time, PREDICTS yields the rates of change and interpolation coefficients for the frequencies and the beginning and ending times of reception, transmission, and occultation. PREDICTS is applicable to S-, X-, and Ka-band signals and can accommodate the following link configurations: (1) one-way (spacecraft to ground), (2) two-way (from a ground station to a spacecraft to the same ground station), and (3) three-way (from a ground transmitting station to a spacecraft to a different ground receiving station).

Zhou, Hanying

2007-01-01

109

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

110

The complex G protein-coupled receptor kinase 2 (GRK2) interactome unveils new physiopathological targets  

PubMed Central

GRK2 is a ubiquitous member of the G protein-coupled receptor kinase (GRK) family that appears to play a central, integrative role in signal transduction cascades. GRKs participate together with arrestins in the regulation of G protein-coupled receptors (GPCR), a family of hundreds of membrane proteins of key physiological and pharmacological importance, by triggering receptor desensitization from G proteins and GPCR internalization, and also by helping assemble macromolecular signalosomes in the receptor environment acting as agonist-regulated adaptor scaffolds, thus contributing to signal propagation. In addition, emerging evidence indicates that GRK2 can phosphorylate a growing number of non-GPCR substrates and associate with a variety of proteins related to signal transduction, thus suggesting that this kinase could also have diverse ‘effector’ functions. We discuss herein the increasing complexity of such GRK2 ‘interactome’, with emphasis on the recently reported roles of this kinase in cell migration and cell cycle progression and on the functional impact of the altered GRK2 levels observed in several relevant cardiovascular, inflammatory or tumour pathologies. Deciphering how the different networks of potential GRK2 functional interactions are orchestrated in a stimulus, cell type or context-specific way is critical to unveil the contribution of GRK2 to basic cellular processes, to understand how alterations in GRK2 levels or functionality may participate in the onset or development of several cardiovascular, tumour or inflammatory diseases, and to assess the feasibility of new therapeutic strategies based on the modulation of the activity, levels or specific interactions of GRK2. PMID:20590581

Penela, Petronila; Murga, Cristina; Ribas, Catalina; Lafarga, Vanesa; Mayor, Federico

2010-01-01

111

Spatiotemporal saliency in dynamic scenes.  

PubMed

A spatiotemporal saliency algorithm based on a center-surround framework is proposed. The algorithm is inspired by biological mechanisms of motion-based perceptual grouping and extends a discriminant formulation of center-surround saliency previously proposed for static imagery. Under this formulation, the saliency of a location is equated to the power of a predefined set of features to discriminate between the visual stimuli in a center and a surround window, centered at that location. The features are spatiotemporal video patches and are modeled as dynamic textures, to achieve a principled joint characterization of the spatial and temporal components of saliency. The combination of discriminant center-surround saliency with the modeling power of dynamic textures yields a robust, versatile, and fully unsupervised spatiotemporal saliency algorithm, applicable to scenes with highly dynamic backgrounds and moving cameras. The related problem of background subtraction is treated as the complement of saliency detection, by classifying nonsalient (with respect to appearance and motion dynamics) points in the visual field as background. The algorithm is tested for background subtraction on challenging sequences, and shown to substantially outperform various state-of-the-art techniques. Quantitatively, its average error rate is almost half that of the closest competitor. PMID:19926907

Mahadevan, Vijay; Vasconcelos, Nuno

2010-01-01

112

Spatiotemporal modelling of ecological and evolutionary problems  

E-print Network

Spatiotemporal modelling of ecological and evolutionary problems DSc. dissertation Czárán Tamás MTA;DSc Dissertation:......................................................................................................................145 #12;DSc Dissertation

Czárán, Tamás

113

Formal classification of integrity constraints in spatiotemporal database applications$  

E-print Network

, tem- poral accuracy, thematic accuracy, and logical consistency. Integrity constraints (ICsFormal classification of integrity constraints in spatiotemporal database applications$ Mehrdad model Integrity constraint Spatiotemporal modeling Data quality Spatiotemporal database a b s t r a c

114

Prediction  

Microsoft Academic Search

This chapter first presents a rather personal view of some different aspects of predictability, going in crescendo from simple linear systems to high-dimensional nonlinear systems with stochastic forcing, which exhibit emergent properties such as phase transitions and regime shifts. Then, a detailed correspondence between the phenomenology of earthquakes, financial crashes and epileptic seizures is offered. The presented statistical evidence provides

Didier Sornette; Ivan Osorio

2010-01-01

115

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

116

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

PubMed

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

117

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

PubMed Central

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

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

2014-01-01

118

The eIF3 interactome reveals the translasome, a supercomplex linking protein synthesis and degradation machineries  

PubMed Central

Summary eIF3 promotes translation initiation, but relatively little is known about its full range of activities in the cell. Here, we employed affinity purification and highly sensitive LC-MS/MS to decipher the fission yeast eIF3 interactome, which was found to contain 230 proteins. eIF3 assembles into a large supercomplex, the translasome, which contains elongation factors, tRNA-synthetases, 40S and 60S ribosomal proteins, chaperones, and the proteasome. eIF3 also associates with ribosome biogenesis factors and the importins-? Kap123p and Sal3p. Our genetic data indicated that the binding to both importins-? is essential for cell growth, and photobleaching experiments revealed a critical role for Sal3p in the nuclear import of one of the translasome constituents, the proteasome. Our data reveal the breadth of the eIF3 interactome and suggest that factors involved in translation initiation, ribosome biogenesis, translation elongation, quality control, and transport are physically linked to facilitate efficient protein synthesis. PMID:19818717

Sha, Zhe; Brill, Laurence M.; Cabrera, Rodrigo; Kleifeld, Oded; Scheliga, Judith S.; Glickman, Michael H.; Chang, Eric C.; Wolf, Dieter A.

2009-01-01

119

Susceptibility genes are enriched in those of the herpes simplex virus 1/host interactome in psychiatric and neurological disorders.  

PubMed

Herpes simplex virus 1 (HSV-1) can promote beta-amyloid deposition and tau phosphorylation, demyelination or cognitive deficits relevant to Alzheimer's disease or multiple sclerosis and to many neuropsychiatric disorders with which it has been implicated. A seroprevalence much higher than disease incidence has called into question any primary causal role. However, as also the case with risk-promoting polymorphisms (also present in control populations), any causal effects are likely to be conditional. During its life cycle, the virus binds to many proteins and modifies the expression of multiple genes creating a host/pathogen interactome involving 1347 host genes. This data set is heavily enriched in the susceptibility genes for multiple sclerosis (P = 1.3E-99) > Alzheimer's disease > schizophrenia > Parkinsonism > depression > bipolar disorder > childhood obesity > chronic fatigue > autism > and anorexia (P = 0.047) but not attention deficit hyperactivity disorder, a relationship maintained for genome-wide association study data sets in multiple sclerosis and Alzheimer's disease. Overlapping susceptibility gene/interactome data sets disrupt signalling networks relevant to each disease, suggesting that disease susceptibility genes may filter the attentions of the pathogen towards particular pathways and pathologies. In this way, the same pathogen could contribute to multiple diseases in a gene-dependent manner and condition the risk-promoting effects of the genes whose function it disrupts. PMID:23913659

Carter, Chris J

2013-12-01

120

Beclin 1 interactome controls the crosstalk between apoptosis, autophagy and inflammasome activation: impact on the aging process.  

PubMed

Autophagy and apoptosis are crucial cellular housekeeping and tissue survival mechanisms. There is emerging evidence of important crosstalk between apoptosis and autophagy which can be linked to inflammasome activation. Beclin 1 is a platform protein which assembles an interactome consisting of diverse proteins which control the initiation of autophagocytosis and distinct phases in endocytosis. Recent studies have demonstrated that the anti-apoptotic Bcl-2 family members can interact with Beclin 1 and inhibit autophagy. Consequently, impaired autophagy can trigger inflammasome activation. Interestingly, the hallmarks of the ageing process include a decline in autophagy, increased resistance to apoptosis and a low-grade inflammatory phenotype. Age-related stresses, e.g. genotoxic, metabolic and environmental insults, enhance the expression of NF-?B-driven anti-apoptotic Bcl-2 proteins which repress the Beclin 1-dependent autophagy. Suppression of autophagocytosis provokes inflammation including NF-?B activation which further potentiates anti-apoptotic defence. In a context-dependent manner, this feedback defence mechanism can enhance the aging process or provoke tumorigenesis or cellular senescence. We will review the role of Beclin 1 interactome in the crosstalk between apoptosis, autophagy and inflammasomes emphasizing that disturbances in Beclin 1-dependent autophagy can have a crucial impact on the aging process. PMID:23220384

Salminen, Antero; Kaarniranta, Kai; Kauppinen, Anu

2013-03-01

121

Decomposing spatiotemporal brain patterns into topographic latent sources.  

PubMed

This paper extends earlier work on spatial modeling of fMRI data to the temporal domain, providing a framework for analyzing high temporal resolution brain imaging modalities such as electroencapholography (EEG). The central idea is to decompose brain imaging data into a covariate-dependent superposition of functions defined over continuous time and space (what we refer to as topographic latent sources). The continuous formulation allows us to parametrically model spatiotemporally localized activations. To make group-level inferences, we elaborate the model hierarchically by sharing sources across subjects. We describe a variational algorithm for parameter estimation that scales efficiently to large data sets. Applied to three EEG data sets, we find that the model produces good predictive performance and reproduces a number of classic findings. Our results suggest that topographic latent sources serve as an effective hypothesis space for interpreting spatiotemporal brain imaging data. PMID:24791745

Gershman, Samuel J; Blei, David M; Norman, Kenneth A; Sederberg, Per B

2014-09-01

122

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

123

Spatiotemporal firing patterns in the cerebellum  

Microsoft Academic Search

Neurons are generally considered to communicate information by increasing or decreasing their firing rate. However, in principle, they could in addition convey messages by using specific spatiotemporal patterns of spiking activities and silent intervals. Here, we review expanding lines of evidence that such spatiotemporal coding occurs in the cerebellum, and that the olivocerebellar system is optimally designed to generate and

Freek E. Hoebeek; Laurens W. J. Bosman; Martijn Schonewille; Laurens Witter; Sebastiaan K. Koekkoek; Chris I. De Zeeuw

2011-01-01

124

Spatiotemporal Monitoring of Urban Vegetation Christopher Small  

E-print Network

recognised as a strong influence on energy demand and development of the urban heat island (e.g. HarringtonSpatiotemporal Monitoring of Urban Vegetation Christopher Small Lamont Doherty Earth Observatory roberta@ciesin.org Monitoring spatiotemporal changes in urban agglomorations will become increasingly

Small, Christopher

125

Spatiotemporal evolution of ventricular fibrillation  

NASA Astrophysics Data System (ADS)

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

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

1998-03-01

126

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

127

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

128

3D hybrid wound devices for spatiotemporally controlled release kinetics.  

PubMed

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

Ozbolat, Ibrahim T; Koc, Bahattin

2012-12-01

129

Fast disparity estimation using spatio-temporal correlation of disparity field for multiview video coding  

Microsoft Academic Search

Disparity estimation is adopted by multiview video coding (MVC) to reduce the inter-view redundancy. However, it consumes enormous computational load. In this paper, a fast disparity estimation is proposed by using the spatio-temporal correlation and the temporal variation of disparity field. For each macroblock, a temporal prediction of the disparity vector is calculated first by utilizing the smoothed disparity field

Wei Zhu; Xiang Tian; Fan Zhou; Yaowu Chen

2010-01-01

130

Leveraging Microblogs for Spatiotemporal Music Information Retrieval  

E-print Network

relationships between particular music preferences and spatial properties, such as month, weekday, and country in 180 countries. Since we ultimately aim at geospatial, semantic music search, we annotated eachLeveraging Microblogs for Spatiotemporal Music Information Retrieval Markus Schedl Department

Widmer, Gerhard

131

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

132

An ontology for spatio-temporal databases  

Microsoft Academic Search

Spatio-temporal databases are representations of four-dimensional spatio-temporal reality. We discuss three different perspectives onto this reality: (a) the 'god' s eye' perspective in which spatio- temporal objects are seen as four-dimensional and non-changing, (b) the perspective of a sweeping plane dissecting four-dimensional reality into three-dimensional slices which we humans perceive the current moment; and (c) the perspective 'from within', which

Thomas Bittner

133

Spatio-Temporal Multimodal Developmental Learning  

Microsoft Academic Search

It is elusive how the skull-enclosed brain enables spatio-temporal multimodal developmental learning. By multimodal, we mean that the system has at least two sensory modalities, e.g., visual and auditory in our experiments. By spatio-temporal, we mean that the behavior from the system depends not only on the spatial pattern in the current sensory inputs, but also those of the recent

Yilu Zhang; Juyang Weng

2010-01-01

134

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

E-print Network

- tome; horizontal gene transfer*Corresponding author Introduction The network of protein. Abbreviations used: HGT, horizontal gene transfer; 16 S rRNA, ribonucleic acid molecule in the small subunit. The new approach allows us also to detect non-canonical evolutionary events, in particular horizontal gene

Pazos, Florencio

135

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

136

Spatiotemporally controlled single cell sonoporation  

PubMed Central

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

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

2012-01-01

137

Spatiotemporal control of cardiac alternans  

NASA Astrophysics Data System (ADS)

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

Echebarria, Blas; Karma, Alain

2002-09-01

138

Spatio-temporal avalanche forecasting with Support Vector Machines  

NASA Astrophysics Data System (ADS)

This paper explores the use of the Support Vector Machine (SVM) as a data exploration tool and a predictive engine for spatio-temporal forecasting of snow avalanches. Based on the historical observations of avalanche activity, meteorological conditions and snowpack observations in the field, an SVM is used to build a data-driven spatio-temporal forecast for the local mountain region. It incorporates the outputs of simple physics-based and statistical approaches used to interpolate meteorological and snowpack-related data over a digital elevation model of the region. The interpretation of the produced forecast is discussed, and the quality of the model is validated using observations and avalanche bulletins of the recent years. The insight into the model behaviour is presented to highlight the interpretability of the model, its abilities to produce reliable forecasts for individual avalanche paths and sensitivity to input data. Estimates of prediction uncertainty are obtained with ensemble forecasting. The case study was carried out using data from the avalanche forecasting service in the Locaber region of Scotland, where avalanches are forecast on a daily basis during the winter months.

Pozdnoukhov, A.; Matasci, G.; Kanevski, M.; Purves, R. S.

2011-02-01

139

Sustained Emerging Spatio-Temporal Co-occurrence Pattern Mining: A Summary of Results  

Microsoft Academic Search

Sustained emerging spatio-temporal co-occurrence patterns (SECOPs) represent subsets of object-types that are increasingly located together in space and time. Discovering SECOPs is important due to many applications, e.g., predicting emerging infectious diseases, predicting defensive and offensive intent from troop movement patterns, and novel predator-prey interactions. However, mining SECOPs is computationally very expensive because the interest measures are computationally complex, datasets

Mete Celik; Shashi Shekhar; James P. Rogers; James A. Shine

2006-01-01

140

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

141

Spatiotemporal model for the progression of transgressive dunes  

NASA Astrophysics Data System (ADS)

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

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

2013-10-01

142

Adaptive Spatio-Temporal Filters Infrared Target Detection  

E-print Network

Adaptive Spatio-Temporal Filters for Infrared Target Detection by Anusha Muthu Natarajan Copyright . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 Chapter 4. Spatio-Temporal Filter Adaptation . . . . . . . . . . . . . . . . . . . . 26 4.1. Adaptation of Filter Temporal Frequency . . . . . . . . . . . . . . . . . . . . . . . . 26 4.2. Adaptation

143

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

144

The interactome of LIM domain proteins: the contributions of LIM domain proteins to heart failure and heart development.  

PubMed

LIM domain proteins all contain at least one double zinc-finger motif. They belong to a large family and here we review those expressed mainly in mammalian hearts, but particularly in cardiomyocytes. These proteins contain between one and five LIM domains and usually these proteins contain other domains that have specific functions such as actin-binding, kinases and nuclear translocation motifs. While several recent reviews have summarised the importance of individual LIM domain proteins, this is the first review of its kind to cover all LIMs associated with the heart. Here we examine 33 LIM proteins (including three that bind to, but do not themselves contain, LIM domains) that are implicated in either the development of the heart, heart disorders and failure, or both. Our analysis is consistent with the view that cardiac LIM domain proteins form multiple extensive networks of multi-protein complexes within the myocardium. This multiplicity of binding partners probably protects the heart as it is challenged to maintain cardiac output, until the imbalance reaches a turning point that results in failure. We believe that the complexity of LIM interactions is properly described by the term LIM interactome. PMID:22253135

Li, Amy; Ponten, Fredrik; dos Remedios, Cristobal G

2012-01-01

145

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

PubMed Central

R-loop is the structure co-transcriptionally formed between nascent RNA transcript and DNA template, leaving the non-transcribed DNA strand unpaired. This structure can be involved in the hyper-mutation and dsDNA breaks in mammalian immunoglobulin (Ig) genes, oncogenes and neurodegenerative disease related genes. R-loops have not been studied at the genome scale yet. To identify the R-loops, we developed a computational algorithm and mapped R-loop forming sequences (RLFS) onto 66?803 sequences defined by UCSC as ‘known’ genes. We found that ?59% of these transcribed sequences contain at least one RLFS. We created R-loopDB (http://rloop.bii.a-star.edu.sg/), the database that collects all RLFS identified within over half of the human genes and links to the UCSC Genome Browser for information integration and visualisation across a variety of bioinformatics sources. We found that many oncogenes and tumour suppressors (e.g. Tp53, BRCA1, BRCA2, Kras and Ptprd) and neurodegenerative diseases related genes (e.g. ATM, Park2, Ptprd and GLDC) could be prone to significant R-loop formation. Our findings suggest that R-loops provide a novel level of RNA–DNA interactome complexity, playing key roles in gene expression controls, mutagenesis, recombination process, chromosomal rearrangement, alternative splicing, DNA-editing and epigenetic modifications. RLFSs could be used as a novel source of prospective therapeutic targets. PMID:22121227

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

2012-01-01

146

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

147

Hierarchic spatio-temporal dynamics in glycolysis  

NASA Astrophysics Data System (ADS)

Yeast extracts exhibit oscillations when the glycolytic system is far away from equilibrium. Spatio-temporal dynamics in this system was studied in the newly developed gel as well as in the solution. Small regions (about 10 um) with very complex shape with high or low concentrations of NADH appeared, and upon these small structures large-scale dynamics were superimposed. Concentration waves propagated, and the source of wave was induced by contact with high ADP. Sink of waves was generated by contacting the reaction gel to two small gels rich in ADP. Upon these spatio-temporal dynamics were superimposed much slower global oscillations throughout the system with a period of about 40 min. Similar dynamics was seen in a solution of yeast extract, but the size of domains was about ten times larger than that in the gel. In this way, the multi-enzyme system of glycolysis exhibits self-organization of hierarchy in spatio-temporal dynamics.

