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Sample records for inferring species interactions

  1. Inferring species interactions through joint mark–recapture analysis

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    Yackulic, Charles B.; Korman, Josh; Yard, Michael D.; Dzul, Maria C.

    2018-01-01

    Introduced species are frequently implicated in declines of native species. In many cases, however, evidence linking introduced species to native declines is weak. Failure to make strong inferences regarding the role of introduced species can hamper attempts to predict population viability and delay effective management responses. For many species, mark–recapture analysis is the more rigorous form of demographic analysis. However, to our knowledge, there are no mark–recapture models that allow for joint modeling of interacting species. Here, we introduce a two‐species mark–recapture population model in which the vital rates (and capture probabilities) of one species are allowed to vary in response to the abundance of the other species. We use a simulation study to explore bias and choose an approach to model selection. We then use the model to investigate species interactions between endangered humpback chub (Gila cypha) and introduced rainbow trout (Oncorhynchus mykiss) in the Colorado River between 2009 and 2016. In particular, we test hypotheses about how two environmental factors (turbidity and temperature), intraspecific density dependence, and rainbow trout abundance are related to survival, growth, and capture of juvenile humpback chub. We also project the long‐term effects of different rainbow trout abundances on adult humpback chub abundances. Our simulation study suggests this approach has minimal bias under potentially challenging circumstances (i.e., low capture probabilities) that characterized our application and that model selection using indicator variables could reliably identify the true generating model even when process error was high. When the model was applied to rainbow trout and humpback chub, we identified negative relationships between rainbow trout abundance and the survival, growth, and capture probability of juvenile humpback chub. Effects on interspecific interactions on survival and capture probability were strongly

  2. Inference of gene-phenotype associations via protein-protein interaction and orthology.

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    Panwen Wang

    Full Text Available One of the fundamental goals of genetics is to understand gene functions and their associated phenotypes. To achieve this goal, in this study we developed a computational algorithm that uses orthology and protein-protein interaction information to infer gene-phenotype associations for multiple species. Furthermore, we developed a web server that provides genome-wide phenotype inference for six species: fly, human, mouse, worm, yeast, and zebrafish. We evaluated our inference method by comparing the inferred results with known gene-phenotype associations. The high Area Under the Curve values suggest a significant performance of our method. By applying our method to two human representative diseases, Type 2 Diabetes and Breast Cancer, we demonstrated that our method is able to identify related Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways. The web server can be used to infer functions and putative phenotypes of a gene along with the candidate genes of a phenotype, and thus aids in disease candidate gene discovery. Our web server is available at http://jjwanglab.org/PhenoPPIOrth.

  3. Evaluating species richness: biased ecological inference results from spatial heterogeneity in species detection probabilities

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    McNew, Lance B.; Handel, Colleen M.

    2015-01-01

    Accurate estimates of species richness are necessary to test predictions of ecological theory and evaluate biodiversity for conservation purposes. However, species richness is difficult to measure in the field because some species will almost always be overlooked due to their cryptic nature or the observer's failure to perceive their cues. Common measures of species richness that assume consistent observability across species are inviting because they may require only single counts of species at survey sites. Single-visit estimation methods ignore spatial and temporal variation in species detection probabilities related to survey or site conditions that may confound estimates of species richness. We used simulated and empirical data to evaluate the bias and precision of raw species counts, the limiting forms of jackknife and Chao estimators, and multi-species occupancy models when estimating species richness to evaluate whether the choice of estimator can affect inferences about the relationships between environmental conditions and community size under variable detection processes. Four simulated scenarios with realistic and variable detection processes were considered. Results of simulations indicated that (1) raw species counts were always biased low, (2) single-visit jackknife and Chao estimators were significantly biased regardless of detection process, (3) multispecies occupancy models were more precise and generally less biased than the jackknife and Chao estimators, and (4) spatial heterogeneity resulting from the effects of a site covariate on species detection probabilities had significant impacts on the inferred relationships between species richness and a spatially explicit environmental condition. For a real dataset of bird observations in northwestern Alaska, the four estimation methods produced different estimates of local species richness, which severely affected inferences about the effects of shrubs on local avian richness. Overall, our results

  4. Do competitive interactions in dry heathlands explain plant abundance patterns and species coexistence?

    DEFF Research Database (Denmark)

    Ransijn, Johannes; Damgaard, Christian; Schmidt, Inger K

    2015-01-01

    Plant community patterns in space and time may be explained by the interactions between competing plant species. The presented study investigates this in a nutrient and species poor ecosystem. The study presents a methodology for inferring competitive interactions from yearly vegetation inventories...... to predict the community dynamics of C. vulgaris and D. flexuosa. This was compared with the observed plant community structure at 198 Danish dry heathland sites. Interspecific competition will most likely lead to competitive exclusion of D. flexuosa at the observed temporal and spatial scale...... and uses this to assess the outcome of competitive interactions and to predict community patterns and dynamics in a Northwest-European dry heathland. Inferred competitive interactions from five consecutive years of measurements in permanent vegetation frames at a single dry heathland site were used...

  5. STRIDE: Species Tree Root Inference from Gene Duplication Events.

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    Emms, David M; Kelly, Steven

    2017-12-01

    The correct interpretation of any phylogenetic tree is dependent on that tree being correctly rooted. We present STRIDE, a fast, effective, and outgroup-free method for identification of gene duplication events and species tree root inference in large-scale molecular phylogenetic analyses. STRIDE identifies sets of well-supported in-group gene duplication events from a set of unrooted gene trees, and analyses these events to infer a probability distribution over an unrooted species tree for the location of its root. We show that STRIDE correctly identifies the root of the species tree in multiple large-scale molecular phylogenetic data sets spanning a wide range of timescales and taxonomic groups. We demonstrate that the novel probability model implemented in STRIDE can accurately represent the ambiguity in species tree root assignment for data sets where information is limited. Furthermore, application of STRIDE to outgroup-free inference of the origin of the eukaryotic tree resulted in a root probability distribution that provides additional support for leading hypotheses for the origin of the eukaryotes. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

  6. Interactive Instruction in Bayesian Inference

    DEFF Research Database (Denmark)

    Khan, Azam; Breslav, Simon; Hornbæk, Kasper

    2018-01-01

    An instructional approach is presented to improve human performance in solving Bayesian inference problems. Starting from the original text of the classic Mammography Problem, the textual expression is modified and visualizations are added according to Mayer’s principles of instruction. These pri......An instructional approach is presented to improve human performance in solving Bayesian inference problems. Starting from the original text of the classic Mammography Problem, the textual expression is modified and visualizations are added according to Mayer’s principles of instruction....... These principles concern coherence, personalization, signaling, segmenting, multimedia, spatial contiguity, and pretraining. Principles of self-explanation and interactivity are also applied. Four experiments on the Mammography Problem showed that these principles help participants answer the questions...... that an instructional approach to improving human performance in Bayesian inference is a promising direction....

  7. Inferring genetic interactions from comparative fitness data.

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    Crona, Kristina; Gavryushkin, Alex; Greene, Devin; Beerenwinkel, Niko

    2017-12-20

    Darwinian fitness is a central concept in evolutionary biology. In practice, however, it is hardly possible to measure fitness for all genotypes in a natural population. Here, we present quantitative tools to make inferences about epistatic gene interactions when the fitness landscape is only incompletely determined due to imprecise measurements or missing observations. We demonstrate that genetic interactions can often be inferred from fitness rank orders, where all genotypes are ordered according to fitness, and even from partial fitness orders. We provide a complete characterization of rank orders that imply higher order epistasis. Our theory applies to all common types of gene interactions and facilitates comprehensive investigations of diverse genetic interactions. We analyzed various genetic systems comprising HIV-1, the malaria-causing parasite Plasmodium vivax , the fungus Aspergillus niger , and the TEM-family of β-lactamase associated with antibiotic resistance. For all systems, our approach revealed higher order interactions among mutations.

  8. Mistaking geography for biology: inferring processes from species distributions.

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    Warren, Dan L; Cardillo, Marcel; Rosauer, Dan F; Bolnick, Daniel I

    2014-10-01

    Over the past few decades, there has been a rapid proliferation of statistical methods that infer evolutionary and ecological processes from data on species distributions. These methods have led to considerable new insights, but they often fail to account for the effects of historical biogeography on present-day species distributions. Because the geography of speciation can lead to patterns of spatial and temporal autocorrelation in the distributions of species within a clade, this can result in misleading inferences about the importance of deterministic processes in generating spatial patterns of biodiversity. In this opinion article, we discuss ways in which patterns of species distributions driven by historical biogeography are often interpreted as evidence of particular evolutionary or ecological processes. We focus on three areas that are especially prone to such misinterpretations: community phylogenetics, environmental niche modelling, and analyses of beta diversity (compositional turnover of biodiversity). Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

  9. Inferring duplications, losses, transfers and incomplete lineage sorting with nonbinary species trees.

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    Stolzer, Maureen; Lai, Han; Xu, Minli; Sathaye, Deepa; Vernot, Benjamin; Durand, Dannie

    2012-09-15

    Gene duplication (D), transfer (T), loss (L) and incomplete lineage sorting (I) are crucial to the evolution of gene families and the emergence of novel functions. The history of these events can be inferred via comparison of gene and species trees, a process called reconciliation, yet current reconciliation algorithms model only a subset of these evolutionary processes. We present an algorithm to reconcile a binary gene tree with a nonbinary species tree under a DTLI parsimony criterion. This is the first reconciliation algorithm to capture all four evolutionary processes driving tree incongruence and the first to reconcile non-binary species trees with a transfer model. Our algorithm infers all optimal solutions and reports complete, temporally feasible event histories, giving the gene and species lineages in which each event occurred. It is fixed-parameter tractable, with polytime complexity when the maximum species outdegree is fixed. Application of our algorithms to prokaryotic and eukaryotic data show that use of an incomplete event model has substantial impact on the events inferred and resulting biological conclusions. Our algorithms have been implemented in Notung, a freely available phylogenetic reconciliation software package, available at http://www.cs.cmu.edu/~durand/Notung. mstolzer@andrew.cmu.edu.

  10. Inferring transcriptional compensation interactions in yeast via stepwise structure equation modeling

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    Wang Woei-Fuh

    2008-03-01

    Full Text Available Abstract Background With the abundant information produced by microarray technology, various approaches have been proposed to infer transcriptional regulatory networks. However, few approaches have studied subtle and indirect interaction such as genetic compensation, the existence of which is widely recognized although its mechanism has yet to be clarified. Furthermore, when inferring gene networks most models include only observed variables whereas latent factors, such as proteins and mRNA degradation that are not measured by microarrays, do participate in networks in reality. Results Motivated by inferring transcriptional compensation (TC interactions in yeast, a stepwise structural equation modeling algorithm (SSEM is developed. In addition to observed variables, SSEM also incorporates hidden variables to capture interactions (or regulations from latent factors. Simulated gene networks are used to determine with which of six possible model selection criteria (MSC SSEM works best. SSEM with Bayesian information criterion (BIC results in the highest true positive rates, the largest percentage of correctly predicted interactions from all existing interactions, and the highest true negative (non-existing interactions rates. Next, we apply SSEM using real microarray data to infer TC interactions among (1 small groups of genes that are synthetic sick or lethal (SSL to SGS1, and (2 a group of SSL pairs of 51 yeast genes involved in DNA synthesis and repair that are of interest. For (1, SSEM with BIC is shown to outperform three Bayesian network algorithms and a multivariate autoregressive model, checked against the results of qRT-PCR experiments. The predictions for (2 are shown to coincide with several known pathways of Sgs1 and its partners that are involved in DNA replication, recombination and repair. In addition, experimentally testable interactions of Rad27 are predicted. Conclusion SSEM is a useful tool for inferring genetic networks, and the

  11. An analysis pipeline for the inference of protein-protein interaction networks

    Energy Technology Data Exchange (ETDEWEB)

    Taylor, Ronald C.; Singhal, Mudita; Daly, Don S.; Gilmore, Jason M.; Cannon, William R.; Domico, Kelly O.; White, Amanda M.; Auberry, Deanna L.; Auberry, Kenneth J.; Hooker, Brian S.; Hurst, G. B.; McDermott, Jason E.; McDonald, W. H.; Pelletier, Dale A.; Schmoyer, Denise A.; Wiley, H. S.

    2009-12-01

    An analysis pipeline has been created for deployment of a novel algorithm, the Bayesian Estimator of Protein-Protein Association Probabilities (BEPro), for use in the reconstruction of protein-protein interaction networks. We have combined the Software Environment for BIological Network Inference (SEBINI), an interactive environment for the deployment and testing of network inference algorithms that use high-throughput data, and the Collective Analysis of Biological Interaction Networks (CABIN), software that allows integration and analysis of protein-protein interaction and gene-to-gene regulatory evidence obtained from multiple sources, to allow interactions computed by BEPro to be stored, visualized, and further analyzed. Incorporating BEPro into SEBINI and automatically feeding the resulting inferred network into CABIN, we have created a structured workflow for protein-protein network inference and supplemental analysis from sets of mass spectrometry bait-prey experiment data. SEBINI demo site: https://www.emsl.pnl.gov /SEBINI/ Contact: ronald.taylor@pnl.gov. BEPro is available at http://www.pnl.gov/statistics/BEPro3/index.htm. Contact: ds.daly@pnl.gov. CABIN is available at http://www.sysbio.org/dataresources/cabin.stm. Contact: mudita.singhal@pnl.gov.

  12. Deciphering microbial interactions and detecting keystone species with co-occurrence networks

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    David eBerry

    2014-05-01

    Full Text Available Co-occurrence networks produced from microbial survey sequencing data are frequently used to identify interactions between community members. While this approach has potential to reveal ecological processes, it has been insufficiently validated due to the technical limitations inherent in studying complex microbial ecosystems. Here, we simulate multi-species microbial communities with known interaction patterns using generalized Lotka-Volterra dynamics, construct co-occurrence networks, and evaluate how well networks reveal the underlying interactions, and how experimental and ecological parameters can affect network inference and interpretation. We find that co-occurrence networks can recapitulate interaction networks under certain conditions, but that they lose interpretability when the effects of habitat filtering become significant. We demonstrate that networks suffer from local hot spots of spurious correlation in the neighborhood of hub species that engage in many interactions. We also identify topological features associated with keystone species in co-occurrence networks. This study provides a substantiated framework to guide environmental microbiologists in the construction and interpretation of co-occurrence networks from microbial survey datasets.

  13. Deciphering microbial interactions and detecting keystone species with co-occurrence networks.

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    Berry, David; Widder, Stefanie

    2014-01-01

    Co-occurrence networks produced from microbial survey sequencing data are frequently used to identify interactions between community members. While this approach has potential to reveal ecological processes, it has been insufficiently validated due to the technical limitations inherent in studying complex microbial ecosystems. Here, we simulate multi-species microbial communities with known interaction patterns using generalized Lotka-Volterra dynamics. We then construct co-occurrence networks and evaluate how well networks reveal the underlying interactions and how experimental and ecological parameters can affect network inference and interpretation. We find that co-occurrence networks can recapitulate interaction networks under certain conditions, but that they lose interpretability when the effects of habitat filtering become significant. We demonstrate that networks suffer from local hot spots of spurious correlation in the neighborhood of hub species that engage in many interactions. We also identify topological features associated with keystone species in co-occurrence networks. This study provides a substantiated framework to guide environmental microbiologists in the construction and interpretation of co-occurrence networks from microbial survey datasets.

  14. Bayesian inference for identifying interaction rules in moving animal groups.

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    Richard P Mann

    Full Text Available The emergence of similar collective patterns from different self-propelled particle models of animal groups points to a restricted set of "universal" classes for these patterns. While universality is interesting, it is often the fine details of animal interactions that are of biological importance. Universality thus presents a challenge to inferring such interactions from macroscopic group dynamics since these can be consistent with many underlying interaction models. We present a Bayesian framework for learning animal interaction rules from fine scale recordings of animal movements in swarms. We apply these techniques to the inverse problem of inferring interaction rules from simulation models, showing that parameters can often be inferred from a small number of observations. Our methodology allows us to quantify our confidence in parameter fitting. For example, we show that attraction and alignment terms can be reliably estimated when animals are milling in a torus shape, while interaction radius cannot be reliably measured in such a situation. We assess the importance of rate of data collection and show how to test different models, such as topological and metric neighbourhood models. Taken together our results both inform the design of experiments on animal interactions and suggest how these data should be best analysed.

  15. Input data for inferring species distributions in Kyphosidae world-wide

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    Steen Wilhelm Knudsen

    2016-09-01

    Full Text Available Input data files for inferring the relationship among the family Kyphosidae, as presented in (Knudsen and Clements, 2016 [1], is here provided together with resulting topologies, to allow the reader to explore the topologies in detail. The input data files comprise seven nexus-files with sequence alignments of mtDNA and nDNA markers for performing Bayesian analysis. A matrix of recoded character states inferred from the morphology examined in museum specimens representing Dichistiidae, Girellidae, Kyphosidae, Microcanthidae and Scorpididae, is also provided, and can be used for performing a parsimonious analysis to infer the relationship among these perciform families. The nucleotide input data files comprise both multiple and single representatives of the various species to allow for inference of the relationship among the species in Kyphosidae and between the families closely related to Kyphosidae. The ‘.xml’-files with various constrained relationships among the families potentially closely related to Kyphosidae are also provided to allow the reader to rerun and explore the results from the stepping-stone analysis. The resulting topologies are supplied in newick-file formats together with input data files for Bayesian analysis, together with ‘.xml’-files. Re-running the input data files in the appropriate software, will enable the reader to examine log-files and tree-files themselves. Keywords: Sea chub, Drummer, Kyphosus, Scorpis, Girella

  16. Fused Regression for Multi-source Gene Regulatory Network Inference.

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    Kari Y Lam

    2016-12-01

    Full Text Available Understanding gene regulatory networks is critical to understanding cellular differentiation and response to external stimuli. Methods for global network inference have been developed and applied to a variety of species. Most approaches consider the problem of network inference independently in each species, despite evidence that gene regulation can be conserved even in distantly related species. Further, network inference is often confined to single data-types (single platforms and single cell types. We introduce a method for multi-source network inference that allows simultaneous estimation of gene regulatory networks in multiple species or biological processes through the introduction of priors based on known gene relationships such as orthology incorporated using fused regression. This approach improves network inference performance even when orthology mapping and conservation are incomplete. We refine this method by presenting an algorithm that extracts the true conserved subnetwork from a larger set of potentially conserved interactions and demonstrate the utility of our method in cross species network inference. Last, we demonstrate our method's utility in learning from data collected on different experimental platforms.

  17. Likelihood inference for unions of interacting discs

    DEFF Research Database (Denmark)

    Møller, Jesper; Helisova, K.

    2010-01-01

    This is probably the first paper which discusses likelihood inference for a random set using a germ-grain model, where the individual grains are unobservable, edge effects occur and other complications appear. We consider the case where the grains form a disc process modelled by a marked point...... process, where the germs are the centres and the marks are the associated radii of the discs. We propose to use a recent parametric class of interacting disc process models, where the minimal sufficient statistic depends on various geometric properties of the random set, and the density is specified......-based maximum likelihood inference and the effect of specifying different reference Poisson models....

  18. Inferring Pairwise Interactions from Biological Data Using Maximum-Entropy Probability Models.

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    Richard R Stein

    2015-07-01

    Full Text Available Maximum entropy-based inference methods have been successfully used to infer direct interactions from biological datasets such as gene expression data or sequence ensembles. Here, we review undirected pairwise maximum-entropy probability models in two categories of data types, those with continuous and categorical random variables. As a concrete example, we present recently developed inference methods from the field of protein contact prediction and show that a basic set of assumptions leads to similar solution strategies for inferring the model parameters in both variable types. These parameters reflect interactive couplings between observables, which can be used to predict global properties of the biological system. Such methods are applicable to the important problems of protein 3-D structure prediction and association of gene-gene networks, and they enable potential applications to the analysis of gene alteration patterns and to protein design.

  19. Coalescent-based species tree inference from gene tree topologies under incomplete lineage sorting by maximum likelihood.

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    Wu, Yufeng

    2012-03-01

    Incomplete lineage sorting can cause incongruence between the phylogenetic history of genes (the gene tree) and that of the species (the species tree), which can complicate the inference of phylogenies. In this article, I present a new coalescent-based algorithm for species tree inference with maximum likelihood. I first describe an improved method for computing the probability of a gene tree topology given a species tree, which is much faster than an existing algorithm by Degnan and Salter (2005). Based on this method, I develop a practical algorithm that takes a set of gene tree topologies and infers species trees with maximum likelihood. This algorithm searches for the best species tree by starting from initial species trees and performing heuristic search to obtain better trees with higher likelihood. This algorithm, called STELLS (which stands for Species Tree InfErence with Likelihood for Lineage Sorting), has been implemented in a program that is downloadable from the author's web page. The simulation results show that the STELLS algorithm is more accurate than an existing maximum likelihood method for many datasets, especially when there is noise in gene trees. I also show that the STELLS algorithm is efficient and can be applied to real biological datasets. © 2011 The Author. Evolution© 2011 The Society for the Study of Evolution.

  20. Species co-occurrence networks: Can they reveal trophic and non-trophic interactions in ecological communities?

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    Freilich, Mara A; Wieters, Evie; Broitman, Bernardo R; Marquet, Pablo A; Navarrete, Sergio A

    2018-03-01

    Co-occurrence methods are increasingly utilized in ecology to infer networks of species interactions where detailed knowledge based on empirical studies is difficult to obtain. Their use is particularly common, but not restricted to, microbial networks constructed from metagenomic analyses. In this study, we test the efficacy of this procedure by comparing an inferred network constructed using spatially intensive co-occurrence data from the rocky intertidal zone in central Chile to a well-resolved, empirically based, species interaction network from the same region. We evaluated the overlap in the information provided by each network and the extent to which there is a bias for co-occurrence data to better detect known trophic or non-trophic, positive or negative interactions. We found a poor correspondence between the co-occurrence network and the known species interactions with overall sensitivity (probability of true link detection) equal to 0.469, and specificity (true non-interaction) equal to 0.527. The ability to detect interactions varied with interaction type. Positive non-trophic interactions such as commensalism and facilitation were detected at the highest rates. These results demonstrate that co-occurrence networks do not represent classical ecological networks in which interactions are defined by direct observations or experimental manipulations. Co-occurrence networks provide information about the joint spatial effects of environmental conditions, recruitment, and, to some extent, biotic interactions, and among the latter, they tend to better detect niche-expanding positive non-trophic interactions. Detection of links (sensitivity or specificity) was not higher for well-known intertidal keystone species than for the rest of consumers in the community. Thus, as observed in previous empirical and theoretical studies, patterns of interactions in co-occurrence networks must be interpreted with caution, especially when extending interaction

  1. Inferences about nested subsets structure when not all species are detected

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    Cam, E.; Nichols, J.D.; Hines, J.E.; Sauer, J.R.

    2000-01-01

    Comparisons of species composition among ecological communities of different size have often provided evidence that the species in communities with lower species richness form nested subsets of the species in larger communities. In the vast majority of studies, the question of nested subsets has been addressed using information on presence-absence, where a '0' is interpreted as the absence of a given species from a given location. Most of the methodological discussion in earlier studies investigating nestedness concerns the approach to generation of model-based matrices. However, it is most likely that in many situations investigators cannot detect all the species present in the location sampled. The possibility that zeros in incidence matrices reflect nondetection rather than absence of species has not been considered in studies addressing nested subsets, even though the position of zeros in these matrices forms the basis of earlier inference methods. These sampling artifacts are likely to lead to erroneous conclusions about both variation over space in species richness and the degree of similarity of the various locations. Here we propose an approach to investigation of nestedness, based on statistical inference methods explicitly incorporating species detection probability, that take into account the probabilistic nature of the sampling process. We use presence-absence data collected under Pollock?s robust capture-recapture design, and resort to an estimator of species richness originally developed for closed populations to assess the proportion of species shared by different locations. We develop testable predictions corresponding to the null hypothesis of a nonnested pattern, and an alternative hypothesis of perfect nestedness. We also present an index for assessing the degree of nestedness of a system of ecological communities. We illustrate our approach using avian data from the North American Breeding Bird Survey collected in Florida Keys.

  2. Inference of a Nonlinear Stochastic Model of the Cardiorespiratory Interaction

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    Smelyanskiy, V. N.; Luchinsky, D. G.; Stefanovska, A.; McClintock, P. V.

    2005-03-01

    We reconstruct a nonlinear stochastic model of the cardiorespiratory interaction in terms of a set of polynomial basis functions representing the nonlinear force governing system oscillations. The strength and direction of coupling and noise intensity are simultaneously inferred from a univariate blood pressure signal. Our new inference technique does not require extensive global optimization, and it is applicable to a wide range of complex dynamical systems subject to noise.

  3. Boolean analysis reveals systematic interactions among low-abundance species in the human gut microbiome.

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    Jens Christian Claussen

    2017-06-01

    Full Text Available The analysis of microbiome compositions in the human gut has gained increasing interest due to the broader availability of data and functional databases and substantial progress in data analysis methods, but also due to the high relevance of the microbiome in human health and disease. While most analyses infer interactions among highly abundant species, the large number of low-abundance species has received less attention. Here we present a novel analysis method based on Boolean operations applied to microbial co-occurrence patterns. We calibrate our approach with simulated data based on a dynamical Boolean network model from which we interpret the statistics of attractor states as a theoretical proxy for microbiome composition. We show that for given fractions of synergistic and competitive interactions in the model our Boolean abundance analysis can reliably detect these interactions. Analyzing a novel data set of 822 microbiome compositions of the human gut, we find a large number of highly significant synergistic interactions among these low-abundance species, forming a connected network, and a few isolated competitive interactions.

  4. Inferring species trees from incongruent multi-copy gene trees using the Robinson-Foulds distance

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    2013-01-01

    Background Constructing species trees from multi-copy gene trees remains a challenging problem in phylogenetics. One difficulty is that the underlying genes can be incongruent due to evolutionary processes such as gene duplication and loss, deep coalescence, or lateral gene transfer. Gene tree estimation errors may further exacerbate the difficulties of species tree estimation. Results We present a new approach for inferring species trees from incongruent multi-copy gene trees that is based on a generalization of the Robinson-Foulds (RF) distance measure to multi-labeled trees (mul-trees). We prove that it is NP-hard to compute the RF distance between two mul-trees; however, it is easy to calculate this distance between a mul-tree and a singly-labeled species tree. Motivated by this, we formulate the RF problem for mul-trees (MulRF) as follows: Given a collection of multi-copy gene trees, find a singly-labeled species tree that minimizes the total RF distance from the input mul-trees. We develop and implement a fast SPR-based heuristic algorithm for the NP-hard MulRF problem. We compare the performance of the MulRF method (available at http://genome.cs.iastate.edu/CBL/MulRF/) with several gene tree parsimony approaches using gene tree simulations that incorporate gene tree error, gene duplications and losses, and/or lateral transfer. The MulRF method produces more accurate species trees than gene tree parsimony approaches. We also demonstrate that the MulRF method infers in minutes a credible plant species tree from a collection of nearly 2,000 gene trees. Conclusions Our new phylogenetic inference method, based on a generalized RF distance, makes it possible to quickly estimate species trees from large genomic data sets. Since the MulRF method, unlike gene tree parsimony, is based on a generic tree distance measure, it is appealing for analyses of genomic data sets, in which many processes such as deep coalescence, recombination, gene duplication and losses as

  5. Inferring gene and protein interactions using PubMed citations and consensus Bayesian networks.

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    Deeter, Anthony; Dalman, Mark; Haddad, Joseph; Duan, Zhong-Hui

    2017-01-01

    The PubMed database offers an extensive set of publication data that can be useful, yet inherently complex to use without automated computational techniques. Data repositories such as the Genomic Data Commons (GDC) and the Gene Expression Omnibus (GEO) offer experimental data storage and retrieval as well as curated gene expression profiles. Genetic interaction databases, including Reactome and Ingenuity Pathway Analysis, offer pathway and experiment data analysis using data curated from these publications and data repositories. We have created a method to generate and analyze consensus networks, inferring potential gene interactions, using large numbers of Bayesian networks generated by data mining publications in the PubMed database. Through the concept of network resolution, these consensus networks can be tailored to represent possible genetic interactions. We designed a set of experiments to confirm that our method is stable across variation in both sample and topological input sizes. Using gene product interactions from the KEGG pathway database and data mining PubMed publication abstracts, we verify that regardless of the network resolution or the inferred consensus network, our method is capable of inferring meaningful gene interactions through consensus Bayesian network generation with multiple, randomized topological orderings. Our method can not only confirm the existence of currently accepted interactions, but has the potential to hypothesize new ones as well. We show our method confirms the existence of known gene interactions such as JAK-STAT-PI3K-AKT-mTOR, infers novel gene interactions such as RAS- Bcl-2 and RAS-AKT, and found significant pathway-pathway interactions between the JAK-STAT signaling and Cardiac Muscle Contraction KEGG pathways.

  6. Model-free inference of direct network interactions from nonlinear collective dynamics.

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    Casadiego, Jose; Nitzan, Mor; Hallerberg, Sarah; Timme, Marc

    2017-12-19

    The topology of interactions in network dynamical systems fundamentally underlies their function. Accelerating technological progress creates massively available data about collective nonlinear dynamics in physical, biological, and technological systems. Detecting direct interaction patterns from those dynamics still constitutes a major open problem. In particular, current nonlinear dynamics approaches mostly require to know a priori a model of the (often high dimensional) system dynamics. Here we develop a model-independent framework for inferring direct interactions solely from recording the nonlinear collective dynamics generated. Introducing an explicit dependency matrix in combination with a block-orthogonal regression algorithm, the approach works reliably across many dynamical regimes, including transient dynamics toward steady states, periodic and non-periodic dynamics, and chaos. Together with its capabilities to reveal network (two point) as well as hypernetwork (e.g., three point) interactions, this framework may thus open up nonlinear dynamics options of inferring direct interaction patterns across systems where no model is known.

  7. Species interactions and plant polyploidy.

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    Segraves, Kari A; Anneberg, Thomas J

    2016-07-01

    Polyploidy is a common mode of speciation that can have far-reaching consequences for plant ecology and evolution. Because polyploidy can induce an array of phenotypic changes, there can be cascading effects on interactions with other species. These interactions, in turn, can have reciprocal effects on polyploid plants, potentially impacting their establishment and persistence. Although there is a wealth of information on the genetic and phenotypic effects of polyploidy, the study of species interactions in polyploid plants remains a comparatively young field. Here we reviewed the available evidence for how polyploidy may impact many types of species interactions that range from mutualism to antagonism. Specifically, we focused on three main questions: (1) Does polyploidy directly cause the formation of novel interactions not experienced by diploids, or does it create an opportunity for natural selection to then form novel interactions? (2) Does polyploidy cause consistent, predictable changes in species interactions vs. the evolution of idiosyncratic differences? (3) Does polyploidy lead to greater evolvability in species interactions? From the scarce evidence available, we found that novel interactions are rare but that polyploidy can induce changes in pollinator, herbivore, and pathogen interactions. Although further tests are needed, it is likely that selection following whole-genome duplication is important in all types of species interaction and that there are circumstances in which polyploidy can enhance the evolvability of interactions with other species. © 2016 Botanical Society of America.

  8. Identifying keystone species in the human gut microbiome from metagenomic timeseries using sparse linear regression.

    Directory of Open Access Journals (Sweden)

    Charles K Fisher

    Full Text Available Human associated microbial communities exert tremendous influence over human health and disease. With modern metagenomic sequencing methods it is now possible to follow the relative abundance of microbes in a community over time. These microbial communities exhibit rich ecological dynamics and an important goal of microbial ecology is to infer the ecological interactions between species directly from sequence data. Any algorithm for inferring ecological interactions must overcome three major obstacles: 1 a correlation between the abundances of two species does not imply that those species are interacting, 2 the sum constraint on the relative abundances obtained from metagenomic studies makes it difficult to infer the parameters in timeseries models, and 3 errors due to experimental uncertainty, or mis-assignment of sequencing reads into operational taxonomic units, bias inferences of species interactions due to a statistical problem called "errors-in-variables". Here we introduce an approach, Learning Interactions from MIcrobial Time Series (LIMITS, that overcomes these obstacles. LIMITS uses sparse linear regression with boostrap aggregation to infer a discrete-time Lotka-Volterra model for microbial dynamics. We tested LIMITS on synthetic data and showed that it could reliably infer the topology of the inter-species ecological interactions. We then used LIMITS to characterize the species interactions in the gut microbiomes of two individuals and found that the interaction networks varied significantly between individuals. Furthermore, we found that the interaction networks of the two individuals are dominated by distinct "keystone species", Bacteroides fragilis and Bacteroided stercosis, that have a disproportionate influence on the structure of the gut microbiome even though they are only found in moderate abundance. Based on our results, we hypothesize that the abundances of certain keystone species may be responsible for individuality in

  9. Cytoprophet: a Cytoscape plug-in for protein and domain interaction networks inference.

    Science.gov (United States)

    Morcos, Faruck; Lamanna, Charles; Sikora, Marcin; Izaguirre, Jesús

    2008-10-01

    Cytoprophet is a software tool that allows prediction and visualization of protein and domain interaction networks. It is implemented as a plug-in of Cytoscape, an open source software framework for analysis and visualization of molecular networks. Cytoprophet implements three algorithms that predict new potential physical interactions using the domain composition of proteins and experimental assays. The algorithms for protein and domain interaction inference include maximum likelihood estimation (MLE) using expectation maximization (EM); the set cover approach maximum specificity set cover (MSSC) and the sum-product algorithm (SPA). After accepting an input set of proteins with Uniprot ID/Accession numbers and a selected prediction algorithm, Cytoprophet draws a network of potential interactions with probability scores and GO distances as edge attributes. A network of domain interactions between the domains of the initial protein list can also be generated. Cytoprophet was designed to take advantage of the visual capabilities of Cytoscape and be simple to use. An example of inference in a signaling network of myxobacterium Myxococcus xanthus is presented and available at Cytoprophet's website. http://cytoprophet.cse.nd.edu.

  10. Explanation in causal inference methods for mediation and interaction

    CERN Document Server

    VanderWeele, Tyler

    2015-01-01

    A comprehensive examination of methods for mediation and interaction, VanderWeele's book is the first to approach this topic from the perspective of causal inference. Numerous software tools are provided, and the text is both accessible and easy to read, with examples drawn from diverse fields. The result is an essential reference for anyone conducting empirical research in the biomedical or social sciences.

  11. Inference of Interactions in Cyanobacterial-Heterotrophic Co-Cultures via Transcriptome Sequencing

    Energy Technology Data Exchange (ETDEWEB)

    Beliaev, Alex S.; Romine, Margaret F.; Serres, Margaret; Bernstein, Hans C.; Linggi, Bryan E.; Markillie, Lye Meng; Isern, Nancy G.; Chrisler, William B.; Kucek, Leo A.; Hill, Eric A.; Pinchuk, Grigoriy; Bryant, Donald A.; Wiley, H. S.; Fredrickson, Jim K.; Konopka, Allan

    2014-04-29

    We employed deep sequencing technology to identify transcriptional adaptation of the euryhaline unicellular cyanobacterium Synechococcus sp. PCC 7002 and the marine facultative aerobe Shewanella putrefaciens W3-18-1 to growth in a co-culture and infer the effect of carbon flux distributions on photoautotroph-heterotroph interactions. The overall transcriptome response of both organisms to co-cultivation was shaped by their respective physiologies and growth constraints. Carbon limitation resulted in the expansion of metabolic capacities which was manifested through the transcriptional upregulation of transport and catabolic pathways. While growth coupling occurred via lactate oxidation or secretion of photosynthetically fixed carbon, there was evidence of specific metabolic interactions between the two organisms. On one hand, the production and excretion of specific amino acids (methionine and alanine) by the cyanobacterium correlated with the putative downregulation of the corresponding biosynthetic machinery of Shewanella W3-18-1. On the other hand, the broad and consistent decrease of mRNA levels for many Fe-regulated Synechococcus 7002 genes during co-cultivation suggested increased Fe availability as well as more facile and energy-efficient mechanisms for Fe acquisition by the cyanobacterium. Furthermore, evidence pointed at potentially novel interactions between oxygenic photoautotrophs and heterotrophs related to the oxidative stress response as transcriptional patterns suggested that Synechococcus 7002 rather than Shewanella W3-18-1 provided scavenging functions for reactive oxygen species under co-culture conditions. This study provides an initial insight into the complexity of photoautotrophic-heterotrophic interactions and brings new perspectives of their role in the robustness and stability of the association.

  12. Bayesian Inference of Ecological Interactions from Spatial Data

    Directory of Open Access Journals (Sweden)

    Christopher R. Stephens

    2017-11-01

    Full Text Available The characterization and quantification of ecological interactions and the construction of species’ distributions and their associated ecological niches are of fundamental theoretical and practical importance. In this paper, we discuss a Bayesian inference framework, which, using spatial data, offers a general formalism within which ecological interactions may be characterized and quantified. Interactions are identified through deviations of the spatial distribution of co-occurrences of spatial variables relative to a benchmark for the non-interacting system and based on a statistical ensemble of spatial cells. The formalism allows for the integration of both biotic and abiotic factors of arbitrary resolution. We concentrate on the conceptual and mathematical underpinnings of the formalism, showing how, using the naive Bayes approximation, it can be used to not only compare and contrast the relative contribution from each variable, but also to construct species’ distributions and ecological niches based on an arbitrary variable type. We also show how non-linear interactions between distinct niche variables can be identified and the degree of confounding between variables accounted for.

  13. Quantitative inferences on the locomotor behaviour of extinct species applied to Simocyon batalleri (Ailuridae, Late Miocene, Spain)

    Science.gov (United States)

    Fabre, Anne-Claire; Salesa, Manuel J.; Cornette, Raphael; Antón, Mauricio; Morales, Jorge; Peigné, Stéphane

    2015-06-01

    Inferences of function and ecology in extinct taxa have long been a subject of interest because it is fundamental to understand the evolutionary history of species. In this study, we use a quantitative approach to investigate the locomotor behaviour of Simocyon batalleri, a key taxon related to the ailurid family. To do so, we use 3D surface geometric morphometric approaches on the three long bones of the forelimb of an extant reference sample. Next, we test the locomotor strategy of S. batalleri using a leave-one-out cross-validated linear discriminant analysis. Our results show that S. batalleri is included in the morphospace of the living species of musteloids. However, each bone of the forelimb appears to show a different functional signal suggesting that inferring the lifestyle or locomotor behaviour of fossils can be difficult and dependent on the bone investigated. This highlights the importance of studying, where possible, a maximum of skeletal elements to be able to make robust inferences on the lifestyle of extinct species. Finally, our results suggest that S. batalleri may be more arboreal than previously suggested.

  14. Inferring the distribution and demography of an invasive species from sighting data: the red fox incursion into Tasmania.

    Directory of Open Access Journals (Sweden)

    Peter Caley

    Full Text Available A recent study has inferred that the red fox (Vulpes vulpes is now widespread in Tasmania as of 2010, based on the extraction of fox DNA from predator scats. Heuristically, this inference appears at first glance to be at odds with the lack of recent confirmed discoveries of either road-killed foxes--the last of which occurred in 2006, or hunter killed foxes--the most recent in 2001. This paper demonstrates a method to codify this heuristic analysis and produce inferences consistent with assumptions and data. It does this by formalising the analysis in a transparent and repeatable manner to make inference on the past, present and future distribution of an invasive species. It utilizes Approximate Bayesian Computation to make inferences. Importantly, the method is able to inform management of invasive species within realistic time frames, and can be applied widely. We illustrate the technique using the Tasmanian fox data. Based on the pattern of carcass discoveries of foxes in Tasmania, we infer that the population of foxes in Tasmania is most likely extinct, or restricted in distribution and demographically weak as of 2013. It is possible, though unlikely, that that population is widespread and/or demographically robust. This inference is largely at odds with the inference from the predator scat survey data. Our results suggest the chances of successfully eradicating the introduced red fox population in Tasmania may be significantly higher than previously thought.

  15. Inferring the distribution and demography of an invasive species from sighting data: the red fox incursion into Tasmania.

    Science.gov (United States)

    Caley, Peter; Ramsey, David S L; Barry, Simon C

    2015-01-01

    A recent study has inferred that the red fox (Vulpes vulpes) is now widespread in Tasmania as of 2010, based on the extraction of fox DNA from predator scats. Heuristically, this inference appears at first glance to be at odds with the lack of recent confirmed discoveries of either road-killed foxes--the last of which occurred in 2006, or hunter killed foxes--the most recent in 2001. This paper demonstrates a method to codify this heuristic analysis and produce inferences consistent with assumptions and data. It does this by formalising the analysis in a transparent and repeatable manner to make inference on the past, present and future distribution of an invasive species. It utilizes Approximate Bayesian Computation to make inferences. Importantly, the method is able to inform management of invasive species within realistic time frames, and can be applied widely. We illustrate the technique using the Tasmanian fox data. Based on the pattern of carcass discoveries of foxes in Tasmania, we infer that the population of foxes in Tasmania is most likely extinct, or restricted in distribution and demographically weak as of 2013. It is possible, though unlikely, that that population is widespread and/or demographically robust. This inference is largely at odds with the inference from the predator scat survey data. Our results suggest the chances of successfully eradicating the introduced red fox population in Tasmania may be significantly higher than previously thought.

  16. Inferring domain-domain interactions from protein-protein interactions with formal concept analysis.

    Directory of Open Access Journals (Sweden)

    Susan Khor

    Full Text Available Identifying reliable domain-domain interactions will increase our ability to predict novel protein-protein interactions, to unravel interactions in protein complexes, and thus gain more information about the function and behavior of genes. One of the challenges of identifying reliable domain-domain interactions is domain promiscuity. Promiscuous domains are domains that can occur in many domain architectures and are therefore found in many proteins. This becomes a problem for a method where the score of a domain-pair is the ratio between observed and expected frequencies because the protein-protein interaction network is sparse. As such, many protein-pairs will be non-interacting and domain-pairs with promiscuous domains will be penalized. This domain promiscuity challenge to the problem of inferring reliable domain-domain interactions from protein-protein interactions has been recognized, and a number of work-arounds have been proposed. This paper reports on an application of Formal Concept Analysis to this problem. It is found that the relationship between formal concepts provides a natural way for rare domains to elevate the rank of promiscuous domain-pairs and enrich highly ranked domain-pairs with reliable domain-domain interactions. This piggybacking of promiscuous domain-pairs onto less promiscuous domain-pairs is possible only with concept lattices whose attribute-labels are not reduced and is enhanced by the presence of proteins that comprise both promiscuous and rare domains.

  17. Inferring Domain-Domain Interactions from Protein-Protein Interactions with Formal Concept Analysis

    Science.gov (United States)

    Khor, Susan

    2014-01-01

    Identifying reliable domain-domain interactions will increase our ability to predict novel protein-protein interactions, to unravel interactions in protein complexes, and thus gain more information about the function and behavior of genes. One of the challenges of identifying reliable domain-domain interactions is domain promiscuity. Promiscuous domains are domains that can occur in many domain architectures and are therefore found in many proteins. This becomes a problem for a method where the score of a domain-pair is the ratio between observed and expected frequencies because the protein-protein interaction network is sparse. As such, many protein-pairs will be non-interacting and domain-pairs with promiscuous domains will be penalized. This domain promiscuity challenge to the problem of inferring reliable domain-domain interactions from protein-protein interactions has been recognized, and a number of work-arounds have been proposed. This paper reports on an application of Formal Concept Analysis to this problem. It is found that the relationship between formal concepts provides a natural way for rare domains to elevate the rank of promiscuous domain-pairs and enrich highly ranked domain-pairs with reliable domain-domain interactions. This piggybacking of promiscuous domain-pairs onto less promiscuous domain-pairs is possible only with concept lattices whose attribute-labels are not reduced and is enhanced by the presence of proteins that comprise both promiscuous and rare domains. PMID:24586450

  18. Incorporating Context Dependency of Species Interactions in Species Distribution Models.

    Science.gov (United States)

    Lany, Nina K; Zarnetske, Phoebe L; Gouhier, Tarik C; Menge, Bruce A

    2017-07-01

    Species distribution models typically use correlative approaches that characterize the species-environment relationship using occurrence or abundance data for a single species. However, species distributions are determined by both abiotic conditions and biotic interactions with other species in the community. Therefore, climate change is expected to impact species through direct effects on their physiology and indirect effects propagated through their resources, predators, competitors, or mutualists. Furthermore, the sign and strength of species interactions can change according to abiotic conditions, resulting in context-dependent species interactions that may change across space or with climate change. Here, we incorporated the context dependency of species interactions into a dynamic species distribution model. We developed a multi-species model that uses a time-series of observational survey data to evaluate how abiotic conditions and species interactions affect the dynamics of three rocky intertidal species. The model further distinguishes between the direct effects of abiotic conditions on abundance and the indirect effects propagated through interactions with other species. We apply the model to keystone predation by the sea star Pisaster ochraceus on the mussel Mytilus californianus and the barnacle Balanus glandula in the rocky intertidal zone of the Pacific coast, USA. Our method indicated that biotic interactions between P. ochraceus and B. glandula affected B. glandula dynamics across >1000 km of coastline. Consistent with patterns from keystone predation, the growth rate of B. glandula varied according to the abundance of P. ochraceus in the previous year. The data and the model did not indicate that the strength of keystone predation by P. ochraceus varied with a mean annual upwelling index. Balanus glandula cover increased following years with high phytoplankton abundance measured as mean annual chlorophyll-a. M. californianus exhibited the same

  19. Exploiting visual search theory to infer social interactions

    Science.gov (United States)

    Rota, Paolo; Dang-Nguyen, Duc-Tien; Conci, Nicola; Sebe, Nicu

    2013-03-01

    In this paper we propose a new method to infer human social interactions using typical techniques adopted in literature for visual search and information retrieval. The main piece of information we use to discriminate among different types of interactions is provided by proxemics cues acquired by a tracker, and used to distinguish between intentional and casual interactions. The proxemics information has been acquired through the analysis of two different metrics: on the one hand we observe the current distance between subjects, and on the other hand we measure the O-space synergy between subjects. The obtained values are taken at every time step over a temporal sliding window, and processed in the Discrete Fourier Transform (DFT) domain. The features are eventually merged into an unique array, and clustered using the K-means algorithm. The clusters are reorganized using a second larger temporal window into a Bag Of Words framework, so as to build the feature vector that will feed the SVM classifier.

  20. ShinyKGode: an Interactive Application for ODE Parameter Inference Using Gradient Matching.

    Science.gov (United States)

    Wandy, Joe; Niu, Mu; Giurghita, Diana; Daly, Rónán; Rogers, Simon; Husmeier, Dirk

    2018-02-27

    Mathematical modelling based on ordinary differential equations (ODEs) is widely used to describe the dynamics of biological systems, particularly in systems and pathway biology. Often the kinetic parameters of these ODE systems are unknown and have to be inferred from the data. Approximate parameter inference methods based on gradient matching (which do not require performing computationally expensive numerical integration of the ODEs) have been getting popular in recent years, but many implementations are difficult to run without expert knowledge. Here we introduce ShinyKGode, an interactive web application to perform fast parameter inference on ODEs using gradient matching. ShinyKGode can be used to infer ODE parameters on simulated and observed data using gradient matching. Users can easily load their own models in Systems Biology Markup Language format, and a set of pre-defined ODE benchmark models are provided in the application. Inferred parameters are visualised alongside diagnostic plots to assess convergence. The R package for ShinyKGode can be installed through the Comprehensive R Archive Network (CRAN). Installation instructions, as well as tutorial videos and source code are available at https://joewandy.github.io/shinyKGode. dirk.husmeier@glasgow.ac.uk. None.