Shinjyo, Takahiro; Nakagawa, Yoshiyuki; Ueda, Tetsuo

148

Spatiotemporal representation of cardiac vectorcardiogram (VCG) signals  

PubMed Central

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

2012-01-01

149

Rule-based spatiotemporal query processing for video databases  

Microsoft Academic Search

In our earlier work, we proposed an architecture for a Web-based video database management system (VDBMS) providing an integrated support for spatiotemporal and seman- tic queries. In this paper, we focus on the task of spatiotemporal query processing and also propose an SQL-like video query language that has the capability to handle a broad range of spatiotemporal queries. The language

Mehmet Emin Donderler

150

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

151

A modified consumer inkjet for spatiotemporal control of gene expression.  

PubMed

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

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

2009-01-01

152

POPULATION ECOLOGY Spatiotemporal variation in reproductive parameters  

E-print Network

Arpat Ozgul � Madan K. Oli � Lucretia E. Olson � Daniel T. Blumstein � Kenneth B. Armitage Received: 8 of yellow-bellied marmots (Marmota flaviventris), and its influence on the realized population growth rate (e.g., Oli and Armitage 2004; Oli and Dob- son 2003; Sæther and Bakke 2000), spatiotemporal variation

Grether, Gregory

153

Spatiotemporal Oriented Energy Features for Visual Tracking  

E-print Network

, representative examples are provided. Perhaps the simplest approach is to make use of image intensity- based to capture a target's multiscale, spatiotemporal orientation structure. A consider- able body of research has these features readily map. Although, the energy features are also applicable to alter- native paradigms, e

Wildes, Richard P.

154

Spatiotemporal chaos in Easter Island ecology.  

PubMed

This paper demonstrates that a recently proposed spatiotemporal model for the ecology of Easter Island admits periodic and chaotic attractors, not previously reported. Such behavior may more realistically depict the population dynamics of general ecosystems and illustrates the power of simple models to produce the kind of complex behavior that is ubiquitous in such systems. PMID:22980451

Sprott, J C

2012-10-01

155

Spatiotemporal transformations of ultrashort terahertz pulses  

E-print Network

Spatiotemporal transformations of ultrashort terahertz pulses Petr Kuzel, Maxim A. Khazan, and Jan-cycle terahertz pulses emitted by large-aperture emitters. The spatial transformations of the beams are connected the temporal waveform and the spectrum of the pulses are altered as a result of these spa- tial transformations

KuÂ?el, Petr

156

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

157

The Phosphotyrosine Interactome of the Insulin Receptor Family and Its Substrates IRS-1 and IRS-2*S?  

PubMed Central

The insulin signaling pathway is critical in regulating glucose levels and is associated with diabetes, obesity, and longevity. A tyrosine phosphorylation cascade creates docking sites for protein interactions, initiating subsequent propagation of the signal throughout the cell. The phosphotyrosine interactome of this medically important pathway has not yet been studied comprehensively. We therefore applied quantitative interaction proteomics to exhaustively profile all potential phosphotyrosine-dependent interaction sites in its key players. We targeted and compared insulin receptor substrates 1 and 2 (IRS-1 and IRS-2) as central distributors of the insulin signal, the insulin receptor, the insulin-like growth factor 1 receptor, and the insulin receptor-related receptor. Using the stable isotope labeling by amino acids in cell culture (SILAC) approach with phosphorylated versus non-phosphorylated bait peptides, we found phosphorylation-specific interaction partners for 52 out of 109 investigated sites. In addition, doubly and triply phosphorylated motifs provided insight into the combinatorial effects of phosphorylation events in close proximity to each other. Our results retrieve known interactions and substantially broaden the spectrum of potential interaction partners of IRS-1 and IRS-2. A large number of common interactors rationalize their extensive functional redundancy. However, several proteins involved in signaling and metabolism interact differentially with IRS-1 and IRS-2 and thus provide leads into their different physiological roles. Differences in interactions at the receptor level are reflected in multisite recruitment of SHP2 by the insulin-like growth factor 1 receptor and limited but exclusive interactions with the IRR. In common with other recent reports, our data furthermore hint at non-SH2 or phosphotyrosine-binding domain-mediated phosphotyrosine binding. PMID:19001411

Hanke, Stefan; Mann, Matthias

2009-01-01

158

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

PubMed

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

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

2014-04-01

159

Quadrature subunits in directionally selective simple cells: spatiotemporal interactions.  

PubMed

I explore here whether linear mechanisms can explain directional selectivity (DS) in simple cells of the cat's striate cortex, a question suggested by a recent upswing in popularity of linear DS models. I chose a simple cell with a space-time inseparable receptive field (RF), i.e. one that shows gradually shifting latency across space, as the RF type most likely to depend on linear mechanisms of DS. However, measured responses of the cell to a moving bar were less modulated, and extended over a larger spatial region than predicted by two different popular "linear" models. They also were more DS in exhibiting a higher ratio of total spikes for the preferred direction. Each of the two models used for comparison has a single "branch" with a single spatiotemporally inseparable linear filter followed by a threshold, hence, a- "1-branch" model. Nonlinear interactions between pairs of bars in a 2-bar linear superposition test of the cell also disagreed in time-course with those of the 1-branch models. The only model whose 1-bar and 2-bar predictions matched the measured cell (including a complete "4-branch" motion energy model that matches complex cells) has two branches that differ in phase by about 90 deg, i.e. in quadrature. Each branch has its own threshold that helps define the preceding spatiotemporal unit as a subunit even after the outputs of the two branches are summed. As subunit phases differ by only 90 deg, flashing bar responses of the 2-subunit model are similar to those of the 1-subunit model. Therefore, the number of subunits is hidden from view when testing with a conventional stationary bar. In summary, movement responses and nonlinear interactions between pairs of bars in the measured cell matched those of the 2-subunit model, while they disagreed with the popular 1-subunit model. Thus, multiple nonlinear subunits appear to be necessary for DS, even in simple cortical cells. PMID:9147487

Emerson, R C

1997-01-01

160

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

161

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

162

Interactome Analyses of Mature ?-Secretase Complexes Reveal Distinct Molecular Environments of Presenilin (PS) Paralogs and Preferential Binding of Signal Peptide Peptidase to PS2*  

PubMed Central

?-Secretase plays a pivotal role in the production of neurotoxic amyloid ?-peptides (A?) in Alzheimer disease (AD) and consists of a heterotetrameric core complex that includes the aspartyl intramembrane protease presenilin (PS). The human genome codes for two presenilin paralogs. To understand the causes for distinct phenotypes of PS paralog-deficient mice and elucidate whether PS mutations associated with early-onset AD affect the molecular environment of mature ?-secretase complexes, quantitative interactome comparisons were undertaken. Brains of mice engineered to express wild-type or mutant PS1, or HEK293 cells stably expressing PS paralogs with N-terminal tandem-affinity purification tags served as biological source materials. The analyses revealed novel interactions of the ?-secretase core complex with a molecular machinery that targets and fuses synaptic vesicles to cellular membranes and with the H+-transporting lysosomal ATPase macrocomplex but uncovered no differences in the interactomes of wild-type and mutant PS1. The catenin/cadherin network was almost exclusively found associated with PS1. Another intramembrane protease, signal peptide peptidase, predominantly co-purified with PS2-containing ?-secretase complexes and was observed to influence A? production. PMID:23589300

Jeon, Amy Hye Won; Bohm, Christopher; Chen, Fusheng; Huo, Hairu; Ruan, Xueying; Ren, Carl He; Ho, Keith; Qamar, Seema; Mathews, Paul M.; Fraser, Paul E.; Mount, Howard T. J.; St George-Hyslop, Peter; Schmitt-Ulms, Gerold

2013-01-01

163

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

PubMed Central

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

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

2014-01-01

164

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

165

Vector Zonal Operations for Spatiotemporal Analysis  

E-print Network

GIS to simulate traffic information using a cadastral map. Turner (2007) developed a GIS-based approach to implement spatial and temporal analysis of landscape patterns and found out that spatiotemporal GIS CM functions can play an important role...) (Krajewski 1987). NWS River Forecast Centers (RFCs) produce regional multisensor precipitation products using information from numerous WSR-88D radars and a network of gauges that send data to RFCs in near real-time (Fulton, 1998). These NEXRAD multisensor...

Xu, Tingting

2009-12-11

166

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

167

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

168

Connecting the Dots: Constructing Spatiotemporal Episodes from Events Schemas  

Microsoft Academic Search

This paper introduces a novel framework for deriving and mining high–level spatiotemporal process models in in-situ sensor\\u000a measurements. The proposed framework is comprised of two complementary components, namely, hierarchical event schemas and\\u000a spatiotemporal episodes. Event schemas are used in this work as the basic building model of spatiotemporal processes while\\u000a episodes are used for organizing events in space and time

Arie Croitoru

2009-01-01

169

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

170

Size-dependent diffusion promotes the emergence of spatiotemporal patterns.  

PubMed

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

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

2014-07-01

171

A solution for change detection in spatio-temporal database  

NASA Astrophysics Data System (ADS)

When modeling spatio-temporal applications, the spatial, temporal but also spatio-temporal aspects like change or motion have to be expressed (Brisaboa, N.R., 1998). For spatio-temporal object (ST-Object), it's necessary to store its correlation link which can be used to track an object's various states over time easily. In this paper, we propose a solution based on spatio-temporal data model to resolve how to detect ST-Object's various states over time and build correlation link and correlation tree into database for different temporal. DLG (Digital Line Graphic) source data of the same area interested.

Wang, Huibing; Tang, Xinming; Shi, Shaoyu

2007-06-01

172

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

173

Targeted interactomics reveals a complex core cell cycle machinery in Arabidopsis thaliana.  

PubMed

Cell proliferation is the main driving force for plant growth. Although genome sequence analysis revealed a high number of cell cycle genes in plants, little is known about the molecular complexes steering cell division. In a targeted proteomics approach, we mapped the core complex machinery at the heart of the Arabidopsis thaliana cell cycle control. Besides a central regulatory network of core complexes, we distinguished a peripheral network that links the core machinery to up- and downstream pathways. Over 100 new candidate cell cycle proteins were predicted and an in-depth biological interpretation demonstrated the hypothesis-generating power of the interaction data. The data set provided a comprehensive view on heterodimeric cyclin-dependent kinase (CDK)-cyclin complexes in plants. For the first time, inhibitory proteins of plant-specific B-type CDKs were discovered and the anaphase-promoting complex was characterized and extended. Important conclusions were that mitotic A- and B-type cyclins form complexes with the plant-specific B-type CDKs and not with CDKA;1, and that D-type cyclins and S-phase-specific A-type cyclins seem to be associated exclusively with CDKA;1. Furthermore, we could show that plants have evolved a combinatorial toolkit consisting of at least 92 different CDK-cyclin complex variants, which strongly underscores the functional diversification among the large family of cyclins and reflects the pivotal role of cell cycle regulation in the developmental plasticity of plants. PMID:20706207

Van Leene, Jelle; Hollunder, Jens; Eeckhout, Dominique; Persiau, Geert; Van De Slijke, Eveline; Stals, Hilde; Van Isterdael, Gert; Verkest, Aurine; Neirynck, Sandy; Buffel, Yelle; De Bodt, Stefanie; Maere, Steven; Laukens, Kris; Pharazyn, Anne; Ferreira, Paulo C G; Eloy, Nubia; Renne, Charlotte; Meyer, Christian; Faure, Jean-Denis; Steinbrenner, Jens; Beynon, Jim; Larkin, John C; Van de Peer, Yves; Hilson, Pierre; Kuiper, Martin; De Veylder, Lieven; Van Onckelen, Harry; Inzé, Dirk; Witters, Erwin; De Jaeger, Geert

2010-08-10

174

A spatio-temporal absorbing state model for disease and syndromic surveillance.  

PubMed

Reliable surveillance models are an important tool in public health because they aid in mitigating disease outbreaks, identify where and when disease outbreaks occur, and predict future occurrences. Although many statistical models have been devised for surveillance purposes, none are able to simultaneously achieve the important practical goals of good sensitivity and specificity, proper use of covariate information, inclusion of spatio-temporal dynamics, and transparent support to decision-makers. In an effort to achieve these goals, this paper proposes a spatio-temporal conditional autoregressive hidden Markov model with an absorbing state. The model performs well in both a large simulation study and in an application to influenza/pneumonia fatality data. PMID:22388709

Heaton, Matthew J; Banks, David L; Zou, Jian; Karr, Alan F; Datta, Gauri; Lynch, James; Vera, Francisco

2012-08-30

175

Directional selectivity and spatiotemporal structure of receptive fields of simple cells in cat striate cortex.  

PubMed

1. Simple cells in cat striate cortex were studied with a number of stimulation paradigms to explore the extent to which linear mechanisms determine direction selectivity. For each paradigm, our aim was to predict the selectivity for the direction of moving stimuli given only the responses to stationary stimuli. We have found that the prediction robustly determines the direction and magnitude of the preferred response but overestimates the nonpreferred response. 2. The main paradigm consisted of comparing the responses of simple cells to contrast reversal sinusoidal gratings with their responses to drifting gratings (of the same orientation, contrast, and spatial and temporal frequencies) in both directions of motion. Although it is known that simple cells display spatiotemporally inseparable responses to contrast reversal gratings, this spatiotemporal inseparability is demonstrated here to predict a certain amount of direction selectivity under the assumption that simple cells sum their inputs linearly. 3. The linear prediction of the directional index (DI), a quantitative measure of the degree of direction selectivity, was compared with the measured DI obtained from the responses to drifting gratings. The median value of the ratio of the two was 0.30, indicating that there is a significant nonlinear component to direction selectivity. 4. The absolute magnitudes of the responses to gratings moving in both directions of motion were compared with the linear predictions as well. Whereas the preferred direction response showed only a slight amount of facilitation compared with the linear prediction, there was a significant amount of nonlinear suppression in the nonpreferred direction. 5. Spatiotemporal inseparability was demonstrated also with stationary temporally modulated bars. The time course of response to these bars was different for different positions in the receptive field. The degree of spatiotemporal inseparability measured with sinusoidally modulated bars agreed quantitatively with that measured in experiments with stationary gratings. 6. A linear prediction of the responses to drifting luminance borders was compared with the actual responses. As with the grating experiments, the prediction was qualitatively accurate, giving the correct preferred direction but underestimating the magnitude of direction selectivity observed.(ABSTRACT TRUNCATED AT 400 WORDS) PMID:1774584

Reid, R C; Soodak, R E; Shapley, R M

1991-08-01

176

Gestural Interaction with Spatiotemporal Linked Open Data Gestural Interaction with Spatiotemporal  

E-print Network

of Linked Open Data about the deforestation of the Brazilian Amazon Rainforest and related ecological the Brazilian Amazon Rain- forest. Keywords: Gestural interaction, spatiotemporal phenomena, Linked Open Data. 1 large amounts of linked data related to deforestation on large screens and we also report on results

Köbben, Barend

177

Spatio-temporal population estimates for risk management  

NASA Astrophysics Data System (ADS)

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

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

2013-04-01

178

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

179

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

180

kltool: A tool to analyze spatiotemporal complexity  

NASA Astrophysics Data System (ADS)

We announce the availability of a software package, called kltool, that can extract phase space information from complex spatiotemporal data via the Karhunen-Loève analysis. Data generated by the periodic, quasiperiodic or chaotic evolution of a small number of spatially coherent structures can be processed. A key feature of kltool is that it allows the user to interact easily with the data processing and its graphical display. We illustrate the use of kltool on numerical data from the Kuramoto-Sivashinsky equation and laboratory data from a flame experiment.

Armbruster, Dieter; Heiland, Randy; Kostelich, Eric J.

1994-06-01

181

Synchronization of coupled systems with spatiotemporal chaos  

NASA Astrophysics Data System (ADS)

We argue that the synchronization transition of stochastically coupled cellular automata, discovered recently by Morelli et al. [Phys. Rev. E 58, R8 (1998)], is generically in the directed percolation universality class. In particular this holds numerically for the specific example studied by these authors, in contrast to their claim. For real-valued systems with spatiotemporal chaos such as coupled map lattices, we claim that the synchronization transition is generically in the universality class of the Kardar-Parisi-Zhang equation with a nonlinear growth limiting term.

Grassberger, Peter

1999-03-01

182

The identification of continuous, spatiotemporal systems  

E-print Network

We present a method for the identification of continuous, spatiotemporal dynamics from experimental data. We use a model in the form of a partial differential equation and formulate an optimization problem for its estimation from data. The solution is found as a multivariate nonlinear regression problem using the ACE-algorithm. The procedure is successfully applied to data, obtained by simulation of the Swift-Hohenberg equation. There are no restrictions on the dimensionality of the investigated system, allowing for the analysis of high-dimensional chaotic as well as transient dynamics. The demands on the experimental data are discussed as well as the sensitivity of the method towards noise.

H. Voss; M. J. Bünner; M. Abel

1999-06-30

183

Spatiotemporal rogue events in femtosecond filamentation  

SciTech Connect

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

Majus, D.; Jukna, V.; Valiulis, G.; Dubietis, A. [Department of Quantum Electronics, Vilnius University, Sauletekio Avenue 9, Building 3, LT-10222 Vilnius (Lithuania); Faccio, D. [School of Engineering and Physical Sciences, SUPA, Heriot-Watt University, Edinburgh EH14 4AS (United Kingdom)

2011-02-15

184

SPATIOTEMPORAL MODELS IN THE ESTIMATION OF AREA PRECIPITATION  

E-print Network

for the optimal combination of weather radar and rain gauges measurements is a matter of great importance. This will be the case of the spatiotemporal models adopted in this work to describe rain gauges and radar measurements radar; area rainfall estimation; kriging; cokriging; time series; spatiotemporal models. 1. THE AREA

Lisbon, University of

185

Quantifiers for spatio-temporal bifurcations in coupled map lattices  

Microsoft Academic Search

The bifurcation behaviour of spatially extended systems shows interesting features which are as yet poorly understood. We analyse spatio-temporal bifurcations in coupled map lattices which maybe classified as purely spatial or spatio-temporal in nature. We construct quantifiers, which can detect all types of bifurcation behaviour. We demonstrate the utility of our quantifiers in the context of spatially or temporally periodic

Nandini Chatterjee; Neelima Gupte

1997-01-01

186

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

187

MobiQuery: a spatiotemporal data service for sensor networks  

Microsoft Academic Search

Spatiotemporal query is a new type of data service that al- lows a user to periodically gather information from a geo- graphic area that moves with the user. A defining feature of this new service model is that each query result is subject to a set of spatiotemporal constraints in terms of response tim e, data freshness, and changing locations

Sangeeta Bhattacharya; Octav Chipara; Brandon Harris; Chenyang Lu; Guoliang Xing; Chien-Liang Fok

2004-01-01

188

Abducing Qualitative Spatio-Temporal Histories from Partial Observations  

E-print Network

circumscription to ab- duce explanations of the sensor data. Exploiting Qualitative Motion Within QualitativeAbducing Qualitative Spatio-Temporal Histories from Partial Observations Shyamanta M Hazarika is constructed from local surveys i.e. par- tial spatio-temporal knowledge. Complete space-time histories

Leeds, University of

189

Spatiotemporal patterns of gene expression during fetal monkey brain development  

Microsoft Academic Search

Human DNA microarrays are used to study the spatiotemporal patterns of gene expression during the course of fetal monkey brain development. The 444 most dynamically expressed genes in four major brain areas are reported at five different fetal ages. The spatiotemporal profiles of gene expression show both regional specificity as well as waves of gene expression across the developing brain.

D. Eugene Redmond; Ji-liang Zhaosupbsu; Jeffry D. Randall; Aron C. Eklund; Leonard O. V. Eusebi; Robert H. Roth; Steven R. Gullans; Roderick V. Jensen

2003-01-01

190

SINA: Scalable Incremental Processing of Continuous Queries in Spatiotemporal Databases  

E-print Network

Queries in Spatiotemporal DatabasesOctober 1, 2007 1 / 27 #12;Outline 1 Motivation 2 Incremental in Spatiotemporal DatabasesOctober 1, 2007 2 / 27 #12;Outline 1 Motivation 2 Incremental Evaluation AlgorithmOctober 1, 2007 3 / 27 #12;Example Positive Update (Q3, +p2) (Q3, +p8) Negative Update (Q1, -p5) (Q2, -p1

Kaiserslautern, Universität

191

Learning of Spatiotemporal Behavior in Cellular Neural Networks  

E-print Network

Learning of Spatiotemporal Behavior in Cellular Neural Networks Samuel Xavier-de-Souza, Johan A In this paper the problem of learning spatiotemporal behavior with cellu- lar neural networks is analyzed learning with recurrent neural networks. Despite of similarities, the two learning problems have underling

192

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

193

Real-Time Spatiotemporal Data Indexing Structure  

E-print Network

This document describes the Po-tree, a new indexing structure for spatiotemporal databases with soft real time constraints. This is crucial for risk management, particularly for the monitoring of volcanic risk. For example, the Popocatepetl, a Mexican volcano, is closely monitored through an network of spatially referenced sensors. They all send back their measurements to a central spatiotemporal database. The Po-tree shall therefore be able to index huge quantities of data in a restricted amount of time. It shall also be able to favor the newer data, which are queried more frequently. While most structures tend to favor the temporal aspect over the spatial, or tend to consider time as another spatial dimension, the Po-tree offers an alternative. It does so by combining two different structures, for spatial and temporal dimensions respectively, stressing the spatial aspect, and linking every source of information to a new temporal sub-tree. While mobility is not yet supported, experimentations and comparisons have shown interesting potential in the structure.

Guillaume Noël; Sylvie Servigne; Robert Laurini

2004-01-01

194

Compact Video Synopsis via Global Spatiotemporal Optimization.  

PubMed

Video synopsis aims at providing condensed representations of video datasets that can be easily captured from digital cameras nowadays, especially for daily surveillance videos. Previous work in video synopsis usually moves active objects along the time axis, which inevitably causes collisions among the moving objects if compressed much. In this paper, we propose a novel approach for compact video synopsis using a unified spatiotemporal optimization. Our approach globally shifts moving objects in both spatial and temporal domains, which shifting objects temporally to reduce the length of the video and shifting colliding objects spatially to avoid visible collision artifacts. Furthermore, using a multi-level patch relocation method, the moving space of the original video is expanded into a compact background based on environmental content to fit with the shifted objects. The shifted objects are finally composited with the expanded moving space to obtain the high-quality video synopsis, which is more condensed while remaining free of collision artifacts. Our experimental results have shown that the compact video synopsis we produced can be browsed quickly, preserves relative spatiotemporal relationships, and avoids motion collisions. PMID:22962088

Nie, Yongwei; Xiao, Chunxia; Sun, Hanqiu; Li, Ping

2012-08-22

195

Compact video synopsis via global spatiotemporal optimization.  

PubMed

Video synopsis aims at providing condensed representations of video data sets that can be easily captured from digital cameras nowadays, especially for daily surveillance videos. Previous work in video synopsis usually moves active objects along the time axis, which inevitably causes collisions among the moving objects if compressed much. In this paper, we propose a novel approach for compact video synopsis using a unified spatiotemporal optimization. Our approach globally shifts moving objects in both spatial and temporal domains, which shifting objects temporally to reduce the length of the video and shifting colliding objects spatially to avoid visible collision artifacts. Furthermore, using a multilevel patch relocation (MPR) method, the moving space of the original video is expanded into a compact background based on environmental content to fit with the shifted objects. The shifted objects are finally composited with the expanded moving space to obtain the high-quality video synopsis, which is more condensed while remaining free of collision artifacts. Our experimental results have shown that the compact video synopsis we produced can be browsed quickly, preserves relative spatiotemporal relationships, and avoids motion collisions. PMID:23929846

Nie, Yongwei; Xiao, Chunxia; Sun, Hanqiu; Li, Ping

2013-10-01

196

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

NASA Astrophysics Data System (ADS)

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

Hu, S.; Wang, E.; Liu, X.

2014-08-01

197

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

NASA Astrophysics Data System (ADS)

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

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

2014-04-01

198

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

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

199

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

200

Emergence of spatiotemporal dislocation chains in drifting patterns  

NASA Astrophysics Data System (ADS)

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

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

2014-06-01

201

Emergence of spatiotemporal dislocation chains in drifting patterns.  

PubMed

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

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

2014-06-01

202

Research of spatio-temporal analysis of agricultural pest  

NASA Astrophysics Data System (ADS)

The increase of agricultural pest disasters in recent years has become one of major problems in agriculture harvest; how to predict and control the disasters of agricultural pest has thus attracted great research interest. Although a series of works have been done and some achievements have been attained, the knowledge in this area remains limited. The migration of agricultural pest is not only related to the time variation, but also the space; consequently, the population of agricultural pest has complex spatio-temporal characteristics. The space factor and the temporal factor must be considered at the same time in the research of dynamics changes of the pest population. Using plant hoppers as an object of study, this study employed the biological analogy deviation model to study the distribution of pest population in different periods of time in Guangdong Province. It is demonstrated that the population distribution of plant hoppers is not only related to the space location, but also has a certain direction. The result reported here offers help to the monitor, prevention and control of plant hoppers in Guangdong Provinces.

Wang, Changwei; Li, Deren; Hu, Yueming; Wu, Xiaofang; Qi, Yu

2009-10-01

203

Systemic risk and spatiotemporal dynamics of the US housing market.  

PubMed

Housing markets play a crucial role in economies and the collapse of a real-estate bubble usually destabilizes the financial system and causes economic recessions. We investigate the systemic risk and spatiotemporal dynamics of the US housing market (1975-2011) at the state level based on the Random Matrix Theory (RMT). We identify richer economic information in the largest eigenvalues deviating from RMT predictions for the housing market than for stock markets and find that the component signs of the eigenvectors contain either geographical information or the extent of differences in house price growth rates or both. By looking at the evolution of different quantities such as eigenvalues and eigenvectors, we find that the US housing market experienced six different regimes, which is consistent with the evolution of state clusters identified by the box clustering algorithm and the consensus clustering algorithm on the partial correlation matrices. We find that dramatic increases in the systemic risk are usually accompanied by regime shifts, which provide a means of early detection of housing bubbles. PMID:24413626

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

2014-01-01

204

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

205

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

206

Spatiotemporal reconstruction of the breathing function.  

PubMed

Breathing waveform extracted via nasal thermistor is the most common method to study respiratory function in sleep studies. In essence, this is a temporal waveform of mean temperatures in the nostril region that at every time step collapses two-dimensional data into a single point. Hence, spatial heat distribution in the nostrils is lost along with valuable functional and anatomical cues. This article presents the construction and experimental validation of a spatiotemporal profile for the breathing function via thermal imaging of the nostrils. The method models nasal airflow advection by using a front-propagating level set algorithm with optimal parameter selection. It is the first time that the full two-dimensional advantage of thermal imaging is brought to the fore in breathing computation. This new multi-dimensional measure is likely to bring diagnostic value in sleep studies and beyond. PMID:23285546

Duong, D; Shastri, D; Tsiamyrtzis, P; Pavlidis, I

2012-01-01

207

Spatio-temporal synchronization of recurrent epidemics.  

PubMed Central

Long-term spatio-temporal datasets of disease incidences have made it clear that many recurring epidemics, especially childhood infections, tend to synchronize in-phase across suburbs. In some special cases, epidemics between suburbs have been found to oscillate in an out-of-phase ('antiphase') relationship for lengthy periods. Here, we use modelling techniques to help explain the presence of in-phase and antiphase synchronization. The nonlinearity of the epidemic dynamics is often such that the intensity of the outbreak influences the phase of the oscillation thereby introducing 'shear', a factor that is found to be important for generating antiphase synchronization. By contrast, the coupling between suburbs via the immigration of infectives tends to enhance in-phase synchronization. The emerging synchronization depends delicately on these opposite factors. We use theoretical results from continuous time models to provide a framework for understanding the relationship between synchronization patterns for different model structures. PMID:12965019

He, Daihai; Stone, Lewi

2003-01-01

208

Spatiotemporal magnetic field monitoring for MR.  

PubMed

MR experiments frequently rely on signal encoding by the application of magnetic fields that vary in both space and time. The accurate interpretation of the resulting signals often requires knowledge of the exact spatiotemporal field evolution during the experiment. To better fulfill this need, a new approach is presented that enables measuring the field evolution concurrently with any MR sequence. Miniature NMR probes are used to monitor the MR phase evolution around the object under investigation. Based on these data, a global phase model is calculated that can then be used as a basis for processing the actual image or spectroscopic data. The new method is demonstrated by MRI of a phantom, using spin-warp, spiral, and EPI trajectories. Throughout, the monitoring results enabled highly accurate image reconstruction, even in the presence of massive gradient imperfections. PMID:18581361

Barmet, Christoph; De Zanche, Nicola; Pruessmann, Klaas P

2008-07-01

209

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

210

Nonlinear Dynamics and Spatiotemporal Instabilities in Semiconductor Laser Arrays.  

NASA Astrophysics Data System (ADS)

By coupling several semiconductor lasers to form a laser array, a compact high power source of coherent radiation can be obtained. In addition to their technological importance, these devices also serve as useful paradigms for the study of spatiotemporal complexity in coupled nonlinear oscillators. In this thesis, we investigate the nature and origin of dynamical instabilities in semiconductor laser arrays and present practical models for their analysis. For a two-emitter array, we use a coupled-mode approach to determine the conditions under which the system can attain a (stable) phase-locked state. We show that with complex coupling, the array is stable over a wider range of coupling strengths eta than it is with real coupling. The antiguiding parameter plays a critical role in the dynamical stability. We also present results pertaining to the stability of larger arrays of identical or dissimilar emitters. For a three-emitter array and for some values of eta, we predict the existence of a remarkable state of synchronized chaos where a subset of emitters in the array synchronize with each other even though the array evolution is chaotic. For other values of eta, the system displays spatiotemporal chaos. We characterize these phenomena using a variety of measures. The coupled-mode approach is normally valid for strongly index-guided lasers. To explore the dynamics of a wider class of laser arrays, we present a propagation model that treats the array as a single waveguiding structure. The model is exact to all orders of eta. We use this model to simulate the dynamics of single-, two - and three-emitter laser arrays and discuss a variety of dynamical instabilities in them. We show that carrier diffusion leads to enhanced stability of a two-emitter laser array while rendering a three-emitter array unstable for almost all eta. Based on the propagation model, we develop an improved coupled-mode theory for a weakly index-guided array. It includes the effects of carrier diffusion and carrier-induced antiguiding. The theory considerably simplifies the analysis of stability and complex behavior in laser arrays. We compare the results obtained from this theory to those obtained from the propagation model and find excellent qualitative and quantitative agreement.

Rahman, Lutfur

1993-01-01

211

Novel semantic similarity measure improves an integrative approach to predicting gene functional associations  

PubMed Central

Background Elucidation of the direct/indirect protein interactions and gene associations is required to fully understand the workings of the cell. This can be achieved through the use of both low- and high-throughput biological experiments and in silico methods. We present GAP (Gene functional Association Predictor), an integrative method for predicting and characterizing gene functional associations. GAP integrates different biological features using a novel taxonomy-based semantic similarity measure in predicting and prioritizing high-quality putative gene associations. The proposed similarity measure increases information gain from the available gene annotations. The annotation information is incorporated from several public pathway databases, Gene Ontology annotations as well as drug and disease associations from the scientific literature. Results We evaluated GAP by comparing its prediction performance with several other well-known functional interaction prediction tools over a comprehensive dataset of known direct and indirect interactions, and observed significantly better prediction performance. We also selected a small set of GAP’s highly-scored novel predicted pairs (i.e., currently not found in any known database or dataset), and by manually searching the literature for experimental evidence accessible in the public domain, we confirmed different categories of predicted functional associations with available evidence of interaction. We also provided extra supporting evidence for subset of the predicted functionally-associated pairs using an expert curated database of genes associated to autism spectrum disorders. Conclusions GAP’s predicted “functional interactome” contains ?1M highly-scored predicted functional associations out of which about 90% are novel (i.e., not experimentally validated). GAP’s novel predictions connect disconnected components and singletons to the main connected component of the known interactome. It can, therefore, be a valuable resource for biologists by providing corroborating evidence for and facilitating the prioritization of potential direct or indirect interactions for experimental validation. GAP is freely accessible through a web portal: http://ophid.utoronto.ca/gap. PMID:23497449

2013-01-01

212

Spatio-temporal interpolation of daily temperatures for global land areas at 1 km resolution  

NASA Astrophysics Data System (ADS)

Combined Global Surface Summary of Day and European Climate Assessment and Dataset daily meteorological data sets (around 9000 stations) were used to build spatio-temporal geostatistical models and predict daily air temperature at ground resolution of 1 km for the global land mass. Predictions in space and time were made for the mean, maximum, and minimum temperatures using spatio-temporal regression-kriging with a time series of Moderate Resolution Imaging Spectroradiometer (MODIS) 8 day images, topographic layers (digital elevation model and topographic wetness index), and a geometric temperature trend as covariates. The accuracy of predicting daily temperatures was assessed using leave-one-out cross validation. To account for geographical point clustering of station data and get a more representative cross-validation accuracy, predicted values were aggregated to blocks of land of size 500×500 km. Results show that the average accuracy for predicting mean, maximum, and minimum daily temperatures is root-mean-square error (RMSE) =±2°C for areas densely covered with stations and between ±2°C and ±4°C for areas with lower station density. The lowest prediction accuracy was observed at high altitudes (>1000 m) and in Antarctica with an RMSE around 6°C. The model and predictions were built for the year 2011 only, but the same methodology could be extended for the whole range of the MODIS land surface temperature images (2001 to today), i.e., to produce global archives of daily temperatures (a next-generation http://WorldClim.org repository) and to feed various global environmental models.

Kilibarda, Milan; Hengl, Tomislav; Heuvelink, Gerard B. M.; Gräler, Benedikt; Pebesma, Edzer; Per?ec Tadi?, Melita; Bajat, Branislav

2014-03-01

213

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

214

Daily spatiotemporal precipitation simulation using latent and transformed Gaussian processes  

E-print Network

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

Katz, Richard

215

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)...

216

UNDERSTANDING SEVERE WEATHER PROCESSES THROUGH SPATIOTEMPORAL RELATIONAL RANDOM FORESTS  

E-print Network

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

217

Spatiotemporal stochastic resonance and its consequences in neural model systems  

Microsoft Academic Search

The realization of spatiotemporal stochastic resonance is studied in a two-dimensional FitzHugh–Nagumo system, and in a one-dimensional system of integrate-and-fire neurons. We show that spatiotemporal stochastic resonance occurs in these neural model systems, independent of the method of modeling. Moreover, the ways of realization are analogous in the two model systems. The biological implications and open questions are discussed.

Ga´bor Bala´zsi; La´szlo´ B. Kish; Frank E. Moss

2001-01-01

218

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

219

Extremum tracking in sensor fields with spatio-temporal correlation  

Microsoft Academic Search

Physical phenomena such as temperature, humidity, and wind velocity often exhibit both spatial and temporal correlation. We consider the problem of tracking the extremum value of a spatio-temporally correlated field using a wireless sensor network. Determining the extremum at the fusion center after making all sensor nodes transmitting their measurements is not energy-efficient because the spatio-temporal correlation of the field

Prithwish Basu; A. Nadamani; Lang Tong

2010-01-01

220

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

221

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

222

Contextualized trajectory parsing with spatiotemporal graph.  

PubMed

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

Liu, Xiaobai; Lin, Liang; Jin, Hai

2013-12-01

223

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

224

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

225

Intercellular Interactomics of Human Brain Endothelial Cells and Th17 Lymphocytes: A Novel Strategy for Identifying Therapeutic Targets of CNS Inflammation  

PubMed Central

Leukocyte infiltration across an activated brain endothelium contributes to the neuroinflammation seen in many neurological disorders. Recent evidence shows that IL-17-producing T-lymphocytes (e.g., Th17 cells) possess brain-homing capability and contribute to the pathogenesis of multiple sclerosis and cerebral ischemia. The leukocyte transmigration across the endothelium is a highly regulated, multistep process involving intercellular communications and interactions between the leukocytes and endothelial cells. The molecules involved in the process are attractive therapeutic targets for inhibiting leukocyte brain migration. We hypothesized and have been successful in demonstrating that molecules of potential therapeutic significance involved in Th17-brain endothelial cell (BEC) communications and interactions can be discovered through the combination of advanced membrane/submembrane proteomic and interactomic methods. We describe elements of this strategy and preliminary results obtained in method and approach development. The Th17-BEC interaction network provides new insights into the complexity of the transmigration process mediated by well-organized, subcellularly localized molecular interactions. These molecules and interactions are potential diagnostic, therapeutic, or theranostic targets for treatment of neurological conditions accompanied or caused by leukocyte infiltration. PMID:21755032

Haqqani, Arsalan S.; Stanimirovic, Danica B.

2011-01-01

226

Elucidation of the Ebola Virus VP24 Cellular Interactome and Disruption of Virus Biology through Targeted Inhibition of Host-Cell Protein Function.  

PubMed

Viral pathogenesis in the infected cell is a balance between antiviral responses and subversion of host-cell processes. Many viral proteins specifically interact with host-cell proteins to promote virus biology. Understanding these interactions can lead to knowledge gains about infection and provide potential targets for antiviral therapy. One such virus is Ebola, which has profound consequences for human health and causes viral hemorrhagic fever where case fatality rates can approach 90%. The Ebola virus VP24 protein plays a critical role in the evasion of the host immune response and is likely to interact with multiple cellular proteins. To map these interactions and better understand the potential functions of VP24, label-free quantitative proteomics was used to identify cellular proteins that had a high probability of forming the VP24 cellular interactome. Several known interactions were confirmed, thus placing confidence in the technique, but new interactions were also discovered including one with ATP1A1, which is involved in osmoregulation and cell signaling. Disrupting the activity of ATP1A1 in Ebola-virus-infected cells with a small molecule inhibitor resulted in a decrease in progeny virus, thus illustrating how quantitative proteomics can be used to identify potential therapeutic targets. PMID:25158218

García-Dorival, Isabel; Wu, Weining; Dowall, Stuart; Armstrong, Stuart; Touzelet, Olivier; Wastling, Jonathan; Barr, John N; Matthews, David; Carroll, Miles; Hewson, Roger; Hiscox, Julian A

2014-11-01

227

Exploring off-targets and off-systems for adverse drug reactions via chemical-protein interactome--clozapine-induced agranulocytosis as a case study.  