  1. Limitations of a metabolic network-based reverse ecology method for inferring host-pathogen interactions.

    Science.gov (United States)

    Takemoto, Kazuhiro; Aie, Kazuki

    2017-05-25

    Host-pathogen interactions are important in a wide range of research fields. Given the importance of metabolic crosstalk between hosts and pathogens, a metabolic network-based reverse ecology method was proposed to infer these interactions. However, the validity of this method remains unclear because of the various explanations presented and the influence of potentially confounding factors that have thus far been neglected. We re-evaluated the importance of the reverse ecology method for evaluating host-pathogen interactions while statistically controlling for confounding effects using oxygen requirement, genome, metabolic network, and phylogeny data. Our data analyses showed that host-pathogen interactions were more strongly influenced by genome size, primary network parameters (e.g., number of edges), oxygen requirement, and phylogeny than the reserve ecology-based measures. These results indicate the limitations of the reverse ecology method; however, they do not discount the importance of adopting reverse ecology approaches altogether. Rather, we highlight the need for developing more suitable methods for inferring host-pathogen interactions and conducting more careful examinations of the relationships between metabolic networks and host-pathogen interactions.

  2. Models for inference in dynamic metacommunity systems

    Science.gov (United States)

    Dorazio, Robert M.; Kery, Marc; Royle, J. Andrew; Plattner, Matthias

    2010-01-01

    A variety of processes are thought to be involved in the formation and dynamics of species assemblages. For example, various metacommunity theories are based on differences in the relative contributions of dispersal of species among local communities and interactions of species within local communities. Interestingly, metacommunity theories continue to be advanced without much empirical validation. Part of the problem is that statistical models used to analyze typical survey data either fail to specify ecological processes with sufficient complexity or they fail to account for errors in detection of species during sampling. In this paper, we describe a statistical modeling framework for the analysis of metacommunity dynamics that is based on the idea of adopting a unified approach, multispecies occupancy modeling, for computing inferences about individual species, local communities of species, or the entire metacommunity of species. This approach accounts for errors in detection of species during sampling and also allows different metacommunity paradigms to be specified in terms of species- and location-specific probabilities of occurrence, extinction, and colonization: all of which are estimable. In addition, this approach can be used to address inference problems that arise in conservation ecology, such as predicting temporal and spatial changes in biodiversity for use in making conservation decisions. To illustrate, we estimate changes in species composition associated with the species-specific phenologies of flight patterns of butterflies in Switzerland for the purpose of estimating regional differences in biodiversity.

  3. Estimating Effects of Species Interactions on Populations of Endangered Species.

    Science.gov (United States)

    Roth, Tobias; Bühler, Christoph; Amrhein, Valentin

    2016-04-01

    Global change causes community composition to change considerably through time, with ever-new combinations of interacting species. To study the consequences of newly established species interactions, one available source of data could be observational surveys from biodiversity monitoring. However, approaches using observational data would need to account for niche differences between species and for imperfect detection of individuals. To estimate population sizes of interacting species, we extended N-mixture models that were developed to estimate true population sizes in single species. Simulations revealed that our model is able to disentangle direct effects of dominant on subordinate species from indirect effects of dominant species on detection probability of subordinate species. For illustration, we applied our model to data from a Swiss amphibian monitoring program and showed that sizes of expanding water frog populations were negatively related to population sizes of endangered yellow-bellied toads and common midwife toads and partly of natterjack toads. Unlike other studies that analyzed presence and absence of species, our model suggests that the spread of water frogs in Central Europe is one of the reasons for the decline of endangered toad species. Thus, studying population impacts of dominant species on population sizes of endangered species using data from biodiversity monitoring programs should help to inform conservation policy and to decide whether competing species should be subject to population management.

  4. The effects of incomplete protein interaction data on structural and evolutionary inferences

    DEFF Research Database (Denmark)

    de Silva, E; Thorne, T; Ingram, P

    2006-01-01

    of the inherent noise in protein interaction data. The effects of the incomplete nature of network data become very noticeable, especially for so-called network motifs. We also consider the effect of incomplete network data on functional and evolutionary inferences. Conclusion Crucially, when only small, partial...

  5. Surfing among species, populations and morphotypes: Inferring boundaries between two species of new world silversides (Atherinopsidae).

    Science.gov (United States)

    González-Castro, Mariano; Rosso, Juan José; Mabragaña, Ezequiel; Díaz de Astarloa, Juan Martín

    2016-01-01

    Atherinopsidae are widespread freshwater and shallow marine fish with singular economic importance. Morphological, genetical and life cycles differences between marine and estuarine populations were already reported in this family, suggesting ongoing speciation. Also, coexistence and interbreeding between closely related species were documented. The aim of this study was to infer boundaries among: (A) Odontesthes bonariensis and O. argentinensis at species level, and intermediate morphs; (B) the population of O. argentinensis of Mar Chiquita Lagoon and its marine conspecifics. To achieve this, we integrated, meristic, Geometrics Morphometrics and DNA Barcode approaches. Four groups were discriminated and subsequently characterized according to their morphological traits, shape and meristic characters. No shared haplotypes between O. bonariensis and O. argentinensis were found. Significative-meristic and body shape differences between the Mar Chiquita and marine individuals of O. argentinensis were found, suggesting they behave as well differentiated populations, or even incipient ecological species. The fact that the Odontesthes morphotypes shared haplotypes with both, O. argentinensis and O. bonariensis, but also possess meristic and morphometric distinctive traits open new questions related to the origin of this morphogroup. Copyright © 2015 Académie des sciences. Published by Elsevier SAS. All rights reserved.

  6. Insights on plant interaction between dominating species from patterns of plant association

    DEFF Research Database (Denmark)

    Damgaard, Christian; Ehlers, Bodil K.; Ransijn, Johannes C.G.

    2018-01-01

    Abstract It has been suggested that in order to infer ecological processes from observed patterns of species abundance we need to investigate the covariance in species abundance. Consequently, an expression for the expected covariance of pin-point cover measurements of two speciesisdeveloped.By c...

  7. Inferring high-confidence human protein-protein interactions

    Directory of Open Access Journals (Sweden)

    Yu Xueping

    2012-05-01

    Full Text Available Abstract Background As numerous experimental factors drive the acquisition, identification, and interpretation of protein-protein interactions (PPIs, aggregated assemblies of human PPI data invariably contain experiment-dependent noise. Ascertaining the reliability of PPIs collected from these diverse studies and scoring them to infer high-confidence networks is a non-trivial task. Moreover, a large number of PPIs share the same number of reported occurrences, making it impossible to distinguish the reliability of these PPIs and rank-order them. For example, for the data analyzed here, we found that the majority (>83% of currently available human PPIs have been reported only once. Results In this work, we proposed an unsupervised statistical approach to score a set of diverse, experimentally identified PPIs from nine primary databases to create subsets of high-confidence human PPI networks. We evaluated this ranking method by comparing it with other methods and assessing their ability to retrieve protein associations from a number of diverse and independent reference sets. These reference sets contain known biological data that are either directly or indirectly linked to interactions between proteins. We quantified the average effect of using ranked protein interaction data to retrieve this information and showed that, when compared to randomly ranked interaction data sets, the proposed method created a larger enrichment (~134% than either ranking based on the hypergeometric test (~109% or occurrence ranking (~46%. Conclusions From our evaluations, it was clear that ranked interactions were always of value because higher-ranked PPIs had a higher likelihood of retrieving high-confidence experimental data. Reducing the noise inherent in aggregated experimental PPIs via our ranking scheme further increased the accuracy and enrichment of PPIs derived from a number of biologically relevant data sets. These results suggest that using our high

  8. Inferring the use of forelimb suspensory locomotion by extinct primate species via shape exploration of the ulna.

    Science.gov (United States)

    Rein, Thomas R; Harvati, Katerina; Harrison, Terry

    2015-01-01

    Uncovering links between skeletal morphology and locomotor behavior is an essential component of paleobiology because it allows researchers to infer the locomotor repertoire of extinct species based on preserved fossils. In this study, we explored ulnar shape in anthropoid primates using 3D geometric morphometrics to discover novel aspects of shape variation that correspond to observed differences in the relative amount of forelimb suspensory locomotion performed by species. The ultimate goal of this research was to construct an accurate predictive model that can be applied to infer the significance of these behaviors. We studied ulnar shape variation in extant species using principal component analysis. Species mainly clustered into phylogenetic groups along the first two principal components. Upon closer examination, the results showed that the position of species within each major clade corresponded closely with the proportion of forelimb suspensory locomotion that they have been observed to perform in nature. We used principal component regression to construct a predictive model for the proportion of these behaviors that would be expected to occur in the locomotor repertoire of anthropoid primates. We then applied this regression analysis to Pliopithecus vindobonensis, a stem catarrhine from the Miocene of central Europe, and found strong evidence that this species was adapted to perform a proportion of forelimb suspensory locomotion similar to that observed in the extant woolly monkey, Lagothrix lagothricha. Copyright © 2014 Elsevier Ltd. All rights reserved.

  9. Competitive interactions between forest trees are driven by species' trait hierarchy, not phylogenetic or functional similarity: implications for forest community assembly.

    Science.gov (United States)

    Kunstler, Georges; Lavergne, Sébastien; Courbaud, Benoît; Thuiller, Wilfried; Vieilledent, Ghislain; Zimmermann, Niklaus E; Kattge, Jens; Coomes, David A

    2012-08-01

    The relative importance of competition vs. environmental filtering in the assembly of communities is commonly inferred from their functional and phylogenetic structure, on the grounds that similar species compete most strongly for resources and are therefore less likely to coexist locally. This approach ignores the possibility that competitive effects can be determined by relative positions of species on a hierarchy of competitive ability. Using growth data, we estimated 275 interaction coefficients between tree species in the French mountains. We show that interaction strengths are mainly driven by trait hierarchy and not by functional or phylogenetic similarity. On the basis of this result, we thus propose that functional and phylogenetic convergence in local tree community might be due to competition-sorting species with different competitive abilities and not only environmental filtering as commonly assumed. We then show a functional and phylogenetic convergence of forest structure with increasing plot age, which supports this view. © 2012 Blackwell Publishing Ltd/CNRS.

  10. Revisiting the phylogeny of Zoanthidea (Cnidaria: Anthozoa): Staggered alignment of hypervariable sequences improves species tree inference.

    Science.gov (United States)

    Swain, Timothy D

    2018-01-01

    The recent rapid proliferation of novel taxon identification in the Zoanthidea has been accompanied by a parallel propagation of gene trees as a tool of species discovery, but not a corresponding increase in our understanding of phylogeny. This disparity is caused by the trade-off between the capabilities of automated DNA sequence alignment and data content of genes applied to phylogenetic inference in this group. Conserved genes or segments are easily aligned across the order, but produce poorly resolved trees; hypervariable genes or segments contain the evolutionary signal necessary for resolution and robust support, but sequence alignment is daunting. Staggered alignments are a form of phylogeny-informed sequence alignment composed of a mosaic of local and universal regions that allow phylogenetic inference to be applied to all nucleotides from both hypervariable and conserved gene segments. Comparisons between species tree phylogenies inferred from all data (staggered alignment) and hypervariable-excluded data (standard alignment) demonstrate improved confidence and greater topological agreement with other sources of data for the complete-data tree. This novel phylogeny is the most comprehensive to date (in terms of taxa and data) and can serve as an expandable tool for evolutionary hypothesis testing in the Zoanthidea. Spanish language abstract available in Text S1. Translation by L. O. Swain, DePaul University, Chicago, Illinois, 60604, USA. Copyright © 2017 Elsevier Inc. All rights reserved.

  11. Competition between species of small mammals

    International Nuclear Information System (INIS)

    Grant, P.R.

    1978-01-01

    Interspecific competition has often been inferred from its results. In evolutionary time it has been responsible for patterns of regularity in the structure of mammalian communities, and in the morphological and ecological characteristics of the constituent species. In contemporary time it gives rise to reciprocal (complementary) numbers and distributions of two or more species. These inferences are strengthened by recent experimental demonstrations of competition between species of North American rodents. Recent observations and experiments are reviewed. The most thoroughly studied competitors are two species of microtine rodents, Microtus pennsylvanicus and Clethrionomys gapperi. Species which compete for space have been studied experimentally more often than have food competitors. Overt aggression is frequently implicated, but its importance in nature in relation to other means of interaction (e.g. through vocal or scent communication) is not known. The definitive study of competition for food between mammal species has yet to be performed

  12. Melanins in Fossil Animals: Is It Possible to Infer Life History Traits from the Coloration of Extinct Species?

    Science.gov (United States)

    Negro, Juan J; Finlayson, Clive; Galván, Ismael

    2018-01-23

    Paleo-colour scientists have recently made the transition from describing melanin-based colouration in fossil specimens to inferring life-history traits of the species involved. Two such cases correspond to counter-shaded dinosaurs: dark-coloured due to melanins dorsally, and light-coloured ventrally. We believe that colour reconstruction of fossils based on the shape of preserved microstructures-the majority of paleo-colour studies involve melanin granules-is not without risks. In addition, animals with contrasting dorso-ventral colouration may be under different selection pressures beyond the need for camouflage, including, for instance, visual communication or ultraviolet (UV) protection. Melanin production is costly, and animals may invest less in areas of the integument where pigments are less needed. In addition, melanocytes exposed to UV radiation produce more melanin than unexposed melanocytes. Pigment economization may thus explain the colour pattern of some counter-shaded animals, including extinct species. Even in well-studied extant species, their diversity of hues and patterns is far from being understood; inferring colours and their functions in species only known from one or few specimens from the fossil record should be exerted with special prudence.

  13. Melanins in Fossil Animals: Is It Possible to Infer Life History Traits from the Coloration of Extinct Species?

    Science.gov (United States)

    Negro, Juan J.; Finlayson, Clive; Galván, Ismael

    2018-01-01

    Paleo-colour scientists have recently made the transition from describing melanin-based colouration in fossil specimens to inferring life-history traits of the species involved. Two such cases correspond to counter-shaded dinosaurs: dark-coloured due to melanins dorsally, and light-coloured ventrally. We believe that colour reconstruction of fossils based on the shape of preserved microstructures—the majority of paleo-colour studies involve melanin granules—is not without risks. In addition, animals with contrasting dorso-ventral colouration may be under different selection pressures beyond the need for camouflage, including, for instance, visual communication or ultraviolet (UV) protection. Melanin production is costly, and animals may invest less in areas of the integument where pigments are less needed. In addition, melanocytes exposed to UV radiation produce more melanin than unexposed melanocytes. Pigment economization may thus explain the colour pattern of some counter-shaded animals, including extinct species. Even in well-studied extant species, their diversity of hues and patterns is far from being understood; inferring colours and their functions in species only known from one or few specimens from the fossil record should be exerted with special prudence. PMID:29360744

  14. Melanins in Fossil Animals: Is It Possible to Infer Life History Traits from the Coloration of Extinct Species?

    Directory of Open Access Journals (Sweden)

    Juan J. Negro

    2018-01-01

    Full Text Available Paleo-colour scientists have recently made the transition from describing melanin-based colouration in fossil specimens to inferring life-history traits of the species involved. Two such cases correspond to counter-shaded dinosaurs: dark-coloured due to melanins dorsally, and light-coloured ventrally. We believe that colour reconstruction of fossils based on the shape of preserved microstructures—the majority of paleo-colour studies involve melanin granules—is not without risks. In addition, animals with contrasting dorso-ventral colouration may be under different selection pressures beyond the need for camouflage, including, for instance, visual communication or ultraviolet (UV protection. Melanin production is costly, and animals may invest less in areas of the integument where pigments are less needed. In addition, melanocytes exposed to UV radiation produce more melanin than unexposed melanocytes. Pigment economization may thus explain the colour pattern of some counter-shaded animals, including extinct species. Even in well-studied extant species, their diversity of hues and patterns is far from being understood; inferring colours and their functions in species only known from one or few specimens from the fossil record should be exerted with special prudence.

  15. Inferring social structure and its drivers from refuge use in the desert tortoise, a relatively solitary species

    Science.gov (United States)

    Sah, Pratha; Nussear, Kenneth E.; Esque, Todd C.; Aiello, Christina M.; Hudson, Peter J.; Bansal, Shweta

    2016-01-01

    For several species, refuges (such as burrows, dens, roosts, nests) are an essential resource for protection from predators and extreme environmental conditions. Refuges also serve as focal sites for social interactions, including mating, courtship, and aggression. Knowledge of refuge use patterns can therefore provide information about social structure, mating, and foraging success, as well as the robustness and health of wildlife populations, especially for species considered to be relatively solitary. In this study, we construct networks of burrow use to infer social associations in a threatened wildlife species typically considered solitary—the desert tortoise. We show that tortoise social networks are significantly different than null networks of random associations, and have moderate spatial constraints. We next use statistical models to identify major mechanisms behind individual-level variation in tortoise burrow use, popularity of burrows in desert tortoise habitat, and test for stressor-driven changes in refuge use patterns. We show that seasonal variation has a strong impact on tortoise burrow switching behavior. On the other hand, burrow age and topographical condition influence the number of tortoises visiting a burrow in desert tortoise habitat. Of three major population stressors affecting this species (translocation, drought, disease), translocation alters tortoise burrow switching behavior, with translocated animals visiting fewer unique burrows than residents. In a species that is not social, our study highlights the importance of leveraging refuge use behavior to study the presence of and mechanisms behind non-random social structure and individual-level variation. Our analysis of the impact of stressors on refuge-based social structure further emphasizes the potential of this method to detect environmental or anthropogenic disturbances.

  16. Inferring the rules of social interaction in migrating caribou.

    Science.gov (United States)

    Torney, Colin J; Lamont, Myles; Debell, Leon; Angohiatok, Ryan J; Leclerc, Lisa-Marie; Berdahl, Andrew M

    2018-05-19

    Social interactions are a significant factor that influence the decision-making of species ranging from humans to bacteria. In the context of animal migration, social interactions may lead to improved decision-making, greater ability to respond to environmental cues, and the cultural transmission of optimal routes. Despite their significance, the precise nature of social interactions in migrating species remains largely unknown. Here we deploy unmanned aerial systems to collect aerial footage of caribou as they undertake their migration from Victoria Island to mainland Canada. Through a Bayesian analysis of trajectories we reveal the fine-scale interaction rules of migrating caribou and show they are attracted to one another and copy directional choices of neighbours, but do not interact through clearly defined metric or topological interaction ranges. By explicitly considering the role of social information on movement decisions we construct a map of near neighbour influence that quantifies the nature of information flow in these herds. These results will inform more realistic, mechanism-based models of migration in caribou and other social ungulates, leading to better predictions of spatial use patterns and responses to changing environmental conditions. Moreover, we anticipate that the protocol we developed here will be broadly applicable to study social behaviour in a wide range of migratory and non-migratory taxa.This article is part of the theme issue 'Collective movement ecology'. © 2018 The Authors.

  17. Seasonal species interactions minimize the impact of species turnover on the likelihood of community persistence.

    Science.gov (United States)

    Saavedra, Serguei; Rohr, Rudolf P; Fortuna, Miguel A; Selva, Nuria; Bascompte, Jordi

    2016-04-01

    Many of the observed species interactions embedded in ecological communities are not permanent, but are characterized by temporal changes that are observed along with abiotic and biotic variations. While work has been done describing and quantifying these changes, little is known about their consequences for species coexistence. Here, we investigate the extent to which changes of species composition impact the likelihood of persistence of the predator-prey community in the highly seasonal Białowieza Primeval Forest (northeast Poland), and the extent to which seasonal changes of species interactions (predator diet) modulate the expected impact. This likelihood is estimated extending recent developments on the study of structural stability in ecological communities. We find that the observed species turnover strongly varies the likelihood of community persistence between summer and winter. Importantly, we demonstrate that the observed seasonal interaction changes minimize the variation in the likelihood of persistence associated with species turnover across the year. We find that these community dynamics can be explained as the coupling of individual species to their environment by minimizing both the variation in persistence conditions and the interaction changes between seasons. Our results provide a homeostatic explanation for seasonal species interactions and suggest that monitoring the association of interactions changes with the level of variation in community dynamics can provide a good indicator of the response of species to environmental pressures.

  18. Multimodel inference and adaptive management

    Science.gov (United States)

    Rehme, S.E.; Powell, L.A.; Allen, Craig R.

    2011-01-01

    Ecology is an inherently complex science coping with correlated variables, nonlinear interactions and multiple scales of pattern and process, making it difficult for experiments to result in clear, strong inference. Natural resource managers, policy makers, and stakeholders rely on science to provide timely and accurate management recommendations. However, the time necessary to untangle the complexities of interactions within ecosystems is often far greater than the time available to make management decisions. One method of coping with this problem is multimodel inference. Multimodel inference assesses uncertainty by calculating likelihoods among multiple competing hypotheses, but multimodel inference results are often equivocal. Despite this, there may be pressure for ecologists to provide management recommendations regardless of the strength of their study’s inference. We reviewed papers in the Journal of Wildlife Management (JWM) and the journal Conservation Biology (CB) to quantify the prevalence of multimodel inference approaches, the resulting inference (weak versus strong), and how authors dealt with the uncertainty. Thirty-eight percent and 14%, respectively, of articles in the JWM and CB used multimodel inference approaches. Strong inference was rarely observed, with only 7% of JWM and 20% of CB articles resulting in strong inference. We found the majority of weak inference papers in both journals (59%) gave specific management recommendations. Model selection uncertainty was ignored in most recommendations for management. We suggest that adaptive management is an ideal method to resolve uncertainty when research results in weak inference.

  19. Inference

    DEFF Research Database (Denmark)

    Møller, Jesper

    (This text written by Jesper Møller, Aalborg University, is submitted for the collection ‘Stochastic Geometry: Highlights, Interactions and New Perspectives', edited by Wilfrid S. Kendall and Ilya Molchanov, to be published by ClarendonPress, Oxford, and planned to appear as Section 4.1 with the ......(This text written by Jesper Møller, Aalborg University, is submitted for the collection ‘Stochastic Geometry: Highlights, Interactions and New Perspectives', edited by Wilfrid S. Kendall and Ilya Molchanov, to be published by ClarendonPress, Oxford, and planned to appear as Section 4.......1 with the title ‘Inference'.) This contribution concerns statistical inference for parametric models used in stochastic geometry and based on quick and simple simulation free procedures as well as more comprehensive methods using Markov chain Monte Carlo (MCMC) simulations. Due to space limitations the focus...

  20. Construction of analytically solvable models for interacting species. [biological species competition

    Science.gov (United States)

    Rosen, G.

    1976-01-01

    The basic form of a model representation for systems of n interacting biological species is a set of essentially nonlinear autonomous ordinary differential equations. A generic canonical expression for the rate functions in the equations is reported which permits the analytical general solution to be obtained by elementary computation. It is shown that a general analytical solution is directly obtainable for models where the rate functions are prescribed by the generic canonical expression from the outset. Some illustrative examples are given which demonstrate that the generic canonical expression can be used to construct analytically solvable models for two interacting species with limit-cycle dynamics as well as for a three-species interdependence.

  1. Species interactions reverse grassland responses to changing climate.

    Science.gov (United States)

    Suttle, K B; Thomsen, Meredith A; Power, Mary E

    2007-02-02

    Predictions of ecological response to climate change are based largely on direct climatic effects on species. We show that, in a California grassland, species interactions strongly influence responses to changing climate, overturning direct climatic effects within 5 years. We manipulated the seasonality and intensity of rainfall over large, replicate plots in accordance with projections of leading climate models and examined responses across several trophic levels. Changes in seasonal water availability had pronounced effects on individual species, but as precipitation regimes were sustained across years, feedbacks and species interactions overrode autecological responses to water and reversed community trajectories. Conditions that sharply increased production and diversity through 2 years caused simplification of the food web and deep reductions in consumer abundance after 5 years. Changes in these natural grassland communities suggest a prominent role for species interactions in ecosystem response to climate change.

  2. The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling.

    Science.gov (United States)

    Wisz, Mary Susanne; Pottier, Julien; Kissling, W Daniel; Pellissier, Loïc; Lenoir, Jonathan; Damgaard, Christian F; Dormann, Carsten F; Forchhammer, Mads C; Grytnes, John-Arvid; Guisan, Antoine; Heikkinen, Risto K; Høye, Toke T; Kühn, Ingolf; Luoto, Miska; Maiorano, Luigi; Nilsson, Marie-Charlotte; Normand, Signe; Öckinger, Erik; Schmidt, Niels M; Termansen, Mette; Timmermann, Allan; Wardle, David A; Aastrup, Peter; Svenning, Jens-Christian

    2013-02-01

    Predicting which species will occur together in the future, and where, remains one of the greatest challenges in ecology, and requires a sound understanding of how the abiotic and biotic environments interact with dispersal processes and history across scales. Biotic interactions and their dynamics influence species' relationships to climate, and this also has important implications for predicting future distributions of species. It is already well accepted that biotic interactions shape species' spatial distributions at local spatial extents, but the role of these interactions beyond local extents (e.g. 10 km(2) to global extents) are usually dismissed as unimportant. In this review we consolidate evidence for how biotic interactions shape species distributions beyond local extents and review methods for integrating biotic interactions into species distribution modelling tools. Drawing upon evidence from contemporary and palaeoecological studies of individual species ranges, functional groups, and species richness patterns, we show that biotic interactions have clearly left their mark on species distributions and realised assemblages of species across all spatial extents. We demonstrate this with examples from within and across trophic groups. A range of species distribution modelling tools is available to quantify species environmental relationships and predict species occurrence, such as: (i) integrating pairwise dependencies, (ii) using integrative predictors, and (iii) hybridising species distribution models (SDMs) with dynamic models. These methods have typically only been applied to interacting pairs of species at a single time, require a priori ecological knowledge about which species interact, and due to data paucity must assume that biotic interactions are constant in space and time. To better inform the future development of these models across spatial scales, we call for accelerated collection of spatially and temporally explicit species data. Ideally

  3. FunCoup 4: new species, data, and visualization

    OpenAIRE

    Ogris, Christoph; Guala, Dimitri; Kaduk, Mateusz; Sonnhammer, Erik L L

    2017-01-01

    Abstract This release of the FunCoup database (http://funcoup.sbc.su.se) is the fourth generation of one of the most comprehensive databases for genome-wide functional association networks. These functional associations are inferred via integrating various data types using a naive Bayesian algorithm and orthology based information transfer across different species. This approach provides high coverage of the included genomes as well as high quality of inferred interactions. In this update of ...

  4. Ploidy levels among species in the 'Oxalis tuberosa alliance' as inferred by flow cytometry.

    Science.gov (United States)

    Emshwiller, Eve

    2002-06-01

    The 'Oxalis tuberosa alliance' is a group of Andean Oxalis species allied to the Andean tuber crop O. tuberosa Molina (Oxalidaceae), commonly known as 'oca'. As part of a larger project studying the origins of polyploidy and domestication of cultivated oca, flow cytometry was used to survey DNA ploidy levels among Bolivian and Peruvian accessions of alliance members. In addition, this study provided a first assessment of C-values in the alliance by estimating nuclear DNA contents of these accessions using chicken erythrocytes as internal standard. Ten Bolivian accessions of cultivated O. tuberosa were confirmed to be octoploid, with a mean nuclear DNA content of approx. 3.6 pg/2C. Two Peruvian wild Oxalis species, O. phaeotricha and O. picchensis, were inferred to be tetraploid (both with approx. 1.67 pg/2C), the latter being one of the putative progenitors of O. tuberosa identified by chloroplast-expressed glutamine synthetase data in prior work. The remaining accessions (from 78 populations provisionally identified as 35 species) were DNA diploid, with nuclear DNA contents varying from 0.79 to 1.34 pg/2C.

  5. Likelihood inference for unions of interacting discs

    DEFF Research Database (Denmark)

    Møller, Jesper; Helisová, Katarina

    To the best of our knowledge, this is the first paper which discusses likelihood inference or a random set using a germ-grain model, where the individual grains are unobservable edge effects occur, and other complications appear. We consider the case where the grains form a disc process modelled...... is specified with respect to a given marked Poisson model (i.e. a Boolean model). We show how edge effects and other complications can be handled by considering a certain conditional likelihood. Our methodology is illustrated by analyzing Peter Diggle's heather dataset, where we discuss the results...... of simulation-based maximum likelihood inference and the effect of specifying different reference Poisson models....

  6. Artificial neural network inference (ANNI: a study on gene-gene interaction for biomarkers in childhood sarcomas.

    Directory of Open Access Journals (Sweden)

    Dong Ling Tong

    Full Text Available OBJECTIVE: To model the potential interaction between previously identified biomarkers in children sarcomas using artificial neural network inference (ANNI. METHOD: To concisely demonstrate the biological interactions between correlated genes in an interaction network map, only 2 types of sarcomas in the children small round blue cell tumors (SRBCTs dataset are discussed in this paper. A backpropagation neural network was used to model the potential interaction between genes. The prediction weights and signal directions were used to model the strengths of the interaction signals and the direction of the interaction link between genes. The ANN model was validated using Monte Carlo cross-validation to minimize the risk of over-fitting and to optimize generalization ability of the model. RESULTS: Strong connection links on certain genes (TNNT1 and FNDC5 in rhabdomyosarcoma (RMS; FCGRT and OLFM1 in Ewing's sarcoma (EWS suggested their potency as central hubs in the interconnection of genes with different functionalities. The results showed that the RMS patients in this dataset are likely to be congenital and at low risk of cardiomyopathy development. The EWS patients are likely to be complicated by EWS-FLI fusion and deficiency in various signaling pathways, including Wnt, Fas/Rho and intracellular oxygen. CONCLUSIONS: The ANN network inference approach and the examination of identified genes in the published literature within the context of the disease highlights the substantial influence of certain genes in sarcomas.

  7. Automated adaptive inference of phenomenological dynamical models

    Science.gov (United States)

    Daniels, Bryan

    Understanding the dynamics of biochemical systems can seem impossibly complicated at the microscopic level: detailed properties of every molecular species, including those that have not yet been discovered, could be important for producing macroscopic behavior. The profusion of data in this area has raised the hope that microscopic dynamics might be recovered in an automated search over possible models, yet the combinatorial growth of this space has limited these techniques to systems that contain only a few interacting species. We take a different approach inspired by coarse-grained, phenomenological models in physics. Akin to a Taylor series producing Hooke's Law, forgoing microscopic accuracy allows us to constrain the search over dynamical models to a single dimension. This makes it feasible to infer dynamics with very limited data, including cases in which important dynamical variables are unobserved. We name our method Sir Isaac after its ability to infer the dynamical structure of the law of gravitation given simulated planetary motion data. Applying the method to output from a microscopically complicated but macroscopically simple biological signaling model, it is able to adapt the level of detail to the amount of available data. Finally, using nematode behavioral time series data, the method discovers an effective switch between behavioral attractors after the application of a painful stimulus.

  8. Generalist Bee Species on Brazilian Bee-Plant Interaction Networks

    Directory of Open Access Journals (Sweden)

    Astrid de Matos Peixoto Kleinert

    2012-01-01

    Full Text Available Determining bee and plant interactions has an important role on understanding general biology of bee species as well as the potential pollinating relationship between them. Bee surveys have been conducted in Brazil since the end of the 1960s. Most of them applied standardized methods and had identified the plant species where the bees were collected. To analyze the most generalist bees on Brazilian surveys, we built a matrix of bee-plant interactions. We estimated the most generalist bees determining the three bee species of each surveyed locality that presented the highest number of interactions. We found 47 localities and 39 species of bees. Most of them belong to Apidae (31 species and Halictidae (6 families and to Meliponini (14 and Xylocopini (6 tribes. However, most of the surveys presented Apis mellifera and/or Trigona spinipes as the most generalist species. Apis mellifera is an exotic bee species and Trigona spinipes, a native species, is also widespread and presents broad diet breath and high number of individuals per colony.

  9. Dynamical Bayesian inference of time-evolving interactions: From a pair of coupled oscillators to networks of oscillators

    Science.gov (United States)

    Duggento, Andrea; Stankovski, Tomislav; McClintock, Peter V. E.; Stefanovska, Aneta

    2012-12-01

    Living systems have time-evolving interactions that, until recently, could not be identified accurately from recorded time series in the presence of noise. Stankovski [Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.109.024101 109, 024101 (2012)] introduced a method based on dynamical Bayesian inference that facilitates the simultaneous detection of time-varying synchronization, directionality of influence, and coupling functions. It can distinguish unsynchronized dynamics from noise-induced phase slips. The method is based on phase dynamics, with Bayesian inference of the time-evolving parameters being achieved by shaping the prior densities to incorporate knowledge of previous samples. We now present the method in detail using numerically generated data, data from an analog electronic circuit, and cardiorespiratory data. We also generalize the method to encompass networks of interacting oscillators and thus demonstrate its applicability to small-scale networks.

  10. Making inference from wildlife collision data: inferring predator absence from prey strikes

    Directory of Open Access Journals (Sweden)

    Peter Caley

    2017-02-01

    Full Text Available Wildlife collision data are ubiquitous, though challenging for making ecological inference due to typically irreducible uncertainty relating to the sampling process. We illustrate a new approach that is useful for generating inference from predator data arising from wildlife collisions. By simply conditioning on a second prey species sampled via the same collision process, and by using a biologically realistic numerical response functions, we can produce a coherent numerical response relationship between predator and prey. This relationship can then be used to make inference on the population size of the predator species, including the probability of extinction. The statistical conditioning enables us to account for unmeasured variation in factors influencing the runway strike incidence for individual airports and to enable valid comparisons. A practical application of the approach for testing hypotheses about the distribution and abundance of a predator species is illustrated using the hypothesized red fox incursion into Tasmania, Australia. We estimate that conditional on the numerical response between fox and lagomorph runway strikes on mainland Australia, the predictive probability of observing no runway strikes of foxes in Tasmania after observing 15 lagomorph strikes is 0.001. We conclude there is enough evidence to safely reject the null hypothesis that there is a widespread red fox population in Tasmania at a population density consistent with prey availability. The method is novel and has potential wider application.

  11. Making inference from wildlife collision data: inferring predator absence from prey strikes.

    Science.gov (United States)

    Caley, Peter; Hosack, Geoffrey R; Barry, Simon C

    2017-01-01

    Wildlife collision data are ubiquitous, though challenging for making ecological inference due to typically irreducible uncertainty relating to the sampling process. We illustrate a new approach that is useful for generating inference from predator data arising from wildlife collisions. By simply conditioning on a second prey species sampled via the same collision process, and by using a biologically realistic numerical response functions, we can produce a coherent numerical response relationship between predator and prey. This relationship can then be used to make inference on the population size of the predator species, including the probability of extinction. The statistical conditioning enables us to account for unmeasured variation in factors influencing the runway strike incidence for individual airports and to enable valid comparisons. A practical application of the approach for testing hypotheses about the distribution and abundance of a predator species is illustrated using the hypothesized red fox incursion into Tasmania, Australia. We estimate that conditional on the numerical response between fox and lagomorph runway strikes on mainland Australia, the predictive probability of observing no runway strikes of foxes in Tasmania after observing 15 lagomorph strikes is 0.001. We conclude there is enough evidence to safely reject the null hypothesis that there is a widespread red fox population in Tasmania at a population density consistent with prey availability. The method is novel and has potential wider application.

  12. Patterns of coexistence of two species of freshwater turtles are affected by spatial scale

    DEFF Research Database (Denmark)

    Segurado, P.; Kunin, W.E.; Filipe, A.F.

    2012-01-01

    Inferring biotic interactions from the examination of patterns of species occurrences has been a central tenet in community ecology, and it has recently gained interest in the context of single-species distribution modelling. However, understanding of how spatial extent and grain size affect such...

  13. On the criticality of inferred models

    Science.gov (United States)

    Mastromatteo, Iacopo; Marsili, Matteo

    2011-10-01

    Advanced inference techniques allow one to reconstruct a pattern of interaction from high dimensional data sets, from probing simultaneously thousands of units of extended systems—such as cells, neural tissues and financial markets. We focus here on the statistical properties of inferred models and argue that inference procedures are likely to yield models which are close to singular values of parameters, akin to critical points in physics where phase transitions occur. These are points where the response of physical systems to external perturbations, as measured by the susceptibility, is very large and diverges in the limit of infinite size. We show that the reparameterization invariant metrics in the space of probability distributions of these models (the Fisher information) are directly related to the susceptibility of the inferred model. As a result, distinguishable models tend to accumulate close to critical points, where the susceptibility diverges in infinite systems. This region is the one where the estimate of inferred parameters is most stable. In order to illustrate these points, we discuss inference of interacting point processes with application to financial data and show that sensible choices of observation time scales naturally yield models which are close to criticality.

  14. On the criticality of inferred models

    International Nuclear Information System (INIS)

    Mastromatteo, Iacopo; Marsili, Matteo

    2011-01-01

    Advanced inference techniques allow one to reconstruct a pattern of interaction from high dimensional data sets, from probing simultaneously thousands of units of extended systems—such as cells, neural tissues and financial markets. We focus here on the statistical properties of inferred models and argue that inference procedures are likely to yield models which are close to singular values of parameters, akin to critical points in physics where phase transitions occur. These are points where the response of physical systems to external perturbations, as measured by the susceptibility, is very large and diverges in the limit of infinite size. We show that the reparameterization invariant metrics in the space of probability distributions of these models (the Fisher information) are directly related to the susceptibility of the inferred model. As a result, distinguishable models tend to accumulate close to critical points, where the susceptibility diverges in infinite systems. This region is the one where the estimate of inferred parameters is most stable. In order to illustrate these points, we discuss inference of interacting point processes with application to financial data and show that sensible choices of observation time scales naturally yield models which are close to criticality

  15. Biotic Interactions Shape the Ecological Distributions of Staphylococcus Species.

    Science.gov (United States)

    Kastman, Erik K; Kamelamela, Noelani; Norville, Josh W; Cosetta, Casey M; Dutton, Rachel J; Wolfe, Benjamin E

    2016-10-18

    Many metagenomic sequencing studies have observed the presence of closely related bacterial species or genotypes in the same microbiome. Previous attempts to explain these patterns of microdiversity have focused on the abiotic environment, but few have considered how biotic interactions could drive patterns of microbiome diversity. We dissected the patterns, processes, and mechanisms shaping the ecological distributions of three closely related Staphylococcus species in cheese rind biofilms. Paradoxically, the most abundant species (S. equorum) is the slowest colonizer and weakest competitor based on growth and competition assays in the laboratory. Through in vitro community reconstructions, we determined that biotic interactions with neighboring fungi help resolve this paradox. Species-specific stimulation of the poor competitor by fungi of the genus Scopulariopsis allows S. equorum to dominate communities in vitro as it does in situ Results of comparative genomic and transcriptomic experiments indicate that iron utilization pathways, including a homolog of the S. aureus staphyloferrin B siderophore operon pathway, are potential molecular mechanisms underlying Staphylococcus-Scopulariopsis interactions. Our integrated approach demonstrates that fungi can structure the ecological distributions of closely related bacterial species, and the data highlight the importance of bacterium-fungus interactions in attempts to design and manipulate microbiomes. Decades of culture-based studies and more recent metagenomic studies have demonstrated that bacterial species in agriculture, medicine, industry, and nature are unevenly distributed across time and space. The ecological processes and molecular mechanisms that shape these distributions are not well understood because it is challenging to connect in situ patterns of diversity with mechanistic in vitro studies in the laboratory. Using tractable cheese rind biofilms and a focus on coagulase-negative staphylococcus (CNS

  16. Inferring about the extinction of a species using certain and uncertain sightings.

    Science.gov (United States)

    Kodikara, Saritha; Demirhan, Haydar; Stone, Lewi

    2018-04-07

    The sighting record of threatened species is often used to infer the possibility of extinction. Most of these sightings have uncertain validity. Solow and Beet(2014) developed two models using a Bayesian approach which allowed for uncertainty in the sighting record by formally incorporating both certain and uncertain sightings, but in different ways. Interestingly, the two methods give completely different conclusions concerning the extinction of the Ivory-billed Woodpecker. We further examined these two methods to provide a mathematical explanation, and to explore in more depth, as to why the results differed from one another. It was found that the first model was more sensitive to the last uncertain sighting, while the second was more sensitive to the last certain sighting. The difficulties in choosing the appropriate model are discussed. Copyright © 2018 Elsevier Ltd. All rights reserved.

  17. Inferring microbial interaction networks from metagenomic data using SgLV-EKF algorithm.

    Science.gov (United States)

    Alshawaqfeh, Mustafa; Serpedin, Erchin; Younes, Ahmad Bani

    2017-03-27

    Inferring the microbial interaction networks (MINs) and modeling their dynamics are critical in understanding the mechanisms of the bacterial ecosystem and designing antibiotic and/or probiotic therapies. Recently, several approaches were proposed to infer MINs using the generalized Lotka-Volterra (gLV) model. Main drawbacks of these models include the fact that these models only consider the measurement noise without taking into consideration the uncertainties in the underlying dynamics. Furthermore, inferring the MIN is characterized by the limited number of observations and nonlinearity in the regulatory mechanisms. Therefore, novel estimation techniques are needed to address these challenges. This work proposes SgLV-EKF: a stochastic gLV model that adopts the extended Kalman filter (EKF) algorithm to model the MIN dynamics. In particular, SgLV-EKF employs a stochastic modeling of the MIN by adding a noise term to the dynamical model to compensate for modeling uncertainties. This stochastic modeling is more realistic than the conventional gLV model which assumes that the MIN dynamics are perfectly governed by the gLV equations. After specifying the stochastic model structure, we propose the EKF to estimate the MIN. SgLV-EKF was compared with two similarity-based algorithms, one algorithm from the integral-based family and two regression-based algorithms, in terms of the achieved performance on two synthetic data-sets and two real data-sets. The first data-set models the randomness in measurement data, whereas, the second data-set incorporates uncertainties in the underlying dynamics. The real data-sets are provided by a recent study pertaining to an antibiotic-mediated Clostridium difficile infection. The experimental results demonstrate that SgLV-EKF outperforms the alternative methods in terms of robustness to measurement noise, modeling errors, and tracking the dynamics of the MIN. Performance analysis demonstrates that the proposed SgLV-EKF algorithm

  18. Inferring Phylogenetic Networks Using PhyloNet.

    Science.gov (United States)

    Wen, Dingqiao; Yu, Yun; Zhu, Jiafan; Nakhleh, Luay

    2018-07-01

    PhyloNet was released in 2008 as a software package for representing and analyzing phylogenetic networks. At the time of its release, the main functionalities in PhyloNet consisted of measures for comparing network topologies and a single heuristic for reconciling gene trees with a species tree. Since then, PhyloNet has grown significantly. The software package now includes a wide array of methods for inferring phylogenetic networks from data sets of unlinked loci while accounting for both reticulation (e.g., hybridization) and incomplete lineage sorting. In particular, PhyloNet now allows for maximum parsimony, maximum likelihood, and Bayesian inference of phylogenetic networks from gene tree estimates. Furthermore, Bayesian inference directly from sequence data (sequence alignments or biallelic markers) is implemented. Maximum parsimony is based on an extension of the "minimizing deep coalescences" criterion to phylogenetic networks, whereas maximum likelihood and Bayesian inference are based on the multispecies network coalescent. All methods allow for multiple individuals per species. As computing the likelihood of a phylogenetic network is computationally hard, PhyloNet allows for evaluation and inference of networks using a pseudolikelihood measure. PhyloNet summarizes the results of the various analyzes and generates phylogenetic networks in the extended Newick format that is readily viewable by existing visualization software.

  19. Infusing considerations of trophic dependencies into species distribution modelling.

    Science.gov (United States)

    Trainor, Anne M; Schmitz, Oswald J

    2014-12-01

    Community ecology involves studying the interdependence of species with each other and their environment to predict their geographical distribution and abundance. Modern species distribution analyses characterise species-environment dependency well, but offer only crude approximations of species interdependency. Typically, the dependency between focal species and other species is characterised using other species' point occurrences as spatial covariates to constrain the focal species' predicted range. This implicitly assumes that the strength of interdependency is homogeneous across space, which is not generally supported by analyses of species interactions. This discrepancy has an important bearing on the accuracy of inferences about habitat suitability for species. We introduce a framework that integrates principles from consumer-resource analyses, resource selection theory and species distribution modelling to enhance quantitative prediction of species geographical distributions. We show how to apply the framework using a case study of lynx and snowshoe hare interactions with each other and their environment. The analysis shows how the framework offers a spatially refined understanding of species distribution that is sensitive to nuances in biophysical attributes of the environment that determine the location and strength of species interactions. © 2014 John Wiley & Sons Ltd/CNRS.

  20. Simulated tri-trophic networks reveal complex relationships between species diversity and interaction diversity.

    Science.gov (United States)

    Pardikes, Nicholas A; Lumpkin, Will; Hurtado, Paul J; Dyer, Lee A

    2018-01-01

    Most of earth's biodiversity is comprised of interactions among species, yet it is unclear what causes variation in interaction diversity across space and time. We define interaction diversity as the richness and relative abundance of interactions linking species together at scales from localized, measurable webs to entire ecosystems. Large-scale patterns suggest that two basic components of interaction diversity differ substantially and predictably between different ecosystems: overall taxonomic diversity and host specificity of consumers. Understanding how these factors influence interaction diversity, and quantifying the causes and effects of variation in interaction diversity are important goals for community ecology. While previous studies have examined the effects of sampling bias and consumer specialization on determining patterns of ecological networks, these studies were restricted to two trophic levels and did not incorporate realistic variation in species diversity and consumer diet breadth. Here, we developed a food web model to generate tri-trophic ecological networks, and evaluated specific hypotheses about how the diversity of trophic interactions and species diversity are related under different scenarios of species richness, taxonomic abundance, and consumer diet breadth. We investigated the accumulation of species and interactions and found that interactions accumulate more quickly; thus, the accumulation of novel interactions may require less sampling effort than sampling species in order to get reliable estimates of either type of diversity. Mean consumer diet breadth influenced the correlation between species and interaction diversity significantly more than variation in both species richness and taxonomic abundance. However, this effect of diet breadth on interaction diversity is conditional on the number of observed interactions included in the models. The results presented here will help develop realistic predictions of the relationships

  1. Hydraulic lift and tolerance to salinity of semiarid species: consequences for species interactions.

    Science.gov (United States)

    Armas, Cristina; Padilla, Francisco M; Pugnaire, Francisco I; Jackson, Robert B

    2010-01-01

    The different abilities of plant species to use ephemeral or permanent water sources strongly affect physiological performance and species coexistence in water-limited ecosystems. In addition to withstanding drought, plants in coastal habitats often have to withstand highly saline soils, an additional ecological stress. Here we tested whether observed competitive abilities and C-water relations of two interacting shrub species from an arid coastal system were more related to differences in root architecture or salinity tolerance. We explored water sources of interacting Juniperus phoenicea Guss. and Pistacia lentiscus L. plants by conducting physiology measurements, including water relations, CO2 exchange, photochemical efficiency, sap osmolality, and water and C isotopes. We also conducted parallel soil analyses that included electrical conductivity, humidity, and water isotopes. During drought, Pistacia shrubs relied primarily on permanent salty groundwater, while isolated Juniperus plants took up the scarce and relatively fresh water stored in upper soil layers. As drought progressed further, the physiological activity of Juniperus plants nearly stopped while Pistacia plants were only slightly affected. Juniperus plants growing with Pistacia had stem-water isotopes that matched Pistacia, unlike values for isolated Juniperus plants. This result suggests that Pistacia shrubs supplied water to nearby Juniperus plants through hydraulic lift. This lifted water, however, did not appear to benefit Juniperus plants, as their physiological performance with co-occurring Pistacia plants was poor, including lower water potentials and rates of photosynthesis than isolated plants. Juniperus was more salt sensitive than Pistacia, which withstood salinity levels similar to that of groundwater. Overall, the different abilities of the two species to use salty water appear to drive the outcome of their interaction, resulting in asymmetric competition where Juniperus is negatively

  2. A graphical user interface for a method to infer kinetics and network architecture (MIKANA).

    Science.gov (United States)

    Mourão, Márcio A; Srividhya, Jeyaraman; McSharry, Patrick E; Crampin, Edmund J; Schnell, Santiago

    2011-01-01

    One of the main challenges in the biomedical sciences is the determination of reaction mechanisms that constitute a biochemical pathway. During the last decades, advances have been made in building complex diagrams showing the static interactions of proteins. The challenge for systems biologists is to build realistic models of the dynamical behavior of reactants, intermediates and products. For this purpose, several methods have been recently proposed to deduce the reaction mechanisms or to estimate the kinetic parameters of the elementary reactions that constitute the pathway. One such method is MIKANA: Method to Infer Kinetics And Network Architecture. MIKANA is a computational method to infer both reaction mechanisms and estimate the kinetic parameters of biochemical pathways from time course data. To make it available to the scientific community, we developed a Graphical User Interface (GUI) for MIKANA. Among other features, the GUI validates and processes an input time course data, displays the inferred reactions, generates the differential equations for the chemical species in the pathway and plots the prediction curves on top of the input time course data. We also added a new feature to MIKANA that allows the user to exclude a priori known reactions from the inferred mechanism. This addition improves the performance of the method. In this article, we illustrate the GUI for MIKANA with three examples: an irreversible Michaelis-Menten reaction mechanism; the interaction map of chemical species of the muscle glycolytic pathway; and the glycolytic pathway of Lactococcus lactis. We also describe the code and methods in sufficient detail to allow researchers to further develop the code or reproduce the experiments described. The code for MIKANA is open source, free for academic and non-academic use and is available for download (Information S1).