PubMed

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

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

2011-03-01

228

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-Jurgen; Spira, Felix; Kollmar, Martin; Gerlich, Daniel W; Urlaub, Henning; Gorlich, Dirk

2013-01-01

229

Ultrashort relativistic electron bunches and spatio-temporal radiation biology  

NASA Astrophysics Data System (ADS)

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

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

2008-08-01

230

Spatio-temporal coupling of EEG signals in epilepsy  

NASA Astrophysics Data System (ADS)

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

Senger, Vanessa; Müller, Jens; Tetzlaff, Ronald

2011-05-01

231

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

232

Dynamic predictive coding by the retina Toshihiko Hosoya1  

E-print Network

Dynamic predictive coding by the retina Toshihiko Hosoya1 , Stephen A. Baccus1 & Markus Meister1 that when this happens, the retina adjusts its processing dynamically. The spatio-temporal receptive fields circuits in the retina predict the local intensity from values at nearby points in space and preceding

Gutkin, Boris

233

Spatio-temporal chaos in a chemotaxis model  

NASA Astrophysics Data System (ADS)

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

Painter, Kevin J.; Hillen, Thomas

2011-02-01

234

Fluorescence advantages with microscopic spatiotemporal control  

PubMed Central

We present a clever design concept of using femtosecond laser pulses in microscopy by selective excitation or de-excitation of one fluorophore over the other overlapping one. Using either a simple pair of femtosecond pulses with variable delay or using a train of laser pulses at 20-50 Giga-Hertz excitation, we show controlled fluorescence excitation or suppression of one of the fluorophores with respect to the other through wave-packet interference, an effect that prevails even after the fluorophore coherence timescale. Such an approach can be used both under the single-photon excitation as well as in the multi-photon excitation conditions resulting in effective higher spatial resolution. Such high spatial resolution advantage with broadband-pulsed excitation is of immense benefit to multi-photon microscopy and can also be an effective detection scheme for trapped nanoparticles with near-infrared light. Such sub-diffraction limit trapping of nanoparticles is challenging and a two-photon fluorescence diagnostics allows a direct observation of a single nanoparticle in a femtosecond high-repetition rate laser trap, which promises new directions to spectroscopy at the single molecule level in solution. The gigantic peak power of femtosecond laser pulses at high repetition rate, even at low average powers, provide huge instantaneous gradient force that most effectively result in a stable optical trap for spatial control at sub-diffraction limit. Such studies have also enabled us to explore simultaneous control of internal and external degrees of freedom that require coupling of various control parameters to result in spatiotemporal control, which promises to be a versatile tool for the microscopic world. PMID:23814447

Goswami, Debabrata; Roy, Debjit; De, Arijit K.

2013-01-01

235

Spatio-temporal variability in ventricular fibrillation  

NASA Astrophysics Data System (ADS)

It is widely believed that reentrant ventricular tachycardia arises when a spiral wave of activation takes over and drives the ventricle at a rate significantly faster than sinus rhythm, and that ventricular fibrillation (VF), a spatio-temporally disorganized form of cardiac activity leading to sudden cardiac death, arises when this spiral breaks down into multiple offspring. Many authors have found that VF displays significant spatial and temporal organization. The purpose of this research is to quantify time scales and temporal and spatial variability in VF. Surface electrograms were obtained from a stable canine model of VF (cf. Nwasokwa and Bodenheimer, Am. J. Physiol. 253, H643 (1987)). These electrograms were analyzed to identify activation times to an accuracy of 1 ms (cf. Garfinkel et al., J. Clin. Invest. 99, 305 (1997)), yielded eighteen usable series, each containing over 1024 intervactivation intervals, two or three from widely spaced sites per episode of VF, 7 total episodes in 4 animals. Spatial and long-term (60 - 120 sec) temporal variability were analyzed and compared by ANOVA techniques (Evans et al., Proc. Royal Soc. B265, 2167 (1998)). In 6 of 7 episodes, spatial variability among sites was statistically more significant than variability between the first and second halves of each series. More recently, Fourier analysis of these series found three distinct scaling regions, with power law dynamics in each and break points of ca. 1 sec and 4 sec. Finally, there was significant variability in the fraction of "short" interactivation intervals (lasting < 60 of 125 ms) among sites. Together these results suggest variability in physiological properties among sites and consequent variability in spiral wave dynamics among sites.

Hastings, Harold M.; Evans, Steven J.; Fenton, Flavio H.; Garfinkel, Alan

2001-03-01

236

Spatiotemporal probability of vent opening at Mt Etna volcano (Sicily, Italy)  

NASA Astrophysics Data System (ADS)

We produced a spatiotemporal probability map of vent opening at Mt Etna, using a statistical analysis of structural features of the flank eruptions of the last 2000 years. The methodology is based on the hypothesis that the location and frequency of future events will have the same causal factors as the eruptions occurring in the past. The study is supported by a detailed knowledge of the volcano structures, including the modalities of shallow magma transfer deriving from dike and dike-fed fissure eruptions analysis on historical eruptions. The geological and structural data are converted in distinct and weighted probability density functions (PDFs), exploiting both spatial and temporal recurrence rates. The spatiotemporal probability map is obtained through a non-homogeneous Poisson process, where the expected recurrence rate per unit area is calculated as the weighted sum of the PDFs, with the weights derived from a backward/forward analysis to highlight the presence of temporal trends in the history of the volcano. The highest probability of new eruptive vents opening at Mt Etna falls within a N-S aligned area passing through the Summit Craters down to about 2000 m a.s.l. on the southern flank. Four other zones of high probability follow respectively the North-East, East-North-East, West and South Rifts, the latter reaching low altitudes (~400 m). Less susceptible areas prone to the opening of new vents were found around the faults cutting the upper portions of Mt Etna, including the western portion of the Pernicana fault system and the northern extent of the Ragalna fault system. The spatiotemporal probability map of vent opening provides detailed recurrence rates (events expected per unit area per unit time) and will hence be an important resource to predict the future timing and location of Etna eruptions. This structural-based map is the first and perhaps most important step in assessing lava flow hazards at Mt Etna, and thus represents a support tool for decision makers.

Cappello, A.; Bilotta, G.; Neri, M.; Acocella, V.; Gallo, G.; Del Negro, C.

2012-04-01

237

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

238

Light-filament dynamics and the spatiotemporal instability of the Townes profile  

SciTech Connect

The origin of the spatiotemporal filament dynamics of ultrashort pulses in nonlinear media, including axial-conical emission coupling, temporal splitting, and X waves, is explained by the spatiotemporal instability of spatially localized nonlinear modes. Our experiments support this interpretation.

Porras, Miguel A. [Departamento de Fisica Aplicada, Universidad Politecnica de Madrid, Rios Rosas 21, ES-28003 (Spain); Parola, Alberto; Faccio, Daniele [INFM and Department of Physics, University of Insubria, Via Valleggio 11, IT-22100 Como (Italy); Couairon, Arnaud [Centre de Physique Theorique, CNRS, Ecole Polytechnique, F-91128, Palaiseau (France); Di Trapani, Paolo [INFM and Department of Physics, University of Insubria, Via Valleggio 11, IT-22100 Como (Italy); Department of Quantum Electronics, Vilnius University, Sauletekio 9, LT 01222, Vilnius (Lithuania)

2007-07-15

239

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

240

Reaction diffusion equation with spatio-temporal delay  

NASA Astrophysics Data System (ADS)

We investigate reaction-diffusion equation with spatio-temporal delays, the global existence, uniqueness and asymptotic behavior of solutions for which in relation to constant steady-state solution, included in the region of attraction of a stable steady solution. It is shown that if the delay reaction function satisfies some conditions and the system possesses a pair of upper and lower solutions then there exists a unique global solution. In terms of the maximal and minimal constant solutions of the corresponding steady-state problem, we get the asymptotic stability of reaction-diffusion equation with spatio-temporal delay. Applying this theory to Lotka-Volterra model with spatio-temporal delay, we get the global solution asymptotically tend to the steady-state problem's steady-state solution.

Zhao, Zhihong; Rong, Erhua

2014-07-01

241

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

242

Yuan, M. and J. McIntosh. 2002. A Typology of Spatiotemporal Information Queries. Mining  

E-print Network

1 Chapter Yuan, M. and J. McIntosh. 2002. A Typology of Spatiotemporal Information Queries. Mining information queries is developed to summarize distinct dimensionalities of inquired information in space of temporal queries, and 4 types of spatiotemporal queries. Mining spatiotemporal information requires

Yuan, May

243

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

244

Routes to spatiotemporal chaos in Kerr optical frequency combs.  

PubMed

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. PMID:24697375

Coillet, Aurélien; Chembo, Yanne K

2014-03-01

245

Spatio-temporal speckle correlations for imaging in turbid media  

E-print Network

We discuss the far-field spatio-temporal cross-correlations of waves multiple-scattered in a turbid medium in which is embedded a hidden heterogeneous region (inclusion) characterized by a distinct scatterer dynamics (as compared to the rest of the medium). We show that the spatio-temporal correlation is affected by the inclusion which suggests a new method of imaging in turbid media. Our results allow qualitative interpretation in terms of diffraction theory: the cross-correlation of scattered waves behaves similarly to the intensity of a wave diffracted by an aperture.

S. E. Skipetrov

2001-03-22

246

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

247

Male reproductive strategy explains spatiotemporal segregation in brown bears  

PubMed Central

1. Spatiotemporal segregation is often explained by the risk for offspring predation or by differences in physiology, predation risk vulnerability or competitive abilities related to size dimorphism. 2. Most large carnivores are size dimorphic and offspring predation is often intraspecific and related to nonparental infanticide (NPI). NPI can be a foraging strategy, a strategy to reduce competition, or a male reproductive strategy. Spatiotemporal segregation is widespread among large carnivores, but its nature remains poorly understood. 3. We evaluated three hypotheses to explain spatiotemporal segregation in the brown bear, a size-dimorphic large carnivore in which NPI is common; the ‘NPI – foraging/competition hypothesis', i.e. NPI as a foraging strategy or a strategy to reduce competition, the ‘NPI – sexual selection hypothesis’, i.e. infanticide as a male reproductive strategy and the ‘body size hypothesis’, i.e. body-size-related differences in physiology, predation risk vulnerability or competitive ability causes spatiotemporal segregation. To test these hypotheses, we quantified spatiotemporal segregation among adult males, lone adult females and females with cubs-of-the-year, based on GPS-relocation data (2006–2010) and resource selection functions in a Scandinavian population. 4. We found that spatiotemporal segregation was strongest between females with cubs-of-the-year and adult males during the mating season. During the mating season, females with cubs-of-the-year selected their resources, in contrast to adult males, in less rugged landscapes in relative close proximity to certain human-related variables, and in more open habitat types. After the mating season, females with cubs-of-the-year markedly shifted their resource selection towards a pattern more similar to that of their conspecifics. No strong spatiotemporal segregation was apparent between females with cubs-of-the-year and conspecifics during the mating and the postmating season. 5. The ‘NPI – sexual selection hypothesis’ best explained spatiotemporal segregation in our study system. We suggest that females with cubs-of-the-year alter their resource selection to avoid infanticidal males. In species exhibiting NPI as a male reproductive strategy, female avoidance of infanticidal males is probably more common than observed or reported, and may come with a fitness cost if females trade safety for optimal resources. PMID:23461483

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

2013-01-01

248

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

249

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

250

Spatiotemporal modelling of viral infection dynamics  

NASA Astrophysics Data System (ADS)

Viral kinetics have been studied extensively in the past through the use of ordinary differential equations describing the time evolution of the diseased state in a spatially well-mixed medium. However, emerging spatial structures such as localized populations of dead cells might affect the spread of infection, similar to the manner in which a counter-fire can stop a forest fire from spreading. In the first phase of the project, a simple two-dimensional cellular automaton model of viral infections was developed. It was validated against clinical immunological data for uncomplicated influenza A infections and shown to be accurate enough to adequately model them. In the second phase of the project, the simple two-dimensional cellular automaton model was used to investigate the effects of relaxing the well-mixed assumption on viral infection dynamics. It was shown that grouping the initially infected cells into patches rather than distributing them uniformly on the grid reduced the infection rate as only cells on the perimeter of the patch have healthy neighbours to infect. Use of a local epithelial cell regeneration rule where dead cells are replaced by healthy cells when an immediate neighbour divides was found to result in more extensive damage of the epithelium and yielded a better fit to experimental influenza A infection data than a global regeneration rule based on division rate of healthy cell. Finally, the addition of immune cell at the site of infection was found to be a better strategy at low infection levels, while addition at random locations on the grid was the better strategy at high infection level. In the last project, the movement of T cells within lymph nodes in the absence of antigen, was investigated. Based on individual T cell track data captured by two-photon microscopy experiments in vivo, a simple model was proposed for the motion of T cells. This is the first step towards the implementation of a more realistic spatiotemporal model of HIV than those proposed thus far.

Beauchemin, Catherine

251

Elucidation of epithelial-mesenchymal transition-related pathways in a triple-negative breast cancer cell line model by multi-omics interactome analysis.  

PubMed

In life sciences, and particularly biomedical research, linking aberrant pathways exhibiting phenotype-specific alterations to the underlying physical condition or disease is an ongoing challenge. Computationally, a key approach for pathway identification is data enrichment, combined with generation of biological networks. This allows identification of intrinsic patterns in the data and their linkage to a specific context such as cellular compartments, diseases or functions. Identification of aberrant pathways by traditional approaches is often limited to biological networks based on either gene expression, protein expression or post-translational modifications. To overcome single omics analysis, we developed a set of computational methods that allow a combined analysis of data collections from multiple omics fields utilizing hybrid interactome networks. We apply these methods to data obtained from a triple-negative breast cancer cell line model, combining data sets of gene and protein expression as well as protein phosphorylation. We focus on alterations associated with the phenotypical differences arising from epithelial-mesenchymal transition in two breast cancer cell lines exhibiting epithelial-like and mesenchymal-like morphology, respectively. Here we identified altered protein signaling activity in a complex biologically relevant network, related to focal adhesion and migration of breast cancer cells. We found dysregulated functional network modules revealing altered phosphorylation-dependent activity in concordance with the phenotypic traits and migrating potential of the tested model. In addition, we identified Ser267 on zyxin, a protein coupled to actin filament polymerization, as a potential in vivo phosphorylation target of cyclin-dependent kinase 1. PMID:25124678

Pauling, Josch K; Christensen, Anne G; Batra, Richa; Alcaraz, Nicolas; Barbosa, Eudes; Larsen, Martin R; Beck, Hans C; Leth-Larsen, Rikke; Azevedo, Vasco; Ditzel, Henrik J; Baumbach, Jan

2014-10-20

252

Analysis of the Robustness of Network-Based Disease-Gene Prioritization Methods Reveals Redundancy in the Human Interactome and Functional Diversity of Disease-Genes  

PubMed Central

Complex biological systems usually pose a trade-off between robustness and fragility where a small number of perturbations can substantially disrupt the system. Although biological systems are robust against changes in many external and internal conditions, even a single mutation can perturb the system substantially, giving rise to a pathophenotype. Recent advances in identifying and analyzing the sequential variations beneath human disorders help to comprehend a systemic view of the mechanisms underlying various disease phenotypes. Network-based disease-gene prioritization methods rank the relevance of genes in a disease under the hypothesis that genes whose proteins interact with each other tend to exhibit similar phenotypes. In this study, we have tested the robustness of several network-based disease-gene prioritization methods with respect to the perturbations of the system using various disease phenotypes from the Online Mendelian Inheritance in Man database. These perturbations have been introduced either in the protein-protein interaction network or in the set of known disease-gene associations. As the network-based disease-gene prioritization methods are based on the connectivity between known disease-gene associations, we have further used these methods to categorize the pathophenotypes with respect to the recoverability of hidden disease-genes. Our results have suggested that, in general, disease-genes are connected through multiple paths in the human interactome. Moreover, even when these paths are disturbed, network-based prioritization can reveal hidden disease-gene associations in some pathophenotypes such as breast cancer, cardiomyopathy, diabetes, leukemia, parkinson disease and obesity to a greater extend compared to the rest of the pathophenotypes tested in this study. Gene Ontology (GO) analysis highlighted the role of functional diversity for such diseases. PMID:24733074

Guney, Emre; Oliva, Baldo

2014-01-01

253

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

254

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 Malskaer; Nielsen, Einar Eg

2013-01-01

255

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

NASA Astrophysics Data System (ADS)

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

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

2012-12-01

256

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

PubMed

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

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

2013-06-01

257

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

258

New model diagnostics for spatio-temporal systems in epidemiology and ecology.  

PubMed

A cardinal challenge in epidemiological and ecological modelling is to develop effective and easily deployed tools for model assessment. The availability of such methods would greatly improve understanding, prediction and management of disease and ecosystems. Conventional Bayesian model assessment tools such as Bayes factors and the deviance information criterion (DIC) are natural candidates but suffer from important limitations because of their sensitivity and complexity. Posterior predictive checks, which use summary statistics of the observed process simulated from competing models, can provide a measure of model fit but appropriate statistics can be difficult to identify. Here, we develop a novel approach for diagnosing mis-specifications of a general spatio-temporal transmission model by embedding classical ideas within a Bayesian analysis. Specifically, by proposing suitably designed non-centred parametrization schemes, we construct latent residuals whose sampling properties are known given the model specification and which can be used to measure overall fit and to elicit evidence of the nature of mis-specifications of spatial and temporal processes included in the model. This model assessment approach can readily be implemented as an addendum to standard estimation algorithms for sampling from the posterior distributions, for example Markov chain Monte Carlo. The proposed methodology is first tested using simulated data and subsequently applied to data describing the spread of Heracleum mantegazzianum (giant hogweed) across Great Britain over a 30-year period. The proposed methods are compared with alternative techniques including posterior predictive checking and the DIC. Results show that the proposed diagnostic tools are effective in assessing competing stochastic spatio-temporal transmission models and may offer improvements in power to detect model mis-specifications. Moreover, the latent-residual framework introduced here extends readily to a broad range of ecological and epidemiological models. PMID:24522782

Lau, Max S Y; Marion, Glenn; Streftaris, George; Gibson, Gavin J

2014-04-01

259

Spatiotemporal Stochastic Resonance and its consequences in a neural system  

Microsoft Academic Search

Biological neurons are good examples of a threshold device—this is why neural systems are in the focus when looking for realization of Stochastic Resonance (SR) and Spatiotemporal Stochastic Resonance (STSR) phenomena. There are two different ways to simulate neural systems—one based on differential equations, the other based on a simple threshold model. In this talk the effect of noise on

Ga´bor Bala´zsi; La´szlo´ B. Kiss; Frank E. Moss

2000-01-01

260

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

261

POSTER PRESENTATION Open Access Spatiotemporal dynamics in the human brain  

E-print Network

POSTER PRESENTATION Open Access Spatiotemporal dynamics in the human brain during rest: a virtual brain study Andreas Spiegler* , Enrique Hansen, Viktor K Jirsa From Twenty Second Annual Computational Neuroscience Meeting: CNS*2013 Paris, France. 13-18 July 2013 Over the past years the ongoing human brain

Paris-Sud XI, Université de

262

Instabilities and solitons in systems with spatiotemporal dispersion  

E-print Network

propagation near the tail of an exciton-polariton resonance in a specially designed semiconductor superlatticeInstabilities and solitons in systems with spatiotemporal dispersion Fabio Biancalana1, "Experimental Demonstration of the Fermi-Pasta-Ulam Recurrence in a Modulationally Unstable Optical Wave," Phys

263

Adaptive joint spatio-temporal error concealment for video communication  

Microsoft Academic Search

In the past years, video communication has found its application in an increasing number of environments. Unfor- tunately, some of them are error-prone and the risk of block losses caused by transmission errors is ubiquitous. To reduce the effects of these block losses, a new spatio-temporal error concealment algorithm is presented. The algorithm uses spatial as well as temporal information

Jürgen Seiler; André Kaup

2008-01-01

264

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

265

Spatiotemporal Distributions of Migratory Birds: Patchy Models with Delay  

Microsoft Academic Search

We derive and analyze a mathematical model for the spatiotemporal distribution of a migratory bird species. The birds have specific sites for breeding and winter feeding, and usually several stopover sites along the migration route, and therefore a patch model is the natural choice. However, we also model the journeys of the birds along the flyways, and this is achieved

Stephen A. Gourley; Rongsong Liu; Jianhong Wu

2010-01-01

266

Distributed Spatio-Temporal Similarity Search Zeinalipour-Yazti  

E-print Network

applications in a wide array of domains, such as cellular networks, wildlife monitoring and video surveillance-temporal Similarity Search, Top-K Query Processing 1. INTRODUCTION The advances in networking technologies along with the wide availability of GPS technology in commodity devices, make spatiotemporal records nowadays

Zeinalipour, Demetris

267

Actin Filament Segmentation using Spatiotemporal Active-Surface and  

E-print Network

Actin Filament Segmentation using Spatiotemporal Active-Surface and Active-Contour Models Hongsheng a novel algorithm for actin filament segmen- tation in a 2D TIRFM image sequence. We treat the 2D time of this approach. 1 Introduction Actin proteins spontaneously assemble into long polymers to build networks

Huang, Xiaolei

268

Spatio-temporal saliency perception via hypercomplex frequency spectral contrast.  