  3. Neutral Community Dynamics and the Evolution of Species Interactions.

    Science.gov (United States)

    Coelho, Marco Túlio P; Rangel, Thiago F

    2018-04-01

    A contemporary goal in ecology is to determine the ecological and evolutionary processes that generate recurring structural patterns in mutualistic networks. One of the great challenges is testing the capacity of neutral processes to replicate observed patterns in ecological networks, since the original formulation of the neutral theory lacks trophic interactions. Here, we develop a stochastic-simulation neutral model adding trophic interactions to the neutral theory of biodiversity. Without invoking ecological differences among individuals of different species, and assuming that ecological interactions emerge randomly, we demonstrate that a spatially explicit multitrophic neutral model is able to capture the recurrent structural patterns of mutualistic networks (i.e., degree distribution, connectance, nestedness, and phylogenetic signal of species interactions). Nonrandom species distribution, caused by probabilistic events of migration and speciation, create nonrandom network patterns. These findings have broad implications for the interpretation of niche-based processes as drivers of ecological networks, as well as for the integration of network structures with demographic stochasticity.

  4. Ploidy Levels among Species in the ‘Oxalis tuberosa Alliance’ as Inferred by Flow Cytometry

    Science.gov (United States)

    EMSHWILLER, EVE

    2002-01-01

    The ‘Oxalis tuberosa alliance’ is a group of Andean Oxalis species allied to the Andean tuber crop O. tuberosa Molina (Oxalidaceae), commonly known as ‘oca’. As part of a larger project studying the origins of polyploidy and domestication of cultivated oca, flow cytometry was used to survey DNA ploidy levels among Bolivian and Peruvian accessions of alliance members. In addition, this study provided a first assessment of C‐values in the alliance by estimating nuclear DNA contents of these accessions using chicken erythrocytes as internal standard. Ten Bolivian accessions of cultivated O. tuberosa were confirmed to be octoploid, with a mean nuclear DNA content of approx. 3·6 pg/2C. Two Peruvian wild Oxalis species, O. phaeotricha and O. picchensis, were inferred to be tetraploid (both with approx. 1·67 pg/2C), the latter being one of the putative progenitors of O. tuberosa identified by chloroplast‐expressed glutamine synthetase data in prior work. The remaining accessions (from 78 populations provisionally identified as 35 species) were DNA diploid, with nuclear DNA contents varying from 0·79 to 1·34 pg/2C. PMID:12102530

  5. Melanins in Fossil Animals: Is It Possible to Infer Life History Traits from the Coloration of Extinct Species?

    OpenAIRE

    Negro, Juan J.; Fynlayson, Clive; Galván, Ismael

    2018-01-01

    Paleo-colour scientists have recently made the transition from describing melanin-based colouration in fossil specimens to inferring life-history traits of the species involved. Two such cases correspond to counter-shaded dinosaurs: dark-coloured due to melanins dorsally, and light-coloured ventrally. We believe that colour reconstruction of fossils based on the shape of preserved microstructures—the majority of paleo-colour studies involve melanin granules—is not without risks. In addition, ...

  6. Inverse Ising inference with correlated samples

    International Nuclear Information System (INIS)

    Obermayer, Benedikt; Levine, Erel

    2014-01-01

    Correlations between two variables of a high-dimensional system can be indicative of an underlying interaction, but can also result from indirect effects. Inverse Ising inference is a method to distinguish one from the other. Essentially, the parameters of the least constrained statistical model are learned from the observed correlations such that direct interactions can be separated from indirect correlations. Among many other applications, this approach has been helpful for protein structure prediction, because residues which interact in the 3D structure often show correlated substitutions in a multiple sequence alignment. In this context, samples used for inference are not independent but share an evolutionary history on a phylogenetic tree. Here, we discuss the effects of correlations between samples on global inference. Such correlations could arise due to phylogeny but also via other slow dynamical processes. We present a simple analytical model to address the resulting inference biases, and develop an exact method accounting for background correlations in alignment data by combining phylogenetic modeling with an adaptive cluster expansion algorithm. We find that popular reweighting schemes are only marginally effective at removing phylogenetic bias, suggest a rescaling strategy that yields better results, and provide evidence that our conclusions carry over to the frequently used mean-field approach to the inverse Ising problem. (paper)

  7. BPhyOG: An interactive server for genome-wide inference of bacterial phylogenies based on overlapping genes

    Directory of Open Access Journals (Sweden)

    Lin Kui

    2007-07-01

    Full Text Available Abstract Background Overlapping genes (OGs in bacterial genomes are pairs of adjacent genes of which the coding sequences overlap partly or entirely. With the rapid accumulation of sequence data, many OGs in bacterial genomes have now been identified. Indeed, these might prove a consistent feature across all microbial genomes. Our previous work suggests that OGs can be considered as robust markers at the whole genome level for the construction of phylogenies. An online, interactive web server for inferring phylogenies is needed for biologists to analyze phylogenetic relationships among a set of bacterial genomes of interest. Description BPhyOG is an online interactive server for reconstructing the phylogenies of completely sequenced bacterial genomes on the basis of their shared overlapping genes. It provides two tree-reconstruction methods: Neighbor Joining (NJ and Unweighted Pair-Group Method using Arithmetic averages (UPGMA. Users can apply the desired method to generate phylogenetic trees, which are based on an evolutionary distance matrix for the selected genomes. The distance between two genomes is defined by the normalized number of their shared OG pairs. BPhyOG also allows users to browse the OGs that were used to infer the phylogenetic relationships. It provides detailed annotation for each OG pair and the features of the component genes through hyperlinks. Users can also retrieve each of the homologous OG pairs that have been determined among 177 genomes. It is a useful tool for analyzing the tree of life and overlapping genes from a genomic standpoint. Conclusion BPhyOG is a useful interactive web server for genome-wide inference of any potential evolutionary relationship among the genomes selected by users. It currently includes 177 completely sequenced bacterial genomes containing 79,855 OG pairs, the annotation and homologous OG pairs of which are integrated comprehensively. The reliability of phylogenies complemented by

  8. On Maximum Entropy and Inference

    Directory of Open Access Journals (Sweden)

    Luigi Gresele

    2017-11-01

    Full Text Available Maximum entropy is a powerful concept that entails a sharp separation between relevant and irrelevant variables. It is typically invoked in inference, once an assumption is made on what the relevant variables are, in order to estimate a model from data, that affords predictions on all other (dependent variables. Conversely, maximum entropy can be invoked to retrieve the relevant variables (sufficient statistics directly from the data, once a model is identified by Bayesian model selection. We explore this approach in the case of spin models with interactions of arbitrary order, and we discuss how relevant interactions can be inferred. In this perspective, the dimensionality of the inference problem is not set by the number of parameters in the model, but by the frequency distribution of the data. We illustrate the method showing its ability to recover the correct model in a few prototype cases and discuss its application on a real dataset.

  9. Species-Specific Effects on Ecosystem Functioning Can Be Altered by Interspecific Interactions.

    Science.gov (United States)

    Clare, David S; Spencer, Matthew; Robinson, Leonie A; Frid, Christopher L J

    2016-01-01

    Biological assemblages are constantly undergoing change, with species being introduced, extirpated and experiencing shifts in their densities. Theory and experimentation suggest that the impacts of such change on ecosystem functioning should be predictable based on the biological traits of the species involved. However, interspecific interactions could alter how species affect functioning, with the strength and sign of interactions potentially depending on environmental context (e.g. homogenous vs. heterogeneous conditions) and the function considered. Here, we assessed how concurrent changes to the densities of two common marine benthic invertebrates, Corophium volutator and Hediste diversicolor, affected the ecological functions of organic matter consumption and benthic-pelagic nutrient flux. Complementary experiments were conducted within homogenous laboratory microcosms and naturally heterogeneous field plots. When the densities of the species were increased within microcosms, interspecific interactions enhanced effects on organic matter consumption and reduced effects on nutrient flux. Trait-based predictions of how each species would affect functioning were only consistently supported when the density of the other species was low. In field plots, increasing the density of either species had a positive effect on organic matter consumption (with no significant interspecific interactions) but no effect on nutrient flux. Our results indicate that species-specific effects on ecosystem functioning can be altered by interspecific interactions, which can be either facilitative (positive) or antagonistic (negative) depending on the function considered. The impacts of biodiversity change may therefore not be predictable based solely on the biological traits of the species involved. Possible explanations for why interactions were detected in microcosms but not in the field are discussed.

  10. Species-Specific Effects on Ecosystem Functioning Can Be Altered by Interspecific Interactions.

    Directory of Open Access Journals (Sweden)

    David S Clare

    Full Text Available Biological assemblages are constantly undergoing change, with species being introduced, extirpated and experiencing shifts in their densities. Theory and experimentation suggest that the impacts of such change on ecosystem functioning should be predictable based on the biological traits of the species involved. However, interspecific interactions could alter how species affect functioning, with the strength and sign of interactions potentially depending on environmental context (e.g. homogenous vs. heterogeneous conditions and the function considered. Here, we assessed how concurrent changes to the densities of two common marine benthic invertebrates, Corophium volutator and Hediste diversicolor, affected the ecological functions of organic matter consumption and benthic-pelagic nutrient flux. Complementary experiments were conducted within homogenous laboratory microcosms and naturally heterogeneous field plots. When the densities of the species were increased within microcosms, interspecific interactions enhanced effects on organic matter consumption and reduced effects on nutrient flux. Trait-based predictions of how each species would affect functioning were only consistently supported when the density of the other species was low. In field plots, increasing the density of either species had a positive effect on organic matter consumption (with no significant interspecific interactions but no effect on nutrient flux. Our results indicate that species-specific effects on ecosystem functioning can be altered by interspecific interactions, which can be either facilitative (positive or antagonistic (negative depending on the function considered. The impacts of biodiversity change may therefore not be predictable based solely on the biological traits of the species involved. Possible explanations for why interactions were detected in microcosms but not in the field are discussed.

  11. Context-dependent interactions and the regulation of species richness in freshwater fish

    Science.gov (United States)

    MacDougall, Andrew S.; Harvey, Eric; McCune, Jenny L.; Nilsson, Karin A.; Bennett, Joseph; Firn, Jennifer; Bartley, Timothy; Grace, James B.; Kelly, Jocelyn; Tunney, Tyler D.; McMeans, Bailey; Matsuzaki, Shin-Ichiro S.; Kadoya, Taku; Esch, Ellen; Cazelles, Kevin; Lester, Nigel; McCann, Kevin S.

    2018-01-01

    Species richness is regulated by a complex network of scale-dependent processes. This complexity can obscure the influence of limiting species interactions, making it difficult to determine if abiotic or biotic drivers are more predominant regulators of richness. Using integrative modeling of freshwater fish richness from 721 lakes along an 11olatitudinal gradient, we find negative interactions to be a relatively minor independent predictor of species richness in lakes despite the widespread presence of predators. Instead, interaction effects, when detectable among major functional groups and 231 species pairs, were strong, often positive, but contextually dependent on environment. These results are consistent with the idea that negative interactions internally structure lake communities but do not consistently ‘scale-up’ to regulate richness independently of the environment. The importance of environment for interaction outcomes and its role in the regulation of species richness highlights the potential sensitivity of fish communities to the environmental changes affecting lakes globally.

  12. Are trade-offs among species' ecological interactions scale dependent? A test using pitcher-plant inquiline species.

    Science.gov (United States)

    Kneitel, Jamie M

    2012-01-01

    Trade-offs among species' ecological interactions is a pervasive explanation for species coexistence. The traits associated with trade-offs are typically measured to mechanistically explain species coexistence at a single spatial scale. However, species potentially interact at multiple scales and this may be reflected in the traits among coexisting species. I quantified species' ecological traits associated with the trade-offs expected at both local (competitive ability and predator tolerance) and regional (competitive ability and colonization rate) community scales. The most common species (four protozoa and a rotifer) from the middle trophic level of a pitcher plant (Sarracenia purpurea) inquiline community were used to link species traits to previously observed patterns of species diversity and abundance. Traits associated with trade-offs (competitive ability, predator tolerance, and colonization rate) and other ecological traits (size, growth rate, and carrying capacity) were measured for each of the focal species. Traits were correlated with one another with a negative relationship indicative of a trade-off. Protozoan and rotifer species exhibited a negative relationship between competitive ability and predator tolerance, indicative of coexistence at the local community scale. There was no relationship between competitive ability and colonization rate. Size, growth rate, and carrying capacity were correlated with each other and the trade-off traits: Size was related to both competitive ability and predator tolerance, but growth rate and carrying capacity were correlated with predator tolerance. When partial correlations were conducted controlling for size, growth rate and carrying capacity, the trade-offs largely disappeared. These results imply that body size is the trait that provides the basis for ecological interactions and trade-offs. Altogether, this study showed that the examination of species' traits in the context of coexistence at different scales

  13. Environmental variability uncovers disruptive effects of species' interactions on population dynamics.

    Science.gov (United States)

    Gudmundson, Sara; Eklöf, Anna; Wennergren, Uno

    2015-08-07

    How species respond to changes in environmental variability has been shown for single species, but the question remains whether these results are transferable to species when incorporated in ecological communities. Here, we address this issue by analysing the same species exposed to a range of environmental variabilities when (i) isolated or (ii) embedded in a food web. We find that all species in food webs exposed to temporally uncorrelated environments (white noise) show the same type of dynamics as isolated species, whereas species in food webs exposed to positively autocorrelated environments (red noise) can respond completely differently compared with isolated species. This is owing to species following their equilibrium densities in a positively autocorrelated environment that in turn enables species-species interactions to come into play. Our results give new insights into species' response to environmental variation. They especially highlight the importance of considering both species' interactions and environmental autocorrelation when studying population dynamics in a fluctuating environment. © 2015 The Author(s).

  14. General two-species interacting Lotka-Volterra system: Population dynamics and wave propagation

    Science.gov (United States)

    Zhu, Haoqi; Wang, Mao-Xiang; Lai, Pik-Yin

    2018-05-01

    The population dynamics of two interacting species modeled by the Lotka-Volterra (LV) model with general parameters that can promote or suppress the other species is studied. It is found that the properties of the two species' isoclines determine the interaction of species, leading to six regimes in the phase diagram of interspecies interaction; i.e., there are six different interspecific relationships described by the LV model. Four regimes allow for nontrivial species coexistence, among which it is found that three of them are stable, namely, weak competition, mutualism, and predator-prey scenarios can lead to win-win coexistence situations. The Lyapunov function for general nontrivial two-species coexistence is also constructed. Furthermore, in the presence of spatial diffusion of the species, the dynamics can lead to steady wavefront propagation and can alter the population map. Propagating wavefront solutions in one dimension are investigated analytically and by numerical solutions. The steady wavefront speeds are obtained analytically via nonlinear dynamics analysis and verified by numerical solutions. In addition to the inter- and intraspecific interaction parameters, the intrinsic speed parameters of each species play a decisive role in species populations and wave properties. In some regimes, both species can copropagate with the same wave speeds in a finite range of parameters. Our results are further discussed in the light of possible biological relevance and ecological implications.

  15. Yakima River Species Interactions Studies, Annual Report 1998

    International Nuclear Information System (INIS)

    Pearsons, Todd N.; Ham, Kenneth D.; McMichael, Geoffrey A.

    1999-01-01

    Species interactions research and monitoring was initiated in 1989 to investigate ecological interactions among fish in response to proposed supplementation of salmon and steelhead in the upper Yakima River basin. This is the seventh of a series of progress reports that address species interactions research and pre-supplementation monitoring of fishes in the Yakima River basin. Data have been collected prior to supplementation to characterize the ecology and demographics of non-target taxa (NTT) and target taxon, and develop methods to monitor interactions and supplementation success. Major topics of this report are associated with monitoring potential impacts to support adaptive management of NTT and baseline monitoring of fish predation indices on spring chinook salmon smolts. This report is organized into three chapters, with a general introduction preceding the first chapter. This annual report summarizes data collected primarily by the Washington Department of Fish and Wildlife (WDFW) between January 1, 1998 and December 31, 1998 in the Yakima basin, however these data were compared to data from previous years to identify preliminary trends and patterns

  16. Inferring species trees from gene trees in a radiation of California trapdoor spiders (Araneae, Antrodiaetidae, Aliatypus.

    Directory of Open Access Journals (Sweden)

    Jordan D Satler

    Full Text Available The California Floristic Province is a biodiversity hotspot, reflecting a complex geologic history, strong selective gradients, and a heterogeneous landscape. These factors have led to high endemic diversity across many lifeforms within this region, including the richest diversity of mygalomorph spiders (tarantulas, trapdoor spiders, and kin in North America. The trapdoor spider genus Aliatypus encompasses twelve described species, eleven of which are endemic to California. Several Aliatypus species show disjunct distributional patterns in California (some are found on both sides of the vast Central Valley, and the genus as a whole occupies an impressive variety of habitats.We collected specimens from 89 populations representing all described species. DNA sequence data were collected from seven gene regions, including two newly developed for spider systematics. Bayesian inference (in individual gene tree and species tree approaches recovered a general "3 clade" structure for the genus (A. gulosus, californicus group, erebus group, with three other phylogenetically isolated species differing slightly in position across different phylogenetic analyses. Because of extremely high intraspecific divergences in mitochondrial COI sequences, the relatively slowly evolving 28S rRNA gene was found to be more useful than mitochondrial data for identification of morphologically indistinguishable immatures. For multiple species spanning the Central Valley, explicit hypothesis testing suggests a lack of monophyly for regional populations (e.g., western Coast Range populations. Phylogenetic evidence clearly shows that syntopy is restricted to distant phylogenetic relatives, consistent with ecological niche conservatism.This study provides fundamental insight into a radiation of trapdoor spiders found in the biodiversity hotspot of California. Species relationships are clarified and undescribed lineages are discovered, with more geographic sampling likely to

  17. [Novel Hyphenated Techniques of Atomic Spectrometry for Metal Species Interaction with Biomolecules].

    Science.gov (United States)

    Li, Yan; Yan, Xiu-ping

    2015-09-01

    Trace metals may be adopted by biological systems to assist in the syntheses and metabolic functions of genes (DNA and RNA) and proteins in the environment. These metals may be beneficial or may pose a risk to humans and other life forms. Novel hybrid techniques are required for studies on the interaction between different metal species and biomolecules, which is significant for biology, biochemistry, nutrition, agriculture, medicine, pharmacy, and environmental science. In recent years, our group dwells on new hyphenated techniques based on capillary electrophoresis (CE), electrothermal atomic absorption spectrometry (ETAAS), and inductively coupled plasma mass spectroscopy (ICP-MS), and their application for different metal species interaction with biomolecules such as DNA, HSA, and GSH. The CE-ETAAS assay and CE-ICP-MS assay allow sensitively probing the level of biomolecules such as DNA damage by different metal species and extracting the kinetic and thermodynamic information on the interactions of different metal species with biomolecules, provides direct evidences for the formation of different metal species--biomolecule adducts. In addition, the consequent structural information were extracted from circular dichroism (CD) and X-ray photoelectron spectroscopy (XPS), Raman spectroscopy, and Fourier transform infrared (FTIR) spectroscopy. The present works represent the most complete and extensive study to date on the interactions between different metal species with biomolecules, and also provide new evidences for and insights into the interactions of different metal species with biomolecules for further understanding of the toxicological effects of metal species.

  18. Climate change and species interactions: ways forward.

    Science.gov (United States)

    Angert, Amy L; LaDeau, Shannon L; Ostfeld, Richard S

    2013-09-01

    With ongoing and rapid climate change, ecologists are being challenged to predict how individual species will change in abundance and distribution, how biotic communities will change in structure and function, and the consequences of these climate-induced changes for ecosystem functioning. It is now well documented that indirect effects of climate change on species abundances and distributions, via climatic effects on interspecific interactions, can outweigh and even reverse the direct effects of climate. However, a clear framework for incorporating species interactions into projections of biological change remains elusive. To move forward, we suggest three priorities for the research community: (1) utilize tractable study systems as case studies to illustrate possible outcomes, test processes highlighted by theory, and feed back into modeling efforts; (2) develop a robust analytical framework that allows for better cross-scale linkages; and (3) determine over what time scales and for which systems prediction of biological responses to climate change is a useful and feasible goal. We end with a list of research questions that can guide future research to help understand, and hopefully mitigate, the negative effects of climate change on biota and the ecosystem services they provide. © 2013 New York Academy of Sciences.

  19. Hydrological Conditions Affect the Interspecific Interaction between Two Emergent Wetland Species

    Directory of Open Access Journals (Sweden)

    Jian Zhou

    2018-01-01

    Full Text Available Hydrological conditions determine the distribution of plant species in wetlands, where conditions such as water depth and hydrological fluctuations are expected to affect the interspecific interactions among emergent wetland species. To test such effects, we conducted a greenhouse experiment with three treatment categories, interspecific interaction (mixed culture or monoculture, water depth (10 or 30 cm depth, and hydrological fluctuation (static or fluctuating water level, and two common emergent wetland plant species, Scirpus planiculumis Fr. (Cyperaceae and Phragmites australis var. baiyangdiansis (Gramineae. An increase in the water depth significantly restrained the growth of both S. planiculumis and P. australis, while hydrological fluctuations did not obviously alter the growth of either species. In addition, both water depth and hydrological fluctuations significantly affected the interspecific interaction between these two wetland species. P. australis benefited from interspecific interaction under increasing water depth and hydrological fluctuations, and the RII values were clearly positive for plants grown at a water depth that fluctuated around 30 cm. The results may have some implications for understanding how S. planiculumis and P. australis, as well as wetland communities, respond to the natural variation or human modification of hydrological conditions.

  20. Macroevolutionary dynamics and historical biogeography of primate diversification inferred from a species supermatrix.

    Directory of Open Access Journals (Sweden)

    Mark S Springer

    Full Text Available Phylogenetic relationships, divergence times, and patterns of biogeographic descent among primate species are both complex and contentious. Here, we generate a robust molecular phylogeny for 70 primate genera and 367 primate species based on a concatenation of 69 nuclear gene segments and ten mitochondrial gene sequences, most of which were extracted from GenBank. Relaxed clock analyses of divergence times with 14 fossil-calibrated nodes suggest that living Primates last shared a common ancestor 71-63 Ma, and that divergences within both Strepsirrhini and Haplorhini are entirely post-Cretaceous. These results are consistent with the hypothesis that the Cretaceous-Paleogene mass extinction of non-avian dinosaurs played an important role in the diversification of placental mammals. Previous queries into primate historical biogeography have suggested Africa, Asia, Europe, or North America as the ancestral area of crown primates, but were based on methods that were coopted from phylogeny reconstruction. By contrast, we analyzed our molecular phylogeny with two methods that were developed explicitly for ancestral area reconstruction, and find support for the hypothesis that the most recent common ancestor of living Primates resided in Asia. Analyses of primate macroevolutionary dynamics provide support for a diversification rate increase in the late Miocene, possibly in response to elevated global mean temperatures, and are consistent with the fossil record. By contrast, diversification analyses failed to detect evidence for rate-shift changes near the Eocene-Oligocene boundary even though the fossil record provides clear evidence for a major turnover event ("Grande Coupure" at this time. Our results highlight the power and limitations of inferring diversification dynamics from molecular phylogenies, as well as the sensitivity of diversification analyses to different species concepts.

  1. Role of the noise on the transient dynamics of an ecosystem of interacting species

    Science.gov (United States)

    Spagnolo, B.; La Barbera, A.

    2002-11-01

    We analyze the transient dynamics of an ecosystem described by generalized Lotka-Volterra equations in the presence of a multiplicative noise and a random interaction parameter between the species. We consider specifically three cases: (i) two competing species, (ii) three interacting species (one predator-two preys), (iii) n-interacting species. The interaction parameter in case (i) is a stochastic process which obeys a stochastic differential equation. We find noise delayed extinction of one of two species, which is akin to the noise-enhanced stability phenomenon. Other two noise-induced effects found are temporal oscillations and spatial patterns of the two competing species. In case (ii) the noise induces correlated spatial patterns of the predator and of the two preys concentrations. Finally, in case (iii) we find the asymptotic behavior of the time average of the ith population when the ecosystem is composed of a great number of interacting species.

  2. Charge-transfer interactions of Cr species with DNA.

    Science.gov (United States)

    Nowicka, Anna M; Matysiak-Brynda, Edyta; Hepel, Maria

    2017-10-01

    Interactions of Cr species with nucleic acids in living organisms depend strongly on Cr oxidation state and the environmental conditions. As the effects of these interactions range from benign to pre-mutagenic to carcinogenic, careful assessment of the hazard they pose to human health is necessary. We have investigated methods that would enable quantifying the DNA damage caused by Cr species under varying environmental conditions, including UV, O 2 , and redox potential, using simple instrumental techniques which could be in future combined into a field-deployable instrumentation. We have employed electrochemical quartz crystal nanogravimetry (EQCN), cyclic voltammetry (CV), and electrochemical impedance spectroscopy (EIS) to evaluate the extent of DNA damage expressed in terms of guanine oxidation yield (η) and changes in specific characteristics provided by these techniques. The effects of the interactions of Cr species with DNA were analyzed using a model calf thymus DNA (ctDNA) film on a gold electrode (Au@ctDNA) in different media, including: (i) Cr(VI), (ii) Cr(VI) reduced at -0.2V, (iii) Cr(III)+UV radiation+O 2 , and Cr(III), obtaining the η values: 7.4±1.4, 1.5±0.4, 1.1±0.31%, and 0%, respectively, thus quantifying the hazard posed. The EIS measurements have enabled utilizing the decrease in charge-transfer resistance (R ct ) for ferri/ferrocyanide redox probe at an Au@ctDNA electrode to assess the oxidative ctDNA damage by Cr(VI) species. In this case, circular dichroism indicates an extensive damage to the ctDNA hydrogen bonding. On the other hand, Cr(III) species have not induced any damage to ctDNA, although the EQCN measurements show an electrostatic binding to DNA. Copyright © 2017 Elsevier Inc. All rights reserved.

  3. Species as Stressors: Heterospecific Interactions and the Cellular Stress Response under Global Change.

    Science.gov (United States)

    Gunderson, Alex R; King, Emily E; Boyer, Kirsten; Tsukimura, Brian; Stillman, Jonathon H

    2017-07-01

    Anthropogenic global change is predicted to increase the physiological stress of organisms through changes in abiotic conditions such as temperature, pH, and pollution. However, organisms can also experience physiological stress through interactions with other species, especially parasites, predators, and competitors. The stress of species interactions could be an important driver of species' responses to global change as the composition of biological communities change through factors such as distributional and phenological shifts. Interactions between biotic and abiotic stressors could also induce non-linear physiological stress responses under global change. One of the primary means by which organisms deal with physiological stress is through the cellular stress response (CSR), which is broadly the upregulation of a conserved set of genes that facilitate the removal and repair of damaged macromolecules. Here, we present data on behavioral interactions and CSR gene expression for two competing species of intertidal zone porcelain crab (Petrolisthes cinctipes and Petrolisthes manimaculis). We found that P. cinctipes and P. manimaculis engage in more agonistic behaviors when interacting with heterospecifics than conspecifics; however, we found no evidence that heterospecific interactions induced a CSR in these species. In addition to our new data, we review the literature with respect to CSR induction via species interactions, focusing on predator-prey systems and heterospecific competition. We find extensive evidence for predators to induce cellular stress and aspects of the CSR in prey, even in the absence of direct physical contact between species. Effects of heterospecific competition on the CSR have been studied far less, but we do find evidence that agonistic interactions with heterospecifics can induce components of the CSR. Across all published studies, there is clear evidence that species interactions can lead to cellular stress and induction of the CSR

  4. TRIP: An interactive retrieving-inferring data imputation approach

    KAUST Repository

    Li, Zhixu

    2016-06-25

    Data imputation aims at filling in missing attribute values in databases. Existing imputation approaches to nonquantitive string data can be roughly put into two categories: (1) inferring-based approaches [2], and (2) retrieving-based approaches [1]. Specifically, the inferring-based approaches find substitutes or estimations for the missing ones from the complete part of the data set. However, they typically fall short in filling in unique missing attribute values which do not exist in the complete part of the data set [1]. The retrieving-based approaches resort to external resources for help by formulating proper web search queries to retrieve web pages containing the missing values from the Web, and then extracting the missing values from the retrieved web pages [1]. This webbased retrieving approach reaches a high imputation precision and recall, but on the other hand, issues a large number of web search queries, which brings a large overhead [1]. © 2016 IEEE.

  5. TRIP: An interactive retrieving-inferring data imputation approach

    KAUST Repository

    Li, Zhixu; Qin, Lu; Cheng, Hong; Zhang, Xiangliang; Zhou, Xiaofang

    2016-01-01

    Data imputation aims at filling in missing attribute values in databases. Existing imputation approaches to nonquantitive string data can be roughly put into two categories: (1) inferring-based approaches [2], and (2) retrieving-based approaches [1]. Specifically, the inferring-based approaches find substitutes or estimations for the missing ones from the complete part of the data set. However, they typically fall short in filling in unique missing attribute values which do not exist in the complete part of the data set [1]. The retrieving-based approaches resort to external resources for help by formulating proper web search queries to retrieve web pages containing the missing values from the Web, and then extracting the missing values from the retrieved web pages [1]. This webbased retrieving approach reaches a high imputation precision and recall, but on the other hand, issues a large number of web search queries, which brings a large overhead [1]. © 2016 IEEE.

  6. Evolutionary responses of native plant species to invasive plants: a review.

    Science.gov (United States)

    Oduor, Ayub M O

    2013-12-01

    Strong competition from invasive plant species often leads to declines in abundances and may, in certain cases, cause localized extinctions of native plant species. Nevertheless, studies have shown that certain populations of native plant species can co-exist with invasive plant species,suggesting the possibility of adaptive evolutionary responses of those populations to the invasive plants. Empirical inference of evolutionary responses of the native plant species to invasive plants has involved experiments comparing two conspecific groups of native plants for differences in expression of growth/reproductive traits: populations that have experienced competition from the invasive plant species (i.e. experienced natives) versus populations with no known history of interactions with the invasive plant species (i.e. naıve natives). Here, I employ a meta-analysis to obtain a general pattern of inferred evolutionary responses of native plant species from 53 such studies. In general, the experienced natives had significantly higher growth/reproductive performances than naıve natives, when grown with or without competition from invasive plants.While the current results indicate that certain populations of native plant species could potentially adapt evolutionarily to invasive plant species, the ecological and evolutionary mechanisms that probably underlie such evolutionary responses remain unexplored and should be the focus of future studies.

  7. Yakima River species interactions studies annual report, 2000; ANNUAL

    International Nuclear Information System (INIS)

    Pearsons, Todd N.

    2001-01-01

    Species interactions research and monitoring was initiated in 1989 to investigate ecological interactions among fish in response to proposed supplementation of salmon and steelhead in the upper Yakima River basin. This is the ninth of a series of progress reports that address species interactions research and supplementation monitoring of fishes in the Yakima River basin. Data have been collected prior to supplementation to characterize the ecology and demographics of non-target taxa (NTT) and target taxon, and develop methods to monitor interactions and supplementation success. Major topics of this report are associated with the chronology of ecological interactions that occur throughout a supplementation program, implementing NTT monitoring prescriptions for detecting potential impacts of hatchery supplementation, hatchery fish interactions, and monitoring fish predation indices. This report is organized into four chapters, with a general introduction preceding the first chapter. This annual report summarizes data collected primarily by the Washington Department of Fish and Wildlife (WDFW) between January 1, 2000 and December 31, 2000 in the Yakima basin, however these data were compared to data from previous years to identify preliminary trends and patterns. Summaries of each of the chapters included in this report are described

  8. A Network Inference Workflow Applied to Virulence-Related Processes in Salmonella typhimurium

    Energy Technology Data Exchange (ETDEWEB)

    Taylor, Ronald C.; Singhal, Mudita; Weller, Jennifer B.; Khoshnevis, Saeed; Shi, Liang; McDermott, Jason E.

    2009-04-20

    Inference of the structure of mRNA transcriptional regulatory networks, protein regulatory or interaction networks, and protein activation/inactivation-based signal transduction networks are critical tasks in systems biology. In this article we discuss a workflow for the reconstruction of parts of the transcriptional regulatory network of the pathogenic bacterium Salmonella typhimurium based on the information contained in sets of microarray gene expression data now available for that organism, and describe our results obtained by following this workflow. The primary tool is one of the network inference algorithms deployed in the Software Environment for BIological Network Inference (SEBINI). Specifically, we selected the algorithm called Context Likelihood of Relatedness (CLR), which uses the mutual information contained in the gene expression data to infer regulatory connections. The associated analysis pipeline automatically stores the inferred edges from the CLR runs within SEBINI and, upon request, transfers the inferred edges into either Cytoscape or the plug-in Collective Analysis of Biological of Biological Interaction Networks (CABIN) tool for further post-analysis of the inferred regulatory edges. The following article presents the outcome of this workflow, as well as the protocols followed for microarray data collection, data cleansing, and network inference. Our analysis revealed several interesting interactions, functional groups, metabolic pathways, and regulons in S. typhimurium.

  9. Inferring species richness and turnover by statistical multiresolution texture analysis of satellite imagery.

    Directory of Open Access Journals (Sweden)

    Matteo Convertino

    richness, or [Formula: see text] diversity, based on the Shannon entropy of pixel intensity.To test our approach, we specifically use the green band of Landsat images for a water conservation area in the Florida Everglades. We validate our predictions against data of species occurrences for a twenty-eight years long period for both wet and dry seasons. Our method correctly predicts 73% of species richness. For species turnover, the newly proposed KL divergence prediction performance is near 100% accurate. This represents a significant improvement over the more conventional Shannon entropy difference, which provides 85% accuracy. Furthermore, we find that changes in soil and water patterns, as measured by fluctuations of the Shannon entropy for the red and blue bands respectively, are positively correlated with changes in vegetation. The fluctuations are smaller in the wet season when compared to the dry season. CONCLUSIONS/SIGNIFICANCE: Texture-based statistical multiresolution image analysis is a promising method for quantifying interseasonal differences and, consequently, the degree to which vegetation, soil, and water patterns vary. The proposed automated method for quantifying species richness and turnover can also provide analysis at higher spatial and temporal resolution than is currently obtainable from expensive monitoring campaigns, thus enabling more prompt, more cost effective inference and decision making support regarding anomalous variations in biodiversity. Additionally, a matrix-based visualization of the statistical multiresolution analysis is presented to facilitate both insight and quick recognition of anomalous data.

  10. Multi-scale inference of interaction rules in animal groups using Bayesian model selection.

    Directory of Open Access Journals (Sweden)

    Richard P Mann

    2012-01-01

    Full Text Available Inference of interaction rules of animals moving in groups usually relies on an analysis of large scale system behaviour. Models are tuned through repeated simulation until they match the observed behaviour. More recent work has used the fine scale motions of animals to validate and fit the rules of interaction of animals in groups. Here, we use a Bayesian methodology to compare a variety of models to the collective motion of glass prawns (Paratya australiensis. We show that these exhibit a stereotypical 'phase transition', whereby an increase in density leads to the onset of collective motion in one direction. We fit models to this data, which range from: a mean-field model where all prawns interact globally; to a spatial Markovian model where prawns are self-propelled particles influenced only by the current positions and directions of their neighbours; up to non-Markovian models where prawns have 'memory' of previous interactions, integrating their experiences over time when deciding to change behaviour. We show that the mean-field model fits the large scale behaviour of the system, but does not capture fine scale rules of interaction, which are primarily mediated by physical contact. Conversely, the Markovian self-propelled particle model captures the fine scale rules of interaction but fails to reproduce global dynamics. The most sophisticated model, the non-Markovian model, provides a good match to the data at both the fine scale and in terms of reproducing global dynamics. We conclude that prawns' movements are influenced by not just the current direction of nearby conspecifics, but also those encountered in the recent past. Given the simplicity of prawns as a study system our research suggests that self-propelled particle models of collective motion should, if they are to be realistic at multiple biological scales, include memory of previous interactions and other non-Markovian effects.

  11. Body and skull morphometric variations between two shovel-headed species of Amphisbaenia (Reptilia: Squamata with morphofunctional inferences on burrowing

    Directory of Open Access Journals (Sweden)

    Leandro dos Santos Lima Hohl

    2017-07-01

    Full Text Available Background Morphological descriptions comparing Leposternon microcephalum and L. scutigerum have been made previously. However, these taxa lack a formal quantitative morphological characterization, and comparative studies suggest that morphology and burrowing performance are be related. The excavatory movements of L. microcephalum have been described in detail. However, there is a lack of studies comparing locomotor patterns and/or performance among different amphisbaenids sharing the same skull shape. This paper presents the first study of comparative morphometric variations between two closely related amphisbaenid species, L. microcephalum and L. scutigerum, with functional inferences on fossorial locomotion efficiency. Methods Inter-specific morphometric variations were verified through statistical analyses of body and cranial measures of L. microcephalum and L. scutigerum specimens. Their burrowing activity was assessed through X-ray videofluoroscopy and then compared. The influence of morphological variation on the speed of digging was tested among Leposternon individuals. Results Leposternon microcephalum and L. scutigerum are morphometrically distinct species. The first is shorter and robust with a wider head while the other is more elongated and slim with a narrower head. They share the same excavatory movements. The animals analyzed reached relatively high speeds, but individuals with narrower skulls dug faster. A negative correlation between the speed and the width of skull was determined, but not with total length or diameter of the body. Discussion The morphometric differences between L. microcephalum and L. scutigerum are in accord with morphological variations previously described. Since these species performed the same excavation pattern, we may infer that closely related amphisbaenids with the same skull type would exhibit the same excavatory pattern. The negative correlation between head width and excavation speed is also

  12. Linking macroecology and community ecology: refining predictions of species distributions using biotic interaction networks.

    Science.gov (United States)

    Staniczenko, Phillip P A; Sivasubramaniam, Prabu; Suttle, K Blake; Pearson, Richard G

    2017-06-01

    Macroecological models for predicting species distributions usually only include abiotic environmental conditions as explanatory variables, despite knowledge from community ecology that all species are linked to other species through biotic interactions. This disconnect is largely due to the different spatial scales considered by the two sub-disciplines: macroecologists study patterns at large extents and coarse resolutions, while community ecologists focus on small extents and fine resolutions. A general framework for including biotic interactions in macroecological models would help bridge this divide, as it would allow for rigorous testing of the role that biotic interactions play in determining species ranges. Here, we present an approach that combines species distribution models with Bayesian networks, which enables the direct and indirect effects of biotic interactions to be modelled as propagating conditional dependencies among species' presences. We show that including biotic interactions in distribution models for species from a California grassland community results in better range predictions across the western USA. This new approach will be important for improving estimates of species distributions and their dynamics under environmental change. © 2017 The Authors. Ecology Letters published by CNRS and John Wiley & Sons Ltd.

  13. Setting realistic recovery targets for two interacting endangered species, sea otter and northern abalone.

    Science.gov (United States)

    Chadès, Iadine; Curtis, Janelle M R; Martin, Tara G

    2012-12-01

    Failure to account for interactions between endangered species may lead to unexpected population dynamics, inefficient management strategies, waste of scarce resources, and, at worst, increased extinction risk. The importance of species interactions is undisputed, yet recovery targets generally do not account for such interactions. This shortcoming is a consequence of species-centered legislation, but also of uncertainty surrounding the dynamics of species interactions and the complexity of modeling such interactions. The northern sea otter (Enhydra lutris kenyoni) and one of its preferred prey, northern abalone (Haliotis kamtschatkana), are endangered species for which recovery strategies have been developed without consideration of their strong predator-prey interactions. Using simulation-based optimization procedures from artificial intelligence, namely reinforcement learning and stochastic dynamic programming, we combined sea otter and northern abalone population models with functional-response models and examined how different management actions affect population dynamics and the likelihood of achieving recovery targets for each species through time. Recovery targets for these interacting species were difficult to achieve simultaneously in the absence of management. Although sea otters were predicted to recover, achieving abalone recovery targets failed even when threats to abalone such as predation and poaching were reduced. A management strategy entailing a 50% reduction in the poaching of northern abalone was a minimum requirement to reach short-term recovery goals for northern abalone when sea otters were present. Removing sea otters had a marginally positive effect on the abalone population but only when we assumed a functional response with strong predation pressure. Our optimization method could be applied more generally to any interacting threatened or invasive species for which there are multiple conservation objectives. © 2012 Society for

  14. Effects of biotic interactions and dispersal on the presence-absence of multiple species

    International Nuclear Information System (INIS)

    Mohd, Mohd Hafiz; Murray, Rua; Plank, Michael J.; Godsoe, William

    2017-01-01

    One of the important issues in ecology is to predict which species will be present (or absent) across a geographical region. Dispersal is thought to have an important influence on the range limits of species, and understanding this problem in a multi-species community with priority effects (i.e. initial abundances determine species presence-absence) is a challenging task because dispersal also interacts with biotic and abiotic factors. Here, we propose a simple multi-species model to investigate the joint effects of biotic interactions and dispersal on species presence-absence. Our results show that dispersal can substantially expand species ranges when biotic and abiotic forces are present; consequently, coexistence of multiple species is possible. The model also exhibits ecologically interesting priority effects, mediated by intense biotic interactions. In the absence of dispersal, competitive exclusion of all but one species occurs. We find that dispersal reduces competitive exclusion effects that occur in no-dispersal case and promotes coexistence of multiple species. These results also show that priority effects are still prevalent in multi-species communities in the presence of dispersal process. We also illustrate the existence of threshold values of competitive strength (i.e. transcritical bifurcations), which results in different species presence-absence in multi-species communities with and without dispersal.

  15. An interactive activation and competition model of person knowledge, suggested by proactive interference by traits spontaneously inferred from behaviours.

    Science.gov (United States)

    Wang, Yuanbo E; Higgins, Nancy C; Uleman, James S; Michaux, Aaron; Vipond, Douglas

    2016-03-01

    People unconsciously and unintentionally make inferences about others' personality traits based on their behaviours. In this study, a classic memory phenomenon--proactive interference (PI)--is for the first time used to detect spontaneous trait inferences. PI should occur when lists of behaviour descriptions, all implying the same trait, are to be remembered. Switching to a new trait should produce 'release' from proactive interference (or RPI). Results from two experiments supported these predictions. PI and RPI effects are consistent with an interactive activation and competition model of person perception (e.g., McNeill & Burton, 2002, J. Exp. Psychol., 55A, 1141), which predicts categorical organization of social behaviours based on personality traits. Advantages of this model are discussed. © 2015 The British Psychological Society.

  16. Land-use change interacts with climate to determine elevational species redistribution.

    Science.gov (United States)

    Guo, Fengyi; Lenoir, Jonathan; Bonebrake, Timothy C

    2018-04-03

    Climate change is driving global species redistribution with profound social and economic impacts. However, species movement is largely constrained by habitat availability and connectivity, of which the interaction effects with climate change remain largely unknown. Here we examine published data on 2798 elevational range shifts from 43 study sites to assess the confounding effect of land-use change on climate-driven species redistribution. We show that baseline forest cover and recent forest cover change are critical predictors in determining the magnitude of elevational range shifts. Forest loss positively interacts with baseline temperature conditions, such that forest loss in warmer regions tends to accelerate species' upslope movement. Consequently, not only climate but also habitat loss stressors and, importantly, their synergistic effects matter in forecasting species elevational redistribution, especially in the tropics where both stressors will increase the risk of net lowland biotic attrition.

  17. Ecological interactions in Aedes species on Reunion Island.

    Science.gov (United States)

    Bagny Beilhe, L; Delatte, H; Juliano, S A; Fontenille, D; Quilici, S

    2013-12-01

    Two invasive, container-breeding mosquito species, Aedes aegypti (Stegomyia aegypti) and Aedes albopictus (Stegomyia albopicta) (Diptera: Culicidae), have different distribution patterns on Reunion Island. Aedes albopictus occurs in all areas and Ae. aegypti colonizes only some restricted areas already occupied by Ae. albopictus. This study investigates the abiotic and biotic ecological mechanisms that determine the distribution of Aedes species on Reunion Island. Life history traits (duration of immature stages, survivorship, fecundity, estimated finite rate of increase) in Ae. aegypti and Ae. albopictus were compared at different temperatures. These fitness measures were characterized in both species in response to competitive interactions among larvae. Aedes aegypti was drastically affected by temperature, performing well only at around 25 °C, at which it achieved its highest survivorship and greatest estimated rate of increase. The narrow distribution of this species in the field on Reunion Island may thus relate to its poor ability to cope with unfavourable temperatures. Aedes aegypti was also more negatively affected by high population densities and to some extent by interactions with Ae. albopictus, particularly in the context of limited food supplies. Aedes albopictus exhibited better population performance across a range of environmental conditions. Its ecological plasticity and its superior competitive ability relative to its congener may further enhance its invasion success on Reunion Island. © 2012 The Royal Entomological Society.