PubMed

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

269

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

270

Nonequilibrium pattern formation and spatiotemporal chaos in fluid convection  

SciTech Connect

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

Michael Cross

2006-09-13

271

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

272

Spatiotemporal Patterns of Spindle Oscillations in Cortex and Thalamus  

E-print Network

Spatiotemporal Patterns of Spindle Oscillations in Cortex and Thalamus Diego Contreras,1 Alain in the thalamus and cor- tex during early stages of sleep. They are generated by the combination of intrinsic oscillations throughout the thalamus are less organized, but the local co- herence (within 2­4 mm) is still

Destexhe, Alain

273

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

274

Spatio-temporal analysis of environmental radiation in Korea  

SciTech Connect

Geostatistical visualization of environmental radiation is a very powerful approach to explore and understand spatio-temporal variabilities of environmental radiation data. Spatial patterns of environmental radiation can be described quantitatively in terms of variogram and kriging, which are based on the idea that statistical variation of data are functions of distance. (authors)

Kim, J.Y.; Lee, B.C. [Seoul National Univ., FNC Technology Co., Ltd. (Korea, Republic of); Shin, H.K. [Korea Institute of Nuclear Safety, Yuseong-gu, Daejeon (Korea, Republic of)

2007-07-01

275

The Truncated Tornado in TMBB: A Spatiotemporal Uncertainty Model for  

E-print Network

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

Bae, Wan

276

Toward Understanding Tornado Formation Through Spatiotemporal Data Mining  

E-print Network

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

McGovern, Amy

277

Learning Overcomplete Spatiotemporal Bubbles from Natural Image Sequences  

E-print Network

Learning Overcomplete Spatiotemporal Bubbles from Natural Image Sequences Libo Ma, and Liqing Zhang, China malibo@sjtu.edu.cn zhang-lq@cs.sjtu.edu.cn Abstract Recently, bubble coding for natural image the complete representation. In this paper, we use Bayesian estimation to extend the bubble coding

Zhang, Liqing

278

Fast Spatiotemporal Smoothing of Calcium Measurements in Dendritic Trees  

E-print Network

1 Fast Spatiotemporal Smoothing of Calcium Measurements in Dendritic Trees Eftychios A smoothing of calcium signals in dendritic trees, given spatially localized imaging data obtained via multi that the cost of the algorithm is also linear in the size of the dendritic tree, making the approach applicable

Columbia University

279

Spatio-temporal EEG source localization using simulated annealing  

Microsoft Academic Search

The estimation of multiple dipole parameters in spatio-temporal source modeling (STSM) of electroencephalographic (EEG) data is a difficult nonlinear optimization problem due to multiple local minima in the cost function. A straightforward iterative optimization approach to such a problem is very susceptible to being trapped in a local minimum, thereby resulting in incorrect estimates of the dipole parameters. Here, the

Deepak Khosla; Manbir Singh; Manuel Don

1997-01-01

280

Environmental heterogeneity and spatiotemporal variability in plant defense traits  

E-print Network

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

Cronin, James T.

281

Judgments about spatio-temporal relations Thomas Bittner  

E-print Network

be able to represent the fact that things move, change, appear, and disappear over time. In this paper we distinct subway trains five meters apart without having had the chance to meet. They have been in different-temporal objects and their location 2.1 Objects and their location Spatio-temporal objects fall into two major

Bittner, Thomas

282

Spatio-Temporal Signal Recovery from Political Tweets in Indonesia  

E-print Network

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

Davulcu, Hasan

283

Spatio-Temporal Dynamics of Cross Polarized Wave Generation  

NASA Astrophysics Data System (ADS)

We use time-domain Spatially and Spectrally Resolved Interferometry (SSRI) to investigate cross-polarized wave (XPW) generation in barium fluoride. We find that the XPW pulse is ?3 smaller than the input in the spatiotemporal domain regardless of the input chirp. Additionally, we calculate a temporally dependent focal length resulting from the nonlinear interaction, and discuss its implications.

Adams, Daniel; Squier, Jeff; Durfee, Charles

2009-10-01

284

Spatio-temporal structures of laser-induced anisotropy  

NASA Astrophysics Data System (ADS)

We report new observations of optical spatio-temporal structures formed in terbium gallium garnet when it is excited at resonance by a strong laser beam. We also present a theoretical description of this pattern formation, which accounts well for our observations. We finally discuss useful applications of both time and power dependence of these structures.

Chen, X.; Chaux, R.

1999-11-01

285

Spatio-temporal structures of laser-induced anisotropy  

Microsoft Academic Search

We report new observations of optical spatio-temporal structures formed in terbium gallium garnet when it is excited at resonance by a strong laser beam. We also present a theoretical description of this pattern formation, which accounts well for our observations. We finally discuss useful applications of both time and power dependence of these structures.

X. Chen; R. Chaux

1999-01-01

286

Spatio-temporal metamodeling for West African monsoon Anestis Antoniadisa  

E-print Network

Spatio-temporal metamodeling for West African monsoon Anestis Antoniadisa , Céline Helberta in Western Africa : West African Monsoon. We are particularly interested in studying the influence of sea-temporal modeling, filtering, multivariate penalized regression 1. Introduction West African monsoon is the major

Paris-Sud XI, Université de

287

Socioscope: Spatio-Temporal Signal Recovery from Social Media  

E-print Network

Socioscope: Spatio-Temporal Signal Recovery from Social Media Jun-Ming Xu , Aniruddha Bhargava: where, when, and how much. Social media is a tantaliz- ing data source for those who wish to monitor to count its occurrences in social media. However, count- ing is plagued by sample bias, incomplete data

Nowak, Robert

288

Fully Bayesian spatio-temporal modeling of FMRI data  

Microsoft Academic Search

We present a fully Bayesian approach to modeling in functional magnetic resonance imaging (FMRI), incorporating spatio-temporal noise modeling and haemodynamic response function (HRF) modeling. A fully Bayesian approach allows for the uncertainties in the noise and signal modeling to be incorporated together to provide full posterior distributions of the HRF parameters. The noise modeling is achieved via a nonseparable space-time

Mark William Woolrich; Mark Jenkinson; J. Michael Brady; Stephen M. Smith

2004-01-01

289

Locally Regularized Spatiotemporal Modeling and Model Comparison for Functional MRI  

E-print Network

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

Rotstein, Horacio G.

290

RESEARCH ARTICLE Fully refocused multi-shot spatiotemporally encoded MRI  

E-print Network

RESEARCH ARTICLE Fully refocused multi-shot spatiotemporally encoded MRI: robust imaging of SPEN-based imaging in the multi-shot MRI of objects, subject to sizable field inhomogeneities that com- plicate conventional imaging approaches. Materials and methods 2D MRI experiments were per- formed at 7

Frydman, Lucio

291

Spatio-Temporal Data Fusion in Cerebral Angiography  

E-print Network

Spatio-Temporal Data Fusion in Cerebral Angiography by Andrew David Copeland B.S., Electrical in Cerebral Angiography by Andrew David Copeland Submitted to the Department of Electrical Engineering- olution time sequences of 3D images that show the dynamics of cerebral blood flow. These sequences allow

Mitter, Sanjoy K.

292

The GLIMS Glacier Database: a spatio-temporal database  

E-print Network

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

Raup, Bruce H.

293

Video Monitoring of Slope Failure Using Spatiotemporal Gabor Filtering  

Microsoft Academic Search

We propose a method for detecting precursors, such as small rock and\\/or soil fall, which occur prior to massive slope failure. The key feature of our method is directly recognizing the trajectory of a small collapse using spatiotemporal Gabor filtering. Simulation analysis, where the conditions of the simulation are quantitatively defined, reveals the effectiveness of the proposed method in detecting

Ken Okamoto; Toshio Watanabe; Akitoshi Hanazawa; Takashi Morie; Hiroshi Ban; Yuji Maeda

2009-01-01

294

Literature review of spatio-temporal database models  

Microsoft Academic Search

Recent efforts in spatial and temporal data models and database systems attempt to achieve an appropriate kind of interaction between the two areas. This paper reviews the different types of spatio-temporal data models that have been proposed in the literature as well as new theories and concepts that have emerged. It provides an overview of previous achievements within the domain

NIKOS PELEKIS; BABIS THEODOULIDIS; IOANNIS KOPANAKIS; YANNIS THEODORIDIS

2004-01-01

295

Spatiotemporal coding of sound in the auditory nerve  

E-print Network

Spatiotemporal coding of sound in the auditory nerve for cochlear implants Ian Christopher Bruce of acoustical and electrical stimuli. In particular, questions and applications of interest to cochlear implant of input fibres is very narrow and temporal integration is very short. In contrast, cochlear nucleus cell

Bruce, Ian

296

Querying Uncertain Spatio-Temporal Data Tobias Emrich #1  

E-print Network

Querying Uncertain Spatio-Temporal Data Tobias Emrich #1 , Hans-Peter Kriegel #1 , Nikos Mamoulis 2 of modeling and managing uncertain data has received a great deal of interest, due to its manifold ap for the economic representation and storage of the data, since only a subset of the object locations need

Kriegel, Hans-Peter

297

Football analysis using spatio-temporal tools Joachim Gudmundsson  

E-print Network

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

Wolle, Thomas

298

Towards Integrating Real-World Spatiotemporal Data with Social Networks  

E-print Network

social activities from the history of people's movements in the real world, i.e., who has been whereTowards Integrating Real-World Spatiotemporal Data with Social Networks Huy Pham Ling Hu Cyrus Shahabi Integrated Media Systems Center University of Southern California (USC) Los Angeles, California

Shahabi, Cyrus

299

A spatio-temporal data mining method for dynamic monitoring of land use  

NASA Astrophysics Data System (ADS)

This study investigated how to manage and use the spatio-temporal data during land use. To realize spatio-temporal data mining, the key issue to be solved in technology is how to organize spatio-temporal data. The spatio-temporal data model is just generated to solve this problem. According to analysis of spatio-temporal data changing character, two factors are very important in spatio-temporal data model. One is object, and the other is event. The object is an essential element that comprises spatio-temporal data information. The event is a fundamental factor that result in changing spatio-temporal data. A new spatio-temporal data model based on both object and event (OESTDM) was put forward to meet the demand. How to organize data, build relations between objects and storage data in spatio-temporal database are also emphatically discussed. At last, a dynamic land use information system based on OESTDM is presented. The system realized the function of managing spatio-temporal data, the retrospect of history information, tracing land parcel change, Area-Data-Change-Statistic and Analysis, and so on efficiently, by taking the land parcel data of some regions in Zhejiang province for study.

Teng, Longmei; Liu, Renyi; Liu, Nan

2005-10-01

300

A psychophysical and computational analysis of the spatio-temporal mechanisms underlying the flash-lag effect.  

PubMed

Several accounts put forth to explain the flash-lag effect (FLE) rely mainly on either spatial or temporal mechanisms. Here we investigated the relationship between these mechanisms by psychophysical and theoretical approaches. In a first experiment we assessed the magnitudes of the FLE and temporal-order judgments performed under identical visual stimulation. The results were interpreted by means of simulations of an artificial neural network, that was also employed to make predictions concerning the FLE. The model predicted that a spatio-temporal mislocalisation would emerge from two, continuous and abrupt-onset, moving stimuli. Additionally, a straightforward prediction of the model revealed that the magnitude of this mislocalisation should be task-dependent, increasing when the use of the abrupt-onset moving stimulus switches from a temporal marker only to both temporal and spatial markers. Our findings confirmed the model's predictions and point to an indissoluble interplay between spatial facilitation and processing delays in the FLE. PMID:19227376

Cravo, André M; Baldo, Marcus V C

2008-01-01

301

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

302

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

PubMed Central

In this paper, asymmetric spatiotemporal chaos induced by a polypoid mass simulating the laryngeal pathology of a vocal polyp is experimentally observed using high-speed imaging in an excised larynx. Spatiotemporal analysis reveals that the normal vocal folds show spatiotemporal correlation and symmetry. Normal vocal fold vibrations are dominated mainly by the first vibratory eigenmode. However, pathological vocal folds with a polypoid mass show broken symmetry and spatiotemporal irregularity. The spatial correlation is decreased. The pathological vocal folds spread vibratory energy across a large number of eigenmodes and induce asymmetric spatiotemporal chaos. High-order eigenmodes show complicated dynamics. Spatiotemporal analysis provides a valuable biomedical application for investigating the spatiotemporal chaotic dynamics of pathological vocal fold systems with a polypoid mass and may represent a valuable clinical tool for the detection of laryngeal mass lesion using high-speed imaging. PMID:19123612

Zhang, Yu; Jiang, Jack J.

2008-01-01

303

Spatio-temporal soil moisture distribution in a Maize field  

NASA Astrophysics Data System (ADS)

The spatio-temporal distribution of water content is important for predicting water flow and solute transport in the unsaturated zone. In a cropped field, this distribution is affected by the interception and redistribution of water by the plants, by surface runoff, by root water uptake, and by the distribution of soil hydraulic properties and boundary conditions of the system. This study was conducted to investigate the relationship between plant root water uptake, soil structure and flow field variability. An experimental plot in a Maize field was installed in July 2009 and measurements were performed between the 23 of July and the 21 of September 2009. Upper boundary conditions were followed with a weather station, while drainage was estimated with deep tensiometers (1.4 m). Four TDR profiles (14 TDR probes at 10, 30, 70 and 125 cm depth) perpendicular to two maize rows were monitored every hour. In addition, a square grid of 76 surface electrodes and 8 boreholes each with 7 electrodes (5, 15, 30, 50, 75, 105 and 140 cm deep) were inserted in the maize field to evaluate the 3-D distribution of the electrical conductivity by ERT. Weekly ERT measurements were performed. Subsequently, the ERT and TDR data were used to estimate the soil moisture dynamics based on petrophysical relationships. We performed root profiles at four times during the experiment to quantify the root distribution. This allowed us to investigate the relationship between plant root water uptake and soil moisture dynamics. After the growing season, a dye tracer experiment was conducted on a 1.4 m-side square, to assess the influence of roots and macropores in water infiltration. The results show the importance of using depth electrodes to estimate the vertical distribution of water content accurately. A high measurement resolution allowed us to observe the 3-D soil water content variability. During the growing season, we observed an increase in the coefficient of variation of soil water content when the soil becomes drier. This is in agreement with the results obtained by Hupet and Vanclooster (2005). Water dynamics in the topsoil was higher than in the lower layer. It seems that the distribution of water content at the end of the growing season was significantly influenced by the row / inter-row of maize and therefore by root water uptake. This highlights the importance of seeding patterns on soil moisture distribution in a field. Reference: F. Hupet and A. Vanclooster. Micro-variability of hydrological processes at the maize row scale: implications for soil water content measurements and evapotranspiration estimates. Journal Of Hydrology, 303(1-4):247-270, March 2005.

Beff, Laure; Couvreur, Valentin; Javaux, Mathieu

2010-05-01

304

Spatio-Temporally Restricted Expression of Cell Adhesion Molecules during Chicken Embryonic Development  

PubMed Central

Differential cell adhesive properties are known to regulate important developmental events like cell sorting and cell migration. Cadherins and protocadherins are known to mediate these cellular properties. Though a large number of such molecules have been predicted, their characterization in terms of interactive properties and cellular roles is far from being comprehensive. To narrow down the tissue context and collect correlative evidence for tissue specific roles of these molecules, we have carried out whole-mount in situ hybridization based RNA expression study for seven cadherins and four protocadherins. In developing chicken embryos (HH stages 18, 22, 26 and 28) cadherins and protocadherins are expressed in tissue restricted manner. This expression study elucidates precise expression domains of cell adhesion molecules in the context of developing embryos. These expression domains provide spatio-temporal context in which the function of these genes can be further explored. PMID:24806091

Roy, Priti; Bandyopadhyay, Amitabha

2014-01-01

305

Efficient Bayesian multivariate fMRI analysis using a sparsifying spatio-temporal prior.  

PubMed

Bayesian logistic regression with a multivariate Laplace prior is introduced as a multivariate approach to the analysis of neuroimaging data. It is shown that, by rewriting the multivariate Laplace distribution as a scale mixture, we can incorporate spatio-temporal constraints which lead to smooth importance maps that facilitate subsequent interpretation. The posterior of interest is computed using an approximate inference method called expectation propagation and becomes feasible due to fast inversion of a sparse precision matrix. We illustrate the performance of the method on an fMRI dataset acquired while subjects were shown handwritten digits. The obtained models perform competitively in terms of predictive performance and give rise to interpretable importance maps. Estimation of the posterior of interest is shown to be feasible even for very large models with thousands of variables. PMID:19958837

van Gerven, Marcel A J; Cseke, Botond; de Lange, Floris P; Heskes, Tom

2010-03-01

306

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

307

Proteomic Profiling of the TRAF3 Interactome Network Reveals a New Role for the ER-to-Golgi Transport Compartments in Innate Immunity  

PubMed Central

Tumor Necrosis Factor receptor-associated factor-3 (TRAF3) is a central mediator important for inducing type I interferon (IFN) production in response to intracellular double-stranded RNA (dsRNA). Here, we report the identification of Sec16A and p115, two proteins of the ER-to-Golgi vesicular transport system, as novel components of the TRAF3 interactome network. Notably, in non-infected cells, TRAF3 was found associated with markers of the ER-Exit-Sites (ERES), ER-to-Golgi intermediate compartment (ERGIC) and the cis-Golgi apparatus. Upon dsRNA and dsDNA sensing however, the Golgi apparatus fragmented into cytoplasmic punctated structures containing TRAF3 allowing its colocalization and interaction with Mitochondrial AntiViral Signaling (MAVS), the essential mitochondria-bound RIG-I-like Helicase (RLH) adaptor. In contrast, retention of TRAF3 at the ER-to-Golgi vesicular transport system blunted the ability of TRAF3 to interact with MAVS upon viral infection and consequently decreased type I IFN response. Moreover, depletion of Sec16A and p115 led to a drastic disorganization of the Golgi paralleled by the relocalization of TRAF3, which under these conditions was unable to associate with MAVS. Consequently, upon dsRNA and dsDNA sensing, ablation of Sec16A and p115 was found to inhibit IRF3 activation and anti-viral gene expression. Reciprocally, mild overexpression of Sec16A or p115 in Hec1B cells increased the activation of IFN?, ISG56 and NF-?B -dependent promoters following viral infection and ectopic expression of MAVS and Tank-binding kinase-1 (TBK1). In line with these results, TRAF3 was found enriched in immunocomplexes composed of p115, Sec16A and TBK1 upon infection. Hence, we propose a model where dsDNA and dsRNA sensing induces the formation of membrane-bound compartments originating from the Golgi, which mediate the dynamic association of TRAF3 with MAVS leading to an optimal induction of innate immune responses. PMID:22792062

Khan, Kashif Aziz; D'Ambrosio, Lisa M.; Do, Florence; St-Amant-Verret, Myriam; Wissanji, Tasheen; Emery, Gregory; Gingras, Anne-Claude; Meloche, Sylvain; Servant, Marc J.