  18. Multi-scale inference of interaction rules in animal groups using Bayesian model selection.

    Directory of Open Access Journals (Sweden)

    Richard P Mann

    Full Text Available Inference of interaction rules of animals moving in groups usually relies on an analysis of large scale system behaviour. Models are tuned through repeated simulation until they match the observed behaviour. More recent work has used the fine scale motions of animals to validate and fit the rules of interaction of animals in groups. Here, we use a Bayesian methodology to compare a variety of models to the collective motion of glass prawns (Paratya australiensis. We show that these exhibit a stereotypical 'phase transition', whereby an increase in density leads to the onset of collective motion in one direction. We fit models to this data, which range from: a mean-field model where all prawns interact globally; to a spatial Markovian model where prawns are self-propelled particles influenced only by the current positions and directions of their neighbours; up to non-Markovian models where prawns have 'memory' of previous interactions, integrating their experiences over time when deciding to change behaviour. We show that the mean-field model fits the large scale behaviour of the system, but does not capture the observed locality of interactions. Traditional self-propelled particle models fail to capture the fine scale dynamics of the system. The most sophisticated model, the non-Markovian model, provides a good match to the data at both the fine scale and in terms of reproducing global dynamics, while maintaining a biologically plausible perceptual range. We conclude that prawns' movements are influenced by not just the current direction of nearby conspecifics, but also those encountered in the recent past. Given the simplicity of prawns as a study system our research suggests that self-propelled particle models of collective motion should, if they are to be realistic at multiple biological scales, include memory of previous interactions and other non-Markovian effects.

  19. Spontaneous cross-species imitation in interactions between chimpanzees and zoo visitors.

    Science.gov (United States)

    Persson, Tomas; Sauciuc, Gabriela-Alina; Madsen, Elainie Alenkær

    2018-01-01

    Imitation is a cornerstone of human development, serving both a cognitive function (e.g. in the acquisition and transmission of skills and knowledge) and a social-communicative function, whereby the imitation of familiar actions serves to maintain social interaction and promote prosociality. In nonhuman primates, this latter function is poorly understood, or even claimed to be absent. In this observational study, we documented interactions between chimpanzees and zoo visitors and found that the two species imitated each other at a similar rate, corresponding to almost 10% of all produced actions. Imitation appeared to accomplish a social-communicative function, as cross-species interactions that contained imitative actions lasted significantly longer than interactions without imitation. In both species, physical proximity promoted cross-species imitation. Overall, imitative precision was higher among visitors than among chimpanzees, but this difference vanished in proximity contexts, i.e. in the indoor environment. Four of five chimpanzees produced imitations; three of them exhibited comparable imitation rates, despite large individual differences in level of cross-species interactivity. We also found that chimpanzees evidenced imitation recognition, yet only when visitors imitated their actions (as opposed to postures). Imitation recognition was expressed by returned imitation in 36% of the cases, and all four imitating chimpanzees engaged in so-called imitative games. Previously regarded as unique to early human socialization, such games serve to maintain social engagement. The results presented here indicate that nonhuman apes exhibit spontaneous imitation that can accomplish a communicative function. The study raises a number of novel questions for imitation research and highlights the imitation of familiar behaviours as a relevant-yet thus far understudied-research topic.

  20. Inference of population splits and mixtures from genome-wide allele frequency data.

    Directory of Open Access Journals (Sweden)

    Joseph K Pickrell

    Full Text Available Many aspects of the historical relationships between populations in a species are reflected in genetic data. Inferring these relationships from genetic data, however, remains a challenging task. In this paper, we present a statistical model for inferring the patterns of population splits and mixtures in multiple populations. In our model, the sampled populations in a species are related to their common ancestor through a graph of ancestral populations. Using genome-wide allele frequency data and a Gaussian approximation to genetic drift, we infer the structure of this graph. We applied this method to a set of 55 human populations and a set of 82 dog breeds and wild canids. In both species, we show that a simple bifurcating tree does not fully describe the data; in contrast, we infer many migration events. While some of the migration events that we find have been detected previously, many have not. For example, in the human data, we infer that Cambodians trace approximately 16% of their ancestry to a population ancestral to other extant East Asian populations. In the dog data, we infer that both the boxer and basenji trace a considerable fraction of their ancestry (9% and 25%, respectively to wolves subsequent to domestication and that East Asian toy breeds (the Shih Tzu and the Pekingese result from admixture between modern toy breeds and "ancient" Asian breeds. Software implementing the model described here, called TreeMix, is available at http://treemix.googlecode.com.

  1. Macroecological signals of species interactions in the Danish avifauna

    DEFF Research Database (Denmark)

    Gotelli, N.J.; Graves, Christopher R.; Rahbek, C.

    2010-01-01

    that community-wide patterns of spatial segregation could not be attributed to the patchy distribution of habitat or to gross differences in habitat utilization among ecologically similar species. We hypothesize that, when habitat patch size is limited, conspecific attraction in concert with interspecific...... territoriality may result in spatially segregated distributions of ecologically similar species at larger spatial scales. In the Danish avifauna, the effects of species interactions on community assembly appear pervasive and can be discerned at grain sizes up to four orders of magnitude larger than those...

  2. Inference of miRNA targets using evolutionary conservation and pathway analysis

    Directory of Open Access Journals (Sweden)

    van Nimwegen Erik

    2007-03-01

    Full Text Available Abstract Background MicroRNAs have emerged as important regulatory genes in a variety of cellular processes and, in recent years, hundreds of such genes have been discovered in animals. In contrast, functional annotations are available only for a very small fraction of these miRNAs, and even in these cases only partially. Results We developed a general Bayesian method for the inference of miRNA target sites, in which, for each miRNA, we explicitly model the evolution of orthologous target sites in a set of related species. Using this method we predict target sites for all known miRNAs in flies, worms, fish, and mammals. By comparing our predictions in fly with a reference set of experimentally tested miRNA-mRNA interactions we show that our general method performs at least as well as the most accurate methods available to date, including ones specifically tailored for target prediction in fly. An important novel feature of our model is that it explicitly infers the phylogenetic distribution of functional target sites, independently for each miRNA. This allows us to infer species-specific and clade-specific miRNA targeting. We also show that, in long human 3' UTRs, miRNA target sites occur preferentially near the start and near the end of the 3' UTR. To characterize miRNA function beyond the predicted lists of targets we further present a method to infer significant associations between the sets of targets predicted for individual miRNAs and specific biochemical pathways, in particular those of the KEGG pathway database. We show that this approach retrieves several known functional miRNA-mRNA associations, and predicts novel functions for known miRNAs in cell growth and in development. Conclusion We have presented a Bayesian target prediction algorithm without any tunable parameters, that can be applied to sequences from any clade of species. The algorithm automatically infers the phylogenetic distribution of functional sites for each miRNA, and

  3. Bayesian Inference for Functional Dynamics Exploring in fMRI Data

    Directory of Open Access Journals (Sweden)

    Xuan Guo

    2016-01-01

    Full Text Available This paper aims to review state-of-the-art Bayesian-inference-based methods applied to functional magnetic resonance imaging (fMRI data. Particularly, we focus on one specific long-standing challenge in the computational modeling of fMRI datasets: how to effectively explore typical functional interactions from fMRI time series and the corresponding boundaries of temporal segments. Bayesian inference is a method of statistical inference which has been shown to be a powerful tool to encode dependence relationships among the variables with uncertainty. Here we provide an introduction to a group of Bayesian-inference-based methods for fMRI data analysis, which were designed to detect magnitude or functional connectivity change points and to infer their functional interaction patterns based on corresponding temporal boundaries. We also provide a comparison of three popular Bayesian models, that is, Bayesian Magnitude Change Point Model (BMCPM, Bayesian Connectivity Change Point Model (BCCPM, and Dynamic Bayesian Variable Partition Model (DBVPM, and give a summary of their applications. We envision that more delicate Bayesian inference models will be emerging and play increasingly important roles in modeling brain functions in the years to come.

  4. Biotic interactions overrule plant responses to climate, depending on the species' biogeography.

    Directory of Open Access Journals (Sweden)

    Astrid Welk

    Full Text Available This study presents an experimental approach to assess the relative importance of climatic and biotic factors as determinants of species' geographical distributions. We asked to what extent responses of grassland plant species to biotic interactions vary with climate, and to what degree this variation depends on the species' biogeography. Using a gradient from oceanic to continental climate represented by nine common garden transplant sites in Germany, we experimentally tested whether congeneric grassland species of different geographic distribution (oceanic vs. continental plant range type responded differently to combinations of climate, competition and mollusc herbivory. We found the relative importance of biotic interactions and climate to vary between the different components of plant performance. While survival and plant height increased with precipitation, temperature had no effect on plant performance. Additionally, species with continental plant range type increased their growth in more benign climatic conditions, while those with oceanic range type were largely unable to take a similar advantage of better climatic conditions. Competition generally caused strong reductions of aboveground biomass and growth. In contrast, herbivory had minor effects on survival and growth. Against expectation, these negative effects of competition and herbivory were not mitigated under more stressful continental climate conditions. In conclusion we suggest variation in relative importance of climate and biotic interactions on broader scales, mediated via species-specific sensitivities and factor-specific response patterns. Our results have important implications for species distribution models, as they emphasize the large-scale impact of biotic interactions on plant distribution patterns and the necessity to take plant range types into account.

  5. Combinatorial Cis-regulation in Saccharomyces Species

    Directory of Open Access Journals (Sweden)

    Aaron T. Spivak

    2016-03-01

    Full Text Available Transcriptional control of gene expression requires interactions between the cis-regulatory elements (CREs controlling gene promoters. We developed a sensitive computational method to identify CRE combinations with conserved spacing that does not require genome alignments. When applied to seven sensu stricto and sensu lato Saccharomyces species, 80% of the predicted interactions displayed some evidence of combinatorial transcriptional behavior in several existing datasets including: (1 chromatin immunoprecipitation data for colocalization of transcription factors, (2 gene expression data for coexpression of predicted regulatory targets, and (3 gene ontology databases for common pathway membership of predicted regulatory targets. We tested several predicted CRE interactions with chromatin immunoprecipitation experiments in a wild-type strain and strains in which a predicted cofactor was deleted. Our experiments confirmed that transcription factor (TF occupancy at the promoters of the CRE combination target genes depends on the predicted cofactor while occupancy of other promoters is independent of the predicted cofactor. Our method has the additional advantage of identifying regulatory differences between species. By analyzing the S. cerevisiae and S. bayanus genomes, we identified differences in combinatorial cis-regulation between the species and showed that the predicted changes in gene regulation explain several of the species-specific differences seen in gene expression datasets. In some instances, the same CRE combinations appear to regulate genes involved in distinct biological processes in the two different species. The results of this research demonstrate that (1 combinatorial cis-regulation can be inferred by multi-genome analysis and (2 combinatorial cis-regulation can explain differences in gene expression between species.

  6. Novel species interactions: American black bears respond to Pacific herring spawn.

    Science.gov (United States)

    Fox, Caroline Hazel; Paquet, Paul Charles; Reimchen, Thomas Edward

    2015-05-26

    In addition to the decline and extinction of the world's species, the decline and eventual loss of species interactions is one of the major consequences of the biodiversity crisis. On the Pacific coast of North America, diminished runs of salmon (Oncorhynchus spp.) drive numerous marine-terrestrial interactions, many of which have been intensively studied, but marine-terrestrial interactions driven by other species remain relatively unknown. Bears (Ursus spp.) are major vectors of salmon into terrestrial ecosystems, but their participation in other cross-ecosystem interactions is similarly poorly described. Pacific herring (Clupea pallasii), a migratory forage fish in coastal marine ecosystems of the North Pacific Ocean and the dominant forage fish in British Columbia (BC), spawn in nearshore subtidal and intertidal zones. Spawn resources (eggs, milt, and spawning adults) at these events are available to coastal predators and scavengers, including terrestrial species. In this study, we investigated the interaction between American black bears (Ursus americanus) and Pacific herring at spawn events in Quatsino Sound, BC, Canada. Using remote cameras to monitor bear activity (1,467 camera days, 29 sites, years 2010-2012) in supratidal and intertidal zones and a machine learning approach, we determined that the quantity of Pacific herring eggs in supratidal and intertidal zones was a leading predictor of black bear activity, with bears positively responding to increasing herring egg masses. Other important predictors included day of the year and Talitrid amphipod (Traskorchestia spp.) mass. A complementary analysis of black bear scats indicated that Pacific herring egg mass was the highest ranked predictor of egg consumption by bears. Pacific herring eggs constituted a substantial yet variable component of the early springtime diet of black bears in Quatsino Sound (frequency of occurrence 0-34%; estimated dietary content 0-63%). Other major dietary items included

  7. Asymmetric biotic interactions and abiotic niche differences revealed by a dynamic joint species distribution model.

    Science.gov (United States)

    Lany, Nina K; Zarnetske, Phoebe L; Schliep, Erin M; Schaeffer, Robert N; Orians, Colin M; Orwig, David A; Preisser, Evan L

    2018-05-01

    A species' distribution and abundance are determined by abiotic conditions and biotic interactions with other species in the community. Most species distribution models correlate the occurrence of a single species with environmental variables only, and leave out biotic interactions. To test the importance of biotic interactions on occurrence and abundance, we compared a multivariate spatiotemporal model of the joint abundance of two invasive insects that share a host plant, hemlock woolly adelgid (HWA; Adelges tsugae) and elongate hemlock scale (EHS; Fiorina externa), to independent models that do not account for dependence among co-occurring species. The joint model revealed that HWA responded more strongly to abiotic conditions than EHS. Additionally, HWA appeared to predispose stands to subsequent increase of EHS, but HWA abundance was not strongly dependent on EHS abundance. This study demonstrates how incorporating spatial and temporal dependence into a species distribution model can reveal the dependence of a species' abundance on other species in the community. Accounting for dependence among co-occurring species with a joint distribution model can also improve estimation of the abiotic niche for species affected by interspecific interactions. © 2018 by the Ecological Society of America.

  8. Concentrations and uncertainties of stratospheric trace species inferred from limb infrared monitor of the stratosphere data. I - Methodology and application to OH and HO2. II - Monthly averaged OH, HO2, H2O2, and HO2NO2

    Science.gov (United States)

    Kaye, J. A.; Jackman, C. H.

    1986-01-01

    Difficulties arise in connection with the verification of multidimensional chemical models of the stratosphere. The present study shows that LIMS data, together with a photochemical equilibrium model, may be used to infer concentrations of a variety of zonally averaged trace Ox, OHx, and NOx species over much of the stratosphere. In the lower stratosphere, where the photochemical equilibrium assumption for HOx species breaks down, inferred concentrations should still be accurate to about a factor of 2 for OH and 2.5 for HO2. The algebraic nature of the considered model makes it possible to see easily to the first order the effect of variation of any model input parameter or its uncertainty on the inferred concontration of the HOx species and their uncertainties.

  9. Species interactions and the effects of climate variability on a wetland amphibian metacommunity

    Science.gov (United States)

    Davis, Courtney L.; Miller, David A.W.; Walls, Susan C.; Barichivich, William J.; Riley, Jeffrey W.; Brown, Mary E.

    2017-01-01

    Disentangling the role that multiple interacting factors have on species responses to shifting climate poses a significant challenge. However, our ability to do so is of utmost importance to predict the effects of climate change on species distributions. We examined how populations of three species of wetland-breeding amphibians, which varied in life history requirements, responded to a six-year period of extremely variable precipitation. This interval was punctuated by both extensive drought and heavy precipitation and flooding, providing a natural experiment to measure community responses to environmental perturbations. We estimated occurrence dynamics using a discrete hidden Markov modeling approach that incorporated information regarding habitat state and predator–prey interactions. This approach allowed us to measure how metapopulation dynamics of each amphibian species was affected by interactions among weather, wetland hydroperiod, and co-occurrence with fish predators. The pig frog, a generalist, proved most resistant to perturbations, with both colonization and persistence being unaffected by seasonal variation in precipitation or co-occurrence with fishes. The ornate chorus frog, an ephemeral wetland specialist, responded positively to periods of drought owing to increased persistence and colonization rates during periods of low-rainfall. Low probabilities of occurrence of the ornate chorus frog in long-duration wetlands were driven by interactions with predators due to low colonization rates when fishes were present. The mole salamander was most sensitive to shifts in water availability. In our study area, this species never occurred in short-duration wetlands and persistence probabilities decreased during periods of drought. At the same time, negative effects occurred with extreme precipitation because flooding facilitated colonization of fishes to isolated wetlands and mole salamanders did not colonize wetlands once fishes were present. We

  10. Diversity-interaction modeling: estimating contributions of species identities and interactions to ecosystem function

    DEFF Research Database (Denmark)

    Kirwan, L; Connolly, J; Finn, J A

    2009-01-01

    to the roles of evenness, functional groups, and functional redundancy. These more parsimonious descriptions can be especially useful in identifying general diversity-function relationships in communities with large numbers of species. We provide an example of the application of the modeling framework......We develop a modeling framework that estimates the effects of species identity and diversity on ecosystem function and permits prediction of the diversity-function relationship across different types of community composition. Rather than just measure an overall effect of diversity, we separately....... These models describe community-level performance and thus do not require separate measurement of the performance of individual species. This flexible modeling approach can be tailored to test many hypotheses in biodiversity research and can suggest the interaction mechanisms that may be acting....

  11. Metabolomics Reveals Cryptic Interactive Effects of Species Interactions and Environmental Stress on Nitrogen and Sulfur Metabolism in Seagrass

    DEFF Research Database (Denmark)

    Hasler-Sheetal, Harald; Castorani, Max C. N.; Glud, Ronnie N.

    2016-01-01

    Eutrophication of estuaries and coastal seas is accelerating, increasing light stress on subtidal marine plants and changing their interactions with other species. To date, we have limited understanding of how such variations in environmental and biological stress modify the impact of interactions...... among foundational species and eventually affect ecosystem health. Here, we used metabolomics to assess the impact of light reductions on interactions between the seagrass Zostera marina, an important habitat-forming marine plant, and the abundant and commercially important blue mussel Mytilus edulis....... Plant performance varied with light availability but was unaffected by the presence of mussels. Metabolomic analysis, on the other hand, revealed an interaction between light availability and presence of M. edulis on seagrass metabolism. Under high light, mussels stimulated seagrass nitrogen and energy...

  12. Patterns of Coral-Reef Finfish Species Disappearances Inferred from Fishers' Knowledge in Global Epicentre of Marine Shorefish Diversity.

    Directory of Open Access Journals (Sweden)

    Margarita N Lavides

    Full Text Available In the Philippines, very high fishing pressure coincides with the globally greatest number of shorefish species, yet no long-term fisheries data are available to explore species-level changes that may have occurred widely in the most species rich and vulnerable marine ecosystem, namely coral reefs. Through 2655 face-to-face interviews conducted between August 2012 and July 2014, we used fishers' recall of past catch rates of reef-associated finfish to infer species disappearances from catches in five marine key biodiversity areas (Lanuza Bay, Danajon Bank, Verde Island Passage, Polillo Islands and Honda Bay. We modeled temporal trends in perceived catch per unit effort (CPUE based on fishers' reports of typical good days' catches using Generalized Linear Mixed Modelling. Fifty-nine different finfish disappeared from catches between the 1950s and 2014; 42 fish were identified to species level, two to genus, seven to family and eight to local name only. Five species occurring at all sites with the greatest number of fishers reporting zero catches were the green bumphead parrotfish (Bolbometopon muricatum, humphead wrasse (Cheilinus undulatus, African pompano (Alectis ciliaris, giant grouper (Epinephelus lanceolatus and mangrove red snapper (Lutjanus argentimaculatus. Between the 1950s and 2014, the mean perceived CPUE of bumphead parrotfish declined by 88%, that of humphead wrasse by 82%, African pompano by 66%, giant grouper by 74% and mangrove red snapper by 64%. These declines were mainly associated with excess and uncontrolled fishing, fish life-history traits like maximum body size and socio-economic factors like access to market infrastructure and services, and overpopulation. The fishers' knowledge is indicative of extirpations where evidence for these losses was otherwise lacking. Our models provide information as basis for area-based conservation and regional resource management particularly for the more vulnerable, once common, large

  13. Patterns of Coral-Reef Finfish Species Disappearances Inferred from Fishers' Knowledge in Global Epicentre of Marine Shorefish Diversity.

    Science.gov (United States)

    Lavides, Margarita N; Molina, Erina Pauline V; de la Rosa, Gregorio E; Mill, Aileen C; Rushton, Stephen P; Stead, Selina M; Polunin, Nicholas V C

    2016-01-01

    In the Philippines, very high fishing pressure coincides with the globally greatest number of shorefish species, yet no long-term fisheries data are available to explore species-level changes that may have occurred widely in the most species rich and vulnerable marine ecosystem, namely coral reefs. Through 2655 face-to-face interviews conducted between August 2012 and July 2014, we used fishers' recall of past catch rates of reef-associated finfish to infer species disappearances from catches in five marine key biodiversity areas (Lanuza Bay, Danajon Bank, Verde Island Passage, Polillo Islands and Honda Bay). We modeled temporal trends in perceived catch per unit effort (CPUE) based on fishers' reports of typical good days' catches using Generalized Linear Mixed Modelling. Fifty-nine different finfish disappeared from catches between the 1950s and 2014; 42 fish were identified to species level, two to genus, seven to family and eight to local name only. Five species occurring at all sites with the greatest number of fishers reporting zero catches were the green bumphead parrotfish (Bolbometopon muricatum), humphead wrasse (Cheilinus undulatus), African pompano (Alectis ciliaris), giant grouper (Epinephelus lanceolatus) and mangrove red snapper (Lutjanus argentimaculatus). Between the 1950s and 2014, the mean perceived CPUE of bumphead parrotfish declined by 88%, that of humphead wrasse by 82%, African pompano by 66%, giant grouper by 74% and mangrove red snapper by 64%. These declines were mainly associated with excess and uncontrolled fishing, fish life-history traits like maximum body size and socio-economic factors like access to market infrastructure and services, and overpopulation. The fishers' knowledge is indicative of extirpations where evidence for these losses was otherwise lacking. Our models provide information as basis for area-based conservation and regional resource management particularly for the more vulnerable, once common, large, yet wide

  14. Bayesian inference of substrate properties from film behavior

    International Nuclear Information System (INIS)

    Aggarwal, R; Demkowicz, M J; Marzouk, Y M

    2015-01-01

    We demonstrate that by observing the behavior of a film deposited on a substrate, certain features of the substrate may be inferred with quantified uncertainty using Bayesian methods. We carry out this demonstration on an illustrative film/substrate model where the substrate is a Gaussian random field and the film is a two-component mixture that obeys the Cahn–Hilliard equation. We construct a stochastic reduced order model to describe the film/substrate interaction and use it to infer substrate properties from film behavior. This quantitative inference strategy may be adapted to other film/substrate systems. (paper)

  15. Reliable effective number of breeders/adult census size ratios in seasonal-breeding species: Opportunity for integrative demographic inferences based on capture-mark-recapture data and multilocus genotypes.

    Science.gov (United States)

    Sánchez-Montes, Gregorio; Wang, Jinliang; Ariño, Arturo H; Vizmanos, José Luis; Martínez-Solano, Iñigo

    2017-12-01

    The ratio of the effective number of breeders ( N b ) to the adult census size ( N a ), N b / N a , approximates the departure from the standard capacity of a population to maintain genetic diversity in one reproductive season. This information is relevant for assessing population status, understanding evolutionary processes operating at local scales, and unraveling how life-history traits affect these processes. However, our knowledge on N b / N a ratios in nature is limited because estimation of both parameters is challenging. The sibship frequency (SF) method is adequate for reliable N b estimation because it is based on sibship and parentage reconstruction from genetic marker data, thereby providing demographic inferences that can be compared with field-based information. In addition, capture-mark-recapture (CMR) robust design methods are well suited for N a estimation in seasonal-breeding species. We used tadpole genotypes of three pond-breeding amphibian species ( Epidalea calamita , Hyla molleri, and Pelophylax perezi , n  =   73-96 single-cohort tadpoles/species genotyped at 15-17 microsatellite loci) and candidate parental genotypes ( n  =   94-300 adults/species) to estimate N b by the SF method. To assess the reliability of N b estimates, we compared sibship and parentage inferences with field-based information and checked for the convergence of results in replicated subsampled analyses. Finally, we used CMR data from a 6-year monitoring program to estimate annual N a in the three species and calculate the N b / N a ratio. Reliable ratios were obtained for E. calamita ( N b / N a  = 0.18-0.28) and P. perezi (0.5), but in H. molleri, N a could not be estimated and genetic information proved insufficient for reliable N b estimation. Integrative demographic studies taking full advantage of SF and CMR methods can provide accurate estimates of the N b / N a ratio in seasonal-breeding species. Importantly, the SF method provides results that can be

  16. Inferences over a narrative text in contexts of interaction in early childhood education [Inferencias sobre un texto narrativo en contextos de interacción en la educación inicial

    Directory of Open Access Journals (Sweden)

    Claudia Patricia Duque Aristizábal

    2012-06-01

    Full Text Available This research explores the relationship between the characteristics of interactions established to favor the narrative text interpretation and the inferences that children make on it. This is marked in the educative, cog- nitive and cultural psychologist. In this research participated four groups of kinder garden with a total of forty four children. This was a descriptive and explorative design. Was realized a discursive analysis and a social nets analysis to process information. It was find that children which teachers favor more interactions and better interactions raised a textual analyses got a high inferencial elaboration, and children which teachers proposed low interaction raised discussions about explicit information in the text, realized a few inferences and with a low level of elaboration.

  17. FunCoup 4: new species, data, and visualization.

    Science.gov (United States)

    Ogris, Christoph; Guala, Dimitri; Sonnhammer, Erik L L

    2018-01-04

    This release of the FunCoup database (http://funcoup.sbc.su.se) is the fourth generation of one of the most comprehensive databases for genome-wide functional association networks. These functional associations are inferred via integrating various data types using a naive Bayesian algorithm and orthology based information transfer across different species. This approach provides high coverage of the included genomes as well as high quality of inferred interactions. In this update of FunCoup we introduce four new eukaryotic species: Schizosaccharomyces pombe, Plasmodium falciparum, Bos taurus, Oryza sativa and open the database to the prokaryotic domain by including networks for Escherichia coli and Bacillus subtilis. The latter allows us to also introduce a new class of functional association between genes - co-occurrence in the same operon. We also supplemented the existing classes of functional association: metabolic, signaling, complex and physical protein interaction with up-to-date information. In this release we switched to InParanoid v8 as the source of orthology and base for calculation of phylogenetic profiles. While populating all other evidence types with new data we introduce a new evidence type based on quantitative mass spectrometry data. Finally, the new JavaScript based network viewer provides the user an intuitive and responsive platform to further evaluate the results. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  18. A new isolation with migration model along complete genomes infers very different divergence processes among closely related great ape species.

    Directory of Open Access Journals (Sweden)

    Thomas Mailund

    Full Text Available We present a hidden Markov model (HMM for inferring gradual isolation between two populations during speciation, modelled as a time interval with restricted gene flow. The HMM describes the history of adjacent nucleotides in two genomic sequences, such that the nucleotides can be separated by recombination, can migrate between populations, or can coalesce at variable time points, all dependent on the parameters of the model, which are the effective population sizes, splitting times, recombination rate, and migration rate. We show by extensive simulations that the HMM can accurately infer all parameters except the recombination rate, which is biased downwards. Inference is robust to variation in the mutation rate and the recombination rate over the sequence and also robust to unknown phase of genomes unless they are very closely related. We provide a test for whether divergence is gradual or instantaneous, and we apply the model to three key divergence processes in great apes: (a the bonobo and common chimpanzee, (b the eastern and western gorilla, and (c the Sumatran and Bornean orang-utan. We find that the bonobo and chimpanzee appear to have undergone a clear split, whereas the divergence processes of the gorilla and orang-utan species occurred over several hundred thousands years with gene flow stopping quite recently. We also apply the model to the Homo/Pan speciation event and find that the most likely scenario involves an extended period of gene flow during speciation.

  19. Using exomarkers to assess mitochondrial reactive species in vivo.

    Science.gov (United States)

    Logan, Angela; Cochemé, Helena M; Li Pun, Pamela Boon; Apostolova, Nadezda; Smith, Robin A J; Larsen, Lesley; Larsen, David S; James, Andrew M; Fearnley, Ian M; Rogatti, Sebastian; Prime, Tracy A; Finichiu, Peter G; Dare, Anna; Chouchani, Edward T; Pell, Victoria R; Methner, Carmen; Quin, Caroline; McQuaker, Stephen J; Krieg, Thomas; Hartley, Richard C; Murphy, Michael P

    2014-02-01

    The ability to measure the concentrations of small damaging and signalling molecules such as reactive oxygen species (ROS) in vivo is essential to understanding their biological roles. While a range of methods can be applied to in vitro systems, measuring the levels and relative changes in reactive species in vivo is challenging. One approach towards achieving this goal is the use of exomarkers. In this, exogenous probe compounds are administered to the intact organism and are then transformed by the reactive molecules in vivo to produce a diagnostic exomarker. The exomarker and the precursor probe can be analysed ex vivo to infer the identity and amounts of the reactive species present in vivo. This is akin to the measurement of biomarkers produced by the interaction of reactive species with endogenous biomolecules. Our laboratories have developed mitochondria-targeted probes that generate exomarkers that can be analysed ex vivo by mass spectrometry to assess levels of reactive species within mitochondria in vivo. We have used one of these compounds, MitoB, to infer the levels of mitochondrial hydrogen peroxide within flies and mice. Here we describe the development of MitoB and expand on this example to discuss how better probes and exomarkers can be developed. This article is part of a Special Issue entitled Current methods to study reactive oxygen species - pros and cons and biophysics of membrane proteins. Guest Editor: Christine Winterbourn. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

  20. Biomechanical warfare in ecology; negative interactions between species by habitat modification

    NARCIS (Netherlands)

    van Wesenbeeck, B. K.; van de Koppel, J.; Herman, P. M. J.; Bakker, J. P.; Bouma, T. J.

    Since the introduction of the term ecosystem engineering by Jones et al. many studies have focused on positive, facilitative interactions caused by ecosystem engineering. Much less emphasis has been placed on the role of ecosystem engineering in causing negative interactions between species. Here,

  1. Biomechanical warfare in ecology; negative interactions between species by habitat modification

    NARCIS (Netherlands)

    Van Wesenbeeck, B.K.; Van de Koppel, J.; Herman, P.M.J.; Bakker, J.P.; Bouma, T.J.

    2007-01-01

    Since the introduction of the term ecosystem engineering by Jones et al. many studies have focused on positive, facilitative interactions caused by ecosystem engineering. Much less emphasis has been placed on the role of ecosystem engineering in causing negative interactions between species. Here,

  2. Co-Inheritance Analysis within the Domains of Life Substantially Improves Network Inference by Phylogenetic Profiling.

    Directory of Open Access Journals (Sweden)

    Junha Shin

    Full Text Available Phylogenetic profiling, a network inference method based on gene inheritance profiles, has been widely used to construct functional gene networks in microbes. However, its utility for network inference in higher eukaryotes has been limited. An improved algorithm with an in-depth understanding of pathway evolution may overcome this limitation. In this study, we investigated the effects of taxonomic structures on co-inheritance analysis using 2,144 reference species in four query species: Escherichia coli, Saccharomyces cerevisiae, Arabidopsis thaliana, and Homo sapiens. We observed three clusters of reference species based on a principal component analysis of the phylogenetic profiles, which correspond to the three domains of life-Archaea, Bacteria, and Eukaryota-suggesting that pathways inherit primarily within specific domains or lower-ranked taxonomic groups during speciation. Hence, the co-inheritance pattern within a taxonomic group may be eroded by confounding inheritance patterns from irrelevant taxonomic groups. We demonstrated that co-inheritance analysis within domains substantially improved network inference not only in microbe species but also in the higher eukaryotes, including humans. Although we observed two sub-domain clusters of reference species within Eukaryota, co-inheritance analysis within these sub-domain taxonomic groups only marginally improved network inference. Therefore, we conclude that co-inheritance analysis within domains is the optimal approach to network inference with the given reference species. The construction of a series of human gene networks with increasing sample sizes of the reference species for each domain revealed that the size of the high-accuracy networks increased as additional reference species genomes were included, suggesting that within-domain co-inheritance analysis will continue to expand human gene networks as genomes of additional species are sequenced. Taken together, we propose that co

  3. Hi-Jack: a novel computational framework for pathway-based inference of host–pathogen interactions

    KAUST Repository

    Kleftogiannis, Dimitrios A.

    2015-03-09

    Motivation: Pathogens infect their host and hijack the host machinery to produce more progeny pathogens. Obligate intracellular pathogens, in particular, require resources of the host to replicate. Therefore, infections by these pathogens lead to alterations in the metabolism of the host, shifting in favor of pathogen protein production. Some computational identification of mechanisms of host-pathogen interactions have been proposed, but it seems the problem has yet to be approached from the metabolite-hijacking angle. Results: We propose a novel computational framework, Hi-Jack, for inferring pathway-based interactions between a host and a pathogen that relies on the idea of metabolite hijacking. Hi-Jack searches metabolic network data from hosts and pathogens, and identifies candidate reactions where hijacking occurs. A novel scoring function ranks candidate hijacked reactions and identifies pathways in the host that interact with pathways in the pathogen, as well as the associated frequent hijacked metabolites. We also describe host-pathogen interaction principles that can be used in the future for subsequent studies. Our case study on Mycobacterium tuberculosis (Mtb) revealed pathways in human-e.g. carbohydrate metabolism, lipids metabolism and pathways related to amino acids metabolism-that are likely to be hijacked by the pathogen. In addition, we report interesting potential pathway interconnections between human and Mtb such as linkage of human fatty acid biosynthesis with Mtb biosynthesis of unsaturated fatty acids, or linkage of human pentose phosphate pathway with lipopolysaccharide biosynthesis in Mtb. © The Author 2015. Published by Oxford University Press. All rights reserved.

  4. Algorithms for MDC-Based Multi-locus Phylogeny Inference

    Science.gov (United States)

    Yu, Yun; Warnow, Tandy; Nakhleh, Luay

    One of the criteria for inferring a species tree from a collection of gene trees, when gene tree incongruence is assumed to be due to incomplete lineage sorting (ILS), is minimize deep coalescence, or MDC. Exact algorithms for inferring the species tree from rooted, binary trees under MDC were recently introduced. Nevertheless, in phylogenetic analyses of biological data sets, estimated gene trees may differ from true gene trees, be incompletely resolved, and not necessarily rooted. In this paper, we propose new MDC formulations for the cases where the gene trees are unrooted/binary, rooted/non-binary, and unrooted/non-binary. Further, we prove structural theorems that allow us to extend the algorithms for the rooted/binary gene tree case to these cases in a straightforward manner. Finally, we study the performance of these methods in coalescent-based computer simulations.

  5. Probabilistic Inference of Biological Networks via Data Integration

    Directory of Open Access Journals (Sweden)

    Mark F. Rogers

    2015-01-01

    Full Text Available There is significant interest in inferring the structure of subcellular networks of interaction. Here we consider supervised interactive network inference in which a reference set of known network links and nonlinks is used to train a classifier for predicting new links. Many types of data are relevant to inferring functional links between genes, motivating the use of data integration. We use pairwise kernels to predict novel links, along with multiple kernel learning to integrate distinct sources of data into a decision function. We evaluate various pairwise kernels to establish which are most informative and compare individual kernel accuracies with accuracies for weighted combinations. By associating a probability measure with classifier predictions, we enable cautious classification, which can increase accuracy by restricting predictions to high-confidence instances, and data cleaning that can mitigate the influence of mislabeled training instances. Although one pairwise kernel (the tensor product pairwise kernel appears to work best, different kernels may contribute complimentary information about interactions: experiments in S. cerevisiae (yeast reveal that a weighted combination of pairwise kernels applied to different types of data yields the highest predictive accuracy. Combined with cautious classification and data cleaning, we can achieve predictive accuracies of up to 99.6%.

  6. Phylogeny and biogeography of highly diverged freshwater fish species (Leuciscinae, Cyprinidae, Teleostei) inferred from mitochondrial genome analysis.

    Science.gov (United States)

    Imoto, Junichi M; Saitoh, Kenji; Sasaki, Takeshi; Yonezawa, Takahiro; Adachi, Jun; Kartavtsev, Yuri P; Miya, Masaki; Nishida, Mutsumi; Hanzawa, Naoto

    2013-02-10

    The distribution of freshwater taxa is a good biogeographic model to study pattern and process of vicariance and dispersal. The subfamily Leuciscinae (Cyprinidae, Teleostei) consists of many species distributed widely in Eurasia and North America. Leuciscinae have been divided into two phyletic groups, leuciscin and phoxinin. The phylogenetic relationships between major clades within the subfamily are poorly understood, largely because of the overwhelming diversity of the group. The origin of the Far Eastern phoxinin is an interesting question regarding the evolutionary history of Leuciscinae. Here we present phylogenetic analysis of 31 species of Leuciscinae and outgroups based on complete mitochondrial genome sequences to clarify the phylogenetic relationships and to infer the evolutionary history of the subfamily. Phylogenetic analysis suggests that the Far Eastern phoxinin species comprised the monophyletic clades Tribolodon, Pseudaspius, Oreoleuciscus and Far Eastern Phoxinus. The Far Eastern phoxinin clade was independent of other Leuciscinae lineages and was closer to North American phoxinins than European leuciscins. All of our analysis also suggested that leuciscins and phoxinins each constituted monophyletic groups. Divergence time estimation suggested that Leuciscinae species diverged from outgroups such as Tincinae to be 83.3 million years ago (Mya) in the Late Cretaceous and leuciscin and phoxinin shared a common ancestor 70.7 Mya. Radiation of Leuciscinae lineages occurred during the Late Cretaceous to Paleocene. This period also witnessed the radiation of tetrapods. Reconstruction of ancestral areas indicates Leuciscinae species originated within Europe. Leuciscin species evolved in Europe and the ancestor of phoxinin was distributed in North America. The Far Eastern phoxinins would have dispersed from North America to Far East across the Beringia land bridge. The present study suggests important roles for the continental rearrangements during the

  7. Interactions between terrestrial mammals and the fruits of two neotropical rainforest tree species

    Science.gov (United States)

    Camargo-Sanabria, Angela A.; Mendoza, Eduardo

    2016-05-01

    Mammalian frugivory is a distinctive biotic interaction of tropical forests; however, most efforts in the Neotropics have focused on cases of animals foraging in the forest canopy, in particular primates and bats. In contrast much less is known about this interaction when it involves fruits deposited on the forest floor and terrestrial mammals. We conducted a camera-trapping survey to analyze the characteristics of the mammalian ensembles visiting fruits of Licania platypus and Pouteria sapota deposited on the forest floor in a well preserved tropical rainforest of Mexico. Both tree species produce large fruits but contrast in their population densities and fruit chemical composition. In particular, we expected that more species of terrestrial mammals would consume P. sapota fruits due to its higher pulp:seed ratio, lower availability and greater carbohydrate content. We monitored fruits at the base of 13 trees (P. sapota, n = 4 and L. platypus, n = 9) using camera-traps. We recorded 13 mammal species from which we had evidence of 8 consuming or removing fruits. These eight species accounted for 70% of the species of mammalian frugivores active in the forest floor of our study area. The ensemble of frugivores associated with L. platypus (6 spp.) was a subset of that associated with P. sapota (8 spp). Large body-sized species such as Tapirus bairdii, Pecari tajacu and Cuniculus paca were the mammals more frequently interacting with fruits of the focal species. Our results further our understanding of the characteristics of the interaction between terrestrial mammalian frugivores and large-sized fruits, helping to gain a more balanced view of its importance across different tropical forests and providing a baseline to compare against defaunated forests.

  8. Role of Speaker Cues in Attention Inference

    Directory of Open Access Journals (Sweden)

    Jin Joo Lee

    2017-10-01

    Full Text Available Current state-of-the-art approaches to emotion recognition primarily focus on modeling the nonverbal expressions of the sole individual without reference to contextual elements such as the co-presence of the partner. In this paper, we demonstrate that the accurate inference of listeners’ social-emotional state of attention depends on accounting for the nonverbal behaviors of their storytelling partner, namely their speaker cues. To gain a deeper understanding of the role of speaker cues in attention inference, we conduct investigations into real-world interactions of children (5–6 years old storytelling with their peers. Through in-depth analysis of human–human interaction data, we first identify nonverbal speaker cues (i.e., backchannel-inviting cues and listener responses (i.e., backchannel feedback. We then demonstrate how speaker cues can modify the interpretation of attention-related backchannels as well as serve as a means to regulate the responsiveness of listeners. We discuss the design implications of our findings toward our primary goal of developing attention recognition models for storytelling robots, and we argue that social robots can proactively use speaker cues to form more accurate inferences about the attentive state of their human partners.

  9. A Bayesian Framework That Integrates Heterogeneous Data for Inferring Gene Regulatory Networks

    Energy Technology Data Exchange (ETDEWEB)

    Santra, Tapesh, E-mail: tapesh.santra@ucd.ie [Systems Biology Ireland, University College Dublin, Dublin (Ireland)

    2014-05-20

    Reconstruction of gene regulatory networks (GRNs) from experimental data is a fundamental challenge in systems biology. A number of computational approaches have been developed to infer GRNs from mRNA expression profiles. However, expression profiles alone are proving to be insufficient for inferring GRN topologies with reasonable accuracy. Recently, it has been shown that integration of external data sources (such as gene and protein sequence information, gene ontology data, protein–protein interactions) with mRNA expression profiles may increase the reliability of the inference process. Here, I propose a new approach that incorporates transcription factor binding sites (TFBS) and physical protein interactions (PPI) among transcription factors (TFs) in a Bayesian variable selection (BVS) algorithm which can infer GRNs from mRNA expression profiles subjected to genetic perturbations. Using real experimental data, I show that the integration of TFBS and PPI data with mRNA expression profiles leads to significantly more accurate networks than those inferred from expression profiles alone. Additionally, the performance of the proposed algorithm is compared with a series of least absolute shrinkage and selection operator (LASSO) regression-based network inference methods that can also incorporate prior knowledge in the inference framework. The results of this comparison suggest that BVS can outperform LASSO regression-based method in some circumstances.

  10. A Bayesian Framework That Integrates Heterogeneous Data for Inferring Gene Regulatory Networks

    International Nuclear Information System (INIS)

    Santra, Tapesh

    2014-01-01

    Reconstruction of gene regulatory networks (GRNs) from experimental data is a fundamental challenge in systems biology. A number of computational approaches have been developed to infer GRNs from mRNA expression profiles. However, expression profiles alone are proving to be insufficient for inferring GRN topologies with reasonable accuracy. Recently, it has been shown that integration of external data sources (such as gene and protein sequence information, gene ontology data, protein–protein interactions) with mRNA expression profiles may increase the reliability of the inference process. Here, I propose a new approach that incorporates transcription factor binding sites (TFBS) and physical protein interactions (PPI) among transcription factors (TFs) in a Bayesian variable selection (BVS) algorithm which can infer GRNs from mRNA expression profiles subjected to genetic perturbations. Using real experimental data, I show that the integration of TFBS and PPI data with mRNA expression profiles leads to significantly more accurate networks than those inferred from expression profiles alone. Additionally, the performance of the proposed algorithm is compared with a series of least absolute shrinkage and selection operator (LASSO) regression-based network inference methods that can also incorporate prior knowledge in the inference framework. The results of this comparison suggest that BVS can outperform LASSO regression-based method in some circumstances.

  11. The evolutionary history of ferns inferred from 25 low-copy nuclear genes.

    Science.gov (United States)

    Rothfels, Carl J; Li, Fay-Wei; Sigel, Erin M; Huiet, Layne; Larsson, Anders; Burge, Dylan O; Ruhsam, Markus; Deyholos, Michael; Soltis, Douglas E; Stewart, C Neal; Shaw, Shane W; Pokorny, Lisa; Chen, Tao; dePamphilis, Claude; DeGironimo, Lisa; Chen, Li; Wei, Xiaofeng; Sun, Xiao; Korall, Petra; Stevenson, Dennis W; Graham, Sean W; Wong, Gane K-S; Pryer, Kathleen M

    2015-07-01

    • Understanding fern (monilophyte) phylogeny and its evolutionary timescale is critical for broad investigations of the evolution of land plants, and for providing the point of comparison necessary for studying the evolution of the fern sister group, seed plants. Molecular phylogenetic investigations have revolutionized our understanding of fern phylogeny, however, to date, these studies have relied almost exclusively on plastid data.• Here we take a curated phylogenomics approach to infer the first broad fern phylogeny from multiple nuclear loci, by combining broad taxon sampling (73 ferns and 12 outgroup species) with focused character sampling (25 loci comprising 35877 bp), along with rigorous alignment, orthology inference and model selection.• Our phylogeny corroborates some earlier inferences and provides novel insights; in particular, we find strong support for Equisetales as sister to the rest of ferns, Marattiales as sister to leptosporangiate ferns, and Dennstaedtiaceae as sister to the eupolypods. Our divergence-time analyses reveal that divergences among the extant fern orders all occurred prior to ∼200 MYA. Finally, our species-tree inferences are congruent with analyses of concatenated data, but generally with lower support. Those cases where species-tree support values are higher than expected involve relationships that have been supported by smaller plastid datasets, suggesting that deep coalescence may be reducing support from the concatenated nuclear data.• Our study demonstrates the utility of a curated phylogenomics approach to inferring fern phylogeny, and highlights the need to consider underlying data characteristics, along with data quantity, in phylogenetic studies. © 2015 Botanical Society of America, Inc.

  12. Positive indirect interactions between neighboring plant species via a lizard pollinator.

    OpenAIRE

    Hansen, D M; Kiesbüy, H C; Jones, C G; Müller, C B

    2007-01-01

    In natural communities, species are embedded in networks of direct and indirect interactions. Most studies on indirect interactions have focused on how they affect predator-prey or competitive relationships. However, it is equally likely that indirect interactions play an important structuring role in mutualistic relationships in a natural community. We demonstrate experimentally that on a small spatial scale, dense thickets of endemic Pandanus plants have a strong positive trait-mediated ind...

  13. Measure solutions for non-local interaction PDEs with two species

    Energy Technology Data Exchange (ETDEWEB)

    Francesco, Marco Di [Department of Mathematical and Statistical Sciences, University of Bath, Claverton Down, Bath, BA2 7AY (United Kingdom); Fagioli, Simone [DISIM—Department of Information Engineering, Computer Science and Mathematics, University of L' Aquila, Via Vetoio 1 (Coppito) 67100 L' Aquila (AQ) (Italy)

    2013-10-01

    This paper presents a systematic existence and uniqueness theory of weak measure solutions for systems of non-local interaction PDEs with two species, which are the PDE counterpart of systems of deterministic interacting particles with two species. The main motivations behind those models arise in cell biology, pedestrian movements, and opinion formation. In case of symmetrizable systems (i.e. with cross-interaction potentials one multiple of the other), we provide a complete existence and uniqueness theory within (a suitable generalization of) the Wasserstein gradient flow theory in Ambrosio et al (2008 Gradient Flows in Metric Spaces and in the Space of Probability Measures (Lectures in Mathematics ETH Zürich) 2nd edn (Basel: Birkhäuser)) and Carrillo et al (2011 Duke Math. J. 156 229–71), which allows the consideration of interaction potentials with a discontinuous gradient at the origin. In the general case of non-symmetrizable systems, we provide an existence result for measure solutions which uses a semi-implicit version of the Jordan–Kinderlehrer–Otto (JKO) scheme (Jordan et al 1998 SIAM J. Math. Anal. 29 1–17), which holds in a reasonable non-smooth setting for the interaction potentials. Uniqueness in the non-symmetrizable case is proven for C{sup 2} potentials using a variant of the method of characteristics. (paper)

  14. Measure solutions for non-local interaction PDEs with two species

    International Nuclear Information System (INIS)

    Francesco, Marco Di; Fagioli, Simone

    2013-01-01

    This paper presents a systematic existence and uniqueness theory of weak measure solutions for systems of non-local interaction PDEs with two species, which are the PDE counterpart of systems of deterministic interacting particles with two species. The main motivations behind those models arise in cell biology, pedestrian movements, and opinion formation. In case of symmetrizable systems (i.e. with cross-interaction potentials one multiple of the other), we provide a complete existence and uniqueness theory within (a suitable generalization of) the Wasserstein gradient flow theory in Ambrosio et al (2008 Gradient Flows in Metric Spaces and in the Space of Probability Measures (Lectures in Mathematics ETH Zürich) 2nd edn (Basel: Birkhäuser)) and Carrillo et al (2011 Duke Math. J. 156 229–71), which allows the consideration of interaction potentials with a discontinuous gradient at the origin. In the general case of non-symmetrizable systems, we provide an existence result for measure solutions which uses a semi-implicit version of the Jordan–Kinderlehrer–Otto (JKO) scheme (Jordan et al 1998 SIAM J. Math. Anal. 29 1–17), which holds in a reasonable non-smooth setting for the interaction potentials. Uniqueness in the non-symmetrizable case is proven for C 2 potentials using a variant of the method of characteristics. (paper)

  15. Inferring local ecological processes amid species pool influences

    DEFF Research Database (Denmark)

    Lessard, Jean-Philippe; Belmaker, Jonathan; Myers, Jonathan A.

    2012-01-01

    studies, null models of community structure, and ecologically explicit definitions of the species pool as a means to compare predominant ecological processes among regions. By uniting concepts and tools from community ecology and macroecology, this approach might facilitate synthesis and resolve many......Resolving contingencies in community ecology requires comparative studies of local communities along broad-scale environmental gradients and in different biogeographic regions. However, comparisons of local ecological processes among regions require a synthetic understanding of how the species pool...... of potential community members influences the structure of ecological communities. Here, we outline an integrative approach for quantifying local ecological processes while explicitly accounting for species pool influences. Specifically, we highlight the utility of combining geographically replicated local...

  16. Balance of Interactions Determines Optimal Survival in Multi-Species Communities.

    Directory of Open Access Journals (Sweden)

    Anshul Choudhary

    Full Text Available We consider a multi-species community modelled as a complex network of populations, where the links are given by a random asymmetric connectivity matrix J, with fraction 1 - C of zero entries, where C reflects the over-all connectivity of the system. The non-zero elements of J are drawn from a Gaussian distribution with mean μ and standard deviation σ. The signs of the elements Jij reflect the nature of density-dependent interactions, such as predatory-prey, mutualism or competition, and their magnitudes reflect the strength of the interaction. In this study we try to uncover the broad features of the inter-species interactions that determine the global robustness of this network, as indicated by the average number of active nodes (i.e. non-extinct species in the network, and the total population, reflecting the biomass yield. We find that the network transitions from a completely extinct system to one where all nodes are active, as the mean interaction strength goes from negative to positive, with the transition getting sharper for increasing C and decreasing σ. We also find that the total population, displays distinct non-monotonic scaling behaviour with respect to the product μC, implying that survival is dependent not merely on the number of links, but rather on the combination of the sparseness of the connectivity matrix and the net interaction strength. Interestingly, in an intermediate window of positive μC, the total population is maximal, indicating that too little or too much positive interactions is detrimental to survival. Rather, the total population levels are optimal when the network has intermediate net positive connection strengths. At the local level we observe marked qualitative changes in dynamical patterns, ranging from anti-phase clusters of period 2 cycles and chaotic bands, to fixed points, under the variation of mean μ of the interaction strengths. We also study the correlation between synchronization and survival

  17. Species Interactions Drive Fish Biodiversity Loss in a High-CO2 World.

    Science.gov (United States)

    Nagelkerken, Ivan; Goldenberg, Silvan U; Ferreira, Camilo M; Russell, Bayden D; Connell, Sean D

    2017-07-24

    Accelerating climate change is eroding the functioning and stability of ecosystems by weakening the interactions among species that stabilize biological communities against change [1]. A key challenge to forecasting the future of ecosystems centers on how to extrapolate results from short-term, single-species studies to community-level responses that are mediated by key mechanisms such as competition, resource availability (bottom-up control), and predation (top-down control) [2]. We used CO 2 vents as potential analogs of ocean acidification combined with in situ experiments to test current predictions of fish biodiversity loss and community change due to elevated CO 2 [3] and to elucidate the potential mechanisms that drive such change. We show that high risk-taking behavior and competitive strength, combined with resource enrichment and collapse of predator populations, fostered already common species, enabling them to double their populations under acidified conditions. However, the release of these competitive dominants from predator control led to suppression of less common and subordinate competitors that did not benefit from resource enrichment and reduced predation. As a result, local biodiversity was lost and novel fish community compositions were created under elevated CO 2 . Our study identifies the species interactions most affected by ocean acidification, revealing potential sources of natural selection. We also reveal how diminished predator abundances can have cascading effects on local species diversity, mediated by complex species interactions. Reduced overfishing of predators could therefore act as a key action to stall diversity loss and ecosystem change in a high-CO 2 world. VIDEO ABSTRACT. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. Multilocus inference of species trees and DNA barcoding.

    Science.gov (United States)

    Mallo, Diego; Posada, David

    2016-09-05

    The unprecedented amount of data resulting from next-generation sequencing has opened a new era in phylogenetic estimation. Although large datasets should, in theory, increase phylogenetic resolution, massive, multilocus datasets have uncovered a great deal of phylogenetic incongruence among different genomic regions, due both to stochastic error and to the action of different evolutionary process such as incomplete lineage sorting, gene duplication and loss and horizontal gene transfer. This incongruence violates one of the fundamental assumptions of the DNA barcoding approach, which assumes that gene history and species history are identical. In this review, we explain some of the most important challenges we will have to face to reconstruct the history of species, and the advantages and disadvantages of different strategies for the phylogenetic analysis of multilocus data. In particular, we describe the evolutionary events that can generate species tree-gene tree discordance, compare the most popular methods for species tree reconstruction, highlight the challenges we need to face when using them and discuss their potential utility in barcoding. Current barcoding methods sacrifice a great amount of statistical power by only considering one locus, and a transition to multilocus barcodes would not only improve current barcoding methods, but also facilitate an eventual transition to species-tree-based barcoding strategies, which could better accommodate scenarios where the barcode gap is too small or inexistent.This article is part of the themed issue 'From DNA barcodes to biomes'. © 2016 The Authors.

  19. Seasonal Habitat Patterns of Japanese Common Squid (Todarodes Pacificus Inferred from Satellite-Based Species Distribution Models

    Directory of Open Access Journals (Sweden)

    Irene D. Alabia

    2016-11-01

    Full Text Available The understanding of the spatio-temporal distributions of the species habitat in the marine environment is central to effectual resource management and conservation. Here, we examined the potential habitat distributions of Japanese common squid (Todarodes pacificus in the Sea of Japan during a four-year period. The seasonal patterns of preferential habitat were inferred from species distribution models, built using squid occurrences detected from night-time visible images and remotely-sensed environmental factors. The predicted squid habitat (i.e., areas with high habitat suitability revealed strong seasonal variability, characterized by a reduction of potential habitat, confined off of the southern part of the basin during the winter–spring period (December–May. Apparent expansion of preferential habitat occurred during summer–autumn months (June–November, concurrent with the formation of highly suitable habitat patches in certain regions of the Sea of Japan. These habitat distribution patterns were in response to changes in oceanographic conditions and synchronous with seasonal migration of squid. Moreover, the most important variables regulating the spatio-temporal patterns of suitable habitat were sea surface temperature, depth, sea surface height anomaly, and eddy kinetic energy. These variables could affect the habitat distributions through their impacts on growth and survival of squid, local nutrient transport, and the availability of favorable spawning and feeding grounds.

  20. What do we gain from simplicity versus complexity in species distribution models?

    Science.gov (United States)

    Merow, Cory; Smith, Matthew J.; Edwards, Thomas C.; Guisan, Antoine; McMahon, Sean M.; Normand, Signe; Thuiller, Wilfried; Wuest, Rafael O.; Zimmermann, Niklaus E.; Elith, Jane

    2014-01-01

    Species distribution models (SDMs) are widely used to explain and predict species ranges and environmental niches. They are most commonly constructed by inferring species' occurrence–environment relationships using statistical and machine-learning methods. The variety of methods that can be used to construct SDMs (e.g. generalized linear/additive models, tree-based models, maximum entropy, etc.), and the variety of ways that such models can be implemented, permits substantial flexibility in SDM complexity. Building models with an appropriate amount of complexity for the study objectives is critical for robust inference. We characterize complexity as the shape of the inferred occurrence–environment relationships and the number of parameters used to describe them, and search for insights into whether additional complexity is informative or superfluous. By building ‘under fit’ models, having insufficient flexibility to describe observed occurrence–environment relationships, we risk misunderstanding the factors shaping species distributions. By building ‘over fit’ models, with excessive flexibility, we risk inadvertently ascribing pattern to noise or building opaque models. However, model selection can be challenging, especially when comparing models constructed under different modeling approaches. Here we argue for a more pragmatic approach: researchers should constrain the complexity of their models based on study objective, attributes of the data, and an understanding of how these interact with the underlying biological processes. We discuss guidelines for balancing under fitting with over fitting and consequently how complexity affects decisions made during model building. Although some generalities are possible, our discussion reflects differences in opinions that favor simpler versus more complex models. We conclude that combining insights from both simple and complex SDM building approaches best advances our knowledge of current and future species

  1. Evolutionary history of the European whitefish Coregonus lavaretus (L.) species complex as inferred from mtDNA phylogeography and gill-raker numbers.

    Science.gov (United States)

    Østbye, K; Bernatchez, L; Naesje, T F; Himberg, K-J M; Hindar, K

    2005-12-01

    We compared mitochondrial DNA and gill-raker number variation in populations of the European whitefish Coregonus lavaretus (L.) species complex to illuminate their evolutionary history, and discuss mechanisms behind diversification. Using single-strand conformation polymorphism (SSCP) and sequencing 528 bp of combined parts of the cytochrome oxidase b (cyt b) and NADH dehydrogenase subunit 3 (ND3) mithochondrial DNA (mtDNA) regions, we documented phylogeographic relationships among populations and phylogeny of mtDNA haplotypes. Demographic events behind geographical distribution of haplotypes were inferred using nested clade analysis (NCA) and mismatch distribution. Concordance between operational taxonomical groups, based on gill-raker numbers, and mtDNA patterns was tested. Three major mtDNA clades were resolved in Europe: a North European clade from northwest Russia to Denmark, a Siberian clade from the Arctic Sea to southwest Norway, and a South European clade from Denmark to the European Alps, reflecting occupation in different glacial refugia. Demographic events inferred from NCA were isolation by distance, range expansion, and fragmentation. Mismatch analysis suggested that clades which colonized Fennoscandia and the Alps expanded in population size 24 500-5800 years before present, with minute female effective population sizes, implying small founder populations during colonization. Gill-raker counts did not commensurate with hierarchical mtDNA clades, and poorly with haplotypes, suggesting recent origin of gill-raker variation. Whitefish designations based on gill-raker numbers were not associated with ancient clades. Lack of congruence in morphology and evolutionary lineages implies that the taxonomy of this species complex should be reconsidered.

  2. Causal inference in biology networks with integrated belief propagation.

    Science.gov (United States)

    Chang, Rui; Karr, Jonathan R; Schadt, Eric E

    2015-01-01

    Inferring causal relationships among molecular and higher order phenotypes is a critical step in elucidating the complexity of living systems. Here we propose a novel method for inferring causality that is no longer constrained by the conditional dependency arguments that limit the ability of statistical causal inference methods to resolve causal relationships within sets of graphical models that are Markov equivalent. Our method utilizes Bayesian belief propagation to infer the responses of perturbation events on molecular traits given a hypothesized graph structure. A distance measure between the inferred response distribution and the observed data is defined to assess the 'fitness' of the hypothesized causal relationships. To test our algorithm, we infer causal relationships within equivalence classes of gene networks in which the form of the functional interactions that are possible are assumed to be nonlinear, given synthetic microarray and RNA sequencing data. We also apply our method to infer causality in real metabolic network with v-structure and feedback loop. We show that our method can recapitulate the causal structure and recover the feedback loop only from steady-state data which conventional method cannot.

  3. Effective like- and unlike-pair interactions at high pressure and high temperature

    International Nuclear Information System (INIS)

    Ree, F.H.; van Thiel, M.

    1991-05-01

    We describe how information on effective interactions of chemical species involving C, O, and N atoms at high pressure and high temperature may be inferred from available shock wave data of NO and CO. Our approach uses a modern statistical mechanical theory and a detailed equation of state (EOS) model for the condensed phases of carbon

  4. Divergence times in Caenorhabditis and Drosophila inferred from direct estimates of the neutral mutation rate.

    Science.gov (United States)

    Cutter, Asher D

    2008-04-01

    Accurate inference of the dates of common ancestry among species forms a central problem in understanding the evolutionary history of organisms. Molecular estimates of divergence time rely on the molecular evolutionary prediction that neutral mutations and substitutions occur at the same constant rate in genomes of related species. This underlies the notion of a molecular clock. Most implementations of this idea depend on paleontological calibration to infer dates of common ancestry, but taxa with poor fossil records must rely on external, potentially inappropriate, calibration with distantly related species. The classic biological models Caenorhabditis and Drosophila are examples of such problem taxa. Here, I illustrate internal calibration in these groups with direct estimates of the mutation rate from contemporary populations that are corrected for interfering effects of selection on the assumption of neutrality of substitutions. Divergence times are inferred among 6 species each of Caenorhabditis and Drosophila, based on thousands of orthologous groups of genes. I propose that the 2 closest known species of Caenorhabditis shared a common ancestor <24 MYA (Caenorhabditis briggsae and Caenorhabditis sp. 5) and that Caenorhabditis elegans diverged from its closest known relatives <30 MYA, assuming that these species pass through at least 6 generations per year; these estimates are much more recent than reported previously with molecular clock calibrations from non-nematode phyla. Dates inferred for the common ancestor of Drosophila melanogaster and Drosophila simulans are roughly concordant with previous studies. These revised dates have important implications for rates of genome evolution and the origin of self-fertilization in Caenorhabditis.

  5. Biodiversity and the Lotka-Volterra theory of species interactions: open systems and the distribution of logarithmic densities.

    Science.gov (United States)

    Wilson, William G; Lundberg, Per

    2004-09-22

    Theoretical interest in the distributions of species abundances observed in ecological communities has focused recently on the results of models that assume all species are identical in their interactions with one another, and rely upon immigration and speciation to promote coexistence. Here we examine a one-trophic level system with generalized species interactions, including species-specific intraspecific and interspecific interaction strengths, and density-independent immigration from a regional species pool. Comparisons between results from numerical integrations and an approximate analytic calculation for random communities demonstrate good agreement, and both approaches yield abundance distributions of nearly arbitrary shape, including bimodality for intermediate immigration rates.

  6. Plant-pollinator interactions over 120 years: loss of species, co-occurrence, and function.

    Science.gov (United States)

    Burkle, Laura A; Marlin, John C; Knight, Tiffany M

    2013-03-29

    Using historic data sets, we quantified the degree to which global change over 120 years disrupted plant-pollinator interactions in a temperate forest understory community in Illinois, USA. We found degradation of interaction network structure and function and extirpation of 50% of bee species. Network changes can be attributed to shifts in forb and bee phenologies resulting in temporal mismatches, nonrandom species extinctions, and loss of spatial co-occurrences between extant species in modified landscapes. Quantity and quality of pollination services have declined through time. The historic network showed flexibility in response to disturbance; however, our data suggest that networks will be less resilient to future changes.

  7. Phylogeny of Celastraceae subfamily Hippocrateoideae inferred from morphological characters and nuclear and plastid loci.

    Science.gov (United States)

    Coughenour, Jennifer M; Simmons, Mark P; Lombardi, Julio A; Yakobson, Kendra; Archer, Robert H

    2011-05-01

    The phylogeny of Celastraceae subfamily Hippocrateoideae (∼ 100 species and 19 genera in the Old and New World tropics) was inferred using morphological characters together with plastid (matK, trnL-F) and nuclear (ITS and 26S rDNA) genes. The subfamily is easily recognized by the synapomorphies of transversely flattened, deeply lobed capsules and seeds with membranous basal wings or narrow stipes together with bisexual, 5-merous flowers that generally have an extrastaminal disk and three stamens. Hippocrateoideae, like Salacioideae, are inferred to have an Old World origin. The narrow stipes of Neotropical species that are water-dispersed are inferred to be derived within the subfamily from ancestral species with wind-dispersed winged seeds. Helictonema, a monotypic genus endemic to tropical Africa, has a small, white, spongy aril that is located at the base of the seed wing and appears to be unique within Hippocrateoideae. Our inference that Helictonema is sister to the remaining members of the subfamily, considered in the context of Sarawakodendron being sister to Salacioideae, suggests that small arils and capsular fruit were primitive within both subfamilies. The aril became dramatically enlarged within Salacioideae, in which the fruits are berries, and lost entirely within Hippocrateoideae, in which the fruits are transversely flattened capsules. All five Old World taxa of Prionostemma and all eight currently recognized species within Simirestis are transferred to Pristimera, one South African variety of Pristimera is raised to species level, and all three taxa in Pristimera subgenus Trochantha are transferred to the new genus Trochantha. Copyright © 2011 Elsevier Inc. All rights reserved.

  8. Model-free information-theoretic approach to infer leadership in pairs of zebrafish.

    Science.gov (United States)

    Butail, Sachit; Mwaffo, Violet; Porfiri, Maurizio

    2016-04-01

    Collective behavior affords several advantages to fish in avoiding predators, foraging, mating, and swimming. Although fish schools have been traditionally considered egalitarian superorganisms, a number of empirical observations suggest the emergence of leadership in gregarious groups. Detecting and classifying leader-follower relationships is central to elucidate the behavioral and physiological causes of leadership and understand its consequences. Here, we demonstrate an information-theoretic approach to infer leadership from positional data of fish swimming. In this framework, we measure social interactions between fish pairs through the mathematical construct of transfer entropy, which quantifies the predictive power of a time series to anticipate another, possibly coupled, time series. We focus on the zebrafish model organism, which is rapidly emerging as a species of choice in preclinical research for its genetic similarity to humans and reduced neurobiological complexity with respect to mammals. To overcome experimental confounds and generate test data sets on which we can thoroughly assess our approach, we adapt and calibrate a data-driven stochastic model of zebrafish motion for the simulation of a coupled dynamical system of zebrafish pairs. In this synthetic data set, the extent and direction of the coupling between the fish are systematically varied across a wide parameter range to demonstrate the accuracy and reliability of transfer entropy in inferring leadership. Our approach is expected to aid in the analysis of collective behavior, providing a data-driven perspective to understand social interactions.

  9. Mechanisms of Disease: Host-Pathogen Interactions between Burkholderia Species and Lung Epithelial Cells

    Science.gov (United States)

    David, Jonathan; Bell, Rachel E.; Clark, Graeme C.

    2015-01-01

    Members of the Burkholderia species can cause a range of severe, often fatal, respiratory diseases. A variety of in vitro models of infection have been developed in an attempt to elucidate the mechanism by which Burkholderia spp. gain entry to and interact with the body. The majority of studies have tended to focus on the interaction of bacteria with phagocytic cells with a paucity of information available with regard to the lung epithelium. However, the lung epithelium is becoming more widely recognized as an important player in innate immunity and the early response to infections. Here we review the complex relationship between Burkholderia species and epithelial cells with an emphasis on the most pathogenic species, Burkholderia pseudomallei and Burkholderia mallei. The current gaps in knowledge in our understanding are highlighted along with the epithelial host-pathogen interactions that offer potential opportunities for therapeutic intervention. PMID:26636042

  10. Mutualistic interactions drive ecological niche convergence in a diverse butterfly community.

    Science.gov (United States)

    Elias, Marianne; Gompert, Zachariah; Jiggins, Chris; Willmott, Keith

    2008-12-02

    Ecological communities are structured in part by evolutionary interactions among their members. A number of recent studies incorporating phylogenetics into community ecology have upheld the paradigm that competition drives ecological divergence among species of the same guild. However, the role of other interspecific interactions, in particular positive interactions such as mutualism, remains poorly explored. We characterized the ecological niche and inferred phylogenetic relationships among members of a diverse community of neotropical Müllerian mimetic butterflies. Müllerian mimicry is one of the best studied examples of mutualism, in which unpalatable species converge in wing pattern locally to advertize their toxicity to predators. We provide evidence that mutualistic interactions can drive convergence along multiple ecological axes, outweighing both phylogeny and competition in shaping community structure. Our findings imply that ecological communities are adaptively assembled to a much greater degree than commonly suspected. In addition, our results show that phenotype and ecology are strongly linked and support the idea that mimicry can cause ecological speciation through multiple cascading effects on species' biology.

  11. Mutualistic interactions drive ecological niche convergence in a diverse butterfly community.

    Directory of Open Access Journals (Sweden)

    Marianne Elias

    2008-12-01

    Full Text Available Ecological communities are structured in part by evolutionary interactions among their members. A number of recent studies incorporating phylogenetics into community ecology have upheld the paradigm that competition drives ecological divergence among species of the same guild. However, the role of other interspecific interactions, in particular positive interactions such as mutualism, remains poorly explored. We characterized the ecological niche and inferred phylogenetic relationships among members of a diverse community of neotropical Müllerian mimetic butterflies. Müllerian mimicry is one of the best studied examples of mutualism, in which unpalatable species converge in wing pattern locally to advertize their toxicity to predators. We provide evidence that mutualistic interactions can drive convergence along multiple ecological axes, outweighing both phylogeny and competition in shaping community structure. Our findings imply that ecological communities are adaptively assembled to a much greater degree than commonly suspected. In addition, our results show that phenotype and ecology are strongly linked and support the idea that mimicry can cause ecological speciation through multiple cascading effects on species' biology.

  12. Shifting species interactions in terrestrial dryland ecosystems under altered water availability and climate change

    Science.gov (United States)

    McCluney, Kevin E.; Belnap, Jayne; Collins, Scott L.; González, Angélica L.; Hagen, Elizabeth M.; Holland, J. Nathaniel; Kotler, Burt P.; Maestre, Fernando T.; Smith, Stanley D.; Wolf, Blair O.

    2012-01-01

    Species interactions play key roles in linking the responses of populations, communities, and ecosystems to environmental change. For instance, species interactions are an important determinant of the complexity of changes in trophic biomass with variation in resources. Water resources are a major driver of terrestrial ecology and climate change is expected to greatly alter the distribution of this critical resource. While previous studies have documented strong effects of global environmental change on species interactions in general, responses can vary from region to region. Dryland ecosystems occupy more than one-third of the Earth's land mass, are greatly affected by changes in water availability, and are predicted to be hotspots of climate change. Thus, it is imperative to understand the effects of environmental change on these globally significant ecosystems. Here, we review studies of the responses of population-level plant-plant, plant-herbivore, and predator-prey interactions to changes in water availability in dryland environments in order to develop new hypotheses and predictions to guide future research. To help explain patterns of interaction outcomes, we developed a conceptual model that views interaction outcomes as shifting between (1) competition and facilitation (plant-plant), (2) herbivory, neutralism, or mutualism (plant-herbivore), or (3) neutralism and predation (predator-prey), as water availability crosses physiological, behavioural, or population-density thresholds. We link our conceptual model to hypothetical scenarios of current and future water availability to make testable predictions about the influence of changes in water availability on species interactions. We also examine potential implications of our conceptual model for the relative importance of top-down effects and the linearity of patterns of change in trophic biomass with changes in water availability. Finally, we highlight key research needs and some possible broader impacts

  13. Shifting species interactions in terrestrial dryland ecosystems under altered water availability and climate change.

    Science.gov (United States)

    McCluney, Kevin E; Belnap, Jayne; Collins, Scott L; González, Angélica L; Hagen, Elizabeth M; Nathaniel Holland, J; Kotler, Burt P; Maestre, Fernando T; Smith, Stanley D; Wolf, Blair O

    2012-08-01

    Species interactions play key roles in linking the responses of populations, communities, and ecosystems to environmental change. For instance, species interactions are an important determinant of the complexity of changes in trophic biomass with variation in resources. Water resources are a major driver of terrestrial ecology and climate change is expected to greatly alter the distribution of this critical resource. While previous studies have documented strong effects of global environmental change on species interactions in general, responses can vary from region to region. Dryland ecosystems occupy more than one-third of the Earth's land mass, are greatly affected by changes in water availability, and are predicted to be hotspots of climate change. Thus, it is imperative to understand the effects of environmental change on these globally significant ecosystems. Here, we review studies of the responses of population-level plant-plant, plant-herbivore, and predator-prey interactions to changes in water availability in dryland environments in order to develop new hypotheses and predictions to guide future research. To help explain patterns of interaction outcomes, we developed a conceptual model that views interaction outcomes as shifting between (1) competition and facilitation (plant-plant), (2) herbivory, neutralism, or mutualism (plant-herbivore), or (3) neutralism and predation (predator-prey), as water availability crosses physiological, behavioural, or population-density thresholds. We link our conceptual model to hypothetical scenarios of current and future water availability to make testable predictions about the influence of changes in water availability on species interactions. We also examine potential implications of our conceptual model for the relative importance of top-down effects and the linearity of patterns of change in trophic biomass with changes in water availability. Finally, we highlight key research needs and some possible broader impacts

  14. Species coexistence: macroevolutionary relationships and the contingency of historical interactions.

    Science.gov (United States)

    Germain, Rachel M; Weir, Jason T; Gilbert, Benjamin

    2016-03-30

    Evolutionary biologists since Darwin have hypothesized that closely related species compete more intensely and are therefore less likely to coexist. However, recent theory posits that species diverge in two ways: either through the evolution of 'stabilizing differences' that promote coexistence by causing individuals to compete more strongly with conspecifics than individuals of other species, or through the evolution of 'fitness differences' that cause species to differ in competitive ability and lead to exclusion of the weaker competitor. We tested macroevolutionary patterns of divergence by competing pairs of annual plant species that differ in their phylogenetic relationships, and in whether they have historically occurred in the same region or different regions (sympatric versus allopatric occurrence). For sympatrically occurring species pairs, stabilizing differences rapidly increased with phylogenetic distance. However, fitness differences also increased with phylogenetic distance, resulting in coexistence outcomes that were unpredictable based on phylogenetic relationships. For allopatric species, stabilizing differences showed no trend with phylogenetic distance, whereas fitness differences increased, causing coexistence to become less likely among distant relatives. Our results illustrate the role of species' historical interactions in shaping how phylogenetic relationships structure competitive dynamics, and offer an explanation for the evolution of invasion potential of non-native species. © 2016 The Author(s).

  15. Causal inference in nonlinear systems: Granger causality versus time-delayed mutual information

    Science.gov (United States)

    Li, Songting; Xiao, Yanyang; Zhou, Douglas; Cai, David

    2018-05-01

    The Granger causality (GC) analysis has been extensively applied to infer causal interactions in dynamical systems arising from economy and finance, physics, bioinformatics, neuroscience, social science, and many other fields. In the presence of potential nonlinearity in these systems, the validity of the GC analysis in general is questionable. To illustrate this, here we first construct minimal nonlinear systems and show that the GC analysis fails to infer causal relations in these systems—it gives rise to all types of incorrect causal directions. In contrast, we show that the time-delayed mutual information (TDMI) analysis is able to successfully identify the direction of interactions underlying these nonlinear systems. We then apply both methods to neuroscience data collected from experiments and demonstrate that the TDMI analysis but not the GC analysis can identify the direction of interactions among neuronal signals. Our work exemplifies inference hazards in the GC analysis in nonlinear systems and suggests that the TDMI analysis can be an appropriate tool in such a case.

  16. Protein-protein interaction network-based detection of functionally similar proteins within species.

    Science.gov (United States)

    Song, Baoxing; Wang, Fen; Guo, Yang; Sang, Qing; Liu, Min; Li, Dengyun; Fang, Wei; Zhang, Deli

    2012-07-01

    Although functionally similar proteins across species have been widely studied, functionally similar proteins within species showing low sequence similarity have not been examined in detail. Identification of these proteins is of significant importance for understanding biological functions, evolution of protein families, progression of co-evolution, and convergent evolution and others which cannot be obtained by detection of functionally similar proteins across species. Here, we explored a method of detecting functionally similar proteins within species based on graph theory. After denoting protein-protein interaction networks using graphs, we split the graphs into subgraphs using the 1-hop method. Proteins with functional similarities in a species were detected using a method of modified shortest path to compare these subgraphs and to find the eligible optimal results. Using seven protein-protein interaction networks and this method, some functionally similar proteins with low sequence similarity that cannot detected by sequence alignment were identified. By analyzing the results, we found that, sometimes, it is difficult to separate homologous from convergent evolution. Evaluation of the performance of our method by gene ontology term overlap showed that the precision of our method was excellent. Copyright © 2012 Wiley Periodicals, Inc.

  17. Species distribution models contribute to determine the effect of climate and interspecific interactions in moving hybrid zones.

    Science.gov (United States)

    Engler, J O; Rödder, D; Elle, O; Hochkirch, A; Secondi, J

    2013-11-01

    Climate is a major factor delimiting species' distributions. However, biotic interactions may also be prominent in shaping geographical ranges, especially for parapatric species forming hybrid zones. Determining the relative effect of each factor and their interaction of the contact zone location has been difficult due to the lack of broad scale environmental data. Recent developments in species distribution modelling (SDM) now allow disentangling the relative contributions of climate and species' interactions in hybrid zones and their responses to future climate change. We investigated the moving hybrid zone between the breeding ranges of two parapatric passerines in Europe. We conducted SDMs representing the climatic conditions during the breeding season. Our results show a large mismatch between the realized and potential distributions of the two species, suggesting that interspecific interactions, not climate, account for the present location of the contact zone. The SDM scenarios show that the southerly distributed species, Hippolais polyglotta, might lose large parts of its southern distribution under climate change, but a similar gain of novel habitat along the hybrid zone seems unlikely, because interactions with the other species (H. icterina) constrain its range expansion. Thus, whenever biotic interactions limit range expansion, species may become 'trapped' if range loss due to climate change is faster than the movement of the contact zone. An increasing number of moving hybrid zones are being reported, but the proximate causes of movement often remain unclear. In a global context of climate change, we call for more interest in their interactions with climate change. © 2013 The Authors. Journal of Evolutionary Biology © 2013 European Society For Evolutionary Biology.

  18. Biological interactions and cooperative management of multiple species.

    Science.gov (United States)

    Jiang, Jinwei; Min, Yong; Chang, Jie; Ge, Ying

    2017-01-01

    Coordinated decision making and actions have become the primary solution for the overexploitation of interacting resources within ecosystems. However, the success of coordinated management is highly sensitive to biological, economic, and social conditions. Here, using a game theoretic framework and a 2-species model that considers various biological relationships (competition, predation, and mutualism), we compute cooperative (or joint) and non-cooperative (or separate) management equilibrium outcomes of the model and investigate the effects of the type and strength of the relationships. We find that cooperation does not always show superiority to non-cooperation in all biological interactions: (1) if and only if resources are involved in high-intensity predation relationships, cooperation can achieve a win-win scenario for ecosystem services and resource diversity; (2) for competitive resources, cooperation realizes higher ecosystem services by sacrificing resource diversity; and (3) for mutual resources, cooperation has no obvious advantage for either ecosystem services or resource evenness but can slightly improve resource abundance. Furthermore, by using a fishery model of the North California Current Marine Ecosystem with 63 species and seven fleets, we demonstrate that the theoretical results can be reproduced in real ecosystems. Therefore, effective ecosystem management should consider the interconnection between stakeholders' social relationship and resources' biological relationships.

  19. It's about time - a critique of macroecological inferences concerning plant competition

    DEFF Research Database (Denmark)

    Damgaard, Christian Frølund; Weiner, Jacob

    2017-01-01

    Several macroecological studies have used static spatial data to evaluate plant competition in natural ecosystems and to investigate its role in plant community dynamics and species assembly. The assumptions on which the inferences are based have not been consistent with ecological knowledge....... Inferences about processes, such as competition, from static data are weak. Macroecology will benefit more from dynamic data, even if limited, than from increasingly sophisticated analyses of static spatial patterns....

  20. Competitive interactions between co-occurring invaders: identifying asymmetries between two invasive crayfish species

    NARCIS (Netherlands)

    Hudina, S.; Galic, N.G.; Roessink, I.; Hock, K.

    2011-01-01

    Ecosystems today increasingly suffer invasions by multiple invasive species. Complex interactions between invasive species can have different fitness implications for each invader, which can in turn determine the future progression of their invasions and result in differential impacts on native

  1. Host-to-host variation of ecological interactions in polymicrobial infections

    International Nuclear Information System (INIS)

    Mukherjee, Sayak; Seok, Sang-Cheol; Ray, Will C; Jayaprakash, C; Vieland, Veronica J; Das, Jayajit; Weimer, Kristin E; Swords, W Edward

    2015-01-01

    Host-to-host variability with respect to interactions between microorganisms and multicellular hosts are commonly observed in infection and in homeostasis. However, the majority of mechanistic models used to analyze host–microorganism relationships, as well as most of the ecological theories proposed to explain coevolution of hosts and microbes, are based on averages across a host population. By assuming that observed variations are random and independent, these models overlook the role of differences between hosts. Here, we analyze mechanisms underlying host-to-host variations of bacterial infection kinetics, using the well characterized experimental infection model of polymicrobial otitis media (OM) in chinchillas, in combination with population dynamic models and a maximum entropy (MaxEnt) based inference scheme. We find that the nature of the interactions between bacterial species critically regulates host-to-host variations in these interactions. Surprisingly, seemingly unrelated phenomena, such as the efficiency of individual bacterial species in utilizing nutrients for growth, and the microbe-specific host immune response, can become interdependent in a host population. The latter finding suggests a potential mechanism that could lead to selection of specific strains of bacterial species during the coevolution of the host immune response and the bacterial species. (paper)

  2. Host-to-host variation of ecological interactions in polymicrobial infections

    Science.gov (United States)

    Mukherjee, Sayak; Weimer, Kristin E.; Seok, Sang-Cheol; Ray, Will C.; Jayaprakash, C.; Vieland, Veronica J.; Swords, W. Edward; Das, Jayajit

    2015-02-01

    Host-to-host variability with respect to interactions between microorganisms and multicellular hosts are commonly observed in infection and in homeostasis. However, the majority of mechanistic models used to analyze host-microorganism relationships, as well as most of the ecological theories proposed to explain coevolution of hosts and microbes, are based on averages across a host population. By assuming that observed variations are random and independent, these models overlook the role of differences between hosts. Here, we analyze mechanisms underlying host-to-host variations of bacterial infection kinetics, using the well characterized experimental infection model of polymicrobial otitis media (OM) in chinchillas, in combination with population dynamic models and a maximum entropy (MaxEnt) based inference scheme. We find that the nature of the interactions between bacterial species critically regulates host-to-host variations in these interactions. Surprisingly, seemingly unrelated phenomena, such as the efficiency of individual bacterial species in utilizing nutrients for growth, and the microbe-specific host immune response, can become interdependent in a host population. The latter finding suggests a potential mechanism that could lead to selection of specific strains of bacterial species during the coevolution of the host immune response and the bacterial species.

  3. Host-to-host variation of ecological interactions in polymicrobial infections.

    Science.gov (United States)

    Mukherjee, Sayak; Weimer, Kristin E; Seok, Sang-Cheol; Ray, Will C; Jayaprakash, C; Vieland, Veronica J; Swords, W Edward; Das, Jayajit

    2014-12-04

    Host-to-host variability with respect to interactions between microorganisms and multicellular hosts are commonly observed in infection and in homeostasis. However, the majority of mechanistic models used to analyze host-microorganism relationships, as well as most of the ecological theories proposed to explain coevolution of hosts and microbes, are based on averages across a host population. By assuming that observed variations are random and independent, these models overlook the role of differences between hosts. Here, we analyze mechanisms underlying host-to-host variations of bacterial infection kinetics, using the well characterized experimental infection model of polymicrobial otitis media (OM) in chinchillas, in combination with population dynamic models and a maximum entropy (MaxEnt) based inference scheme. We find that the nature of the interactions between bacterial species critically regulates host-to-host variations in these interactions. Surprisingly, seemingly unrelated phenomena, such as the efficiency of individual bacterial species in utilizing nutrients for growth, and the microbe-specific host immune response, can become interdependent in a host population. The latter finding suggests a potential mechanism that could lead to selection of specific strains of bacterial species during the coevolution of the host immune response and the bacterial species.

  4. Implementing and analyzing the multi-threaded LP-inference

    Science.gov (United States)

    Bolotova, S. Yu; Trofimenko, E. V.; Leschinskaya, M. V.

    2018-03-01

    The logical production equations provide new possibilities for the backward inference optimization in intelligent production-type systems. The strategy of a relevant backward inference is aimed at minimization of a number of queries to external information source (either to a database or an interactive user). The idea of the method is based on the computing of initial preimages set and searching for the true preimage. The execution of each stage can be organized independently and in parallel and the actual work at a given stage can also be distributed between parallel computers. This paper is devoted to the parallel algorithms of the relevant inference based on the advanced scheme of the parallel computations “pipeline” which allows to increase the degree of parallelism. The author also provides some details of the LP-structures implementation.

  5. Predicting species distribution and abundance responses to climate change: why it is essential to include biotic interactions across trophic levels.

    Science.gov (United States)

    Van der Putten, Wim H; Macel, Mirka; Visser, Marcel E

    2010-07-12

    Current predictions on species responses to climate change strongly rely on projecting altered environmental conditions on species distributions. However, it is increasingly acknowledged that climate change also influences species interactions. We review and synthesize literature information on biotic interactions and use it to argue that the abundance of species and the direction of selection during climate change vary depending on how their trophic interactions become disrupted. Plant abundance can be controlled by aboveground and belowground multitrophic level interactions with herbivores, pathogens, symbionts and their enemies. We discuss how these interactions may alter during climate change and the resulting species range shifts. We suggest conceptual analogies between species responses to climate warming and exotic species introduced in new ranges. There are also important differences: the herbivores, pathogens and mutualistic symbionts of range-expanding species and their enemies may co-migrate, and the continuous gene flow under climate warming can make adaptation in the expansion zone of range expanders different from that of cross-continental exotic species. We conclude that under climate change, results of altered species interactions may vary, ranging from species becoming rare to disproportionately abundant. Taking these possibilities into account will provide a new perspective on predicting species distribution under climate change.

  6. Assessment of network inference methods: how to cope with an underdetermined problem.

    Directory of Open Access Journals (Sweden)

    Caroline Siegenthaler

    Full Text Available The inference of biological networks is an active research area in the field of systems biology. The number of network inference algorithms has grown tremendously in the last decade, underlining the importance of a fair assessment and comparison among these methods. Current assessments of the performance of an inference method typically involve the application of the algorithm to benchmark datasets and the comparison of the network predictions against the gold standard or reference networks. While the network inference problem is often deemed underdetermined, implying that the inference problem does not have a (unique solution, the consequences of such an attribute have not been rigorously taken into consideration. Here, we propose a new procedure for assessing the performance of gene regulatory network (GRN inference methods. The procedure takes into account the underdetermined nature of the inference problem, in which gene regulatory interactions that are inferable or non-inferable are determined based on causal inference. The assessment relies on a new definition of the confusion matrix, which excludes errors associated with non-inferable gene regulations. For demonstration purposes, the proposed assessment procedure is applied to the DREAM 4 In Silico Network Challenge. The results show a marked change in the ranking of participating methods when taking network inferability into account.

  7. The aggregate site frequency spectrum for comparative population genomic inference.

    Science.gov (United States)

    Xue, Alexander T; Hickerson, Michael J

    2015-12-01

    Understanding how assemblages of species responded to past climate change is a central goal of comparative phylogeography and comparative population genomics, an endeavour that has increasing potential to integrate with community ecology. New sequencing technology now provides the potential to perform complex demographic inference at unprecedented resolution across assemblages of nonmodel species. To this end, we introduce the aggregate site frequency spectrum (aSFS), an expansion of the site frequency spectrum to use single nucleotide polymorphism (SNP) data sets collected from multiple, co-distributed species for assemblage-level demographic inference. We describe how the aSFS is constructed over an arbitrary number of independent population samples and then demonstrate how the aSFS can differentiate various multispecies demographic histories under a wide range of sampling configurations while allowing effective population sizes and expansion magnitudes to vary independently. We subsequently couple the aSFS with a hierarchical approximate Bayesian computation (hABC) framework to estimate degree of temporal synchronicity in expansion times across taxa, including an empirical demonstration with a data set consisting of five populations of the threespine stickleback (Gasterosteus aculeatus). Corroborating what is generally understood about the recent postglacial origins of these populations, the joint aSFS/hABC analysis strongly suggests that the stickleback data are most consistent with synchronous expansion after the Last Glacial Maximum (posterior probability = 0.99). The aSFS will have general application for multilevel statistical frameworks to test models involving assemblages and/or communities, and as large-scale SNP data from nonmodel species become routine, the aSFS expands the potential for powerful next-generation comparative population genomic inference. © 2015 The Authors. Molecular Ecology Published by John Wiley & Sons Ltd.

  8. Species Coexistence in Nitrifying Chemostats: A Model of Microbial Interactions

    Directory of Open Access Journals (Sweden)

    Maxime Dumont

    2016-12-01

    Full Text Available In a previous study, the two nitrifying functions (ammonia oxidizing bacteria (AOB or nitrite-oxidizing bacteria (NOB of a nitrification reactor—operated continuously over 525 days with varying inputs—were assigned using a mathematical modeling approach together with the monitoring of bacterial phylotypes. Based on these theoretical identifications, we develop here a chemostat model that does not explicitly include only the resources’ dynamics (different forms of soluble nitrogen but also explicitly takes into account microbial inter- and intra-species interactions for the four dominant phylotypes detected in the chemostat. A comparison of the models obtained with and without interactions has shown that such interactions permit the coexistence of two competing ammonium-oxidizing bacteria and two competing nitrite-oxidizing bacteria in competition for ammonium and nitrite, respectively. These interactions are analyzed and discussed.

  9. Interactions among species in a tri-trophic system: the influence of ...

    African Journals Online (AJOL)

    BioMAP

    persistence/abundance are affected by more than two interacting species (Begon ... importance of methodology in revealing why an endangered population is ..... closely related butterfly which also oviposits on thyme buds) failed because the ...

  10. Probability of detecting marine predator-prey and species interactions using novel hybrid acoustic transmitter-receiver tags.

    Directory of Open Access Journals (Sweden)

    Laurie L Baker

    Full Text Available Understanding the nature of inter-specific and conspecific interactions in the ocean is challenging because direct observation is usually impossible. The development of dual transmitter/receivers, Vemco Mobile Transceivers (VMT, and satellite-linked (e.g. GPS tags provides a unique opportunity to better understand between and within species interactions in space and time. Quantifying the uncertainty associated with detecting a tagged animal, particularly under varying field conditions, is vital for making accurate biological inferences when using VMTs. We evaluated the detection efficiency of VMTs deployed on grey seals, Halichoerus grypus, off Sable Island (NS, Canada in relation to environmental characteristics and seal behaviour using generalized linear models (GLM to explore both post-processed detection data and summarized raw VMT data. When considering only post-processed detection data, only about half of expected detections were recorded at best even when two VMT-tagged seals were estimated to be within 50-200 m of one another. At a separation of 400 m, only about 15% of expected detections were recorded. In contrast, when incomplete transmissions from the summarized raw data were also considered, the ratio of complete transmission to complete and incomplete transmissions was about 70% for distances ranging from 50-1000 m, with a minimum of around 40% at 600 m and a maximum of about 85% at 50 m. Distance between seals, wind stress, and depth were the most important predictors of detection efficiency. Access to the raw VMT data allowed us to focus on the physical and environmental factors that limit a transceiver's ability to resolve a transmitter's identity.

  11. Causal inference based on counterfactuals

    Directory of Open Access Journals (Sweden)

    Höfler M

    2005-09-01

    Full Text Available Abstract Background The counterfactual or potential outcome model has become increasingly standard for causal inference in epidemiological and medical studies. Discussion This paper provides an overview on the counterfactual and related approaches. A variety of conceptual as well as practical issues when estimating causal effects are reviewed. These include causal interactions, imperfect experiments, adjustment for confounding, time-varying exposures, competing risks and the probability of causation. It is argued that the counterfactual model of causal effects captures the main aspects of causality in health sciences and relates to many statistical procedures. Summary Counterfactuals are the basis of causal inference in medicine and epidemiology. Nevertheless, the estimation of counterfactual differences pose several difficulties, primarily in observational studies. These problems, however, reflect fundamental barriers only when learning from observations, and this does not invalidate the counterfactual concept.

  12. Barcoding and Phylogenetic Inferences in Nine Mugilid Species (Pisces, Mugiliformes

    Directory of Open Access Journals (Sweden)

    Neonila Polyakova

    2013-10-01

    Full Text Available Accurate identification of fish and fish products, from eggs to adults, is important in many areas. Grey mullets of the family Mugilidae are distributed worldwide and inhabit marine, estuarine, and freshwater environments in all tropical and temperate regions. Various Mugilid species are commercially important species in fishery and aquaculture of many countries. For the present study we have chosen two Mugilid genes with different phylogenetic signals: relatively variable mitochondrial cytochrome oxidase subunit I (COI and conservative nuclear rhodopsin (RHO. We examined their diversity within and among 9 Mugilid species belonging to 4 genera, many of which have been examined from multiple specimens, with the goal of determining whether DNA barcoding can achieve unambiguous species recognition of Mugilid species. The data obtained showed that information based on COI sequences was diagnostic not only for species-level identification but also for recognition of intraspecific units, e.g., allopatric populations of circumtropical Mugil cephalus, or even native and acclimatized specimens of Chelon haematocheila. All RHO sequences appeared strictly species specific. Based on the data obtained, we conclude that COI, as well as RHO sequencing can be used to unambiguously identify fish species. Topologies of phylogeny based on RHO and COI sequences coincided with each other, while together they had a good phylogenetic signal.

  13. Protein Inference from the Integration of Tandem MS Data and Interactome Networks.

    Science.gov (United States)

    Zhong, Jiancheng; Wang, Jianxing; Ding, Xiaojun; Zhang, Zhen; Li, Min; Wu, Fang-Xiang; Pan, Yi

    2017-01-01

    Since proteins are digested into a mixture of peptides in the preprocessing step of tandem mass spectrometry (MS), it is difficult to determine which specific protein a shared peptide belongs to. In recent studies, besides tandem MS data and peptide identification information, some other information is exploited to infer proteins. Different from the methods which first use only tandem MS data to infer proteins and then use network information to refine them, this study proposes a protein inference method named TMSIN, which uses interactome networks directly. As two interacting proteins should co-exist, it is reasonable to assume that if one of the interacting proteins is confidently inferred in a sample, its interacting partners should have a high probability in the same sample, too. Therefore, we can use the neighborhood information of a protein in an interactome network to adjust the probability that the shared peptide belongs to the protein. In TMSIN, a multi-weighted graph is constructed by incorporating the bipartite graph with interactome network information, where the bipartite graph is built with the peptide identification information. Based on multi-weighted graphs, TMSIN adopts an iterative workflow to infer proteins. At each iterative step, the probability that a shared peptide belongs to a specific protein is calculated by using the Bayes' law based on the neighbor protein support scores of each protein which are mapped by the shared peptides. We carried out experiments on yeast data and human data to evaluate the performance of TMSIN in terms of ROC, q-value, and accuracy. The experimental results show that AUC scores yielded by TMSIN are 0.742 and 0.874 in yeast dataset and human dataset, respectively, and TMSIN yields the maximum number of true positives when q-value less than or equal to 0.05. The overlap analysis shows that TMSIN is an effective complementary approach for protein inference.