2012-01-01

308

Video saliency incorporating spatiotemporal cues and uncertainty weighting.  

PubMed

We propose a novel algorithm to detect visual saliency from video signals by combining both spatial and temporal information and statistical uncertainty measures. The main novelty of the proposed method is twofold. First, separate spatial and temporal saliency maps are generated, where the computation of temporal saliency incorporates a recent psychological study of human visual speed perception. Second, the spatial and temporal saliency maps are merged into one using a spatiotemporally adaptive entropy-based uncertainty weighting approach. The spatial uncertainty weighing incorporates the characteristics of proximity and continuity of spatial saliency, while the temporal uncertainty weighting takes into account the variations of background motion and local contrast. Experimental results show that the proposed spatiotemporal uncertainty weighting algorithm significantly outperforms state-of-the-art video saliency detection models. PMID:25051549

Fang, Yuming; Wang, Zhou; Lin, Weisi; Fang, Zhijun

2014-09-01

309

Spatiotemporal representation of moving luminance edges in human vision.  

PubMed

The edges of straight bars in a square-wave luminance grating appear undulating to an observer when the retinal image of this pattern is in motion. The amplitude of the perceived undulations increases linearly with retinal image speed with an average slope of 30 +/- 4 ms. The period of the motion-induced bulges is 2.5 +/- 0.5 degree and shows no consistent variation with the retinal image velocity of the pattern. The close quantitative agreement between the spatiotemporal extent of this effect and recent estimates of the spatiotemporal parameters of human motion-sensitive mechanisms suggests the existence of motion-sensitive cells in the central nervous system that have a fixed time constant but change the shape and size of their retinal support with retinal image velocity. PMID:2067723

Marcus, J T; Toet, A

1991-04-01

310

Spatiotemporal intermittency and scaling laws in coupled map lattices  

E-print Network

We discuss the spatiotemporal intermittency (STI) seen in coupled map lattices (CML-s). We identify the types of intermittency seen in such systems in the context of several specific CML-s. The Chat\\'e-Manneville CML is introduced and the on-going debate on the connection of the spatiotemporal intermittency seen in this model with the problem of directed percolation is summarised. We also discuss the STI seen in the sine circle map model and its connection with the directed percolation problem, as well as the inhomogenous logistic map lattice which shows the novel phenomenon of spatial intermittency and other types of behaviour not seen in the other models. The connection of the bifurcation behaviour in this model with STI is touched upon. We conclude with a discussion of open problems.

Neelima Gupte; Zahera Jabeen

2005-04-11

311

Application of spatio-temporal filtering to fetal electrocardiogram enhancement.  

PubMed

In this paper we propose a new structure of the instrumentation for electrocardiographic fetal monitoring. We apply a single-channel approach to maternal electrocardiogram suppression in the recorded four abdominal bioelectric signals. Then we exploit spatial and temporal properties of the extracted four-channel fetal electrocardiogram to construct a new channel with higher signal-to-noise ratio. Finally, we perform detection of fetal QRS complexes. The proposed approach is investigated with the help of the constructed database of the maternal abdominal signals. During the detection tests, the spatio-temporal filtering allowed us to decrease significantly the number of the detection errors of different detectors applied. Moreover, we present visually that even if the fetal QRS complexes are buried in noise, the spatio-temporal filtering can produce the signal with the discernible ones. PMID:20701992

Kotas, M; Jezewski, J; Horoba, K; Matonia, A

2011-10-01

312

Predicting Forest Microclimate in Heterogeneous Landscapes  

Microsoft Academic Search

Forest microclimate plays an integral role in ecosystem processes, yet a predictive understanding of its spatial and temporal\\u000a variability in heterogeneous landscapes is largely lacking. In this study, we used regression kriging (RK) to analyze the\\u000a degree to which physiographic versus ecological variables influence spatio-temporal variation in understory microclimate conditions.\\u000a We monitored understory temperature in 200 forest plots within a

T. Vanwalleghem; R. K. Meentemeyer

2009-01-01

313

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

314

Vector zonal operations for spatio-temporal analysis  

E-print Network

and Geographic Information Science, 32(1): 17- 32. Vary only in Space Vary only in time Vary both in space and time NEXRAD Precipitation Database • Radar estimates of precipitation (correct with available rain gauges) • 4km x 4km spatial resolution • Hourly... temporal resolution • NEXRAD Tool Spatiotemporal Vector Zone Calculate daily sub-watershed precipitation for non-point source pollution models + 24 hours (daily) time Area Weight Precipitation ? ? = == 9 1 9 1 * i i i ii a ap p Antecedent...

Xu, Tingting

2008-11-19

315

Mining spatio-temporal patterns in object mobility databases  

Microsoft Academic Search

With the increasing use of wireless communication devices and the ability to track people and objects cheaply and easily,\\u000a the amount of spatio-temporal data is growing substantially. Many of these applications cannot easily locate the exact position\\u000a of objects, but they can determine the region in which each object is contained. Furthermore, the regions are fixed and may\\u000a vary greatly

Florian Verhein; Sanjay Chawla

2008-01-01

316

Bayesian Spatiotemporal Context Integration Sources in Robot Vision Systems  

Microsoft Academic Search

Having as a main motivation the development of robust and high performing robot vision systems that can operate in dynamic\\u000a environments, we propose a bayesian spatiotemporal context-based vision system for a mobile robot with a mobile camera, which\\u000a uses three different context-coherence instances: current frame coherence, last frame coherence and high level tracking coherence\\u000a (coherence with tracked objects). We choose

Rodrigo Palma Amestoy; Pablo Guerrero; Javier Ruiz-del-solar; Claudio Garretón

2008-01-01

317

On the persistence of spatiotemporal oscillations generated by invasion  

NASA Astrophysics Data System (ADS)

Many systems in biology and chemistry are oscillatory, with a stable, spatially homogeneous steady state which consists of periodic temporal oscillations in the interacting species, and such systems have been extensively studied on infinite or semi-infinite spatial domains. We consider the effect of a finite domain, with zero-flux boundary conditions, on the behaviour of solutions to oscillatory reaction-diffusion equations after invasion. We begin by considering numerical simulations of various oscillatory predatory-prey systems. We conclude that when regular spatiotemporal oscillations are left in the wake of invasion, these die out, beginning with a decrease in the spatial frequency of the oscillations at one boundary, which then propagates across the domain. The long-time solution in this case is purely temporal oscillations, corresponding to the limit cycle of the kinetics. Contrastingly, when irregular spatiotemporal oscillations are left in the wake of invasion, they persist, even in very long time simulations. To study this phenomenon in more detail, we consider the {lambda}-{omega} class of reaction-diffusion systems. Numerical simulations show that these systems also exhibit die-out of regular spatiotemporal oscillations and persistence of irregular spatiotemporal oscillations. Exploiting the mathematical simplicity of the {lambda}-{omega} form, we derive analytically an approximation to the transition fronts in r and {theta}x which occur during the die-out of the regular oscillations. We then use this approximation to describe how the die-out occurs, and to derive a measure of its rate, as a function of parameter values. We discuss applications of our results to ecology, calcium signalling and chemistry.

Kay, A. L.; Sherratt, J. A.

1999-10-01

318

Spatiotemporal wavelet maximum a posteriori estimation for video denoising  

NASA Astrophysics Data System (ADS)

We examine one way to extend recently proposed wavelet-based maximum a posteriori estimation rules for image denoising to video. The proposed approach takes into account both spatial and temporal dependencies between wavelet coefficients, and is general enough to incorporate different spherically contoured prior distributions on noiseless coefficients, as well as different spatiotemporal coefficient neighborhoods. Presented extensions of the algorithm have reasonable complexity and are suited to vectorized, convolution-based implementations.

Khazron, Pavel A.; Selesnick, Ivan W.

2010-10-01

319

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

320

Spatiotemporal modes of climatic variability: building blocks of complex networks?  

NASA Astrophysics Data System (ADS)

The theory of complex networks offers a rich set of tools aimed at understanding various aspects of high-dimensional spatiotemporal systems [1]. Recently, methods based on complex network theory have been applied to quantities characterizing climatic variability (e.g. [2]) with the aim of characterizing the behavior of the atmospheric system. Typically, complex network methods are applied directly to reanalysis data [3], which are available on a high resolution planetary grid. An important pre-requisite to the application of complex network methods is the quantification of pairwise interactions in the spatiotemporal process. When estimating such dependencies, multiple sources of bias must be taken into account, such as spatial smoothness [4] or dynamical memory variability [5]. The attenuation or mitigation of selected biases may be aided by a suitable reduced representation of the climatic spatiotemporal process. We study decompositions based on multivariate analysis methods such as PCA, ICA or spectral clustering [6] with the purpose of providing a reduced representation of the climate system amenable to analysis using symmetric and asymmetric dependence measures. Some of the key studied questions are robustness, temporal variability and method-induced bias of the obtained spatiotemporal components. Robustness of the components is an important facet of the general validity of the decomposition and strongly affects the suitability of the resulting components as nodes in a complex network. Temporal variability will be studied especially with respect to the activity of the North Atlantic Oscillation (NAO), a major climatic mode in the Northern hemisphere. Acknowledgment This study is supported by the Czech Science Foundation, Project No. P103/11/J068.

Vejmelka, M.; Hlinka, J.; Hartman, D.; Palus, M.

2012-04-01

321

Spatio-temporal analysis of early brain development  

Microsoft Academic Search

Analysis of human brain development is a crucial step for improved understanding of neurodevelopmental disorders. We focus on normal brain development as is observed in the multimodal longitudinal MRI\\/DTI data of neonates to two years of age. We present a spatio-temporal analysis framework using Gompertz function as a population growth model with three different spatial localization strategies: voxel-based, data driven

Neda Sadeghi; Marcel Prastawa; John H. Gilmore; Weili Lin; Guido Gerig

2010-01-01

322

Stability of Wavelengths and Spatiotemporal Intermittency in Coupled Map Lattices  

E-print Network

In relation to spatiotemporal intermittency, as it can be observed in coupled map lattices, we study the stability of different wavelengths in competition. Introducing a two dimensional map, we compare its dynamics with the one of the whole lattice. We conclude a good agreement between the two. The reduced model also allows to introduce an order parameter which combines the diffusion parameter and the spatial wavelength under consideration.

A. Lambert; R. Lima

1994-08-01

323

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

324

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

325

Visual memory performance for color depends on spatiotemporal context.  

PubMed

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

Olivers, Christian N L; Schreij, Daniel

2014-10-01

326

A Bayesian spatio-temporal method for disease outbreak detection  

PubMed Central

A system that monitors a region for a disease outbreak is called a disease outbreak surveillance system. A spatial surveillance system searches for patterns of disease outbreak in spatial subregions of the monitored region. A temporal surveillance system looks for emerging patterns of outbreak disease by analyzing how patterns have changed during recent periods of time. If a non-spatial, non-temporal system could be converted to a spatio-temporal one, the performance of the system might be improved in terms of early detection, accuracy, and reliability. A Bayesian network framework is proposed for a class of space-time surveillance systems called BNST. The framework is applied to a non-spatial, non-temporal disease outbreak detection system called PC in order to create the spatio-temporal system called PCTS. Differences in the detection performance of PC and PCTS are examined. The results show that the spatio-temporal Bayesian approach performs well, relative to the non-spatial, non-temporal approach. PMID:20595315

Cooper, Gregory F

2010-01-01

327

Plasticity of recurring spatiotemporal activity patterns in cortical networks  

NASA Astrophysics Data System (ADS)

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.

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

2007-09-01

328

Spatiotemporal relaxation of electrons in non-isothermal plasmas  

NASA Astrophysics Data System (ADS)

A powerful method for the study of time-dependent electron kinetics in spatially one-dimensional plasmas is presented. The method is based on the solution of the space- and time-dependent kinetic equation for the electron velocity distribution function in two-term approximation. The resulting three-dimensional partial differential equation for the isotropic part of the velocity distribution function is numerically solved as an initial-boundary value problem over the space of the spatial coordinate and the total energy proceeding in time. As an application, the spatiotemporal relaxation of electrons in the column-anode plasma of a glow discharge in krypton, acted upon by a space-independent electric field and initiated by a constant electron influx at the cathode side of the plasma, is studied. The electron relaxation process is traced up to the establishment into a spatially structured, time-independent state. A detailed analysis of the spatiotemporal behaviour of the velocity distribution function and relevant macroscopic quantities of the electrons is given for different electric field strengths and boundary conditions. In particular, a significant increase in the relaxation time of the spatiotemporal electron relaxation compared with the relaxation time to approach steady state in spatially homogeneous plasmas has been found.

Loffhagen, D.; Winkler, R.

2001-05-01

329

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

330

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

331

A novel multiresolution spatiotemporal saliency detection model and its applications in image and video compression.  

PubMed

Salient areas in natural scenes are generally regarded as areas which the human eye will typically focus on, and finding these areas is the key step in object detection. In computer vision, many models have been proposed to simulate the behavior of eyes such as SaliencyToolBox (STB), Neuromorphic Vision Toolkit (NVT), and others, but they demand high computational cost and computing useful results mostly relies on their choice of parameters. Although some region-based approaches were proposed to reduce the computational complexity of feature maps, these approaches still were not able to work in real time. Recently, a simple and fast approach called spectral residual (SR) was proposed, which uses the SR of the amplitude spectrum to calculate the image's saliency map. However, in our previous work, we pointed out that it is the phase spectrum, not the amplitude spectrum, of an image's Fourier transform that is key to calculating the location of salient areas, and proposed the phase spectrum of Fourier transform (PFT) model. In this paper, we present a quaternion representation of an image which is composed of intensity, color, and motion features. Based on the principle of PFT, a novel multiresolution spatiotemporal saliency detection model called phase spectrum of quaternion Fourier transform (PQFT) is proposed in this paper to calculate the spatiotemporal saliency map of an image by its quaternion representation. Distinct from other models, the added motion dimension allows the phase spectrum to represent spatiotemporal saliency in order to perform attention selection not only for images but also for videos. In addition, the PQFT model can compute the saliency map of an image under various resolutions from coarse to fine. Therefore, the hierarchical selectivity (HS) framework based on the PQFT model is introduced here to construct the tree structure representation of an image. With the help of HS, a model called multiresolution wavelet domain foveation (MWDF) is proposed in this paper to improve coding efficiency in image and video compression. Extensive tests of videos, natural images, and psychological patterns show that the proposed PQFT model is more effective in saliency detection and can predict eye fixations better than other state-of-the-art models in previous literature. Moreover, our model requires low computational cost and, therefore, can work in real time. Additional experiments on image and video compression show that the HS-MWDF model can achieve higher compression rate than the traditional model. PMID:19709976

Guo, Chenlei; Zhang, Liming

2010-01-01

332

Learning Functional Object-Categories from a Relational Spatio-Temporal Representation  

Microsoft Academic Search

We propose a framework that learns functional object- categories from spatio-temporal data sets such as those abstracted from video. The data is represented as one activity graph that encodes qualitative spatio-temporal patterns of interaction betw een objects. Event classes are induced by statistical generalization, t he instances of which encode similar patterns of spatio-temporal relati onships be- tween objects. Equivalence

Muralikrishna Sridhar; Anthony G. Cohn; David C. Hogg

2008-01-01

333

Model-driven development of covariances for spatiotemporal environmental health assessment.  

PubMed

Known conceptual and technical limitations of mainstream environmental health data analysis have directed research to new avenues. The goal is to deal more efficiently with the inherent uncertainty and composite space-time heterogeneity of key attributes, account for multi-sourced knowledge bases (health models, survey data, empirical relationships etc.), and generate more accurate predictions across space-time. Based on a versatile, knowledge synthesis methodological framework, we introduce new space-time covariance functions built by integrating epidemic propagation models and we apply them in the analysis of existing flu datasets. Within the knowledge synthesis framework, the Bayesian maximum entropy theory is our method of choice for the spatiotemporal prediction of the ratio of new infectives (RNI) for a case study of flu in France. The space-time analysis is based on observations during a period of 15 weeks in 1998-1999. We present general features of the proposed covariance functions, and use these functions to explore the composite space-time RNI dependency. We then implement the findings to generate sufficiently detailed and informative maps of the RNI patterns across space and time. The predicted distributions of RNI suggest substantive relationships in accordance with the typical physiographic and climatologic features of the country. PMID:22411031

Kolovos, Alexander; Angulo, José Miguel; Modis, Konstantinos; Papantonopoulos, George; Wang, Jin-Feng; Christakos, George

2013-01-01

334

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

335

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

336

Learn priors on the spatiotemporal relationship between edges in the alpha matte and the composite image  

E-print Network

Low energy C B Background subtraction Spatiotemporal consistency solution Photoshop Ruzon Photoshop Photoshop Ruzon Ruzon Notemporal consistency Withtemporal consistency = x + x C F (1-) B Given Given

Apostoloff, Nicholas

337

Relationship between orientation sensitivity and spatiotemporal receptive field structures of neurons in the cat lateral geniculate nucleus.  

PubMed

Although it is thought that orientation selectivity first emerges in the primary visual cortex, several studies have reported that neurons in the cat lateral geniculate nucleus (LGN) are sensitive to stimulus orientation, especially for high spatial frequency (SF) stimuli. To understand how this orientation sensitivity emerges, we investigated the spatiotemporal structures of linear receptive fields (RFs) of LGN neurons. Orientation tunings at several SFs were measured using sinusoidal drifting grating stimuli. Fine spatiotemporal structures of the linear RFs were measured using a reverse correlation technique and two-dimensional dynamic Gaussian white noise stimuli. A non-linear response modulation function was estimated by comparing measured responses with responses predicted from a linear RF structure. Although we found that a population of LGN neurons exhibited significantly elongated linear RF centers and that the angles of the long axes corresponded well to the preferred orientations, the orientation tunings predicted from the linear RFs were significantly broader than those measured. These results suggest that orientation-tuned non-linear response modulation induced by stimulation outside the classical RF contributes to the sharp orientation tuning seen in LGN neurons. PMID:22885244

Suematsu, Naofumi; Naito, Tomoyuki; Sato, Hiromichi

2012-11-01

338

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

PubMed

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

Ghosh, Erina; Kovács, Sándor J

2012-03-01

339

Spatiotemporal pH dynamics in concentration polarization near ion-selective membranes.  