  14. Estimating the effect of the reorganization of interactions on the adaptability of species to changing environments.

    Science.gov (United States)

    Cenci, Simone; Montero-Castaño, Ana; Saavedra, Serguei

    2018-01-21

    A major challenge in community ecology is to understand how species respond to environmental changes. Previous studies have shown that the reorganization of interactions among co-occurring species can modulate their chances to adapt to novel environmental conditions. Moreover, empirical evidence has shown that these ecological dynamics typically facilitate the persistence of groups of species rather than entire communities. However, so far, we have no systematic methodology to identify those groups of species with the highest or lowest chances to adapt to new environments through a reorganization of their interactions. Yet, this could prove extremely valuable for developing new conservation strategies. Here, we introduce a theoretical framework to estimate the effect of the reorganization of interactions on the adaptability of a group of species, within a community, to novel environmental conditions. We introduce the concept of the adaptation space of a group of species based on a feasibility analysis of a population dynamics model. We define the adaptation space of a group as the set of environmental conditions that can be made compatible with its persistence thorough the reorganization of interactions among species within the group. The larger the adaptation space of a group, the larger its likelihood to adapt to a novel environment. We show that the interactions in the community outside a group can act as structural constraints and be used to quantitatively compare the size of the adaptation space among different groups of species within a community. To test our theoretical framework, we perform a data analysis on several pairs of natural and artificially perturbed ecological communities. Overall, we find that the groups of species present in both control and perturbed communities are among the ones with the largest adaptation space. We believe that the results derived from our framework point out towards new directions to understand and estimate the

  15. A canonical correlation analysis-based dynamic bayesian network prior to infer gene regulatory networks from multiple types of biological data.

    Science.gov (United States)

    Baur, Brittany; Bozdag, Serdar

    2015-04-01

    One of the challenging and important computational problems in systems biology is to infer gene regulatory networks (GRNs) of biological systems. Several methods that exploit gene expression data have been developed to tackle this problem. In this study, we propose the use of copy number and DNA methylation data to infer GRNs. We developed an algorithm that scores regulatory interactions between genes based on canonical correlation analysis. In this algorithm, copy number or DNA methylation variables are treated as potential regulator variables, and expression variables are treated as potential target variables. We first validated that the canonical correlation analysis method is able to infer true interactions in high accuracy. We showed that the use of DNA methylation or copy number datasets leads to improved inference over steady-state expression. Our results also showed that epigenetic and structural information could be used to infer directionality of regulatory interactions. Additional improvements in GRN inference can be gleaned from incorporating the result in an informative prior in a dynamic Bayesian algorithm. This is the first study that incorporates copy number and DNA methylation into an informative prior in dynamic Bayesian framework. By closely examining top-scoring interactions with different sources of epigenetic or structural information, we also identified potential novel regulatory interactions.

  16. Fluxes of chemically reactive species inferred from mean concentration measurements

    NARCIS (Netherlands)

    Galmarini, S.; Vilà-Guerau De Arellano, J.; Duyzer, J.H.

    1997-01-01

    A method is presented for the calculation of the fluxes of chemically reactive species on the basis of routine measurements of meteorological variables and chemical species. The method takes explicity into account the influence of chemical reactions on the fluxes of the species. As a demonstration

  17. It's About Time: A Critique of Macroecological Inferences Concerning Plant Competition.

    Science.gov (United States)

    Damgaard, Christian; Weiner, Jacob

    2017-02-01

    Several macroecological studies have used static spatial data to evaluate plant competition in natural ecosystems and to investigate its role in plant community dynamics and species assembly. The assumptions on which the inferences are based have not been consistent with ecological knowledge. Inferences about processes, such as competition, from static data are weak. Macroecology will benefit more from dynamic data, even if limited, than from increasingly sophisticated analyses of static spatial patterns. Copyright © 2016 Elsevier Ltd. All rights reserved.

  18. Separation of methyltin species from inorganic tin, and their interactions with humates in natural waters

    International Nuclear Information System (INIS)

    Omar, M.; Bowen, H.J.M.

    1982-01-01

    Tin(II) and tin(IV) are absorbed from aqueous solutions by Sephadex G-25 gel, from which they can be eluted by humates or fulvates, with which they interact more strongly. Methyltin species are not absorbed by Sephadex G-25, and so can be separated from inorganic tin. Both inorganic tin and methyltin species in natural waters at pH 7.4 can be quantitatively retained by passing through small columns of Chelex-100 resin: the methyltin species can then be washed off the resin with 4M nitric acid. Trimethyltin chloride 113 Sn in water scarcely interacts with fulvates, humates, kaolinite or montmorillonite but is absorbed by Sphagnum peat. Dimethyltin dichloride- 113 Sn reacts significantly with all the above materials after 2 hours equilibration. Methyltin trichloride- 113 Sn interacts weakly in alkaline solutions. (author)

  19. Anchoring quartet-based phylogenetic distances and applications to species tree reconstruction.

    Science.gov (United States)

    Sayyari, Erfan; Mirarab, Siavash

    2016-11-11

    Inferring species trees from gene trees using the coalescent-based summary methods has been the subject of much attention, yet new scalable and accurate methods are needed. We introduce DISTIQUE, a new statistically consistent summary method for inferring species trees from gene trees under the coalescent model. We generalize our results to arbitrary phylogenetic inference problems; we show that two arbitrarily chosen leaves, called anchors, can be used to estimate relative distances between all other pairs of leaves by inferring relevant quartet trees. This results in a family of distance-based tree inference methods, with running times ranging between quadratic to quartic in the number of leaves. We show in simulated studies that DISTIQUE has comparable accuracy to leading coalescent-based summary methods and reduced running times.

  20. Bayesian network model for identification of pathways by integrating protein interaction with genetic interaction data.

    Science.gov (United States)

    Fu, Changhe; Deng, Su; Jin, Guangxu; Wang, Xinxin; Yu, Zu-Guo

    2017-09-21

    Molecular interaction data at proteomic and genetic levels provide physical and functional insights into a molecular biosystem and are helpful for the construction of pathway structures complementarily. Despite advances in inferring biological pathways using genetic interaction data, there still exists weakness in developed models, such as, activity pathway networks (APN), when integrating the data from proteomic and genetic levels. It is necessary to develop new methods to infer pathway structure by both of interaction data. We utilized probabilistic graphical model to develop a new method that integrates genetic interaction and protein interaction data and infers exquisitely detailed pathway structure. We modeled the pathway network as Bayesian network and applied this model to infer pathways for the coherent subsets of the global genetic interaction profiles, and the available data set of endoplasmic reticulum genes. The protein interaction data were derived from the BioGRID database. Our method can accurately reconstruct known cellular pathway structures, including SWR complex, ER-Associated Degradation (ERAD) pathway, N-Glycan biosynthesis pathway, Elongator complex, Retromer complex, and Urmylation pathway. By comparing N-Glycan biosynthesis pathway and Urmylation pathway identified from our approach with that from APN, we found that our method is able to overcome its weakness (certain edges are inexplicable). According to underlying protein interaction network, we defined a simple scoring function that only adopts genetic interaction information to avoid the balance difficulty in the APN. Using the effective stochastic simulation algorithm, the performance of our proposed method is significantly high. We developed a new method based on Bayesian network to infer detailed pathway structures from interaction data at proteomic and genetic levels. The results indicate that the developed method performs better in predicting signaling pathways than previously

  1. Inferring the conservative causal core of gene regulatory networks

    Directory of Open Access Journals (Sweden)

    Emmert-Streib Frank

    2010-09-01

    Full Text Available Abstract Background Inferring gene regulatory networks from large-scale expression data is an important problem that received much attention in recent years. These networks have the potential to gain insights into causal molecular interactions of biological processes. Hence, from a methodological point of view, reliable estimation methods based on observational data are needed to approach this problem practically. Results In this paper, we introduce a novel gene regulatory network inference (GRNI algorithm, called C3NET. We compare C3NET with four well known methods, ARACNE, CLR, MRNET and RN, conducting in-depth numerical ensemble simulations and demonstrate also for biological expression data from E. coli that C3NET performs consistently better than the best known GRNI methods in the literature. In addition, it has also a low computational complexity. Since C3NET is based on estimates of mutual information values in conjunction with a maximization step, our numerical investigations demonstrate that our inference algorithm exploits causal structural information in the data efficiently. Conclusions For systems biology to succeed in the long run, it is of crucial importance to establish methods that extract large-scale gene networks from high-throughput data that reflect the underlying causal interactions among genes or gene products. Our method can contribute to this endeavor by demonstrating that an inference algorithm with a neat design permits not only a more intuitive and possibly biological interpretation of its working mechanism but can also result in superior results.

  2. Inferring the conservative causal core of gene regulatory networks.

    Science.gov (United States)

    Altay, Gökmen; Emmert-Streib, Frank

    2010-09-28

    Inferring gene regulatory networks from large-scale expression data is an important problem that received much attention in recent years. These networks have the potential to gain insights into causal molecular interactions of biological processes. Hence, from a methodological point of view, reliable estimation methods based on observational data are needed to approach this problem practically. In this paper, we introduce a novel gene regulatory network inference (GRNI) algorithm, called C3NET. We compare C3NET with four well known methods, ARACNE, CLR, MRNET and RN, conducting in-depth numerical ensemble simulations and demonstrate also for biological expression data from E. coli that C3NET performs consistently better than the best known GRNI methods in the literature. In addition, it has also a low computational complexity. Since C3NET is based on estimates of mutual information values in conjunction with a maximization step, our numerical investigations demonstrate that our inference algorithm exploits causal structural information in the data efficiently. For systems biology to succeed in the long run, it is of crucial importance to establish methods that extract large-scale gene networks from high-throughput data that reflect the underlying causal interactions among genes or gene products. Our method can contribute to this endeavor by demonstrating that an inference algorithm with a neat design permits not only a more intuitive and possibly biological interpretation of its working mechanism but can also result in superior results.

  3. Using Approximate Bayesian Computation to infer sex ratios from acoustic data.

    Science.gov (United States)

    Lehnen, Lisa; Schorcht, Wigbert; Karst, Inken; Biedermann, Martin; Kerth, Gerald; Puechmaille, Sebastien J

    2018-01-01

    Population sex ratios are of high ecological relevance, but are challenging to determine in species lacking conspicuous external cues indicating their sex. Acoustic sexing is an option if vocalizations differ between sexes, but is precluded by overlapping distributions of the values of male and female vocalizations in many species. A method allowing the inference of sex ratios despite such an overlap will therefore greatly increase the information extractable from acoustic data. To meet this demand, we developed a novel approach using Approximate Bayesian Computation (ABC) to infer the sex ratio of populations from acoustic data. Additionally, parameters characterizing the male and female distribution of acoustic values (mean and standard deviation) are inferred. This information is then used to probabilistically assign a sex to a single acoustic signal. We furthermore develop a simpler means of sex ratio estimation based on the exclusion of calls from the overlap zone. Applying our methods to simulated data demonstrates that sex ratio and acoustic parameter characteristics of males and females are reliably inferred by the ABC approach. Applying both the ABC and the exclusion method to empirical datasets (echolocation calls recorded in colonies of lesser horseshoe bats, Rhinolophus hipposideros) provides similar sex ratios as molecular sexing. Our methods aim to facilitate evidence-based conservation, and to benefit scientists investigating ecological or conservation questions related to sex- or group specific behaviour across a wide range of organisms emitting acoustic signals. The developed methodology is non-invasive, low-cost and time-efficient, thus allowing the study of many sites and individuals. We provide an R-script for the easy application of the method and discuss potential future extensions and fields of applications. The script can be easily adapted to account for numerous biological systems by adjusting the type and number of groups to be

  4. Matrix dimensions bias demographic inferences: implications for comparative plant demography.

    Science.gov (United States)

    Salguero-Gómez, Roberto; Plotkin, Joshua B

    2010-12-01

    While the wealth of projection matrices in plant demography permits comparative studies, variation in matrix dimensions complicates interspecific comparisons. Collapsing matrices to a common dimension may facilitate such comparisons but may also bias the inferred demographic parameters. Here we examine how matrix dimension affects inferred demographic elasticities and how different collapsing criteria perform. We analyzed 13 x 13 matrices representing nine plant species, collapsing these matrices (i) into even 7 x 7, 5 x 5, 4 x 4, and 3 x 3 matrices and (ii) into 5 x 5 matrices using different criteria. Stasis and fecundity elasticities increased when matrix dimension was reduced, whereas those of progression and retrogression decreased. We suggest a collapsing criterion that minimizes dissimilarities between the original- and collapsed-matrix elasticities and apply it to 66 plant species to study how life span and growth form influence the relationship between matrix dimension and elasticities. Our analysis demonstrates that (i) projection matrix dimension has significant effects on inferred demographic parameters, (ii) there are better-performing methods than previously suggested for standardizing matrix dimension, and (iii) herbaceous perennial projection matrices are particularly sensitive to changes in matrix dimensionality. For comparative demographic studies, we recommend normalizing matrices to a common dimension by collapsing higher classes and leaving the first few classes unaltered.

  5. Metis: A Pure Metropolis Markov Chain Monte Carlo Bayesian Inference Library

    Energy Technology Data Exchange (ETDEWEB)

    Bates, Cameron Russell [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Mckigney, Edward Allen [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2018-01-09

    The use of Bayesian inference in data analysis has become the standard for large scienti c experiments [1, 2]. The Monte Carlo Codes Group(XCP-3) at Los Alamos has developed a simple set of algorithms currently implemented in C++ and Python to easily perform at-prior Markov Chain Monte Carlo Bayesian inference with pure Metropolis sampling. These implementations are designed to be user friendly and extensible for customization based on speci c application requirements. This document describes the algorithmic choices made and presents two use cases.

  6. Inferring the demographic history of European Ficedula flycatcher populations

    Directory of Open Access Journals (Sweden)

    Backström Niclas

    2013-01-01

    Full Text Available Abstract Background Inference of population and species histories and population stratification using genetic data is important for discriminating between different speciation scenarios and for correct interpretation of genome scans for signs of adaptive evolution and trait association. Here we use data from 24 intronic loci re-sequenced in population samples of two closely related species, the pied flycatcher and the collared flycatcher. Results We applied Isolation-Migration models, assignment analyses and estimated the genetic differentiation and diversity between species and between populations within species. The data indicate a divergence time between the species of Conclusions Our results provide further evidence for a divergence process where different genomic regions may be at different stages of speciation. We also conclude that forthcoming analyses of genotype-phenotype relations in these ecological model species should be designed to take population stratification into account.

  7. Hierarchical Active Inference: A Theory of Motivated Control.

    Science.gov (United States)

    Pezzulo, Giovanni; Rigoli, Francesco; Friston, Karl J

    2018-04-01

    Motivated control refers to the coordination of behaviour to achieve affectively valenced outcomes or goals. The study of motivated control traditionally assumes a distinction between control and motivational processes, which map to distinct (dorsolateral versus ventromedial) brain systems. However, the respective roles and interactions between these processes remain controversial. We offer a novel perspective that casts control and motivational processes as complementary aspects - goal propagation and prioritization, respectively - of active inference and hierarchical goal processing under deep generative models. We propose that the control hierarchy propagates prior preferences or goals, but their precision is informed by the motivational context, inferred at different levels of the motivational hierarchy. The ensuing integration of control and motivational processes underwrites action and policy selection and, ultimately, motivated behaviour, by enabling deep inference to prioritize goals in a context-sensitive way. Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.

  8. Multi-Agent Inference in Social Networks: A Finite Population Learning Approach.

    Science.gov (United States)

    Fan, Jianqing; Tong, Xin; Zeng, Yao

    When people in a society want to make inference about some parameter, each person may want to use data collected by other people. Information (data) exchange in social networks is usually costly, so to make reliable statistical decisions, people need to trade off the benefits and costs of information acquisition. Conflicts of interests and coordination problems will arise in the process. Classical statistics does not consider people's incentives and interactions in the data collection process. To address this imperfection, this work explores multi-agent Bayesian inference problems with a game theoretic social network model. Motivated by our interest in aggregate inference at the societal level, we propose a new concept, finite population learning , to address whether with high probability, a large fraction of people in a given finite population network can make "good" inference. Serving as a foundation, this concept enables us to study the long run trend of aggregate inference quality as population grows.

  9. Aggregation Behaviors of a Two-Species System with Lose-Lose Interactions

    International Nuclear Information System (INIS)

    Song Meixia; Lin Zhenquan; Li Xiaodong; Ke Jianhong

    2010-01-01

    We propose an aggregation evolution model of two-species (A- and B-species) aggregates to study the prevalent aggregation phenomena in social and economic systems. In this model, A- and B-species aggregates perform self-exchange-driven growths with the exchange rate kernels K (k,l) = Kkl and L(k,l) = Lkl, respectively, and the two species aggregates perform self-birth processes with the rate kernels J 1 (k) = J 1 k and J 2 (k) = J 2 k, and meanwhile the interaction between the aggregates of different species A and B causes a lose-lose scheme with the rate kernel H(k,l) = Hkl. Based on the mean-field theory, we investigated the evolution behaviors of the two species aggregates to study the competitions among above three aggregate evolution schemes on the distinct initial monomer concentrations A 0 and B 0 of the two species. The results show that the evolution behaviors of A- and B-species are crucially dominated by the competition between the two self-birth processes, and the initial monomer concentrations A 0 and B 0 play important roles, while the lose-lose scheme play important roles in some special cases. (interdisciplinary physics and related areas of science and technology)

  10. Species traits and their non-additive interactions control the water economy of bryophyte cushions.

    NARCIS (Netherlands)

    Michel, P.; Lee, W.G.; During, H.J.; Cornelissen, J.H.C.; van der Putten, W.H.

    2012-01-01

    1. Ecological processes in mixed-species assemblages are not always an additive function of those in monocultures. In areas with high ground cover of bryophytes, renowned for their considerable water retention capacity, non-additive interactions in mixed-species cushions could play a key role in the

  11. Predator-prey interactions as macro-scale drivers of species diversity in mammals

    DEFF Research Database (Denmark)

    Sandom, Christopher James; Sandel, Brody Steven; Dalby, Lars

    Background/Question/Methods Understanding the importance of predator-prey interactions for species diversity is a central theme in ecology, with fundamental consequences for predicting the responses of ecosystems to land use and climate change. We assessed the relative support for different...... mechanistic drivers of mammal species richness at macro-scales for two trophic levels: predators and prey. To disentangle biotic (i.e. functional predator-prey interactions) from abiotic (i.e. environmental) and bottom-up from top-down determinants we considered three hypotheses: 1) environmental factors...... that determine ecosystem productivity drive prey and predator richness (the productivity hypothesis, abiotic, bottom-up), 2) consumer richness is driven by resource diversity (the resource diversity hypothesis, biotic, bottom-up) and 3) consumers drive richness of their prey (the top-down hypothesis, biotic, top...

  12. Is Drosophila-microbe association species-specific or region specific? A study undertaken involving six Indian Drosophila species.

    Science.gov (United States)

    Singhal, Kopal; Khanna, Radhika; Mohanty, Sujata

    2017-06-01

    The present work aims to identify the microbial diversity associated with six Indian Drosophila species using next generation sequencing (NGS) technology and to discover the nature of their distribution across species and eco-geographic regions. Whole fly gDNA of six Drosophila species were used to generate sequences in an Illumina platform using NGS technology. De novo based assembled raw reads were blasted against the NR database of NCBI using BLASTn for identification of their bacterial loads. We have tried to include Drosophila species from different taxonomical groups and subgroups and from three different eco-climatic regions India; four species belong to Central India, while the rest two, D. melanogaster and D. ananassae, belong to West and South India to determine both their species-wise and region-wide distribution. We detected the presence of 33 bacterial genera across all six study species, predominated by the class Proteobacteria. Amongst all, D. melanogaster was found to be the most diverse by carrying around 85% of the bacterial diversity. Our findings infer both species-specific and environment-specific nature of the bacterial species inhabiting the Drosophila host. Though the present results are consistent with most of the earlier studies, they also remain incoherent with some. The present study outcome on the host-bacteria association and their species specific adaptation may provide some insight to understand the host-microbial interactions and the phenotypic implications of microbes on the host physiology. The knowledge gained may be importantly applied into the recent insect and pest population control strategy going to implement through gut microflora in India and abroad.

  13. Arabidopsis thaliana polyamine content is modified by the interaction with different Trichoderma species.

    Science.gov (United States)

    Salazar-Badillo, Fatima Berenice; Sánchez-Rangel, Diana; Becerra-Flora, Alicia; López-Gómez, Miguel; Nieto-Jacobo, Fernanda; Mendoza-Mendoza, Artemio; Jiménez-Bremont, Juan Francisco

    2015-10-01

    Plants are associated with a wide range of microorganisms throughout their life cycle, and some interactions result on plant benefits. Trichoderma species are plant beneficial fungi that enhance plant growth and development, contribute to plant nutrition and induce defense responses. Nevertheless, the molecules involved in these beneficial effects still need to be identify. Polyamines are ubiquitous molecules implicated in plant growth and development, and in the establishment of plant microbe interactions. In this study, we assessed the polyamine profile in Arabidopsis plants during the interaction with Trichoderma virens and Trichoderma atroviride, using a system that allows direct plant-fungal contact or avoids their physical interaction (split system). The plantlets that grew in the split system exhibited higher biomass than the ones in direct contact with Trichoderma species. After 3 days of interaction, a significant decrease in Arabidopsis polyamine levels was observed in both systems (direct contact and split). After 5 days of interaction polyamine levels were increased. The highest levels were observed with T. atroviride (split system), and with T. virens (direct contact). The expression levels of Arabidopsis ADC1 and ADC2 genes during the interaction with the fungi were also assessed. We observed a time dependent regulation of ADC1 and ADC2 genes, which correlates with polyamine levels. Our data show an evident change in polyamine profile during Arabidopsis - Trichoderma interaction, accompanied by evident alterations in plant root architecture. Polyamines could be involved in the changes undergone by plant during the interaction with this beneficial fungus. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

  14. The impact of phenotypic and molecular data on the inference of Colletotrichum diversity associated with Musa.

    Science.gov (United States)

    Vieira, Willie A S; Lima, Waléria G; Nascimento, Eduardo S; Michereff, Sami J; Câmara, Marcos P S; Doyle, Vinson P

    2017-01-01

    Developing a comprehensive and reliable taxonomy for the Colletotrichum gloeosporioides species complex will require adopting data standards on the basis of an understanding of how methodological choices impact morphological evaluations and phylogenetic inference. We explored the impact of methodological choices in a morphological and molecular evaluation of Colletotrichum species associated with banana in Brazil. The choice of alignment filtering algorithm has a significant impact on topological inference and the retention of phylogenetically informative sites. Similarly, the choice of phylogenetic marker affects the delimitation of species boundaries, particularly if low phylogenetic signal is confounded with strong discordance, and inference of the species tree from multiple-gene trees. According to both phylogenetic informativeness profiling and Bayesian concordance analyses, the most informative loci are DNA lyase (APN2), intergenic spacer (IGS) between DNA lyase and the mating-type locus MAT1-2-1 (APN2/MAT-IGS), calmodulin (CAL), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), glutamine synthetase (GS), β-tubulin (TUB2), and a new marker, the intergenic spacer between GAPDH and an hypothetical protein (GAP2-IGS). Cornmeal agar minimizes the variance in conidial dimensions compared with potato dextrose agar and synthetic nutrient-poor agar, such that species are more readily distinguishable based on phenotypic differences. We apply these insights to investigate the diversity of Colletotrichum species associated with banana anthracnose in Brazil and report C. musae, C. tropicale, C. theobromicola, and C. siamense in association with banana anthracnose. One lineage did not cluster with any previously described species and is described here as C. chrysophilum.

  15. Inferring time-varying network topologies from gene expression data.

    Science.gov (United States)

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

    2007-01-01

    Most current methods for gene regulatory network identification lead to the inference of steady-state networks, that is, networks prevalent over all times, a hypothesis which has been challenged. There has been a need to infer and represent networks in a dynamic, that is, time-varying fashion, in order to account for different cellular states affecting the interactions amongst genes. In this work, we present an approach, regime-SSM, to understand gene regulatory networks within such a dynamic setting. The approach uses a clustering method based on these underlying dynamics, followed by system identification using a state-space model for each learnt cluster--to infer a network adjacency matrix. We finally indicate our results on the mouse embryonic kidney dataset as well as the T-cell activation-based expression dataset and demonstrate conformity with reported experimental evidence.

  16. Inter and intra-guild interactions in egg parasitoid species of the soybean stink bug complex

    Directory of Open Access Journals (Sweden)

    Sujii Edison Ryoiti

    2002-01-01

    Full Text Available The objective of this research was to evaluate the parasitism behavior of Telenomus podisi Ashmead, Trissolcus basalis (Wollaston e Trissolcus urichi Crawford (Hymenoptera: Scelionidae on eggs of Nezara viridula L., Euschistus heros F., Piezodorus guildinii Westwood and Acrosternum aseadum Rolston (Heteroptera: Pentatomidae, in no choice and multiple choice experiments. For all parasitoid species, the results demonstrated the existence of a main host species that maximizes the reproductive success. The competitive interactions among the parasitoid species were investigated in experiments of sequential and simultaneous release of different combinations of parasitoid pairs on the hosts N. viridula, E. heros and A. aseadum. Exploitative competition was observed for egg batches at the genus level (Telenomus vs. Trissolcus and interference competition at the species level (T. basalis vs. T. urichi. Trissolcus urichi was the most aggressive species, interfering with the parasitism of T. basalis. Generally, T. basalis showed an opportunistic behavior trying to parasitise eggs after T. urichi had abandoned the egg batch. The selection of parasitoid species for use in augmentative biological control programs should take into account the diversity of pentatomids present in soybean in addition to the interactions among the different species of parasitoids.

  17. Assessing species boundaries using multilocus species delimitation in a morphologically conserved group of neotropical freshwater fishes, the Poecilia sphenops species complex (Poeciliidae.

    Directory of Open Access Journals (Sweden)

    Justin C Bagley

    Full Text Available Accurately delimiting species is fundamentally important for understanding species diversity and distributions and devising effective strategies to conserve biodiversity. However, species delimitation is problematic in many taxa, including 'non-adaptive radiations' containing morphologically cryptic lineages. Fortunately, coalescent-based species delimitation methods hold promise for objectively estimating species limits in such radiations, using multilocus genetic data. Using coalescent-based approaches, we delimit species and infer evolutionary relationships in a morphologically conserved group of Central American freshwater fishes, the Poecilia sphenops species complex. Phylogenetic analyses of multiple genetic markers (sequences of two mitochondrial DNA genes and five nuclear loci from 10/15 species and genetic lineages recognized in the group support the P. sphenops species complex as monophyletic with respect to outgroups, with eight mitochondrial 'major-lineages' diverged by ≥2% pairwise genetic distances. From general mixed Yule-coalescent models, we discovered (conservatively 10 species within our concatenated mitochondrial DNA dataset, 9 of which were strongly supported by subsequent multilocus Bayesian species delimitation and species tree analyses. Results suggested species-level diversity is underestimated or overestimated by at least ~15% in different lineages in the complex. Nonparametric statistics and coalescent simulations indicate genealogical discordance among our gene tree results has mainly derived from interspecific hybridization in the nuclear genome. However, mitochondrial DNA show little evidence for introgression, and our species delimitation results appear robust to effects of this process. Overall, our findings support the utility of combining multiple lines of genetic evidence and broad phylogeographical sampling to discover and validate species using coalescent-based methods. Our study also highlights the

  18. A caveat regarding diatom-inferred nitrogen concentrations in oligotrophic lakes

    Science.gov (United States)

    Arnett, Heather A.; Saros, Jasmine E.; Mast, M. Alisa

    2012-01-01

    Atmospheric deposition of reactive nitrogen (Nr) has enriched oligotrophic lakes with nitrogen (N) in many regions of the world and elicited dramatic changes in diatom community structure. The lakewater concentrations of nitrate that cause these community changes remain unclear, raising interest in the development of diatom-based transfer functions to infer nitrate. We developed a diatom calibration set using surface sediment samples from 46 high-elevation lakes across the Rocky Mountains of the western US, a region spanning an N deposition gradient from very low to moderate levels (phosphorus, and hypolimnetic water temperature were related to diatom distributions. A transfer function was developed for nitrate and applied to a sedimentary diatom profile from Heart Lake in the central Rockies. The model coefficient of determination (bootstrapping validation) of 0.61 suggested potential for diatom-inferred reconstructions of lakewater nitrate concentrations over time, but a comparison of observed versus diatom-inferred nitrate values revealed the poor performance of this model at low nitrate concentrations. Resource physiology experiments revealed that nitrogen requirements of two key taxa were opposite to nitrate optima defined in the transfer function. Our data set reveals two underlying ecological constraints that impede the development of nitrate transfer functions in oligotrophic lakes: (1) even in lakes with nitrate concentrations below quantification (<1 μg L−1), diatom assemblages were already dominated by species indicative of moderate N enrichment; (2) N-limited oligotrophic lakes switch to P limitation after receiving only modest inputs of reactive N, shifting the controls on diatom species changes along the length of the nitrate gradient. These constraints suggest that quantitative inferences of nitrate from diatom assemblages will likely require experimental approaches.

  19. Ulysses - an application for the projection of molecular interactions across species.

    Science.gov (United States)

    Kemmer, Danielle; Huang, Yong; Shah, Sohrab P; Lim, Jonathan; Brumm, Jochen; Yuen, Macaire M S; Ling, John; Xu, Tao; Wasserman, Wyeth W; Ouellette, B F Francis

    2005-01-01

    We developed Ulysses as a user-oriented system that uses a process called Interolog Analysis for the parallel analysis and display of protein interactions detected in various species. Ulysses was designed to perform such Interolog Analysis by the projection of model organism interaction data onto homologous human proteins, and thus serves as an accelerator for the analysis of uncharacterized human proteins. The relevance of projections was assessed and validated against published reference collections. All source code is freely available, and the Ulysses system can be accessed via a web interface http://www.cisreg.ca/ulysses.

  20. Climate-induced changes in lake ecosystem structure inferred from coupled neo- and paleoecological approaches

    Science.gov (United States)

    Saros, Jasmine E.; Stone, Jeffery R.; Pederson, Gregory T.; Slemmons, Krista; Spanbauer, Trisha; Schliep, Anna; Cahl, Douglas; Williamson, Craig E.; Engstrom, Daniel R.

    2015-01-01

    Over the 20th century, surface water temperatures have increased in many lake ecosystems around the world, but long-term trends in the vertical thermal structure of lakes remain unclear, despite the strong control that thermal stratification exerts on the biological response of lakes to climate change. Here we used both neo- and paleoecological approaches to develop a fossil-based inference model for lake mixing depths and thereby refine understanding of lake thermal structure change. We focused on three common planktonic diatom taxa, the distributions of which previous research suggests might be affected by mixing depth. Comparative lake surveys and growth rate experiments revealed that these species respond to lake thermal structure when nitrogen is sufficient, with species optima ranging from shallower to deeper mixing depths. The diatom-based mixing depth model was applied to sedimentary diatom profiles extending back to 1750 AD in two lakes with moderate nitrate concentrations but differing climate settings. Thermal reconstructions were consistent with expected changes, with shallower mixing depths inferred for an alpine lake where treeline has advanced, and deeper mixing depths inferred for a boreal lake where wind strength has increased. The inference model developed here provides a new tool to expand and refine understanding of climate-induced changes in lake ecosystems.

  1. Multifunctionality is affected by interactions between green roof plant species, substrate depth, and substrate type.

    Science.gov (United States)

    Dusza, Yann; Barot, Sébastien; Kraepiel, Yvan; Lata, Jean-Christophe; Abbadie, Luc; Raynaud, Xavier

    2017-04-01

    Green roofs provide ecosystem services through evapotranspiration and nutrient cycling that depend, among others, on plant species, substrate type, and substrate depth. However, no study has assessed thoroughly how interactions between these factors alter ecosystem functions and multifunctionality of green roofs. We simulated some green roof conditions in a pot experiment. We planted 20 plant species from 10 genera and five families (Asteraceae, Caryophyllaceae, Crassulaceae, Fabaceae, and Poaceae) on two substrate types (natural vs. artificial) and two substrate depths (10 cm vs. 30 cm). As indicators of major ecosystem functions, we measured aboveground and belowground biomasses, foliar nitrogen and carbon content, foliar transpiration, substrate water retention, and dissolved organic carbon and nitrates in leachates. Interactions between substrate type and depth strongly affected ecosystem functions. Biomass production was increased in the artificial substrate and deeper substrates, as was water retention in most cases. In contrast, dissolved organic carbon leaching was higher in the artificial substrates. Except for the Fabaceae species, nitrate leaching was reduced in deep, natural soils. The highest transpiration rates were associated with natural soils. All functions were modulated by plant families or species. Plant effects differed according to the observed function and the type and depth of the substrate. Fabaceae species grown on natural soils had the most noticeable patterns, allowing high biomass production and high water retention but also high nitrate leaching from deep pots. No single combination of factors enhanced simultaneously all studied ecosystem functions, highlighting that soil-plant interactions induce trade-offs between ecosystem functions. Substrate type and depth interactions are major drivers for green roof multifunctionality.

  2. Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks

    Science.gov (United States)

    Marbach, Daniel; Roy, Sushmita; Ay, Ferhat; Meyer, Patrick E.; Candeias, Rogerio; Kahveci, Tamer; Bristow, Christopher A.; Kellis, Manolis

    2012-01-01

    Gaining insights on gene regulation from large-scale functional data sets is a grand challenge in systems biology. In this article, we develop and apply methods for transcriptional regulatory network inference from diverse functional genomics data sets and demonstrate their value for gene function and gene expression prediction. We formulate the network inference problem in a machine-learning framework and use both supervised and unsupervised methods to predict regulatory edges by integrating transcription factor (TF) binding, evolutionarily conserved sequence motifs, gene expression, and chromatin modification data sets as input features. Applying these methods to Drosophila melanogaster, we predict ∼300,000 regulatory edges in a network of ∼600 TFs and 12,000 target genes. We validate our predictions using known regulatory interactions, gene functional annotations, tissue-specific expression, protein–protein interactions, and three-dimensional maps of chromosome conformation. We use the inferred network to identify putative functions for hundreds of previously uncharacterized genes, including many in nervous system development, which are independently confirmed based on their tissue-specific expression patterns. Last, we use the regulatory network to predict target gene expression levels as a function of TF expression, and find significantly higher predictive power for integrative networks than for motif or ChIP-based networks. Our work reveals the complementarity between physical evidence of regulatory interactions (TF binding, motif conservation) and functional evidence (coordinated expression or chromatin patterns) and demonstrates the power of data integration for network inference and studies of gene regulation at the systems level. PMID:22456606

  3. Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks.

    Science.gov (United States)

    Marbach, Daniel; Roy, Sushmita; Ay, Ferhat; Meyer, Patrick E; Candeias, Rogerio; Kahveci, Tamer; Bristow, Christopher A; Kellis, Manolis

    2012-07-01

    Gaining insights on gene regulation from large-scale functional data sets is a grand challenge in systems biology. In this article, we develop and apply methods for transcriptional regulatory network inference from diverse functional genomics data sets and demonstrate their value for gene function and gene expression prediction. We formulate the network inference problem in a machine-learning framework and use both supervised and unsupervised methods to predict regulatory edges by integrating transcription factor (TF) binding, evolutionarily conserved sequence motifs, gene expression, and chromatin modification data sets as input features. Applying these methods to Drosophila melanogaster, we predict ∼300,000 regulatory edges in a network of ∼600 TFs and 12,000 target genes. We validate our predictions using known regulatory interactions, gene functional annotations, tissue-specific expression, protein-protein interactions, and three-dimensional maps of chromosome conformation. We use the inferred network to identify putative functions for hundreds of previously uncharacterized genes, including many in nervous system development, which are independently confirmed based on their tissue-specific expression patterns. Last, we use the regulatory network to predict target gene expression levels as a function of TF expression, and find significantly higher predictive power for integrative networks than for motif or ChIP-based networks. Our work reveals the complementarity between physical evidence of regulatory interactions (TF binding, motif conservation) and functional evidence (coordinated expression or chromatin patterns) and demonstrates the power of data integration for network inference and studies of gene regulation at the systems level.

  4. Historical and projected interactions between climate change and insect voltinism in a multivoltine species

    Science.gov (United States)

    Patrick C. Tobin; Sudha Nagarkatti; Greg Loeb; Michael C. Saunders

    2008-01-01

    Climate change can cause major changes to the dynamics of individual species and to those communities in which they interact. One effect of increasing temperatures is on insect voltinism, with the logical assumption that increases in surface temperatures would permit multivoltine species to increase the number of generations per year. Though insect development is...

  5. Inverse Ising Inference Using All the Data

    Science.gov (United States)

    Aurell, Erik; Ekeberg, Magnus

    2012-03-01

    We show that a method based on logistic regression, using all the data, solves the inverse Ising problem far better than mean-field calculations relying only on sample pairwise correlation functions, while still computationally feasible for hundreds of nodes. The largest improvement in reconstruction occurs for strong interactions. Using two examples, a diluted Sherrington-Kirkpatrick model and a two-dimensional lattice, we also show that interaction topologies can be recovered from few samples with good accuracy and that the use of l1 regularization is beneficial in this process, pushing inference abilities further into low-temperature regimes.

  6. Inference of Transcription Regulatory Network in Low Phytic Acid Soybean Seeds

    Directory of Open Access Journals (Sweden)

    Neelam Redekar

    2017-11-01

    Full Text Available A dominant loss of function mutation in myo-inositol phosphate synthase (MIPS gene and recessive loss of function mutations in two multidrug resistant protein type-ABC transporter genes not only reduce the seed phytic acid levels in soybean, but also affect the pathways associated with seed development, ultimately resulting in low emergence. To understand the regulatory mechanisms and identify key genes that intervene in the seed development process in low phytic acid crops, we performed computational inference of gene regulatory networks in low and normal phytic acid soybeans using a time course transcriptomic data and multiple network inference algorithms. We identified a set of putative candidate transcription factors and their regulatory interactions with genes that have functions in myo-inositol biosynthesis, auxin-ABA signaling, and seed dormancy. We evaluated the performance of our unsupervised network inference method by comparing the predicted regulatory network with published regulatory interactions in Arabidopsis. Some contrasting regulatory interactions were observed in low phytic acid mutants compared to non-mutant lines. These findings provide important hypotheses on expression regulation of myo-inositol metabolism and phytohormone signaling in developing low phytic acid soybeans. The computational pipeline used for unsupervised network learning in this study is provided as open source software and is freely available at https://lilabatvt.github.io/LPANetwork/.

  7. Genetic interactions underlying hybrid male sterility in the Drosophila bipectinata species complex.

    Science.gov (United States)

    Mishra, Paras Kumar; Singh, Bashisth Narayan

    2006-06-01

    Understanding genetic mechanisms underlying hybrid male sterility is one of the most challenging problems in evolutionary biology especially speciation. By using the interspecific hybridization method roles of Y chromosome, Major Hybrid Sterility (MHS) genes and cytoplasm in sterility of hybrid males have been investigated in a promising group, the Drosophila bipectinata species complex that consists of four closely related species: D. pseudoananassae, D. bipectinata, D. parabipectinata and D. malerkotliana. The interspecific introgression analyses show that neither cytoplasm nor MHS genes are involved but X-Y interactions may be playing major role in hybrid male sterility between D. pseudoananassae and the other three species. The results of interspecific introgression analyses also show considerable decrease in the number of males in the backcross offspring and all males have atrophied testes. There is a significant positive correlation between sex - ratio distortion and severity of sterility in backcross males. These findings provide evidence that D. pseudoananassae is remotely related with other three species of the D. bipectinata species complex.

  8. Improved functional overview of protein complexes using inferred epistatic relationships

    LENUS (Irish Health Repository)

    Ryan, Colm

    2011-05-23

    Abstract Background Epistatic Miniarray Profiling(E-MAP) quantifies the net effect on growth rate of disrupting pairs of genes, often producing phenotypes that may be more (negative epistasis) or less (positive epistasis) severe than the phenotype predicted based on single gene disruptions. Epistatic interactions are important for understanding cell biology because they define relationships between individual genes, and between sets of genes involved in biochemical pathways and protein complexes. Each E-MAP screen quantifies the interactions between a logically selected subset of genes (e.g. genes whose products share a common function). Interactions that occur between genes involved in different cellular processes are not as frequently measured, yet these interactions are important for providing an overview of cellular organization. Results We introduce a method for combining overlapping E-MAP screens and inferring new interactions between them. We use this method to infer with high confidence 2,240 new strongly epistatic interactions and 34,469 weakly epistatic or neutral interactions. We show that accuracy of the predicted interactions approaches that of replicate experiments and that, like measured interactions, they are enriched for features such as shared biochemical pathways and knockout phenotypes. We constructed an expanded epistasis map for yeast cell protein complexes and show that our new interactions increase the evidence for previously proposed inter-complex connections, and predict many new links. We validated a number of these in the laboratory, including new interactions linking the SWR-C chromatin modifying complex and the nuclear transport apparatus. Conclusion Overall, our data support a modular model of yeast cell protein network organization and show how prediction methods can considerably extend the information that can be extracted from overlapping E-MAP screens.

  9. Reconciliation with non-binary species trees.

    Science.gov (United States)

    Vernot, Benjamin; Stolzer, Maureen; Goldman, Aiton; Durand, Dannie

    2008-10-01

    Reconciliation extracts information from the topological incongruence between gene and species trees to infer duplications and losses in the history of a gene family. The inferred duplication-loss histories provide valuable information for a broad range of biological applications, including ortholog identification, estimating gene duplication times, and rooting and correcting gene trees. While reconciliation for binary trees is a tractable and well studied problem, there are no algorithms for reconciliation with non-binary species trees. Yet a striking proportion of species trees are non-binary. For example, 64% of branch points in the NCBI taxonomy have three or more children. When applied to non-binary species trees, current algorithms overestimate the number of duplications because they cannot distinguish between duplication and incomplete lineage sorting. We present the first algorithms for reconciling binary gene trees with non-binary species trees under a duplication-loss parsimony model. Our algorithms utilize an efficient mapping from gene to species trees to infer the minimum number of duplications in O(|V(G) | x (k(S) + h(S))) time, where |V(G)| is the number of nodes in the gene tree, h(S) is the height of the species tree and k(S) is the size of its largest polytomy. We present a dynamic programming algorithm which also minimizes the total number of losses. Although this algorithm is exponential in the size of the largest polytomy, it performs well in practice for polytomies with outdegree of 12 or less. We also present a heuristic which estimates the minimal number of losses in polynomial time. In empirical tests, this algorithm finds an optimal loss history 99% of the time. Our algorithms have been implemented in NOTUNG, a robust, production quality, tree-fitting program, which provides a graphical user interface for exploratory analysis and also supports automated, high-throughput analysis of large data sets.

  10. Human infants' understanding of social imitation: Inferences of affiliation from third party observations.

    Science.gov (United States)

    Powell, Lindsey J; Spelke, Elizabeth S

    2018-01-01

    Imitation is ubiquitous in positive social interactions. For adult and child observers, it also supports inferences about the participants in such interactions and their social relationships, but the origins of these inferences are obscure. Do infants attach social significance to this form of interaction? Here we test 4- to 5.5-month-old infants' interpretation of imitation, asking if the imitative interactions they observe support inferences of social affiliation, across 10 experimental conditions that varied the modality of the imitation (movement vs. sound), the roles of specific characters (imitators vs. targets), the number of characters in the displays (3 vs. 5), and the number of parties initiating affiliative test events (1 vs. 2). These experiments, together with one experiment conducted with 12-month-old infants, yielded three main findings. First, infants expect that characters who engaged in imitation will approach and affiliate with the characters whom they imitated. Second, infants show no evidence of expecting that characters who were targets of imitation will approach and affiliate with their imitators. Third, analyzing imitative interactions is difficult for young infants, whose expectations vary in strength depending on the number of characters to be tracked and the number of affiliative actors to be compared. These findings have implications for our understanding of social imitation, and they provide methods for advancing understanding of other aspects of early social cognitive development. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. Entropic Inference

    Science.gov (United States)

    Caticha, Ariel

    2011-03-01

    In this tutorial we review the essential arguments behing entropic inference. We focus on the epistemological notion of information and its relation to the Bayesian beliefs of rational agents. The problem of updating from a prior to a posterior probability distribution is tackled through an eliminative induction process that singles out the logarithmic relative entropy as the unique tool for inference. The resulting method of Maximum relative Entropy (ME), includes as special cases both MaxEnt and Bayes' rule, and therefore unifies the two themes of these workshops—the Maximum Entropy and the Bayesian methods—into a single general inference scheme.

  12. Estimating phylogenetic relationships despite discordant gene trees across loci: the species tree of a diverse species group of feather mites (Acari: Proctophyllodidae).

    Science.gov (United States)

    Knowles, Lacey L; Klimov, Pavel B

    2011-11-01

    With the increased availability of multilocus sequence data, the lack of concordance of gene trees estimated for independent loci has focused attention on both the biological processes producing the discord and the methodologies used to estimate phylogenetic relationships. What has emerged is a suite of new analytical tools for phylogenetic inference--species tree approaches. In contrast to traditional phylogenetic methods that are stymied by the idiosyncrasies of gene trees, approaches for estimating species trees explicitly take into account the cause of discord among loci and, in the process, provides a direct estimate of phylogenetic history (i.e. the history of species divergence, not divergence of specific loci). We illustrate the utility of species tree estimates with an analysis of a diverse group of feather mites, the pinnatus species group (genus Proctophyllodes). Discord among four sequenced nuclear loci is consistent with theoretical expectations, given the short time separating speciation events (as evident by short internodes relative to terminal branch lengths in the trees). Nevertheless, many of the relationships are well resolved in a Bayesian estimate of the species tree; the analysis also highlights ambiguous aspects of the phylogeny that require additional loci. The broad utility of species tree approaches is discussed, and specifically, their application to groups with high speciation rates--a history of diversification with particular prevalence in host/parasite systems where species interactions can drive rapid diversification.

  13. Antagonistic interactions between an invasive alien and a native coccinellid species may promote coexistence.

    Science.gov (United States)

    Hentley, William T; Vanbergen, Adam J; Beckerman, Andrew P; Brien, Melanie N; Hails, Rosemary S; Jones, T Hefin; Johnson, Scott N

    2016-07-01

    Despite the capacity of invasive alien species to alter ecosystems, the mechanisms underlying their impact remain only partly understood. Invasive alien predators, for example, can significantly disrupt recipient communities by consuming prey species or acting as an intraguild predator (IGP). Behavioural interactions are key components of interspecific competition between predators, yet these are often overlooked invasion processes. Here, we show how behavioural, non-lethal IGP interactions might facilitate the establishment success of an invading alien species. We experimentally assessed changes in feeding behaviour (prey preference and consumption rate) of native UK coccinellid species (Adalia bipunctata and Coccinella septempunctata), whose populations are, respectively, declining and stable, when exposed to the invasive intraguild predator, Harmonia axyridis. Using a population dynamics model parameterized with these experimental data, we predicted how intraguild predation, accommodating interspecific behavioural interactions, might impact the abundance of the native and invasive alien species over time. When competing for the same aphid resource, the feeding rate of A. bipunctata significantly increased compared to the feeding in isolation, while the feeding rate of H. axyridis significantly decreased. This suggests that despite significant declines in the UK, A. bipunctata is a superior competitor to the intraguild predator H. axyridis. In contrast, the behaviour of non-declining C. septempunctata was unaltered by the presence of H. axyridis. Our experimental data show the differential behavioural plasticity of competing native and invasive alien predators, but do not explain A. bipunctata declines observed in the UK. Using behavioural plasticity as a parameter in a population dynamic model for A. bipunctata and H. axyridis, coexistence is predicted between the native and invasive alien following an initial period of decline in the native species. We

  14. A new fast method for inferring multiple consensus trees using k-medoids.

    Science.gov (United States)

    Tahiri, Nadia; Willems, Matthieu; Makarenkov, Vladimir

    2018-04-05

    Gene trees carry important information about specific evolutionary patterns which characterize the evolution of the corresponding gene families. However, a reliable species consensus tree cannot be inferred from a multiple sequence alignment of a single gene family or from the concatenation of alignments corresponding to gene families having different evolutionary histories. These evolutionary histories can be quite different due to horizontal transfer events or to ancient gene duplications which cause the emergence of paralogs within a genome. Many methods have been proposed to infer a single consensus tree from a collection of gene trees. Still, the application of these tree merging methods can lead to the loss of specific evolutionary patterns which characterize some gene families or some groups of gene families. Thus, the problem of inferring multiple consensus trees from a given set of gene trees becomes relevant. We describe a new fast method for inferring multiple consensus trees from a given set of phylogenetic trees (i.e. additive trees or X-trees) defined on the same set of species (i.e. objects or taxa). The traditional consensus approach yields a single consensus tree. We use the popular k-medoids partitioning algorithm to divide a given set of trees into several clusters of trees. We propose novel versions of the well-known Silhouette and Caliński-Harabasz cluster validity indices that are adapted for tree clustering with k-medoids. The efficiency of the new method was assessed using both synthetic and real data, such as a well-known phylogenetic dataset consisting of 47 gene trees inferred for 14 archaeal organisms. The method described here allows inference of multiple consensus trees from a given set of gene trees. It can be used to identify groups of gene trees having similar intragroup and different intergroup evolutionary histories. The main advantage of our method is that it is much faster than the existing tree clustering approaches, while

  15. Conditions Promoting Mycorrhizal Parasitism Are of Minor Importance for Competitive Interactions in Two Differentially Mycotrophic Species

    Science.gov (United States)

    Friede, Martina; Unger, Stephan; Hellmann, Christine; Beyschlag, Wolfram

    2016-01-01

    Interactions of plants with arbuscular mycorrhizal fungi (AMF) may range along a broad continuum from strong mutualism to parasitism, with mycorrhizal benefits received by the plant being determined by climatic and edaphic conditions affecting the balance between carbon costs vs. nutritional benefits. Thus, environmental conditions promoting either parasitism or mutualism can influence the mycorrhizal growth dependency (MGD) of a plant and in consequence may play an important role in plant-plant interactions. In a multifactorial field experiment we aimed at disentangling the effects of environmental and edaphic conditions, namely the availability of light, phosphorus and nitrogen, and the implications for competitive interactions between Hieracium pilosella and Corynephorus canescens for the outcome of the AMF symbiosis. Both species were planted in single, intraspecific and interspecific combinations using a target-neighbor approach with six treatments distributed along a gradient simulating conditions for the interaction between plants and AMF ranking from mutualistic to parasitic. Across all treatments we found mycorrhizal association of H. pilosella being consistently mutualistic, while pronounced parasitism was observed in C. canescens, indicating that environmental and edaphic conditions did not markedly affect the cost:benefit ratio of the mycorrhizal symbiosis in both species. Competitive interactions between both species were strongly affected by AMF, with the impact of AMF on competition being modulated by colonization. Biomass in both species was lowest when grown in interspecific competition, with colonization being increased in the less mycotrophic C. canescens, while decreased in the obligate mycotrophic H. pilosella. Although parasitism-promoting conditions negatively affected MGD in C. canescens, these effects were small as compared to growth decreases related to increased colonization levels in this species. Thus, the lack of plant control over

  16. Conditions Promoting Mycorrhizal Parasitism are of Minor Importance for Competitive Interactions in Two Differentially Mycotrophic Species

    Directory of Open Access Journals (Sweden)

    Martina Friede

    2016-09-01

    Full Text Available Interactions of plants with arbuscular mycorrhizal fungi (AMF may range along a broad continuum from strong mutualism to parasitism, with mycorrhizal benefits received by the plant being determined by climatic and edaphic conditions affecting the balance between carbon costs vs. nutritional benefits. Thus, environmental conditions promoting either parasitism or mutualism can influence the mycorrhizal growth dependency (MGD of a plant and in consequence may play an important role in plant-plant interactions.In a multifactorial field experiment we aimed at disentangling the effects of environmental and edaphic conditions, namely the availability of light, phosphorus and nitrogen, and the implications for competitive interactions between Hieracium pilosella and Corynephorus canescens for the outcome of the AMF symbiosis. Both species were planted in single, intraspecific and interspecific combinations using a target-neighbor approach with six treatments distributed along a gradient simulating conditions for the interaction between plants and AMF ranking from mutualistic to parasitic.Across all treatments we found mycorrhizal association of H. pilosella being consistently mutualistic, while pronounced parasitism was observed in C. canescens, indicating that environmental and edaphic conditions did not markedly affect the cost:benefit ratio of the mycorrhizal symbiosis in both species. Competitive interactions between both species were strongly affected by AMF, with the impact of AMF on competition being modulated by colonization. Biomass in both species was lowest when grown in interspecific competition, with colonization being increased in the less mycotrophic C. canescens, while decreased in the obligate mycotrophic H. pilosella. Although parasitism-promoting conditions negatively affected MGD in C. canescens, these effects were small as compared to growth decreases related to increased colonization levels in this species. Thus, the lack of plant

  17. Large-scale biotic interaction effects - tree cover interacts with shade toler-ance to affect distribution patterns of herb and shrub species across the Alps

    DEFF Research Database (Denmark)

    Nieto-Lugilde, Diego; Lenoir, Jonathan; Abdulhak, Sylvain

    2012-01-01

    on the occurrence on light-demanding species via size-asymmetric competition for light, but a facilitative effect on shade-tolerant species. In order to compare the relative importance of tree cover, four models with different combinations of variables (climate, soil and tree cover) were run for each species. Then...... role. Results indicated that high tree cover causes range contraction, especially at the upper limit, for light-demanding species, whereas it causes shade-tolerant species to extend their range upwards and downwards. Tree cover thus drives plant-plant interactions to shape plant species distribution...

  18. Changes in hyphal morphology and activity of phenoloxidases during interactions between selected ectomycorrhizal fungi and two species of Trichoderma.

    Science.gov (United States)

    Mucha, Joanna

    2011-06-01

    Patterns of phenoloxidase activity can be used to characterize fungi of different life styles, and changes in phenoloxidase synthesis were suspected to play a role in the interaction between ectomycorrhizal and two species of Trichoderma. Confrontation between the ectomycorrhizal fungi Amanita muscaria and Laccaria laccata with species of Trichoderma resulted in induction of laccase synthesis, and the laccase enzyme was bound to mycelia of ectomycorrhizal fungi. Tyrosinase release was noted only during interaction of L. laccata strains with Trichoderma harzianum and T. virens. Ectomycorrhizal fungi, especially strains of Suillus bovinus and S. luteus, inhibited growth of Trichoderma species and caused morphological changes in its colonies in the zone of interaction. In contrast, hyphal changes occurred less often in the ectomycorrhizal fungi tested. Species of Suillus are suggested to present a different mechanism in their interaction with other fungi than A. muscaria and L. laccata.

  19. Genetic interaction motif finding by expectation maximization – a novel statistical model for inferring gene modules from synthetic lethality

    Directory of Open Access Journals (Sweden)

    Ye Ping

    2005-12-01

    Full Text Available Abstract Background Synthetic lethality experiments identify pairs of genes with complementary function. More direct functional associations (for example greater probability of membership in a single protein complex may be inferred between genes that share synthetic lethal interaction partners than genes that are directly synthetic lethal. Probabilistic algorithms that identify gene modules based on motif discovery are highly appropriate for the analysis of synthetic lethal genetic interaction data and have great potential in integrative analysis of heterogeneous datasets. Results We have developed Genetic Interaction Motif Finding (GIMF, an algorithm for unsupervised motif discovery from synthetic lethal interaction data. Interaction motifs are characterized by position weight matrices and optimized through expectation maximization. Given a seed gene, GIMF performs a nonlinear transform on the input genetic interaction data and automatically assigns genes to the motif or non-motif category. We demonstrate the capacity to extract known and novel pathways for Saccharomyces cerevisiae (budding yeast. Annotations suggested for several uncharacterized genes are supported by recent experimental evidence. GIMF is efficient in computation, requires no training and automatically down-weights promiscuous genes with high degrees. Conclusion GIMF effectively identifies pathways from synthetic lethality data with several unique features. It is mostly suitable for building gene modules around seed genes. Optimal choice of one single model parameter allows construction of gene networks with different levels of confidence. The impact of hub genes the generic probabilistic framework of GIMF may be used to group other types of biological entities such as proteins based on stochastic motifs. Analysis of the strongest motifs discovered by the algorithm indicates that synthetic lethal interactions are depleted between genes within a motif, suggesting that synthetic

  20. Species-Level Phylogeny and Polyploid Relationships in Hordeum (Poaceae) Inferred by Next-Generation Sequencing and In Silico Cloning of Multiple Nuclear Loci.

    Science.gov (United States)

    Brassac, Jonathan; Blattner, Frank R

    2015-09-01

    Polyploidization is an important speciation mechanism in the barley genus Hordeum. To analyze evolutionary changes after allopolyploidization, knowledge of parental relationships is essential. One chloroplast and 12 nuclear single-copy loci were amplified by polymerase chain reaction (PCR) in all Hordeum plus six out-group species. Amplicons from each of 96 individuals were pooled, sheared, labeled with individual-specific barcodes and sequenced in a single run on a 454 platform. Reference sequences were obtained by cloning and Sanger sequencing of all loci for nine supplementary individuals. The 454 reads were assembled into contigs representing the 13 loci and, for polyploids, also homoeologues. Phylogenetic analyses were conducted for all loci separately and for a concatenated data matrix of all loci. For diploid taxa, a Bayesian concordance analysis and a coalescent-based dated species tree was inferred from all gene trees. Chloroplast matK was used to determine the maternal parent in allopolyploid taxa. The relative performance of different multilocus analyses in the presence of incomplete lineage sorting and hybridization was also assessed. The resulting multilocus phylogeny reveals for the first time species phylogeny and progenitor-derivative relationships of all di- and polyploid Hordeum taxa within a single analysis. Our study proves that it is possible to obtain a multilocus species-level phylogeny for di- and polyploid taxa by combining PCR with next-generation sequencing, without cloning and without creating a heavy load of sequence data. © The Author(s) 2015. Published by Oxford University Press, on behalf of the Society of Systematic Biologists.

  1. Inference of expanded Lrp-like feast/famine transcription factor targets in a non-model organism using protein structure-based prediction.

    Science.gov (United States)

    Ashworth, Justin; Plaisier, Christopher L; Lo, Fang Yin; Reiss, David J; Baliga, Nitin S

    2014-01-01

    Widespread microbial genome sequencing presents an opportunity to understand the gene regulatory networks of non-model organisms. This requires knowledge of the binding sites for transcription factors whose DNA-binding properties are unknown or difficult to infer. We adapted a protein structure-based method to predict the specificities and putative regulons of homologous transcription factors across diverse species. As a proof-of-concept we predicted the specificities and transcriptional target genes of divergent archaeal feast/famine regulatory proteins, several of which are encoded in the genome of Halobacterium salinarum. This was validated by comparison to experimentally determined specificities for transcription factors in distantly related extremophiles, chromatin immunoprecipitation experiments, and cis-regulatory sequence conservation across eighteen related species of halobacteria. Through this analysis we were able to infer that Halobacterium salinarum employs a divergent local trans-regulatory strategy to regulate genes (carA and carB) involved in arginine and pyrimidine metabolism, whereas Escherichia coli employs an operon. The prediction of gene regulatory binding sites using structure-based methods is useful for the inference of gene regulatory relationships in new species that are otherwise difficult to infer.

  2. More than one kind of inference: re-examining what's learned in feature inference and classification.

    Science.gov (United States)

    Sweller, Naomi; Hayes, Brett K

    2010-08-01

    Three studies examined how task demands that impact on attention to typical or atypical category features shape the category representations formed through classification learning and inference learning. During training categories were learned via exemplar classification or by inferring missing exemplar features. In the latter condition inferences were made about missing typical features alone (typical feature inference) or about both missing typical and atypical features (mixed feature inference). Classification and mixed feature inference led to the incorporation of typical and atypical features into category representations, with both kinds of features influencing inferences about familiar (Experiments 1 and 2) and novel (Experiment 3) test items. Those in the typical inference condition focused primarily on typical features. Together with formal modelling, these results challenge previous accounts that have characterized inference learning as producing a focus on typical category features. The results show that two different kinds of inference learning are possible and that these are subserved by different kinds of category representations.

  3. Generating inferences from knowledge structures based on general automata

    Energy Technology Data Exchange (ETDEWEB)

    Koenig, E C

    1983-01-01

    The author shows that the model for knowledge structures for computers based on general automata accommodates procedures for establishing inferences. Algorithms are presented which generate inferences as output of a computer when its sentence input names appropriate knowledge elements contained in an associated knowledge structure already stored in the memory of the computer. The inferences are found to have either a single graph tuple or more than one graph tuple of associated knowledge. Six algorithms pertain to a single graph tuple and a seventh pertains to more than one graph tuple of associated knowledge. A named term is either the automaton, environment, auxiliary receptor, principal receptor, auxiliary effector, or principal effector. The algorithm pertaining to more than one graph tuple requires that the input sentence names the automaton, transformation response, and environment of one of the tuples of associated knowledge in a sequence of tuples. Interaction with the computer may be either in a conversation or examination mode. The algorithms are illustrated by an example. 13 references.

  4. Process-Based Species Pools Reveal the Hidden Signature of Biotic Interactions Amid the Influence of Temperature Filtering.

    Science.gov (United States)

    Lessard, Jean-Philippe; Weinstein, Ben G; Borregaard, Michael K; Marske, Katharine A; Martin, Danny R; McGuire, Jimmy A; Parra, Juan L; Rahbek, Carsten; Graham, Catherine H

    2016-01-01

    A persistent challenge in ecology is to tease apart the influence of multiple processes acting simultaneously and interacting in complex ways to shape the structure of species assemblages. We implement a heuristic approach that relies on explicitly defining species pools and permits assessment of the relative influence of the main processes thought to shape assemblage structure: environmental filtering, dispersal limitations, and biotic interactions. We illustrate our approach using data on the assemblage composition and geographic distribution of hummingbirds, a comprehensive phylogeny and morphological traits. The implementation of several process-based species pool definitions in null models suggests that temperature-but not precipitation or dispersal limitation-acts as the main regional filter of assemblage structure. Incorporating this environmental filter directly into the definition of assemblage-specific species pools revealed an otherwise hidden pattern of phylogenetic evenness, indicating that biotic interactions might further influence hummingbird assemblage structure. Such hidden patterns of assemblage structure call for a reexamination of a multitude of phylogenetic- and trait-based studies that did not explicitly consider potentially important processes in their definition of the species pool. Our heuristic approach provides a transparent way to explore patterns and refine interpretations of the underlying causes of assemblage structure.

  5. Perceptual inference.

    Science.gov (United States)

    Aggelopoulos, Nikolaos C

    2015-08-01

    Perceptual inference refers to the ability to infer sensory stimuli from predictions that result from internal neural representations built through prior experience. Methods of Bayesian statistical inference and decision theory model cognition adequately by using error sensing either in guiding action or in "generative" models that predict the sensory information. In this framework, perception can be seen as a process qualitatively distinct from sensation, a process of information evaluation using previously acquired and stored representations (memories) that is guided by sensory feedback. The stored representations can be utilised as internal models of sensory stimuli enabling long term associations, for example in operant conditioning. Evidence for perceptual inference is contributed by such phenomena as the cortical co-localisation of object perception with object memory, the response invariance in the responses of some neurons to variations in the stimulus, as well as from situations in which perception can be dissociated from sensation. In the context of perceptual inference, sensory areas of the cerebral cortex that have been facilitated by a priming signal may be regarded as comparators in a closed feedback loop, similar to the better known motor reflexes in the sensorimotor system. The adult cerebral cortex can be regarded as similar to a servomechanism, in using sensory feedback to correct internal models, producing predictions of the outside world on the basis of past experience. Copyright © 2015 Elsevier Ltd. All rights reserved.

  6. SEMANTIC PATCH INFERENCE

    DEFF Research Database (Denmark)

    Andersen, Jesper

    2009-01-01

    Collateral evolution the problem of updating several library-using programs in response to API changes in the used library. In this dissertation we address the issue of understanding collateral evolutions by automatically inferring a high-level specification of the changes evident in a given set ...... specifications inferred by spdiff in Linux are shown. We find that the inferred specifications concisely capture the actual collateral evolution performed in the examples....

  7. Phylogeny of Celastraceae tribe Euonymeae inferred from morphological characters and nuclear and plastid genes.

    Science.gov (United States)

    Simmons, Mark P; McKenna, Miles J; Bacon, Christine D; Yakobson, Kendra; Cappa, Jennifer J; Archer, Robert H; Ford, Andrew J

    2012-01-01

    The phylogeny of Celastraceae tribe Euonymeae (≈ 230 species in eight genera in both the Old and New Worlds) was inferred using morphological characters together with plastid (matK, trnL-F) and nuclear (ITS and 26S rDNA) genes. Tribe Euonymeae has been defined as those genera of Celastraceae with generally opposite leaves, isomerous carpels, loculicidally dehiscent capsules, and arillate seeds (except Microtropis). Euonymus is the most diverse (129 species) and widely cultivated genus in the tribe. We infer that tribe Euonymeae consists of at least six separate lineages within Celastraceae and that a revised natural classification of the family is needed. Microtropis and Quetzalia are inferred to be distinct sister groups that together are sister to Zinowiewia. The endangered Monimopetalum chinense is an isolated and early derived lineage of Celastraceae that represents an important component of phylogenetic diversity within the family. Hedraianthera is sister to Brassiantha, and we describe a second species (Brassiantha hedraiantheroides A.J. Ford) that represents the first reported occurrence of this genus in Australia. Euonymus globularis, from eastern Australia, is sister to Menepetalum, which is endemic to New Caledonia, and we erect a new genus (Dinghoua R.H. Archer) for it. The Madagascan species of Euonymus are sister to Pleurostylia and recognized as a distinct genus (Astrocassine ined.). Glyptopetalum, Torralbasia, and Xylonymus are all closely related to Euonymus sensu stricto and are questionably distinct from it. Current intrageneric classifications of Euonymus are not completely natural and require revision. Copyright © 2011 Elsevier Inc. All rights reserved.

  8. Synergistic Interactions within a Multispecies Biofilm Enhance Individual Species Protection against Grazing by a Pelagic Protozoan

    Directory of Open Access Journals (Sweden)

    Prem K. Raghupathi

    2018-01-01

    Full Text Available Biofilm formation has been shown to confer protection against grazing, but little information is available on the effect of grazing on biofilm formation and protection in multispecies consortia. With most biofilms in nature being composed of multiple bacterial species, the interactions and dynamics of a multispecies bacterial biofilm subject to grazing by a pelagic protozoan predator were investigated. To this end, a mono and multispecies biofilms of four bacterial soil isolates, namely Xanthomonas retroflexus, Stenotrophomonas rhizophila, Microbacterium oxydans and Paenibacillus amylolyticus, were constructed and subjected to grazing by the ciliate Tetrahymena pyriformis. In monocultures, grazing strongly reduced planktonic cell numbers in P. amylolyticus and S. rhizophila and also X. retroflexus. At the same time, cell numbers in the underlying biofilms increased in S. rhizophila and X. retroflexus, but not in P. amylolyticus. This may be due to the fact that while grazing enhanced biofilm formation in the former two species, no biofilm was formed by P. amylolyticus in monoculture, either with or without grazing. In four-species biofilms, biofilm formation was higher than in the best monoculture, a strong biodiversity effect that was even more pronounced in the presence of grazing. While cell numbers of X. retroflexus, S. rhizophila, and P. amylolyticus in the planktonic fraction were greatly reduced in the presence of grazers, cell numbers of all three species strongly increased in the biofilm. Our results show that synergistic interactions between the four-species were important to induce biofilm formation, and suggest that bacterial members that produce more biofilm when exposed to the grazer not only protect themselves but also supported other members which are sensitive to grazing, thereby providing a “shared grazing protection” within the four-species biofilm model. Hence, complex interactions shape the dynamics of the biofilm and

  9. Role of Utility and Inference in the Evolution of Functional Information

    Science.gov (United States)

    Sharov, Alexei A.

    2009-01-01

    Functional information means an encoded network of functions in living organisms from molecular signaling pathways to an organism’s behavior. It is represented by two components: code and an interpretation system, which together form a self-sustaining semantic closure. Semantic closure allows some freedom between components because small variations of the code are still interpretable. The interpretation system consists of inference rules that control the correspondence between the code and the function (phenotype) and determines the shape of the fitness landscape. The utility factor operates at multiple time scales: short-term selection drives evolution towards higher survival and reproduction rate within a given fitness landscape, and long-term selection favors those fitness landscapes that support adaptability and lead to evolutionary expansion of certain lineages. Inference rules make short-term selection possible by shaping the fitness landscape and defining possible directions of evolution, but they are under control of the long-term selection of lineages. Communication normally occurs within a set of agents with compatible interpretation systems, which I call communication system. Functional information cannot be directly transferred between communication systems with incompatible inference rules. Each biological species is a genetic communication system that carries unique functional information together with inference rules that determine evolutionary directions and constraints. This view of the relation between utility and inference can resolve the conflict between realism/positivism and pragmatism. Realism overemphasizes the role of inference in evolution of human knowledge because it assumes that logic is embedded in reality. Pragmatism substitutes usefulness for truth and therefore ignores the advantage of inference. The proposed concept of evolutionary pragmatism rejects the idea that logic is embedded in reality; instead, inference rules are

  10. Individual-based ant-plant networks: diurnal-nocturnal structure and species-area relationship.

    Directory of Open Access Journals (Sweden)

    Wesley Dáttilo

    Full Text Available Despite the importance and increasing knowledge of ecological networks, sampling effort and intrapopulation variation has been widely overlooked. Using continuous daily sampling of ants visiting three plant species in the Brazilian Neotropical savanna, we evaluated for the first time the topological structure over 24 h and species-area relationships (based on the number of extrafloral nectaries available in individual-based ant-plant networks. We observed that diurnal and nocturnal ant-plant networks exhibited the same pattern of interactions: a nested and non-modular pattern and an average level of network specialization. Despite the high similarity in the ants' composition between the two collection periods, ant species found in the central core of highly interacting species totally changed between diurnal and nocturnal sampling for all plant species. In other words, this "night-turnover" suggests that the ecological dynamics of these ant-plant interactions can be temporally partitioned (day and night at a small spatial scale. Thus, it is possible that in some cases processes shaping mutualistic networks formed by protective ants and plants may be underestimated by diurnal sampling alone. Moreover, we did not observe any effect of the number of extrafloral nectaries on ant richness and their foraging on such plants in any of the studied ant-plant networks. We hypothesize that competitively superior ants could monopolize individual plants and allow the coexistence of only a few other ant species, however, other alternative hypotheses are also discussed. Thus, sampling period and species-area relationship produces basic information that increases our confidence in how individual-based ant-plant networks are structured, and the need to consider nocturnal records in ant-plant network sampling design so as to decrease inappropriate inferences.

  11. Antagonistic interactions between an invasive alien and a native coccinellid species may promote coexistence.

    OpenAIRE

    Hentley, W.T.; Vanbergen, A.J.; Beckerman, A.P.; Brien, M.N.; Hails, R.S.; Jones, T.H.; Johnson, S.N.

    2016-01-01

    1. Despite the capacity of invasive alien species to alter ecosystems, the mechanisms underlying their impact remain only partly understood. Invasive alien predators, for example, can significantly disrupt recipient communities by consuming prey species or acting as an intraguild predator (IGP). 2. Behavioural interactions are key components of interspecific competition between predators,yet these are often overlooked invasion processes. Here, we show how behavioural, nonlethal IGP intera...

  12. Offshore Fish Community: Ecological Interactions | Science ...

    Science.gov (United States)

    The offshore (>80 m) fish community of Lake Superior is made up of predominately native species. The most prominent species are deepwater sculpin, kiyi, cisco, siscowet lake trout, burbot, and the exotic sea lamprey. Bloater and shortjaw cisco are also found in the offshore zone. Bloater is abundant in the offshore zone but appears restricted to depths shallower than 150 m (Selgeby and Hoff 1996; Stockwell et al. 2010), although it occuppied greater depths several decades ago (Dryer 1966; Peck 1977). Shortjaw is relatively rare in the offshore zone (Hoff and Todd 2004; Gorman and Hoff 2009; Gorman and Todd 2007). Lake whitefish is also known to frequent bathymetric depths >100 m (Yule et al. 2008b). In this chapter, we develop a conceptual model of the offshore food web based on data collected during 2001-2005 and on inferences from species interactions known for the nearshore fish community. We then develop a framework for examination of energy and nutrient movements within the pelagic and benthic habitats of the offshore zone and across the offshore and nearshore zones. To document research results.

  13. Cross-Species Virus-Host Protein-Protein Interactions Inhibiting Innate Immunity

    Science.gov (United States)

    2016-07-01

    diseases are a regular occurrence globally (Figure 1). The Zika virus is the latest example gaining widespread attention. Many of the (re-)emerging...for establishing infection and/or modulating pathogenesis (Figures 2 and 3). 3 Figure 2. Schematic of several virus -host protein interactions within...8725 John J. Kingman Road, MS 6201 Fort Belvoir, VA 22060-6201 T E C H N IC A L R E P O R T DTRA-TR-16-79 Cross-species virus -host

  14. Cortical hierarchies perform Bayesian causal inference in multisensory perception.

    Directory of Open Access Journals (Sweden)

    Tim Rohe

    2015-02-01

    Full Text Available To form a veridical percept of the environment, the brain needs to integrate sensory signals from a common source but segregate those from independent sources. Thus, perception inherently relies on solving the "causal inference problem." Behaviorally, humans solve this problem optimally as predicted by Bayesian Causal Inference; yet, the underlying neural mechanisms are unexplored. Combining psychophysics, Bayesian modeling, functional magnetic resonance imaging (fMRI, and multivariate decoding in an audiovisual spatial localization task, we demonstrate that Bayesian Causal Inference is performed by a hierarchy of multisensory processes in the human brain. At the bottom of the hierarchy, in auditory and visual areas, location is represented on the basis that the two signals are generated by independent sources (= segregation. At the next stage, in posterior intraparietal sulcus, location is estimated under the assumption that the two signals are from a common source (= forced fusion. Only at the top of the hierarchy, in anterior intraparietal sulcus, the uncertainty about the causal structure of the world is taken into account and sensory signals are combined as predicted by Bayesian Causal Inference. Characterizing the computational operations of signal interactions reveals the hierarchical nature of multisensory perception in human neocortex. It unravels how the brain accomplishes Bayesian Causal Inference, a statistical computation fundamental for perception and cognition. Our results demonstrate how the brain combines information in the face of uncertainty about the underlying causal structure of the world.

  15. Reactive oxygen species, essential molecules, during plant-pathogen interactions.

    Science.gov (United States)

    Camejo, Daymi; Guzmán-Cedeño, Ángel; Moreno, Alexander

    2016-06-01

    Reactive oxygen species (ROS) are continually generated as a consequence of the normal metabolism in aerobic organisms. Accumulation and release of ROS into cell take place in response to a wide variety of adverse environmental conditions including salt, temperature, cold stresses and pathogen attack, among others. In plants, peroxidases class III, NADPH oxidase (NOX) locates in cell wall and plasma membrane, respectively, may be mainly enzymatic systems involving ROS generation. It is well documented that ROS play a dual role into cells, acting as important signal transduction molecules and as toxic molecules with strong oxidant power, however some aspects related to its function during plant-pathogen interactions remain unclear. This review focuses on the principal enzymatic systems involving ROS generation addressing the role of ROS as signal molecules during plant-pathogen interactions. We described how the chloroplasts, mitochondria and peroxisomes perceive the external stimuli as pathogen invasion, and trigger resistance response using ROS as signal molecule. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

  16. Temperature-Dependent Species Interactions Shape Priority Effects and the Persistence of Unequal Competitors.

    Science.gov (United States)

    Grainger, Tess Nahanni; Rego, Adam Ivan; Gilbert, Benjamin

    2018-02-01

    The order of species arrival at a site can determine the outcome of competitive interactions when early arrivers alter the environment or deplete shared resources. These priority effects are predicted to be stronger at high temperatures, as higher vital rates caused by warming allow early arrivers to more rapidly impact a shared environment. We tested this prediction using a pair of congeneric aphid species that specialize on milkweed plants. We manipulated temperature and arrival order of the two aphid species and measured aphid population dynamics and milkweed survival and defensive traits. We found that warming increased the impact of aphids on the quantity and quality of milkweed, which amplified the importance of priority effects by increasing the competitive exclusion of the inferior competitor when it arrived late. Warming also enhanced interspecific differences in dispersal, which could alter relative arrival times at a regional scale. Our experiment provides a first link between temperature-dependent trophic interactions, priority effects, and dispersal. This study suggests that the indirect and cascading effects of temperature observed here may be important determinants of diversity in the temporally and spatially complex landscapes that characterize ecological communities.

  17. Selective logging in tropical forests decreases the robustness of liana-tree interaction networks to the loss of host tree species.

    Science.gov (United States)

    Magrach, Ainhoa; Senior, Rebecca A; Rogers, Andrew; Nurdin, Deddy; Benedick, Suzan; Laurance, William F; Santamaria, Luis; Edwards, David P

    2016-03-16

    Selective logging is one of the major drivers of tropical forest degradation, causing important shifts in species composition. Whether such changes modify interactions between species and the networks in which they are embedded remain fundamental questions to assess the 'health' and ecosystem functionality of logged forests. We focus on interactions between lianas and their tree hosts within primary and selectively logged forests in the biodiversity hotspot of Malaysian Borneo. We found that lianas were more abundant, had higher species richness, and different species compositions in logged than in primary forests. Logged forests showed heavier liana loads disparately affecting slow-growing tree species, which could exacerbate the loss of timber value and carbon storage already associated with logging. Moreover, simulation scenarios of host tree local species loss indicated that logging might decrease the robustness of liana-tree interaction networks if heavily infested trees (i.e. the most connected ones) were more likely to disappear. This effect is partially mitigated in the short term by the colonization of host trees by a greater diversity of liana species within logged forests, yet this might not compensate for the loss of preferred tree hosts in the long term. As a consequence, species interaction networks may show a lagged response to disturbance, which may trigger sudden collapses in species richness and ecosystem function in response to additional disturbances, representing a new type of 'extinction debt'. © 2016 The Author(s).

  18. Selective logging in tropical forests decreases the robustness of liana–tree interaction networks to the loss of host tree species

    Science.gov (United States)

    Magrach, Ainhoa; Senior, Rebecca A.; Rogers, Andrew; Nurdin, Deddy; Benedick, Suzan; Laurance, William F.; Santamaria, Luis; Edwards, David P.

    2016-01-01

    Selective logging is one of the major drivers of tropical forest degradation, causing important shifts in species composition. Whether such changes modify interactions between species and the networks in which they are embedded remain fundamental questions to assess the ‘health’ and ecosystem functionality of logged forests. We focus on interactions between lianas and their tree hosts within primary and selectively logged forests in the biodiversity hotspot of Malaysian Borneo. We found that lianas were more abundant, had higher species richness, and different species compositions in logged than in primary forests. Logged forests showed heavier liana loads disparately affecting slow-growing tree species, which could exacerbate the loss of timber value and carbon storage already associated with logging. Moreover, simulation scenarios of host tree local species loss indicated that logging might decrease the robustness of liana–tree interaction networks if heavily infested trees (i.e. the most connected ones) were more likely to disappear. This effect is partially mitigated in the short term by the colonization of host trees by a greater diversity of liana species within logged forests, yet this might not compensate for the loss of preferred tree hosts in the long term. As a consequence, species interaction networks may show a lagged response to disturbance, which may trigger sudden collapses in species richness and ecosystem function in response to additional disturbances, representing a new type of ‘extinction debt’. PMID:26936241

  19. Inferring on the Intentions of Others by Hierarchical Bayesian Learning

    Science.gov (United States)

    Diaconescu, Andreea O.; Mathys, Christoph; Weber, Lilian A. E.; Daunizeau, Jean; Kasper, Lars; Lomakina, Ekaterina I.; Fehr, Ernst; Stephan, Klaas E.

    2014-01-01

    Inferring on others' (potentially time-varying) intentions is a fundamental problem during many social transactions. To investigate the underlying mechanisms, we applied computational modeling to behavioral data from an economic game in which 16 pairs of volunteers (randomly assigned to “player” or “adviser” roles) interacted. The player performed a probabilistic reinforcement learning task, receiving information about a binary lottery from a visual pie chart. The adviser, who received more predictive information, issued an additional recommendation. Critically, the game was structured such that the adviser's incentives to provide helpful or misleading information varied in time. Using a meta-Bayesian modeling framework, we found that the players' behavior was best explained by the deployment of hierarchical learning: they inferred upon the volatility of the advisers' intentions in order to optimize their predictions about the validity of their advice. Beyond learning, volatility estimates also affected the trial-by-trial variability of decisions: participants were more likely to rely on their estimates of advice accuracy for making choices when they believed that the adviser's intentions were presently stable. Finally, our model of the players' inference predicted the players' interpersonal reactivity index (IRI) scores, explicit ratings of the advisers' helpfulness and the advisers' self-reports on their chosen strategy. Overall, our results suggest that humans (i) employ hierarchical generative models to infer on the changing intentions of others, (ii) use volatility estimates to inform decision-making in social interactions, and (iii) integrate estimates of advice accuracy with non-social sources of information. The Bayesian framework presented here can quantify individual differences in these mechanisms from simple behavioral readouts and may prove useful in future clinical studies of maladaptive social cognition. PMID:25187943

  20. The effect of nonstationarity on models inferred from neural data

    International Nuclear Information System (INIS)

    Tyrcha, Joanna; Roudi, Yasser; Marsili, Matteo; Hertz, John

    2013-01-01

    Neurons subject to a common nonstationary input may exhibit a correlated firing behavior. Correlations in the statistics of neural spike trains also arise as the effect of interaction between neurons. Here we show that these two situations can be distinguished with machine learning techniques, provided that the data are rich enough. In order to do this, we study the problem of inferring a kinetic Ising model, stationary or nonstationary, from the available data. We apply the inference procedure to two data sets: one from salamander retinal ganglion cells and the other from a realistic computational cortical network model. We show that many aspects of the concerted activity of the salamander retinal neurons can be traced simply to the external input. A model of non-interacting neurons subject to a nonstationary external field outperforms a model with stationary input with couplings between neurons, even accounting for the differences in the number of model parameters. When couplings are added to the nonstationary model, for the retinal data, little is gained: the inferred couplings are generally not significant. Likewise, the distribution of the sizes of sets of neurons that spike simultaneously and the frequency of spike patterns as a function of their rank (Zipf plots) are well explained by an independent-neuron model with time-dependent external input, and adding connections to such a model does not offer significant improvement. For the cortical model data, robust couplings, well correlated with the real connections, can be inferred using the nonstationary model. Adding connections to this model slightly improves the agreement with the data for the probability of synchronous spikes but hardly affects the Zipf plot. (paper)

  1. The effect of nonstationarity on models inferred from neural data

    Energy Technology Data Exchange (ETDEWEB)

    Tyrcha, Joanna [Department of Mathematical Statistics, Stockholm University, SE-10691 Stockholm (Sweden); Roudi, Yasser [Kavli Institute for Systems Neuroscience, NTNU, NO-7010 Trondheim (Norway); Marsili, Matteo [The Abdus Salam ICTP, Strada Costiera 11, I-34151, Trieste (Italy); Hertz, John [Nordita, Royal Institute of Technology and Stockholm University, SE-106 91 Stockholm (Sweden)

    2013-03-01

    Neurons subject to a common nonstationary input may exhibit a correlated firing behavior. Correlations in the statistics of neural spike trains also arise as the effect of interaction between neurons. Here we show that these two situations can be distinguished with machine learning techniques, provided that the data are rich enough. In order to do this, we study the problem of inferring a kinetic Ising model, stationary or nonstationary, from the available data. We apply the inference procedure to two data sets: one from salamander retinal ganglion cells and the other from a realistic computational cortical network model. We show that many aspects of the concerted activity of the salamander retinal neurons can be traced simply to the external input. A model of non-interacting neurons subject to a nonstationary external field outperforms a model with stationary input with couplings between neurons, even accounting for the differences in the number of model parameters. When couplings are added to the nonstationary model, for the retinal data, little is gained: the inferred couplings are generally not significant. Likewise, the distribution of the sizes of sets of neurons that spike simultaneously and the frequency of spike patterns as a function of their rank (Zipf plots) are well explained by an independent-neuron model with time-dependent external input, and adding connections to such a model does not offer significant improvement. For the cortical model data, robust couplings, well correlated with the real connections, can be inferred using the nonstationary model. Adding connections to this model slightly improves the agreement with the data for the probability of synchronous spikes but hardly affects the Zipf plot. (paper)

  2. Inferring network structure from cascades

    Science.gov (United States)

    Ghonge, Sushrut; Vural, Dervis Can

    2017-07-01

    Many physical, biological, and social phenomena can be described by cascades taking place on a network. Often, the activity can be empirically observed, but not the underlying network of interactions. In this paper we offer three topological methods to infer the structure of any directed network given a set of cascade arrival times. Our formulas hold for a very general class of models where the activation probability of a node is a generic function of its degree and the number of its active neighbors. We report high success rates for synthetic and real networks, for several different cascade models.

  3. Is 30 years enough time to niche segregation between a non-native and a native congeneric fish species? Evidences from stable isotopes

    Directory of Open Access Journals (Sweden)

    Gustavo Henrique Zaia Alves

    2015-12-01

    Full Text Available The invasion of non-native species that are phylogenetically similar to native species was observed in the Upper Paraná River following the construction of the Itaipu hydroelectric plant and subsequent removal of a natural geographic barrier (Sete Quedas Falls. Endemic fish species from the Lower Paraná River, such as the piranha Serrasalmus marginatus, successfully colonized the new environment. A few years later, S. marginatus had become the dominant species, while the prevalence of the congeneric species, Serrasalmus maculatus, had declined. Considering that the two piranha species naturally coexist in the Pantanal and that S. marginatus is a non-native species in the Upper Paraná River floodplain, we hypothesized that trophic niche overlap between Serrasalmus species only occurred in the Upper Paraná River floodplain due to short-term co-existence. The study area in which the isotopic niche overlap between S. maculatus and S. marginatus was evaluated consisted of two ponds located in different floodplains, the Pantanal and the Upper Paraná River. We used carbon and nitrogen stable isotope analysis to elucidate the differences in the energy intake by the native and non-native species. We used mixing models and calculated the isotopic niche area and niche overlap to infer the nature of the trophic interactions between the species in both habitats. According to the mixing model, the predominant source of carbon for both species was terrestrial. Nevertheless, in Upper Paraná River, the δ13C signature of the two species differed significantly and the non-native species had a greater niche width than the native species. In the Pantanal, there were no differences in δ13C, but the species differed with respect to δ 15N, and the niche widths were narrow for both species.Based on these results, it can be inferred that the species depend on different food sources. Piranhas obtain energy from distinct prey species, which probably consume

  4. Pollinator species richness: Are the declines slowing down?

    Directory of Open Access Journals (Sweden)

    Tom J. M. Van Dooren

    2016-09-01

    Full Text Available Changes in pollinator abundances and diversity are of major concern. A recent study inferred that pollinator species richnesses are decreasing more slowly in recent decades in several taxa and European countries. A more careful interpretation of these results reveals that this conclusion cannot be drawn and that we can only infer that declines decelerate for bees (Anthophila in the Netherlands.

  5. Optimal inference with suboptimal models: Addiction and active Bayesian inference

    Science.gov (United States)

    Schwartenbeck, Philipp; FitzGerald, Thomas H.B.; Mathys, Christoph; Dolan, Ray; Wurst, Friedrich; Kronbichler, Martin; Friston, Karl

    2015-01-01

    When casting behaviour as active (Bayesian) inference, optimal inference is defined with respect to an agent’s beliefs – based on its generative model of the world. This contrasts with normative accounts of choice behaviour, in which optimal actions are considered in relation to the true structure of the environment – as opposed to the agent’s beliefs about worldly states (or the task). This distinction shifts an understanding of suboptimal or pathological behaviour away from aberrant inference as such, to understanding the prior beliefs of a subject that cause them to behave less ‘optimally’ than our prior beliefs suggest they should behave. Put simply, suboptimal or pathological behaviour does not speak against understanding behaviour in terms of (Bayes optimal) inference, but rather calls for a more refined understanding of the subject’s generative model upon which their (optimal) Bayesian inference is based. Here, we discuss this fundamental distinction and its implications for understanding optimality, bounded rationality and pathological (choice) behaviour. We illustrate our argument using addictive choice behaviour in a recently described ‘limited offer’ task. Our simulations of pathological choices and addictive behaviour also generate some clear hypotheses, which we hope to pursue in ongoing empirical work. PMID:25561321

  6. Interactions of fire and nonnative species across an elevation/plant community gradient in Hawaii volcanoes national park

    Science.gov (United States)

    Alison Ainsworth; J. Boone Kauffman

    2010-01-01

    Invasive species interacting with fires pose a relatively unknown, but potentially serious, threat to the tropical forests of Hawaii. Fires may create conditions that facilitate species invasions, but the degree to which this occurs in different tropical plant communities has not been quantified. We documented the survival and establishment of plant species for 2 yr...

  7. Inference rule and problem solving

    Energy Technology Data Exchange (ETDEWEB)

    Goto, S

    1982-04-01

    Intelligent information processing signifies an opportunity of having man's intellectual activity executed on the computer, in which inference, in place of ordinary calculation, is used as the basic operational mechanism for such an information processing. Many inference rules are derived from syllogisms in formal logic. The problem of programming this inference function is referred to as a problem solving. Although logically inference and problem-solving are in close relation, the calculation ability of current computers is on a low level for inferring. For clarifying the relation between inference and computers, nonmonotonic logic has been considered. The paper deals with the above topics. 16 references.

  8. Natural selection interacts with recombination to shape the evolution of hybrid genomes.

    Science.gov (United States)

    Schumer, Molly; Xu, Chenling; Powell, Daniel L; Durvasula, Arun; Skov, Laurits; Holland, Chris; Blazier, John C; Sankararaman, Sriram; Andolfatto, Peter; Rosenthal, Gil G; Przeworski, Molly

    2018-05-11

    To investigate the consequences of hybridization between species, we studied three replicate hybrid populations that formed naturally between two swordtail fish species, estimating their fine-scale genetic map and inferring ancestry along the genomes of 690 individuals. In all three populations, ancestry from the "minor" parental species is more common in regions of high recombination and where there is linkage to fewer putative targets of selection. The same patterns are apparent in a reanalysis of human and archaic admixture. These results support models in which ancestry from the minor parental species is more likely to persist when rapidly uncoupled from alleles that are deleterious in hybrids. Our analyses further indicate that selection on swordtail hybrids stems predominantly from deleterious combinations of epistatically interacting alleles. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

  9. Interaction of selenite with reduced Fe and/or S species: An XRD and XAS study.

    Science.gov (United States)

    Finck, Nicolas; Dardenne, Kathy

    2016-05-01

    In this study, we investigated the interaction between selenite and either Fe((II))aq or S((-II))aq in solution, and the results were used to investigate the interaction between Se((IV))aq and FeS in suspension. The reaction products were characterized by a combination of methods (SEM, XRD and XAS) and the reaction mechanisms were identified. In a first experiment, Se((IV))aq was reduced to Se((0)) by interaction with Fe((II))aq which was oxidized to Fe((III)), but the reaction was only partial. Subsequently, some Fe((III)) produced akaganeite (β-FeOOH) and the release of proton during that reaction decreased the pH. The pH decrease changed the Se speciation in solution which hindered further Se((IV)) reduction by Fe((II))aq. In a second experiment, Se((IV))aq was quantitatively reduced to Se((0)) by S((-II))aq and the reaction was fast. Two sulfide species were needed to reduce one Se((IV)), and the observed pH increase was due to a proton consumption. For both experiments, experimental results are consistent with expectations based on the oxidation reduction potential of the various species. Upon interaction with FeS, Se((IV))aq was reduced to Se((0)) and minute amounts of pyrite were detected, a consequence of partial mackinawite oxidation at surface sulfur sites. These results are of prime importance with respect to safe deep disposal of nuclear waste which contains the long-lived radionuclide (79)Se. This study shows that after release of (79)Se((IV)) upon nuclear waste matrix corrosion, selenite can be reduced in the near field to low soluble Se((0)) by interaction with Fe((II))aq and/or S((-II))aq species. Because the solubility of Se((0)) species is significantly lower than that of Se((IV)), selenium will become much less (bio)available and its migration out of deep HLW repositories may be drastically hindered. Copyright © 2016. Published by Elsevier B.V.

  10. Species limits and relationships within Otidea inferred from multiple gene phylogenies

    NARCIS (Netherlands)

    Hansen, K.; Olariaga, I.