PubMed

We present a detailed analysis of the transient pH dynamics for a weak, buffered electrolyte subject to voltage-driven transport through an ion-selective membrane. We show that pH fronts emanate from the concentration polarization zone next to the membrane and that these propagating fronts change the pH in the system several units from its equilibrium value. The analysis is based on a 1D model using the unsteady Poisson-Nernst-Planck equations with nonequilibrium chemistry and without assumptions of electroneutrality or asymptotically thin electric double layers. Nonequilibrium chemical effects, especially for water splitting, are shown to be important for the dynamical and spatiotemporal evolution of the pH fronts. Nonetheless, the model also shows that at steady state the assumption of chemical equilibrium can still lead to good approximations of the global pH distribution. Moreover, our model shows that the transport of the hydronium ion in the extended space charge region is governed by a balance between electromigration and water self-ionization. On the basis of this observation, we present a simple model showing that the net flux of the hydronium ion is proportional to the length of the extended space charge region and the water self-ionization rate. To demonstrate these effects in practice, we have adopted the experiment of Mai et al. (Mai, J.; Miller, H.; Hatch, A. V. Spatiotemporal Mapping of Concentration Polarization Induced pH Changes at Nanoconstrictions. ACS Nano 2012, 6, 10206) as a model problem, and by including the full chemistry and transport, we show that the present model can capture the experimentally observed pH fronts. Our model can, among other things, be used to predict and engineer pH dynamics, which can be essential to the performance of membrane-based systems for biochemical separation and analysis. PMID:24892492

Andersen, Mathias B; Rogers, David M; Mai, Junyu; Schudel, Benjamin; Hatch, Anson V; Rempe, Susan B; Mani, Ali

2014-07-01

340

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

341

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

342

Gaussian predictive process models for large spatial data sets.  

PubMed

With scientific data available at geocoded locations, investigators are increasingly turning to spatial process models for carrying out statistical inference. Over the last decade, hierarchical models implemented through Markov chain Monte Carlo methods have become especially popular for spatial modelling, given their flexibility and power to fit models that would be infeasible with classical methods as well as their avoidance of possibly inappropriate asymptotics. However, fitting hierarchical spatial models often involves expensive matrix decompositions whose computational complexity increases in cubic order with the number of spatial locations, rendering such models infeasible for large spatial data sets. This computational burden is exacerbated in multivariate settings with several spatially dependent response variables. It is also aggravated when data are collected at frequent time points and spatiotemporal process models are used. With regard to this challenge, our contribution is to work with what we call predictive process models for spatial and spatiotemporal data. Every spatial (or spatiotemporal) process induces a predictive process model (in fact, arbitrarily many of them). The latter models project process realizations of the former to a lower dimensional subspace, thereby reducing the computational burden. Hence, we achieve the flexibility to accommodate non-stationary, non-Gaussian, possibly multivariate, possibly spatiotemporal processes in the context of large data sets. We discuss attractive theoretical properties of these predictive processes. We also provide a computational template encompassing these diverse settings. Finally, we illustrate the approach with simulated and real data sets. PMID:19750209

Banerjee, Sudipto; Gelfand, Alan E; Finley, Andrew O; Sang, Huiyan

2008-09-01

343

Use of Spatial Information to Predict Multidrug Resistance in Tuberculosis Patients, Peru  

PubMed Central

To determine whether spatiotemporal information could help predict multidrug resistance at the time of tuberculosis diagnosis, we investigated tuberculosis patients who underwent drug susceptibility testing in Lima, Peru, during 2005–2007. We found that crude representation of spatial location at the level of the health center improved prediction of multidrug resistance. PMID:22516236

Lin, Hsien-Ho; Shin, Sonya S.; Contreras, Carmen; Asencios, Luis; Paciorek, Christopher J.

2012-01-01

344

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

PubMed

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

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

2014-08-01

345

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

NASA Astrophysics Data System (ADS)

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

Gollas, Frank; Tetzlaff, Ronald

2009-05-01

346

Spatiotemporal patterns, annual baseline and movement-related incidence of Streptococcus agalactiae infection in Danish dairy herds: 2000-2009.  

PubMed

Several decades after the inception of the five-point plan for the control of contagious mastitis pathogens, Streptococcus agalactiae (S. agalactiae) persists as a fundamental threat to the dairy industry in many countries. A better understanding of the relative importance of within- and between-herd sources of new herd infections coupled with the spatiotemporal distribution of the infection, may aid in effective targeting of control efforts. Thus, the objectives of this study were: (1) to describe the spatiotemporal patterns of infection with S. agalactiae in the population of Danish dairy herds from 2000 to 2009 and (2) to estimate the annual herd-level baseline and movement-related incidence risks of S. agalactiae infection over the 10-year period. The analysis involved registry data on bacteriological culture of all bulk tank milk samples collected as part of the mandatory Danish S. agalactiae surveillance scheme as well as live cattle movements into dairy herds during the specified 10-year period. The results indicated that the predicted risk of a herd becoming infected with S. agalactiae varied spatiotemporally; the risk being more homogeneous and higher in the period after 2005. Additionally, the annual baseline risks yielded significant yet distinctive patterns before and after 2005 - the risk of infection being higher in the latter phase. On the contrary, the annual movement-related risks revealed a non-significant pattern over the 10-year period. There was neither evidence for spatial clustering of cases relative to the population of herds at risk nor spatial dependency between herds. Nevertheless, the results signal a need to beef up within-herd biosecurity in order to reduce the risk of new herd infections. PMID:24269038

Mweu, Marshal M; Nielsen, Søren S; Halasa, Tariq; Toft, Nils

2014-02-01

347

Structural Bioinformatics of the Interactome  

PubMed Central

The last decade has seen a dramatic expansion in the number and range of techniques available to obtain genome-wide information, and to analyze this information so as to infer both the function of individual molecules and how they interact to modulate the behavior of biological systems. Here we review these techniques, focusing on the construction of physical protein-protein interaction networks, and highlighting approaches that incorporate protein structure which is becoming an increasingly important component of systems-level computational techniques. We also discuss how network analyses are being applied to enhance the basic understanding of biological systems and their disregulation, and how they are being applied in drug development. PMID:24895853

Petrey, Donald; Honig, Barry

2014-01-01

348

Curating the innate immunity interactome  

Microsoft Academic Search

BACKGROUND: The innate immune response is the first line of defence against invading pathogens and is regulated by complex signalling and transcriptional networks. Systems biology approaches promise to shed new light on the regulation of innate immunity through the analysis and modelling of these networks. A key initial step in this process is the contextual cataloguing of the components of

David J Lynn; Calvin Chan; Misbah Naseer; Melissa Yau; Raymond Lo; Anastasia Sribnaia; Giselle Ring; Jaimmie Que; Kathleen Wee; Geoffrey L Winsor; Matthew R Laird; Karin Breuer; Amir K Foroushani; Fiona SL Brinkman; Robert EW Hancock

2010-01-01

349

Disordered interactome of human papillomavirus.  

PubMed

Intrinsically disordered proteins (IDPs) and proteins with long intrinsically disordered protein regions (IDPRs) lack ordered structure but are involved in a multitude of biological processes, where they often serve as major regulators and controllers of various functions of their binding partners. Furthermore, IDPs/IDPRs are often related to the pathogenesis of various diseases, including cancer. Intrinsic disorder confers multiple functional advantages to its carriers. As a result, due to their functional versatility and structural plasticity, IDPs and IDPRs are common in various proteomes, including proteomes of different pathological organisms. Viruses are "well-educated" users of various aspects of intrinsic disorder for their advantage. These small but highly efficient invaders broadly use intrinsic disorder to overrun the host organism's defense system, as well as to seize and overrun host systems and pathways forcing them to work for the virus needs, to ensure accommodation of viruses to their variable and often hostile habitats, and to promote and support the economic usage of the viral genetic material. Human papillomaviruses (HPVs), with their tiny proteomes (the entire HPV genome includes just eight open reading frames), intricate life cycle, and ability to either cause benign papillomas/warts or promote the development of carcinomas of the genital tract, head and neck and epidermis, attracted considerable attention of researchers. This review analyzes the plentitude and demeanor of intrinsic disorder in proteins from HPVs and their cellular targets. PMID:23713779

Xue, Bin; Ganti, Ketaki; Rabionet, Alejandro; Banks, Lawrence; Uversky, Vladimir N

2014-01-01

350

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

Dollinger, Michael; Dubrovskiy, Denis; Patel, Rita

2012-01-01

351

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 monthly basis. Several key steps have been implemented to gain a better understanding of the spatiotemporal distributions, including (1) development and application of China's CO2 emission inventories using provincial statistics; (2) separate calculations of emissions from large point sources and accurate identification of their geographical locations; (3) development of 1 km×1 km gridded population and GDP data for China from 2000 to 2009 and application of them as dynamic spatial proxies to allocate emissions; and (4) monthly variation curves of CO2 emissions from various sectors were developed for each province and applied to our inventory. China's total CO2 emission from fossil fuel and industrial process have increased from 3.6 billion tons in 2000 to 8.6 billion tons in 2009, which may be off by 14-18% and are enough to skew global totals. And the resulting spatiotemporal distributions of our inventories also differed greatly in several ways from those derived using national statistics and population-based approach for the various economic development levels, industrial and energy structures, and even large point emissions sources within China and each province.

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

2013-07-01

352

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

353

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

354

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

355

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

356

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

357

Model selection in spatio-temporal electromagnetic source analysis.  

PubMed

Several methods [model selection procedures (MSPs)] to determine the number of sources in electroencephalogram (EEG) and magnetoencphalogram (MEG) data have previously been investigated in an instantaneous analysis. In this paper, these MSPs are extended to a spatio-temporal analysis if possible. It is seen that the residual variance (RV) tends to overestimate the number of sources. The Akaike information criterion (AIC) and the Wald test on amplitudes (WA) and the Wald test on locations (WL) have the highest probabilities of selecting the correct number of sources. The WA has the advantage that it offers the opportunity to test which source is active at which time sample. PMID:15759571

Waldorp, Lourens J; Huizenga, Hilde M; Nehorai, Arye; Grasman, Raoul P P P; Molenaar, Peter C M

2005-03-01

358

Large scale stochastic spatio-temporal modelling with PCRaster  

NASA Astrophysics Data System (ADS)

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

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

2013-04-01

359

Spontaneous bursting: From temporal to spatio-temporal intermittency  

SciTech Connect

A simple model for temporal bursting is introduced. This model invokes either dynamic or random forcing of a bifurcation parameter of some simple dynamical system in a way that makes the bifurcation parameter spend suitable amounts of time below and above the bifurcation threshold. This model is extended to coupled map lattices to produce spontaneous spatio-temporal burstings. It models physical systems which are embedded in a random background that is statistically homogeneous in space and time. An application of this model to optical turbulence is discussed. {copyright} {ital 1996 American Institute of Physics.}

Platt, N.; Hammel, S.M. [Code B44, Nonlinear Dynamics and Wavelets Group, Naval Surface Warfare Center, 10901 New Hampshire Ave, Silver Spring, Maryland, 20903-5640 (United States)

1996-06-01

360

Spatio-temporal autocorrelation of road network data  

Microsoft Academic Search

Modelling autocorrelation structure among space–time observations is crucial in space–time modelling and forecasting. The\\u000a aim of this research is to examine the spatio-temporal autocorrelation structure of road networks in order to determine likely\\u000a requirements for building a suitable space–time forecasting model. Exploratory space–time autocorrelation analysis is carried\\u000a out using journey time data collected on London’s road network. Through the use

Tao Cheng; James Haworth; Jiaqiu Wang

2011-01-01

361

Spatio-temporal dynamics in the origin of genetic information  

NASA Astrophysics Data System (ADS)

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

Kim, Pan-Jun; Jeong, Hawoong

2005-04-01

362

Neuronal Spatiotemporal Pattern Discrimination: The Dynamical Evolution of Seizures  

PubMed Central

We developed a modern numerical approach to the multivariate linear discrimination of Fisher from 1936 based upon singular value decomposition that is sufficiently stable to permit widespread application to spatiotemporal neuronal patterns. We demonstrate this approach on an old problem in neuroscience – whether seizures have distinct dynamical states as they evolve with time. A practical result was the first demonstration that human seizures have distinct initiation and termination dynamics, an important characterization as we seek to better understand how seizures start and stop. Our approach is broadly applicable to a wide variety of neuronal data, from multichannel EEG or MEG, to sequentially acquired optical imaging data or fMRI. PMID:16198127

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

2005-01-01

363

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"

364

Spatiotemporal Source Tuning Filter Bank for Multiclass EEG based Brain Computer Interfaces  

Microsoft Academic Search

Non invasive brain-computer interfaces (BCI) allow people to communicate by modulating features of their electroencephalogram (EEG). Spatiotemporal filtering has a vital role in multi-class, EEG based BCI. In this study, we used a novel combination of principle component analysis, independent component analysis and dipole source localization to design a spatiotemporal multiple source tuning (SPAMSORT) filter bank, each channel of which

Soumyadipta Acharya; Mohsen Mollazadeh; Kartikeya Murari; Nitish Thakor

2006-01-01

365

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.

366

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

SciTech Connect

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

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

2011-12-15

367

Effect of colored noises on spatiotemporal chaos in the complex Ginzburg-Landau equation  

Microsoft Academic Search

The effect of colored noises, which are correlated both in space and time, on spatiotemporal chaos in the complex Ginzburg-Landau equation has been studied numerically. The correlations of spatiotemporal patterns as a function of characteristics of noise were calculated. We found that there exists an optimal correlation length of noise where the system establishes its maximal spatial correlation; a small

Hongli Wang; Qi Ouyang

2002-01-01

368

Velocity and Acceleration Measurement from the Spatio-Temporal Fourier Transform of Low Light Level Images  

Microsoft Academic Search

The spatio-temporal Fourier transform is usually applied to determine the velocity of an object from a series of standard light intensity frames. In this paper the technique has been extended to determine the object acceleration. The techniques for velocity and acceleration determination based on the spatio-temporal Fourier transform have been applied to experimental low light level images. Under these conditions,

Manuel P. Cagigal; Pedro M. Prieto

1995-01-01

369

SPATIO-TEMPORAL JOINT PROBABILITY IMAGES FOR VIDEO SEGMENTATION School of Computing Science  

E-print Network

effectiveness and efficiency. Ngo, Pong and Chin [4] presented a spatio-temporal method for gradual sceneSPATIO-TEMPORAL JOINT PROBABILITY IMAGES FOR VIDEO SEGMENTATION Ze-Nian Li School of Computing and wipes based on the anal- ysis of spatio-temporal behaviors of Joint Probability Im- ages (JPIs

Li, Ze-Nian

370

4-Dimensional Local Spatio-Temporal Features for Human Activity Recognition  

E-print Network

-dimensional (4D) local spatio-temporal feature that combines both intensity and depth information. The feature detector applies separate filters along the 3D spatial dimensions and the 1D temporal dimension to detect the distortion in this pattern. In this paper, we propose a new 4D local spatio-temporal feature that combines

Parker, Lynne E.

371

Scalable Spatio-temporal Continuous Query Processing for Location-aware Services  

E-print Network

Real-time spatio-temporal query processing needs to effectively handle a large number of moving objects into a spatial join. The main idea is to group the set of continuous spatio- temporal queries in one table called paradigm to support all mutability variations of continuous spatio-temporal queries. We propose three join

Mokbel, Mohamed F.

372

Unraveling the distributed neural code of facial identity through spatiotemporal pattern analysis  

E-print Network

Unraveling the distributed neural code of facial identity through spatiotemporal pattern analysis. The present study investigates the neural code of facial identity perception with the aim of ascertain- ing-based brain mapping and dynamic discrimi- nation analysis to locate spatiotemporal patterns that support face

Behrmann, Marlene

373

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

374

A SPATIO-TEMPORAL MODEL OF HOUSING PRICES BASED ON INDIVIDUAL  

E-print Network

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

Smith, Tony E.

375

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

PubMed Central

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

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

2013-01-01

376

Spatiotemporal variation in reproductive parameters of yellow-bellied marmots.  

PubMed

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

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

2007-11-01

377

Integrating GIS and ABM to Explore Spatiotemporal Dynamics  

NASA Astrophysics Data System (ADS)

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

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

2013-12-01

378

Spatio-temporal Granger causality: a new framework.  

PubMed

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

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

2013-10-01

379

Event Detection using Twitter: A Spatio-Temporal Approach  

PubMed Central

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

Cheng, Tao; Wicks, Thomas

2014-01-01

380

Spatio-temporal processing of tactile stimuli in autistic children.  

PubMed

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

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

2014-01-01

381

Stochastic spatio-temporal modelling with PCRaster Python  

NASA Astrophysics Data System (ADS)

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

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

2012-04-01

382

Spatiotemporal analysis of NORA10 data of significant wave height  

NASA Astrophysics Data System (ADS)

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

Vanem, Erik

2014-06-01

383

Multiple dipole modeling of spatio-temporal MEG (magnetoencephalogram) data  

SciTech Connect

An array of SQUID biomagentometers may be used to measure the spatio-temporal neuromagnetic field produced by the brain in response to a given sensory stimulus. A popular model for the neural activity that produces these fields is a set of current dipoles. We present here a common linear algebraic framework for three common spatio-temporal dipole models: moving and rotating dipoles, rotating dipoles with fixed location, and dipoles with fixed orientation and location. Our intent here is not to argue the merits of one model over another, but rather show how each model may be solved efficiently, and within the same framework as the others. In all cases, we assume that the location, orientation, and magnitude of the dipoles are unknown. We present the parameter estimation problem for these three models in a common framework, and show how, in each case, the problem may be decomposed into the estimation of the dipole locations using nonlinear minimization followed by linear estimation of the associated moment time series. Numerically efficient means of calculating the cost function are presented, and problems of model order selection and missing moments are also investigated. The methods described are demonstrated in a simulated application to a three dipole problem. 21 refs., 2 figs., 1 tab.

Mosher, J.C. (TRW Defense Systems Group, Redondo Beach, CA (USA). Systems Engineering and Development Div. University of Southern California, Los Angeles, CA (USA). Signal and Image Processing Inst.); Lewis, P.S. (Los Alamos National Lab., NM (USA)); Leahy, R. (University of Southern California, Los Angeles, CA (USA). Signal and Image Processing Inst.); Singh, M. (University of Southern Californi

1990-01-01

384

Measurement of spatio-temporal transport in live cells  

NASA Astrophysics Data System (ADS)

The live cell is a highly dynamical system with complicated biophysical and biochemical processes taking place at diverse spatiotemporal scales. Though it is well known that microtubules and actin filaments play important roles in intracellular transport, their dynamic behavior is not entirely understood. We propose a unified approach to studying transport in live cells. We used Spatial Light Interference Microscopy, a quantitative phase imaging method developed in our laboratory, to extract cell mass distributions over broad spatiotemporal scales. The dispersion relations for this transport dynamics, i.e. frequency bandwidth vs. spatial frequencies, reveal deterministic mass transport at large spatial scales (w˜q) and diffusive transport at small spatial scales (w˜q?2). At submicron scales, we observed a w˜q?3 behavior, which indicates whip-like movements of protein filaments. Further control experiments where both the microtubule and actin polymerization were blocked suggests that essentially actin governs the long spatial scales behavior and microtubules the short scales. This label-free method enables us to access different components of cell dynamics and quantify diffusion coefficients and speed of motor proteins.

Wang, Ru; Wang, Zhuo; Millet, Larry; Gillette, Martha U.; Popescu, Gabriel

2010-03-01

385

Cell Population Tracking and Lineage Construction with Spatiotemporal Context 1  

PubMed Central

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

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

2008-01-01

386

Active sensing via movement shapes spatiotemporal patterns of sensory feedback.  

PubMed

Previous work has shown that animals alter their locomotor behavior to increase sensing volumes. However, an animal's own movement also determines the spatial and temporal dynamics of sensory feedback. Because each sensory modality has unique spatiotemporal properties, movement has differential and potentially independent effects on each sensory system. Here we show that weakly electric fish dramatically adjust their locomotor behavior in relation to changes of modality-specific information in a task in which increasing sensory volume is irrelevant. We varied sensory information during a refuge-tracking task by changing illumination (vision) and conductivity (electroreception). The gain between refuge movement stimuli and fish tracking responses was functionally identical across all sensory conditions. However, there was a significant increase in the tracking error in the dark (no visual cues). This was a result of spontaneous whole-body oscillations (0.1 to 1 Hz) produced by the fish. These movements were costly: in the dark, fish swam over three times further when tracking and produced more net positive mechanical work. The magnitudes of these oscillations increased as electrosensory salience was degraded via increases in conductivity. In addition, tail bending (1.5 to 2.35 Hz), which has been reported to enhance electrosensory perception, occurred only during trials in the dark. These data show that both categories of movements - whole-body oscillations and tail bends - actively shape the spatiotemporal dynamics of electrosensory feedback. PMID:22496294

Stamper, Sarah A; Roth, Eatai; Cowan, Noah J; Fortune, Eric S

2012-05-01

387

Spatiotemporal behavior induced by differential diffusion in landolt systems.  

PubMed

The spatiotemporal dynamics of Landolt type reactions, for instance reactions between sulfite ions and strong oxidants, performed in a medium fed by the diffusion from a boundary is investigated numerically by using a simple general reaction scheme. In these conditions, the model can generate various spatiotemporal phenomena, e.g., spatial bistability, simple and complex oscillations, birhythmicity, and chaos, even though in a spatially homogeneous open reactor only steady-state bistability can develop. The model consists of two reactions, a protonation equilibrium of the reductant and an oxidation step that is autoactivated by hydrogen ions. The rich dynamics is the result of two factors: (i) long-range activation, through the rapidly diffusing hydrogen ions, (ii) the presence of two parallel autocatalytic pathways. Long range activation provides the necessary negative feedback, whereas the dual nature of the autocatalysis leads to the appearance of two different oscillatory modes. The presence of a second-order term in the rate law of the autocatalytic reaction is linked to a large amplitude oscillations that affect the system as a whole, whereas the third-order one gives rise to localized front oscillations. The complex phenomena, like mixed mode and chaotic oscillations are observed at the meeting of these different oscillatory modes. PMID:25340848

Szalai, István

2014-11-13

388

Deep Spatiotemporal Feature Learning with Application to Image Classification  

SciTech Connect

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

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

2010-01-01

389

Spatiotemporal variations of reference crop evapotranspiration in northern xinjiang, china.  

PubMed

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

Wang, Jian; Lv, Xin; Wang, Jiang-Li; Lin, Hai-Rong

2014-01-01

390

Spatiotemporal Variations of Reference Crop Evapotranspiration in Northern Xinjiang, China  

PubMed Central

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

Lv, Xin; Lin, Hai-rong

2014-01-01

391

Image-guided, noninvasive, spatiotemporal control of gene expression  

PubMed Central

Spatiotemporal control of transgene expression is of paramount importance in gene therapy. Here, we demonstrate the use of magnetic resonance temperature imaging (MRI)-guided, high-intensity focused ultrasound (HIFU) in combination with a heat-inducible promoter [heat shock protein 70 (HSP70)] for the in vivo spatiotemporal control of transgene activation. Local gene activation induced by moderate hyperthermia in a transgenic mouse expressing luciferase under the control of the HSP70 promoter showed a high similarity between the local temperature distribution in vivo and the region emitting light. Modulation of gene expression is possible by changing temperature, duration, and location of regional heating. Mild heating protocols (2 min at 43°C) causing no tissue damage were sufficient for significant gene activation. The HSP70 promoter was shown to be induced by the local temperature increase and not by the mechanical effects of ultrasound. Therefore, the combination of MRI-guided HIFU heating and transgenes under control of heat-inducible HSP promoter provides a direct, noninvasive, spatial control of gene expression via local hyperthermia. PMID:19164593

Deckers, Roel; Quesson, Bruno; Arsaut, Josette; Eimer, Sandrine; Couillaud, Franck; Moonen, Chrit T. W.

2009-01-01

392

Spatiotemporal dynamics of the biological interface between cancer and the microenvironment: a fractal anomalous diffusion model with microenvironment plasticity  

PubMed Central

Background The invasion-metastasis cascade of cancer involves a process of parallel progression. A biological interface (module) in which cells is linked with ECM (extracellular matrix) by CAMs (cell adhesion molecules) has been proposed as a tool for tracing cancer spatiotemporal dynamics. Methods A mathematical model was established to simulate cancer cell migration. Human uterine leiomyoma specimens, in vitro cell migration assay, quantitative real-time PCR, western blotting, dynamic viscosity, and an in vivo C57BL6 mouse model were used to verify the predictive findings of our model. Results The return to origin probability (RTOP) and its related CAM expression ratio in tumors, so-called "tumor self-seeding", gradually decreased with increased tumor size, and approached the 3D Pólya random walk constant (0.340537) in a periodic structure. The biphasic pattern of cancer cell migration revealed that cancer cells initially grew together and subsequently began spreading. A higher viscosity of fillers applied to the cancer surface was associated with a significantly greater inhibitory effect on cancer migration, in accordance with the Stokes-Einstein equation. Conclusion The positional probability and cell-CAM-ECM interface (module) in the fractal framework helped us decipher cancer spatiotemporal dynamics; in addition we modeled the methods of cancer control by manipulating the microenvironment plasticity or inhibiting the CAM expression to the Pólya random walk, Pólya constant. PMID:22889191

2012-01-01

393

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

PubMed Central

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

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

2014-01-01

394

A Hybrid Spatio-Temporal Data Indexing Method for Trajectory Databases  

PubMed Central

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

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

2014-01-01

395

NextPlace: A Spatio-Temporal Prediction Framework for Pervasive Systems  

E-print Network

, and recreational social networking tools for smart-phones. Existing techniques based on linear and probabilistic, rather than on the transitions between differ- ent locations. We report about our evaluation using four-based social network services such as Facebook Places and Foursquare may provide "location-aware" sponsored

Hand, Steven

396

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

E-print Network

-cost GPS technology allows the col- lection of traffic data using passive mobile probes (Work et al., 2010 segments. But, they provide fairly sparse coverage due to low GPS sampling frequency (i.e., often imposed privacy issues, and produce highly-varying speeds a

Jaillet, Patrick

397

Quantized vortices in a rotating Bose-Einstein condensate with spatiotemporally modulated interaction  

SciTech Connect

We present theoretical analysis and numerical studies of the quantized vortices in a rotating Bose-Einstein condensate with spatiotemporally modulated interaction in harmonic and anharmonic potentials, respectively. The exact quantized vortex and giant vortex solutions are constructed explicitly by similarity transformation. Their stability behavior has been examined by numerical simulation, which shows that a new series of stable vortex states (defined by radial and angular quantum numbers) can be supported by the spatiotemporally modulated interaction in this system. We find that there exist stable quantized vortices with large topological charges in repulsive condensates with spatiotemporally modulated interaction. We also give an experimental protocol to observe these vortex states in future experiments.

Wang Dengshan; Song Shuwei; Xiong Bo; Liu, W. M. [Beijing National Laboratory for Condensed Matter Physics, Institute of Physics, Chinese Academy of Sciences, Beijing 100190 (China)

2011-11-15

398

Insight into others’ minds: spatio-temporal representations by intrinsic frame of reference  

PubMed Central

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

Sun, Yanlong; Wang, Hongbin

2014-01-01

399

The effects of density-dependent dispersal on the spatiotemporal dynamics of cyclic populations.  

PubMed

Density-dependent dispersal occurs throughout the animal kingdom, and has been shown to occur in some taxa whose populations exhibit multi-year population cycles. However, the importance of density-dependent dispersal for the spatiotemporal dynamics of cyclic populations is unknown. We investigated the potential effects of density-dependent dispersal on the properties of periodic travelling waves predicted by two coupled reaction-diffusion models: a commonly used predator-prey model, and a general model of cyclic trophic interactions. We compared the effects of varying the gradient of both positive and negative density-dependent dispersal rates, to varying the ratio of the (constant) dispersal rates of the two interacting populations. Our comparison focussed on the possible range of wave properties, and on the waves generated by landscape obstacles and invasions. In all scenarios that we studied, varying the gradient of density-dependent dispersal has small quantitative effects on the travelling wave properties, relative to the effects of varying the ratio of the diffusion coefficients. PMID:18640692

Smith, Matthew J; Sherratt, Jonathan A; Lambin, Xavier

2008-09-21

400

The influence of spatio-temporal resource fluctuations on insular rat population dynamics  

PubMed Central

Local spatio-temporal resource variations can strongly influence the population dynamics of small mammals. This is particularly true on islands which are bottom-up driven systems, lacking higher order predators and with high variability in resource subsidies. The influence of resource fluctuations on animal survival may be mediated by individual movement among habitat patches, but simultaneously analysing survival, resource availability and habitat selection requires sophisticated analytical methods. We use a Bayesian multi-state capture–recapture model to estimate survival and movement probabilities of non-native black rats (Rattus rattus) across three habitats seasonally varying in resource availability. We find that survival varies most strongly with temporal rainfall patterns, overwhelming minor spatial variation among habitats. Surprisingly for a generalist forager, movement between habitats was rare, suggesting individuals do not opportunistically respond to spatial resource subsidy variations. Climate is probably the main driver of rodent population dynamics on islands, and even substantial habitat and seasonal spatial subsidies are overwhelmed in magnitude by predictable annual patterns in resource pulses. Marked variation in survival and capture has important implications for the timing of rat control. PMID:21775327

Russell, James C.; Ruffino, Lise

2012-01-01

401

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

NASA Astrophysics Data System (ADS)

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

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

2012-12-01

402

Spatiotemporal separation of PER and CRY posttranslational regulation in the mammalian circadian clock.  

PubMed

Posttranslational regulation of clock proteins is an essential part of mammalian circadian rhythms, conferring sensitivity to metabolic state and offering promising targets for pharmacological control. Two such regulators, casein kinase 1 (CKI) and F-box and leucine-rich repeat protein 3 (FBXL3), modulate the stability of closely linked core clock proteins period (PER) and cryptochrome (CRY), respectively. Inhibition of either CKI or FBXL3 leads to longer periods, and their effects are independent despite targeting proteins with similar roles in clock function. A mechanistic understanding of this independence, however, has remained elusive. Our analysis of cellular circadian clock gene reporters further differentiated between the actions of CKI and FBXL3 by revealing opposite amplitude responses from each manipulation. To understand the functional relationship between the CKI-PER and FBXL3-CRY pathways, we generated robust mechanistic predictions by applying a bootstrap uncertainty analysis to multiple mathematical circadian models. Our results indicate that CKI primarily regulates the accumulating phase of the PER-CRY repressive complex by controlling the nuclear import rate, whereas FBXL3 separately regulates the duration of transcriptional repression in the nucleus. Dynamic simulations confirmed that this spatiotemporal separation is able to reproduce the independence of the two regulators in period regulation, as well as their opposite amplitude effect. As a result, this study provides further insight into the molecular clock machinery responsible for maintaining robust circadian rhythms. PMID:24449901

St John, Peter C; Hirota, Tsuyoshi; Kay, Steve A; Doyle, Francis J

2014-02-01

403

Invasion rate of deer ked depends on spatiotemporal variation in host density.  

PubMed

Invasive parasites are of great global concern. Understanding the factors influencing the spread of invading pest species is a first step in developing effective countermeasures. Growing empirical evidence suggests that spread rates are essentially influenced by spatiotemporal dynamics of host-parasite interactions, yet approaches modelling spread rate have typically assumed static environmental conditions. We analysed invasion history of the deer ked (Lipoptena cervi) in Finland with a diffusion-reaction model, which assumed either the movement rate, the population growth rate, or both rates may depend on spatial and temporal distribution of moose (Alces alces), the main host of deer ked. We fitted the model to the data in a Bayesian framework, and used the Bayesian information criterion to show that accounting for the variation in local moose density improved the model's ability to describe the pattern of the invasion. The highest ranked model predicted higher movement rate and growth rate of deer ked with increasing moose density. Our results suggest that the historic increase in host density has facilitated the spread of the deer ked. Our approach illustrates how information about the ecology of an invasive species can be extracted from the spatial pattern of spread even with rather limited data. PMID:24521661

Meier, C M; Bonte, D; Kaitala, A; Ovaskainen, O

2014-06-01

404

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

NASA Astrophysics Data System (ADS)

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

Lee, Chieh-Han; Yu, Hwa-Lung

2014-05-01

405

Spatiotemporal dynamics of condensins I and II: evolutionary insights from the primitive red alga Cyanidioschyzon merolae  

PubMed Central

Condensins are multisubunit complexes that play central roles in chromosome organization and segregation in eukaryotes. Many eukaryotic species have two different condensin complexes (condensins I and II), although some species, such as fungi, have condensin I only. Here we use the red alga Cyanidioschyzon merolae as a model organism because it represents the smallest and simplest organism that is predicted to possess both condensins I and II. We demonstrate that, despite the great evolutionary distance, spatiotemporal dynamics of condensins in C. merolae is strikingly similar to that observed in mammalian cells: condensin II is nuclear throughout the cell cycle, whereas condensin I appears on chromosomes only after the nuclear envelope partially dissolves at prometaphase. Unlike in mammalian cells, however, condensin II is confined to centromeres in metaphase, whereas condensin I distributes more broadly along arms. We firmly establish a targeted gene disruption technique in this organism and find, to our surprise, that condensin II is not essential for mitosis under laboratory growth conditions, although it plays a crucial role in facilitating sister centromere resolution in the presence of a microtubule drug. The results provide fundamental insights into the evolution of condensin-based chromosome architecture and dynamics. PMID:23783031

Fujiwara, Takayuki; Tanaka, Kan; Kuroiwa, Tsuneyoshi; Hirano, Tatsuya

2013-01-01

406

A spatio-temporal understanding of growth regulation during the salt stress response in Arabidopsis.  

PubMed

Plant environmental responses involve dynamic changes in growth and signaling, yet little is understood as to how progress through these events is regulated. Here, we explored the phenotypic and transcriptional events involved in the acclimation of the Arabidopsis thaliana seedling root to a rapid change in salinity. Using live-imaging analysis, we show that growth is dynamically regulated with a period of quiescence followed by recovery then homeostasis. Through the use of a new high-resolution spatio-temporal transcriptional map, we identify the key hormone signaling pathways that regulate specific transcriptional programs, predict their spatial domain of action, and link the activity of these pathways to the regulation of specific phases of growth. We use tissue-specific approaches to suppress the abscisic acid (ABA) signaling pathway and demonstrate that ABA likely acts in select tissue layers to regulate spatially localized transcriptional programs and promote growth recovery. Finally, we show that salt also regulates many tissue-specific and time point-specific transcriptional responses that are expected to modify water transport, Casparian strip formation, and protein translation. Together, our data reveal a sophisticated assortment of regulatory programs acting together to coordinate spatially patterned biological changes involved in the immediate and long-term response to a stressful shift in environment. PMID:23898029

Geng, Yu; Wu, Rui; Wee, Choon Wei; Xie, Fei; Wei, Xueliang; Chan, Penny Mei Yeen; Tham, Cliff; Duan, Lina; Dinneny, José R

2013-06-01

407

Geographical information system (GIS) mapping of spatio-temporal pollution status of rivers in Ibadan, Nigeria.  

PubMed

More accurate spatio-temporal predictions of urban environment are needed as a basis for assessing exposures as a part of environmental studies and to inform urban protection policy and management. In this study, an information system was developed to manage the physico-chemical pollution information of Ibadan river system, Oyo State, Southwest Nigeria. The study took into account the seasonal influences of point and non-point discharges on the levels of physico-chemical parameters. The overall sensitivity of the watershed to physicochemical environmental pollution revealed that during dry season, of the 22 (100%) sample points, only 3 (13.6%) were unpolluted; 6 (27.3%) were slightly polluted; 10(45.4%) were moderately polluted; 2 (9.1%) were seriously polluted and 1 (4.5%) was exceptionally polluted. During rainy season, 3 (13.6%) were unpolluted; 7 (31.8%) were slightly polluted; 9 (40.9%) were moderately polluted; 2 (9.1%) were seriously polluted and 1 (4.5%) was exceptionally polluted. There is a considerable environmental risk associated with the present level of pollution of the Ibadan river water body on fish health and biodiversity. This research provides a basis for aquatic management and assist in policy making at national and international levels. Appropriate strategies for the control of point and non-point pollution sources, amendments and enforcement of legislation should be developed. PMID:18810966

Adeyemo, Olanike K; Babalobi, Olutayo O

2008-04-01

408

Stable isotope analysis of precipitation samples obtained via crowdsourcing reveals the spatiotemporal evolution of Superstorm Sandy.  

PubMed

Extra-tropical cyclones, such as 2012 Superstorm Sandy, pose a significant climatic threat to the northeastern United Sates, yet prediction of hydrologic and thermodynamic processes within such systems is complicated by their interaction with mid-latitude water patterns as they move poleward. Fortunately, the evolution of these systems is also recorded in the stable isotope ratios of storm-associated precipitation and water vapor, and isotopic analysis provides constraints on difficult-to-observe cyclone dynamics. During Superstorm Sandy, a unique crowdsourced approach enabled 685 precipitation samples to be obtained for oxygen and hydrogen isotopic analysis, constituting the largest isotopic sampling of a synoptic-scale system to date. Isotopically, these waters span an enormous range of values (> 21‰ for ?(18)O, > 160‰ for ?(2)H) and exhibit strong spatiotemporal structure. Low isotope ratios occurred predominantly in the west and south quadrants of the storm, indicating robust isotopic distillation that tracked the intensity of the storm's warm core. Elevated values of deuterium-excess (> 25‰) were found primarily in the New England region after Sandy made landfall. Isotope mass balance calculations and Lagrangian back-trajectory analysis suggest that these samples reflect the moistening of dry continental air entrained from a mid-latitude trough. These results demonstrate the power of rapid-response isotope monitoring to elucidate the structure and dynamics of water cycling within synoptic-scale systems and improve our understanding of storm evolution, hydroclimatological impacts, and paleo-storm proxies. PMID:24618882

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

2014-01-01

409