    2015-01-01

    The genus Otidea is one of the more conspicuous members of the Pyronemataceae, with high species diversity in hemiboreal and boreal forests. The genus is morphologically coherent and in previous higher-level multi-gene analyses it formed a highly supported monophyletic group. Species delimitation

  11. Knowledge and inference

    CERN Document Server

    Nagao, Makoto

    1990-01-01

    Knowledge and Inference discusses an important problem for software systems: How do we treat knowledge and ideas on a computer and how do we use inference to solve problems on a computer? The book talks about the problems of knowledge and inference for the purpose of merging artificial intelligence and library science. The book begins by clarifying the concept of """"knowledge"""" from many points of view, followed by a chapter on the current state of library science and the place of artificial intelligence in library science. Subsequent chapters cover central topics in the artificial intellig

  12. Competitive interactions between native and invasive exotic plant species are altered under elevated carbon dioxide.

    Science.gov (United States)

    Manea, Anthony; Leishman, Michelle R

    2011-03-01

    We hypothesized that the greater competitive ability of invasive exotic plants relative to native plants would increase under elevated CO(2) because they typically have traits that confer the ability for fast growth when resources are not limiting and thus are likely to be more responsive to elevated CO(2). A series of competition experiments under ambient and elevated CO(2) glasshouse conditions were conducted to determine an index of relative competition intensity for 14 native-invasive exotic species-pairs. Traits including specific leaf area, leaf mass ratio, leaf area ratio, relative growth rate, net assimilation rate and root weight ratio were measured. Competitive rankings within species-pairs were not affected by CO(2) concentration: invasive exotic species were more competitive in 9 of the 14 species-pairs and native species were more competitive in the remaining 5 species-pairs, regardless of CO(2) concentration. However, there was a significant interaction between plant type and CO(2) treatment due to reduced competitive response of native species under elevated compared with ambient CO(2) conditions. Native species had significantly lower specific leaf area and leaf area ratio under elevated compared with ambient CO(2). We also compared traits of more-competitive with less-competitive species, regardless of plant type, under both CO(2) treatments. More-competitive species had smaller leaf weight ratio and leaf area ratio, and larger relative growth rate and net assimilation rate under both ambient and elevated CO(2) conditions. These results suggest that growth and allocation traits can be useful predictors of the outcome of competitive interactions under both ambient and elevated CO(2) conditions. Under predicted future atmospheric CO(2) conditions, competitive rankings among species may not change substantially, but the relative success of invasive exotic species may be increased. Thus, under future atmospheric CO(2) conditions, the ecological and

  13. Inference of the Genetic Network Regulating Lateral Root Initiation in Arabidopsis thaliana

    KAUST Repository

    Muraro, D.; Voss, U.; Wilson, M.; Bennett, M.; Byrne, H.; De Smet, I.; Hodgman, C.; King, J.

    2013-01-01

    thaliana is stimulated by a cascade of regulators of which only the interactions of its initial elements have been identified. Using simulated gene expression data with known network topology, we compare the performance of inference algorithms, based

  14. Geometric statistical inference

    International Nuclear Information System (INIS)

    Periwal, Vipul

    1999-01-01

    A reparametrization-covariant formulation of the inverse problem of probability is explicitly solved for finite sample sizes. The inferred distribution is explicitly continuous for finite sample size. A geometric solution of the statistical inference problem in higher dimensions is outlined

  15. Intracranial EEG correlates of implicit relational inference within the hippocampus.

    Science.gov (United States)

    Reber, T P; Do Lam, A T A; Axmacher, N; Elger, C E; Helmstaedter, C; Henke, K; Fell, J

    2016-01-01

    Drawing inferences from past experiences enables adaptive behavior in future situations. Inference has been shown to depend on hippocampal processes. Usually, inference is considered a deliberate and effortful mental act which happens during retrieval, and requires the focus of our awareness. Recent fMRI studies hint at the possibility that some forms of hippocampus-dependent inference can also occur during encoding and possibly also outside of awareness. Here, we sought to further explore the feasibility of hippocampal implicit inference, and specifically address the temporal evolution of implicit inference using intracranial EEG. Presurgical epilepsy patients with hippocampal depth electrodes viewed a sequence of word pairs, and judged the semantic fit between two words in each pair. Some of the word pairs entailed a common word (e.g., "winter-red," "red-cat") such that an indirect relation was established in following word pairs (e.g., "winter-cat"). The behavioral results suggested that drawing inference implicitly from past experience is feasible because indirect relations seemed to foster "fit" judgments while the absence of indirect relations fostered "do not fit" judgments, even though the participants were unaware of the indirect relations. A event-related potential (ERP) difference emerging 400 ms post-stimulus was evident in the hippocampus during encoding, suggesting that indirect relations were already established automatically during encoding of the overlapping word pairs. Further ERP differences emerged later post-stimulus (1,500 ms), were modulated by the participants' responses and were evident during encoding and test. Furthermore, response-locked ERP effects were evident at test. These ERP effects could hence be a correlate of the interaction of implicit memory with decision-making. Together, the data map out a time-course in which the hippocampus automatically integrates memories from discrete but related episodes to implicitly influence future

  16. Species co-occurrence affects the trophic interactions of two juvenile reef shark species in tropical lagoon nurseries in Moorea (French Polynesia).

    Science.gov (United States)

    Matich, Philip; Kiszka, Jeremy J; Mourier, Johann; Planes, Serge; Heithaus, Michael R

    2017-06-01

    Food web structure is shaped by interactions within and across trophic levels. As such, understanding how the presence and absence of predators, prey, and competitors affect species foraging patterns is important for predicting the consequences of changes in species abundances, distributions, and behaviors. Here, we used plasma δ 13 C and δ 15 N values from juvenile blacktip reef sharks (Carcharhinus melanopterus) and juvenile sicklefin lemon sharks (Negaprion acutidens) to investigate how species co-occurrence affects their trophic interactions in littoral waters of Moorea, French Polynesia. Co-occurrence led to isotopic niche partitioning among sharks within nurseries, with significant increases in δ 15 N values among sicklefin lemon sharks, and significant decreases in δ 15 N among blacktip reef sharks. Niche segregation likely promotes coexistence of these two predators during early years of growth and development, but data do not suggest coexistence affects life history traits, such as body size, body condition, and ontogenetic niche shifts. Plasticity in trophic niches among juvenile blacktip reef sharks and sicklefin lemon sharks also suggests these predators are able to account for changes in community structure, resource availability, and intra-guild competition, and may fill similar functional roles in the absence of the other species, which is important as environmental change and human impacts persist in coral reef ecosystems. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. Intraspecific relationship within the genus convolvulus l. inferred by rbcl gene using different phylogenetic approaches

    International Nuclear Information System (INIS)

    Kausar, S.; Qamarunnisa, S.

    2016-01-01

    A molecular systematics analysis was conducted using sequence data of chloroplast rbcL gene for the genus Convolvulus L., by distance and character based phylogenetic methods. Fifteen representative members from genus Convolvulus L., were included as in group whereas two members from a sister family Solanaceae were taken as out group to root the tree. Intraspecific relationships within Convolvulus were inferred by distance matrix, maximum parsimony and bayesian analysis. Transition/transversion ratio was also calculated and it was revealed that in the investigated Convolvulus species, transitional changes were more prevalent in rbcL gene. The nature of rbcL gene in the present study was observed to be conserved, as it does not show major variations between examined species. Distance matrix represented the minimal genetic variations between some species (C. glomeratus and C. pyrrhotrichus), thus exhibiting them as close relatives. The result of parsimonious and bayesian analysis revealed almost similar clades however maximum parsimony based tree was unable to establish relationship between some Convolvulus species. The bayesian inference method was found to be the method of choice for establishing intraspecific associations between Convolvulus species using rbcL data as it clearly defined the connections supported by posterior probability values. (author)

  18. Genetic variation in foundation species governs the dynamics of trophic interactions

    Science.gov (United States)

    Valencia-Cuevas, Leticia; Mussali-Galante, Patricia; Cano-Santana, Zenón; Pujade-Villar, Juli; Equihua-Martínez, Armando

    2018-01-01

    Abstract Various studies have demonstrated that the foundation species genetic diversity can have direct effects that extend beyond the individual or population level, affecting the dependent communities. Additionally, these effects may be indirectly extended to higher trophic levels throughout the entire community. Quercus castanea is an oak species with characteristics of foundation species beyond presenting a wide geographical distribution and being a dominant element of Mexican temperate forests. In this study, we analyzed the influence of population (He) and individual (HL) genetic diversity of Q. castanea on its canopy endophagous insect community and associated parasitoids. Specifically, we studied the composition, richness (S) and density of leaf-mining moths (Lepidoptera: Tischeridae, Citheraniidae), gall-forming wasps (Hymenoptera: Cynipidae), and canopy parasitoids of Q. castanea. We sampled 120 trees belonging to six populations (20/site) through the previously recognized gradient of genetic diversity. In total, 22 endophagous insect species belonging to three orders (Hymenoptera, Lepidoptera, and Diptera) and 20 parasitoid species belonging to 13 families were identified. In general, we observed that the individual genetic diversity of the host plant (HL) has a significant positive effect on the S and density of the canopy endophagous insect communities. In contrast, He has a significant negative effect on the S of endophagous insects. Additionally, indirect effects of HL were observed, affecting the S and density of parasitoid insects. Our results suggest that genetic variation in foundation species can be one of the most important factors governing the dynamics of tritrophic interactions that involve oaks, herbivores, and parasitoids. PMID:29492034

  19. An Intuitive Dashboard for Bayesian Network Inference

    International Nuclear Information System (INIS)

    Reddy, Vikas; Farr, Anna Charisse; Wu, Paul; Mengersen, Kerrie; Yarlagadda, Prasad K D V

    2014-01-01

    Current Bayesian network software packages provide good graphical interface for users who design and develop Bayesian networks for various applications. However, the intended end-users of these networks may not necessarily find such an interface appealing and at times it could be overwhelming, particularly when the number of nodes in the network is large. To circumvent this problem, this paper presents an intuitive dashboard, which provides an additional layer of abstraction, enabling the end-users to easily perform inferences over the Bayesian networks. Unlike most software packages, which display the nodes and arcs of the network, the developed tool organises the nodes based on the cause-and-effect relationship, making the user-interaction more intuitive and friendly. In addition to performing various types of inferences, the users can conveniently use the tool to verify the behaviour of the developed Bayesian network. The tool has been developed using QT and SMILE libraries in C++

  20. An Intuitive Dashboard for Bayesian Network Inference

    Science.gov (United States)

    Reddy, Vikas; Charisse Farr, Anna; Wu, Paul; Mengersen, Kerrie; Yarlagadda, Prasad K. D. V.

    2014-03-01

    Current Bayesian network software packages provide good graphical interface for users who design and develop Bayesian networks for various applications. However, the intended end-users of these networks may not necessarily find such an interface appealing and at times it could be overwhelming, particularly when the number of nodes in the network is large. To circumvent this problem, this paper presents an intuitive dashboard, which provides an additional layer of abstraction, enabling the end-users to easily perform inferences over the Bayesian networks. Unlike most software packages, which display the nodes and arcs of the network, the developed tool organises the nodes based on the cause-and-effect relationship, making the user-interaction more intuitive and friendly. In addition to performing various types of inferences, the users can conveniently use the tool to verify the behaviour of the developed Bayesian network. The tool has been developed using QT and SMILE libraries in C++.

  1. Inferring ontology graph structures using OWL reasoning

    KAUST Repository

    Rodriguez-Garcia, Miguel Angel

    2018-01-05

    Ontologies are representations of a conceptualization of a domain. Traditionally, ontologies in biology were represented as directed acyclic graphs (DAG) which represent the backbone taxonomy and additional relations between classes. These graphs are widely exploited for data analysis in the form of ontology enrichment or computation of semantic similarity. More recently, ontologies are developed in a formal language such as the Web Ontology Language (OWL) and consist of a set of axioms through which classes are defined or constrained. While the taxonomy of an ontology can be inferred directly from the axioms of an ontology as one of the standard OWL reasoning tasks, creating general graph structures from OWL ontologies that exploit the ontologies\\' semantic content remains a challenge.We developed a method to transform ontologies into graphs using an automated reasoner while taking into account all relations between classes. Searching for (existential) patterns in the deductive closure of ontologies, we can identify relations between classes that are implied but not asserted and generate graph structures that encode for a large part of the ontologies\\' semantic content. We demonstrate the advantages of our method by applying it to inference of protein-protein interactions through semantic similarity over the Gene Ontology and demonstrate that performance is increased when graph structures are inferred using deductive inference according to our method. Our software and experiment results are available at http://github.com/bio-ontology-research-group/Onto2Graph .Onto2Graph is a method to generate graph structures from OWL ontologies using automated reasoning. The resulting graphs can be used for improved ontology visualization and ontology-based data analysis.

  2. Inferring ontology graph structures using OWL reasoning.

    Science.gov (United States)

    Rodríguez-García, Miguel Ángel; Hoehndorf, Robert

    2018-01-05

    Ontologies are representations of a conceptualization of a domain. Traditionally, ontologies in biology were represented as directed acyclic graphs (DAG) which represent the backbone taxonomy and additional relations between classes. These graphs are widely exploited for data analysis in the form of ontology enrichment or computation of semantic similarity. More recently, ontologies are developed in a formal language such as the Web Ontology Language (OWL) and consist of a set of axioms through which classes are defined or constrained. While the taxonomy of an ontology can be inferred directly from the axioms of an ontology as one of the standard OWL reasoning tasks, creating general graph structures from OWL ontologies that exploit the ontologies' semantic content remains a challenge. We developed a method to transform ontologies into graphs using an automated reasoner while taking into account all relations between classes. Searching for (existential) patterns in the deductive closure of ontologies, we can identify relations between classes that are implied but not asserted and generate graph structures that encode for a large part of the ontologies' semantic content. We demonstrate the advantages of our method by applying it to inference of protein-protein interactions through semantic similarity over the Gene Ontology and demonstrate that performance is increased when graph structures are inferred using deductive inference according to our method. Our software and experiment results are available at http://github.com/bio-ontology-research-group/Onto2Graph . Onto2Graph is a method to generate graph structures from OWL ontologies using automated reasoning. The resulting graphs can be used for improved ontology visualization and ontology-based data analysis.

  3. Algorithms for MDC-based multi-locus phylogeny inference: beyond rooted binary gene trees on single alleles.

    Science.gov (United States)

    Yu, Yun; Warnow, Tandy; Nakhleh, Luay

    2011-11-01

    One of the criteria for inferring a species tree from a collection of gene trees, when gene tree incongruence is assumed to be due to incomplete lineage sorting (ILS), is Minimize Deep Coalescence (MDC). Exact algorithms for inferring the species tree from rooted, binary trees under MDC were recently introduced. Nevertheless, in phylogenetic analyses of biological data sets, estimated gene trees may differ from true gene trees, be incompletely resolved, and not necessarily rooted. In this article, we propose new MDC formulations for the cases where the gene trees are unrooted/binary, rooted/non-binary, and unrooted/non-binary. Further, we prove structural theorems that allow us to extend the algorithms for the rooted/binary gene tree case to these cases in a straightforward manner. In addition, we devise MDC-based algorithms for cases when multiple alleles per species may be sampled. We study the performance of these methods in coalescent-based computer simulations.

  4. Trophic interactions between native and introduced fish species in a littoral fish community.

    Science.gov (United States)

    Monroy, M; Maceda-Veiga, A; Caiola, N; De Sostoa, A

    2014-11-01

    The trophic interactions between 15 native and two introduced fish species, silverside Odontesthes bonariensis and rainbow trout Oncorhynchus mykiss, collected in a major fishery area at Lake Titicaca were explored by integrating traditional ecological knowledge and stable-isotope analyses (SIA). SIA suggested the existence of six trophic groups in this fish community based on δ(13)C and δ(15)N signatures. This was supported by ecological evidence illustrating marked spatial segregation between groups, but a similar trophic level for most of the native groups. Based on Bayesian ellipse analyses, niche overlap appeared to occur between small O. bonariensis (<90 mm) and benthopelagic native species (31.6%), and between the native pelagic killifish Orestias ispi and large O. bonariensis (39%) or O. mykiss (19.7%). In addition, Bayesian mixing models suggested that O. ispi and epipelagic species are likely to be the main prey items for the two introduced fish species. This study reveals a trophic link between native and introduced fish species, and demonstrates the utility of combining both SIA and traditional ecological knowledge to understand trophic relationships between fish species with similar feeding habits. © 2014 The Fisheries Society of the British Isles.

  5. Plant species distribution along environmental gradient: do belowground interactions with fungi matter?

    Directory of Open Access Journals (Sweden)

    Loïc ePellissier

    2013-12-01

    Full Text Available The distribution of plants along environmental gradients is constrained by abiotic and biotic factors. Cumulative evidence attests of the impact of abiotic factors on plant distributions, but only few studies discuss the role of belowground communities. Soil fungi, in particular, are thought to play an important role in how plant species assemble locally into communities. We first review existing evidence, and then test the effect of the number of soil fungal operational taxonomic units (OTUs on plant species distributions using a recently collected dataset of plant and metagenomic information on soil fungi in the Western Swiss Alps. Using species distribution models, we investigated whether the distribution of individual plant species is correlated to the number of OTUs of two important soil fungal classes known to interact with plants: the Glomeromycetes, that are obligatory symbionts of plants, and the Agaricomycetes, that may be facultative plant symbionts, pathogens, or wood decayers. We show that including the fungal richness information in the models of plant species distributions improves predictive accuracy. Number of fungal OTUs is especially correlated to the distribution of high elevation plant species. We suggest that high elevation soil show greater variation in fungal assemblages that may in turn impact plant turnover among communities. We finally discuss how to move beyond correlative analyses, through the design of field experiments manipulating plant and fungal communities along environmental gradients.

  6. Goal inferences about robot behavior : goal inferences and human response behaviors

    NARCIS (Netherlands)

    Broers, H.A.T.; Ham, J.R.C.; Broeders, R.; De Silva, P.; Okada, M.

    2014-01-01

    This explorative research focused on the goal inferences human observers draw based on a robot's behavior, and the extent to which those inferences predict people's behavior in response to that robot. Results show that different robot behaviors cause different response behavior from people.

  7. Interaction of Uranium with Bacterial Cell Surfaces: Inferences from Phosphatase-Mediated Uranium Precipitation

    Science.gov (United States)

    Kulkarni, Sayali; Misra, Chitra Seetharam; Gupta, Alka; Ballal, Anand

    2016-01-01

    ABSTRACT Deinococcus radiodurans and Escherichia coli expressing either PhoN, a periplasmic acid phosphatase, or PhoK, an extracellular alkaline phosphatase, were evaluated for uranium (U) bioprecipitation under two specific geochemical conditions (GCs): (i) a carbonate-deficient condition at near-neutral pH (GC1), and (ii) a carbonate-abundant condition at alkaline pH (GC2). Transmission electron microscopy revealed that recombinant cells expressing PhoN/PhoK formed cell-associated uranyl phosphate precipitate under GC1, whereas the same cells displayed extracellular precipitation under GC2. These results implied that the cell-bound or extracellular location of the precipitate was governed by the uranyl species prevalent at that particular GC, rather than the location of phosphatase. MINTEQ modeling predicted the formation of predominantly positively charged uranium hydroxide ions under GC1 and negatively charged uranyl carbonate-hydroxide complexes under GC2. Both microbes adsorbed 6- to 10-fold more U under GC1 than under GC2, suggesting that higher biosorption of U to the bacterial cell surface under GC1 may lead to cell-associated U precipitation. In contrast, at alkaline pH and in the presence of excess carbonate under GC2, poor biosorption of negatively charged uranyl carbonate complexes on the cell surface might have resulted in extracellular precipitation. The toxicity of U observed under GC1 being higher than that under GC2 could also be attributed to the preferential adsorption of U on cell surfaces under GC1. This work provides a vivid description of the interaction of U complexes with bacterial cells. The findings have implications for the toxicity of various U species and for developing biological aqueous effluent waste treatment strategies. IMPORTANCE The present study provides illustrative insights into the interaction of uranium (U) complexes with recombinant bacterial cells overexpressing phosphatases. This work demonstrates the effects of aqueous

  8. From inter-specific behavioural interactions to species distribution patterns along gradients of habitat heterogeneity.

    Science.gov (United States)

    Laiolo, Paola

    2013-01-01

    The strength of the behavioural processes associated with competitor coexistence may vary when different physical environments, and their biotic communities, come into contact, although empirical evidence of how interference varies across gradients of environmental complexity is still scarce in vertebrates. Here, I analyse how behavioural interactions and habitat selection regulate the local distribution of steppeland larks (Alaudidae) in a gradient from simple to heterogeneous agricultural landscapes in Spain, using crested lark Galerida cristata and Thekla lark G. theklae as study models. Galerida larks significantly partitioned by habitat but frequently co-occurred in heterogeneous environments. Irrespective of habitat divergence, however, the local densities of the two larks were negatively correlated, and the mechanisms beyond this pattern were investigated by means of playback experiments. When simulating the intrusion of the congener by broadcasting the species territorial calls, both larks responded with an aggressive response as intense with respect to warning and approach behaviour as when responding to the intrusion of a conspecific. However, birds promptly responded to playbacks only when congener territories were nearby, a phenomenon that points to learning as the mechanisms through which individuals finely tune their aggressive responses to the local competition levels. Heterospecifics occurred in closer proximity in diverse agro-ecosystems, possibly because of more abundant or diverse resources, and here engage in antagonistic interactions. The drop of species diversity associated with agricultural homogenisation is therefore likely to also bring about the disappearance of the behavioural repertoires associated with species interactions.

  9. ROUNDTABLE SESSION 2B: NATIONAL INTERACTIONS BETWEEN NON-INDIGENOUS AND INDIGENOUS CRAYFISH SPECIES

    Directory of Open Access Journals (Sweden)

    GHERARDI F.

    2002-07-01

    Full Text Available The main object of the present essay is to summarise some aspects underlying the interactions between non-indigenous (NICS and indigenous (ICS crayfish species. The discussion has been also extended to the effects exercised by NICS on the natural habitats they occupy. While doing research on the dyads NICS/ICS, one starting point is to extrapolate common traits that make NICS good invaders from the analysis of their biology, ecology and ethology and the comparison with indigenous species. A subsequent step is to switch attention to the understanding of the characteristics that make ecosystems less vulnerable to invasions and then to analyse both the complex interactions of invaders and target communities and the negative and positive impacts exerted by NICS on the occupied habitats. Examples from Sweden, Britain, and Italy have shown that NICS can replace the native species by a combination of several interacting mechanisms. Besides the transmission of the crayfish plague fungus, mechanisms into action include mostly competitive interference, but also diverse life history traits, recruitment failure, differential susceptibility to predation, and reproductive interference. It has been claimed that invasion theory is full of rules of thumb that, having no precise predictive powers, are thus useless to guide reliable public policy. The solution of the prediction problem requires an in-depth study of every potential invader and target community, trespassing the boundaries among disciplines and having a look at crayfish as a whole and not a single entity. The expectation is thus the return to precise and clear empirical generalisations that can be most useful to develop management strategies.

  10. Process-based species pools reveal the hidden signature of biotic interactions amid the influence of temperature filtering

    DEFF Research Database (Denmark)

    Lessard, Jean-Philippe; Weinstein, Ben G.; Borregaard, Michael Krabbe

    2016-01-01

    A persistent challenge in ecology is to tease apart the in-fluence of multiple processes acting simultaneously and interacting in complex ways to shape the structure of species assemblages. We implement a heuristic approach that relies on explicitly defining spe-cies pools and permits assessment ...

  11. Genetic population structure of the desert shrub species lycium ruthenicum inferred from chloroplast dna

    International Nuclear Information System (INIS)

    Chen, H.; Yonezawa, T.

    2014-01-01

    Lycium ruthenicum (Solananeae), a spiny shrub mostly distributed in the desert regions of north and northwest China, has been shown to exhibit high tolerance to the extreme environment. In this study, the phylogeography and evolutionary history of L. ruthenicum were examined, on the basis of 80 individuals from eight populations. Using the sequence variations of two spacer regions of chloroplast DNA (trnH-psbA and rps16-trnK) , the absence of a geographic component in the chloroplast DNA genetic structure was identified (GST = 0.351, NST = 0.304, NST< GST), which was consisted with the result of SAMOVA, suggesting weak phylogeographic structure of this species. Phylogenetic and network analyses showed that a total of 10 haplotypes identified in the present study clustered into two clades, in which clade I harbored the ancestral haplotypes that inferred two independent glacial refugia in the middle of Qaidam Basin and the western Inner Mongolia. The existence of regional evolutionary differences was supported by GENETREE, which revealed that one of the population in Qaidam Basin and the two populations in Tarim Basin had experienced rapid expansion, and the other populations retained relatively stable population size during the Pleistocene . Given the results of long-term gene flow and pairwise differences, strong gene flow was insufficient to reduce the genetic differentiation among populations or within populations, probably due to the genetic composition containing a common haplotype and the high number of private haplotypes fixed for most of the population. The divergence times of different lineages were consistent with the rapid uplift phases of the Qinghai-Tibetan Plateau and the initiation and expansion of deserts in northern China, suggesting that the origin and evolution of L. ruthenicum were strongly influenced by Quaternary environment changes. (author)

  12. Entropic Inference

    OpenAIRE

    Caticha, Ariel

    2010-01-01

    In this tutorial we review the essential arguments behing entropic inference. We focus on the epistemological notion of information and its relation to the Bayesian beliefs of rational agents. The problem of updating from a prior to a posterior probability distribution is tackled through an eliminative induction process that singles out the logarithmic relative entropy as the unique tool for inference. The resulting method of Maximum relative Entropy (ME), includes as special cases both MaxEn...

  13. The multidimensional behavioural hypervolumes of two interacting species predict their space use and survival.

    Science.gov (United States)

    Lichtenstein, James L L; Wright, Colin M; McEwen, Brendan; Pinter-Wollman, Noa; Pruitt, Jonathan N

    2017-10-01

    Individual animals differ consistently in their behaviour, thus impacting a wide variety of ecological outcomes. Recent advances in animal personality research have established the ecological importance of the multidimensional behavioural volume occupied by individuals and by multispecies communities. Here, we examine the degree to which the multidimensional behavioural volume of a group predicts the outcome of both intra- and interspecific interactions. In particular, we test the hypothesis that a population of conspecifics will experience low intraspecific competition when the population occupies a large volume in behavioural space. We further hypothesize that populations of interacting species will exhibit greater interspecific competition when one or both species occupy large volumes in behavioural space. We evaluate these hypotheses by studying groups of katydids ( Scudderia nymphs) and froghoppers ( Philaenus spumarius ), which compete for food and space on their shared host plant, Solidago canadensis . We found that individuals in single-species groups of katydids positioned themselves closer to one another, suggesting reduced competition, when groups occupied a large behavioural volume. When both species were placed together, we found that the survival of froghoppers was greatest when both froghoppers and katydids occupied a small volume in behavioural space, particularly at high froghopper densities. These results suggest that groups that occupy large behavioural volumes can have low intraspecific competition but high interspecific competition. Thus, behavioural hypervolumes appear to have ecological consequences at both the level of the population and the community and may help to predict the intensity of competition both within and across species.

  14. Inferring regulatory networks from expression data using tree-based methods.

    Directory of Open Access Journals (Sweden)

    Vân Anh Huynh-Thu

    2010-09-01

    Full Text Available One of the pressing open problems of computational systems biology is the elucidation of the topology of genetic regulatory networks (GRNs using high throughput genomic data, in particular microarray gene expression data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM challenge aims to evaluate the success of GRN inference algorithms on benchmarks of simulated data. In this article, we present GENIE3, a new algorithm for the inference of GRNs that was best performer in the DREAM4 In Silico Multifactorial challenge. GENIE3 decomposes the prediction of a regulatory network between p genes into p different regression problems. In each of the regression problems, the expression pattern of one of the genes (target gene is predicted from the expression patterns of all the other genes (input genes, using tree-based ensemble methods Random Forests or Extra-Trees. The importance of an input gene in the prediction of the target gene expression pattern is taken as an indication of a putative regulatory link. Putative regulatory links are then aggregated over all genes to provide a ranking of interactions from which the whole network is reconstructed. In addition to performing well on the DREAM4 In Silico Multifactorial challenge simulated data, we show that GENIE3 compares favorably with existing algorithms to decipher the genetic regulatory network of Escherichia coli. It doesn't make any assumption about the nature of gene regulation, can deal with combinatorial and non-linear interactions, produces directed GRNs, and is fast and scalable. In conclusion, we propose a new algorithm for GRN inference that performs well on both synthetic and real gene expression data. The algorithm, based on feature selection with tree-based ensemble methods, is simple and generic, making it adaptable to other types of genomic data and interactions.

  15. Geographical patterns of adaptation within a species' range : Interactions between drift and gene flow

    NARCIS (Netherlands)

    Alleaume-Benharira, M; Pen, IR; Ronce, O

    We use individual-based stochastic simulations and analytical deterministic predictions to investigate the interaction between drift, natural selection and gene flow on the patterns of local adaptation across a fragmented species' range under clinally varying selection. Migration between populations

  16. The robustness of pollination networks to the loss of species and interactions: a quantitative approach incorporating pollinator behaviour.

    Science.gov (United States)

    Kaiser-Bunbury, Christopher N; Muff, Stefanie; Memmott, Jane; Müller, Christine B; Caflisch, Amedeo

    2010-04-01

    Species extinctions pose serious threats to the functioning of ecological communities worldwide. We used two qualitative and quantitative pollination networks to simulate extinction patterns following three removal scenarios: random removal and systematic removal of the strongest and weakest interactors. We accounted for pollinator behaviour by including potential links into temporal snapshots (12 consecutive 2-week networks) to reflect mutualists' ability to 'switch' interaction partners (re-wiring). Qualitative data suggested a linear or slower than linear secondary extinction while quantitative data showed sigmoidal decline of plant interaction strength upon removal of the strongest interactor. Temporal snapshots indicated greater stability of re-wired networks over static systems. Tolerance of generalized networks to species extinctions was high in the random removal scenario, with an increase in network stability if species formed new interactions. Anthropogenic disturbance, however, that promote the extinction of the strongest interactors might induce a sudden collapse of pollination networks.

  17. Impact of interspecific interactions on the soil water uptake depth in a young temperate mixed species plantation

    Science.gov (United States)

    Grossiord, Charlotte; Gessler, Arthur; Granier, André; Berger, Sigrid; Bréchet, Claude; Hentschel, Rainer; Hommel, Robert; Scherer-Lorenzen, Michael; Bonal, Damien

    2014-11-01

    Interactions between tree species in forests can be beneficial to ecosystem functions and services related to the carbon and water cycles by improving for example transpiration and productivity. However, little is known on below- and above-ground processes leading to these positive effects. We tested whether stratification in soil water uptake depth occurred between four tree species in a 10-year-old temperate mixed species plantation during a dry summer. We selected dominant and co-dominant trees of European beech, Sessile oak, Douglas fir and Norway spruce in areas with varying species diversity, competition intensity, and where different plant functional types (broadleaf vs. conifer) were present. We applied a deuterium labelling approach that consisted of spraying labelled water to the soil surface to create a strong vertical gradient of the deuterium isotope composition in the soil water. The deuterium isotope composition of both the xylem sap and the soil water was measured before labelling, and then again three days after labelling, to estimate the soil water uptake depth using a simple modelling approach. We also sampled leaves and needles from selected trees to measure their carbon isotope composition (a proxy for water use efficiency) and total nitrogen content. At the end of the summer, we found differences in the soil water uptake depth between plant functional types but not within types: on average, coniferous species extracted water from deeper layers than did broadleaved species. Neither species diversity nor competition intensity had a detectable influence on soil water uptake depth, foliar water use efficiency or foliar nitrogen concentration in the species studied. However, when coexisting with an increasing proportion of conifers, beech extracted water from progressively deeper soil layers. We conclude that complementarity for water uptake could occur in this 10-year-old plantation because of inherent differences among functional groups (conifers

  18. Interactive influences of wildfire and nonnative species on plant community succession in Hawaii Volcanoes National Park.

    Science.gov (United States)

    Alison Ainsworth

    2007-01-01

    The role of fire as a natural disturbance, its interactions with nonnative species and effects of repeated fires in the Hawaiian Islands have received little investigation. We are unsure of the role fire played in shaping forest structure and composition as well as affecting evolutionary processes of the native biota. Yet, many species do have adaptations that...

  19. Learning Convex Inference of Marginals

    OpenAIRE

    Domke, Justin

    2012-01-01

    Graphical models trained using maximum likelihood are a common tool for probabilistic inference of marginal distributions. However, this approach suffers difficulties when either the inference process or the model is approximate. In this paper, the inference process is first defined to be the minimization of a convex function, inspired by free energy approximations. Learning is then done directly in terms of the performance of the inference process at univariate marginal prediction. The main ...

  20. Inference of reactive transport model parameters using a Bayesian multivariate approach

    Science.gov (United States)

    Carniato, Luca; Schoups, Gerrit; van de Giesen, Nick

    2014-08-01

    Parameter estimation of subsurface transport models from multispecies data requires the definition of an objective function that includes different types of measurements. Common approaches are weighted least squares (WLS), where weights are specified a priori for each measurement, and weighted least squares with weight estimation (WLS(we)) where weights are estimated from the data together with the parameters. In this study, we formulate the parameter estimation task as a multivariate Bayesian inference problem. The WLS and WLS(we) methods are special cases in this framework, corresponding to specific prior assumptions about the residual covariance matrix. The Bayesian perspective allows for generalizations to cases where residual correlation is important and for efficient inference by analytically integrating out the variances (weights) and selected covariances from the joint posterior. Specifically, the WLS and WLS(we) methods are compared to a multivariate (MV) approach that accounts for specific residual correlations without the need for explicit estimation of the error parameters. When applied to inference of reactive transport model parameters from column-scale data on dissolved species concentrations, the following results were obtained: (1) accounting for residual correlation between species provides more accurate parameter estimation for high residual correlation levels whereas its influence for predictive uncertainty is negligible, (2) integrating out the (co)variances leads to an efficient estimation of the full joint posterior with a reduced computational effort compared to the WLS(we) method, and (3) in the presence of model structural errors, none of the methods is able to identify the correct parameter values.

  1. Network inference from functional experimental data (Conference Presentation)

    Science.gov (United States)

    Desrosiers, Patrick; Labrecque, Simon; Tremblay, Maxime; Bélanger, Mathieu; De Dorlodot, Bertrand; Côté, Daniel C.

    2016-03-01

    Functional connectivity maps of neuronal networks are critical tools to understand how neurons form circuits, how information is encoded and processed by neurons, how memory is shaped, and how these basic processes are altered under pathological conditions. Current light microscopy allows to observe calcium or electrical activity of thousands of neurons simultaneously, yet assessing comprehensive connectivity maps directly from such data remains a non-trivial analytical task. There exist simple statistical methods, such as cross-correlation and Granger causality, but they only detect linear interactions between neurons. Other more involved inference methods inspired by information theory, such as mutual information and transfer entropy, identify more accurately connections between neurons but also require more computational resources. We carried out a comparative study of common connectivity inference methods. The relative accuracy and computational cost of each method was determined via simulated fluorescence traces generated with realistic computational models of interacting neurons in networks of different topologies (clustered or non-clustered) and sizes (10-1000 neurons). To bridge the computational and experimental works, we observed the intracellular calcium activity of live hippocampal neuronal cultures infected with the fluorescent calcium marker GCaMP6f. The spontaneous activity of the networks, consisting of 50-100 neurons per field of view, was recorded from 20 to 50 Hz on a microscope controlled by a homemade software. We implemented all connectivity inference methods in the software, which rapidly loads calcium fluorescence movies, segments the images, extracts the fluorescence traces, and assesses the functional connections (with strengths and directions) between each pair of neurons. We used this software to assess, in real time, the functional connectivity from real calcium imaging data in basal conditions, under plasticity protocols, and epileptic

  2. Inferring probabilistic stellar rotation periods using Gaussian processes

    Science.gov (United States)

    Angus, Ruth; Morton, Timothy; Aigrain, Suzanne; Foreman-Mackey, Daniel; Rajpaul, Vinesh

    2018-02-01

    Variability in the light curves of spotted, rotating stars is often non-sinusoidal and quasi-periodic - spots move on the stellar surface and have finite lifetimes, causing stellar flux variations to slowly shift in phase. A strictly periodic sinusoid therefore cannot accurately model a rotationally modulated stellar light curve. Physical models of stellar surfaces have many drawbacks preventing effective inference, such as highly degenerate or high-dimensional parameter spaces. In this work, we test an appropriate effective model: a Gaussian Process with a quasi-periodic covariance kernel function. This highly flexible model allows sampling of the posterior probability density function of the periodic parameter, marginalizing over the other kernel hyperparameters using a Markov Chain Monte Carlo approach. To test the effectiveness of this method, we infer rotation periods from 333 simulated stellar light curves, demonstrating that the Gaussian process method produces periods that are more accurate than both a sine-fitting periodogram and an autocorrelation function method. We also demonstrate that it works well on real data, by inferring rotation periods for 275 Kepler stars with previously measured periods. We provide a table of rotation periods for these and many more, altogether 1102 Kepler objects of interest, and their posterior probability density function samples. Because this method delivers posterior probability density functions, it will enable hierarchical studies involving stellar rotation, particularly those involving population modelling, such as inferring stellar ages, obliquities in exoplanet systems, or characterizing star-planet interactions. The code used to implement this method is available online.

  3. Periodic and chaotic events in a discrete model of logistic type for the competitive interaction of two species

    International Nuclear Information System (INIS)

    Lopez-Ruiz, Ricardo; Fournier-Prunaret, Daniele

    2009-01-01

    Two symmetrically coupled logistic equations are proposed to mimic the competitive interaction between two species. The phenomena of coexistence, oscillations and chaos are present in this cubic discrete system. This work, together with two other similar ones recently published by the authors, completes a triptych dedicated to the two species relationships present in Nature, namely the symbiosis, the predator-prey and the competition. These models can be used as basic ingredients to build up more complex interactions in the ecological networks.

  4. Probabilistic inductive inference: a survey

    OpenAIRE

    Ambainis, Andris

    2001-01-01

    Inductive inference is a recursion-theoretic theory of learning, first developed by E. M. Gold (1967). This paper surveys developments in probabilistic inductive inference. We mainly focus on finite inference of recursive functions, since this simple paradigm has produced the most interesting (and most complex) results.

  5. LAIT: a local ancestry inference toolkit.

    Science.gov (United States)

    Hui, Daniel; Fang, Zhou; Lin, Jerome; Duan, Qing; Li, Yun; Hu, Ming; Chen, Wei

    2017-09-06

    Inferring local ancestry in individuals of mixed ancestry has many applications, most notably in identifying disease-susceptible loci that vary among different ethnic groups. Many software packages are available for inferring local ancestry in admixed individuals. However, most of these existing software packages require specific formatted input files and generate output files in various types, yielding practical inconvenience. We developed a tool set, Local Ancestry Inference Toolkit (LAIT), which can convert standardized files into software-specific input file formats as well as standardize and summarize inference results for four popular local ancestry inference software: HAPMIX, LAMP, LAMP-LD, and ELAI. We tested LAIT using both simulated and real data sets and demonstrated that LAIT provides convenience to run multiple local ancestry inference software. In addition, we evaluated the performance of local ancestry software among different supported software packages, mainly focusing on inference accuracy and computational resources used. We provided a toolkit to facilitate the use of local ancestry inference software, especially for users with limited bioinformatics background.

  6. Bayesian statistical inference

    Directory of Open Access Journals (Sweden)

    Bruno De Finetti

    2017-04-01

    Full Text Available This work was translated into English and published in the volume: Bruno De Finetti, Induction and Probability, Biblioteca di Statistica, eds. P. Monari, D. Cocchi, Clueb, Bologna, 1993.Bayesian statistical Inference is one of the last fundamental philosophical papers in which we can find the essential De Finetti's approach to the statistical inference.

  7. Inference of Transmission Network Structure from HIV Phylogenetic Trees.

    Science.gov (United States)

    Giardina, Federica; Romero-Severson, Ethan Obie; Albert, Jan; Britton, Tom; Leitner, Thomas

    2017-01-01

    Phylogenetic inference is an attractive means to reconstruct transmission histories and epidemics. However, there is not a perfect correspondence between transmission history and virus phylogeny. Both node height and topological differences may occur, depending on the interaction between within-host evolutionary dynamics and between-host transmission patterns. To investigate these interactions, we added a within-host evolutionary model in epidemiological simulations and examined if the resulting phylogeny could recover different types of contact networks. To further improve realism, we also introduced patient-specific differences in infectivity across disease stages, and on the epidemic level we considered incomplete sampling and the age of the epidemic. Second, we implemented an inference method based on approximate Bayesian computation (ABC) to discriminate among three well-studied network models and jointly estimate both network parameters and key epidemiological quantities such as the infection rate. Our ABC framework used both topological and distance-based tree statistics for comparison between simulated and observed trees. Overall, our simulations showed that a virus time-scaled phylogeny (genealogy) may be substantially different from the between-host transmission tree. This has important implications for the interpretation of what a phylogeny reveals about the underlying epidemic contact network. In particular, we found that while the within-host evolutionary process obscures the transmission tree, the diversification process and infectivity dynamics also add discriminatory power to differentiate between different types of contact networks. We also found that the possibility to differentiate contact networks depends on how far an epidemic has progressed, where distance-based tree statistics have more power early in an epidemic. Finally, we applied our ABC inference on two different outbreaks from the Swedish HIV-1 epidemic.

  8. Is there a hierarchy of social inferences? The likelihood and speed of inferring intentionality, mind, and personality.

    Science.gov (United States)

    Malle, Bertram F; Holbrook, Jess

    2012-04-01

    People interpret behavior by making inferences about agents' intentionality, mind, and personality. Past research studied such inferences 1 at a time; in real life, people make these inferences simultaneously. The present studies therefore examined whether 4 major inferences (intentionality, desire, belief, and personality), elicited simultaneously in response to an observed behavior, might be ordered in a hierarchy of likelihood and speed. To achieve generalizability, the studies included a wide range of stimulus behaviors, presented them verbally and as dynamic videos, and assessed inferences both in a retrieval paradigm (measuring the likelihood and speed of accessing inferences immediately after they were made) and in an online processing paradigm (measuring the speed of forming inferences during behavior observation). Five studies provide evidence for a hierarchy of social inferences-from intentionality and desire to belief to personality-that is stable across verbal and visual presentations and that parallels the order found in developmental and primate research. (c) 2012 APA, all rights reserved.

  9. Interaction of species traits and environmental disturbance predicts invasion success of aquatic microorganisms.

    Directory of Open Access Journals (Sweden)

    Elvira Mächler

    Full Text Available Factors such as increased mobility of humans, global trade and climate change are affecting the range of many species, and cause large-scale translocations of species beyond their native range. Many introduced species have a strong negative influence on the new local environment and lead to high economic costs. There is a strong interest to understand why some species are successful in invading new environments and others not. Most of our understanding and generalizations thereof, however, are based on studies of plants and animals, and little is known on invasion processes of microorganisms. We conducted a microcosm experiment to understand factors promoting the success of biological invasions of aquatic microorganisms. In a controlled lab experiment, protist and rotifer species originally isolated in North America invaded into a natural, field-collected community of microorganisms of European origin. To identify the importance of environmental disturbances on invasion success, we either repeatedly disturbed the local patches, or kept them as undisturbed controls. We measured both short-term establishment and long-term invasion success, and correlated it with species-specific life-history traits. We found that environmental disturbances significantly affected invasion success. Depending on the invading species' identity, disturbances were either promoting or decreasing invasion success. The interaction between habitat disturbance and species identity was especially pronounced for long-term invasion success. Growth rate was the most important trait promoting invasion success, especially when the species invaded into a disturbed local community. We conclude that neither species traits nor environmental factors alone conclusively predict invasion success, but an integration of both of them is necessary.

  10. Pathogenomic inference of virulence-associated genes in Leptospira interrogans.

    Science.gov (United States)

    Lehmann, Jason S; Fouts, Derrick E; Haft, Daniel H; Cannella, Anthony P; Ricaldi, Jessica N; Brinkac, Lauren; Harkins, Derek; Durkin, Scott; Sanka, Ravi; Sutton, Granger; Moreno, Angelo; Vinetz, Joseph M; Matthias, Michael A

    2013-01-01

    Leptospirosis is a globally important, neglected zoonotic infection caused by spirochetes of the genus Leptospira. Since genetic transformation remains technically limited for pathogenic Leptospira, a systems biology pathogenomic approach was used to infer leptospiral virulence genes by whole genome comparison of culture-attenuated Leptospira interrogans serovar Lai with its virulent, isogenic parent. Among the 11 pathogen-specific protein-coding genes in which non-synonymous mutations were found, a putative soluble adenylate cyclase with host cell cAMP-elevating activity, and two members of a previously unstudied ∼15 member paralogous gene family of unknown function were identified. This gene family was also uniquely found in the alpha-proteobacteria Bartonella bacilliformis and Bartonella australis that are geographically restricted to the Andes and Australia, respectively. How the pathogenic Leptospira and these two Bartonella species came to share this expanded gene family remains an evolutionary mystery. In vivo expression analyses demonstrated up-regulation of 10/11 Leptospira genes identified in the attenuation screen, and profound in vivo, tissue-specific up-regulation by members of the paralogous gene family, suggesting a direct role in virulence and host-pathogen interactions. The pathogenomic experimental design here is generalizable as a functional systems biology approach to studying bacterial pathogenesis and virulence and should encourage similar experimental studies of other pathogens.

  11. INFERENCE BUILDING BLOCKS

    Science.gov (United States)

    2018-02-15

    expressed a variety of inference techniques on discrete and continuous distributions: exact inference, importance sampling, Metropolis-Hastings (MH...without redoing any math or rewriting any code. And although our main goal is composable reuse, our performance is also good because we can use...control paths. • The Hakaru language can express mixtures of discrete and continuous distributions, but the current disintegration transformation

  12. Practical Bayesian Inference

    Science.gov (United States)

    Bailer-Jones, Coryn A. L.

    2017-04-01

    Preface; 1. Probability basics; 2. Estimation and uncertainty; 3. Statistical models and inference; 4. Linear models, least squares, and maximum likelihood; 5. Parameter estimation: single parameter; 6. Parameter estimation: multiple parameters; 7. Approximating distributions; 8. Monte Carlo methods for inference; 9. Parameter estimation: Markov chain Monte Carlo; 10. Frequentist hypothesis testing; 11. Model comparison; 12. Dealing with more complicated problems; References; Index.

  13. Inference of the Genetic Network Regulating Lateral Root Initiation in Arabidopsis thaliana

    KAUST Repository

    Muraro, D.

    2013-01-01

    Regulation of gene expression is crucial for organism growth, and it is one of the challenges in systems biology to reconstruct the underlying regulatory biological networks from transcriptomic data. The formation of lateral roots in Arabidopsis thaliana is stimulated by a cascade of regulators of which only the interactions of its initial elements have been identified. Using simulated gene expression data with known network topology, we compare the performance of inference algorithms, based on different approaches, for which ready-to-use software is available. We show that their performance improves with the network size and the inclusion of mutants. We then analyze two sets of genes, whose activity is likely to be relevant to lateral root initiation in Arabidopsis, and assess causality of their regulatory interactions by integrating sequence analysis with the intersection of the results of the best performing methods on time series and mutants. The methods applied capture known interactions between genes that are candidate regulators at early stages of development. The network inferred from genes significantly expressed during lateral root formation exhibits distinct scale free, small world and hierarchical properties and the nodes with a high out-degree may warrant further investigation. © 2004-2012 IEEE.

  14. Integration of steady-state and temporal gene expression data for the inference of gene regulatory networks.

    Science.gov (United States)

    Wang, Yi Kan; Hurley, Daniel G; Schnell, Santiago; Print, Cristin G; Crampin, Edmund J

    2013-01-01

    We develop a new regression algorithm, cMIKANA, for inference of gene regulatory networks from combinations of steady-state and time-series gene expression data. Using simulated gene expression datasets to assess the accuracy of reconstructing gene regulatory networks, we show that steady-state and time-series data sets can successfully be combined to identify gene regulatory interactions using the new algorithm. Inferring gene networks from combined data sets was found to be advantageous when using noisy measurements collected with either lower sampling rates or a limited number of experimental replicates. We illustrate our method by applying it to a microarray gene expression dataset from human umbilical vein endothelial cells (HUVECs) which combines time series data from treatment with growth factor TNF and steady state data from siRNA knockdown treatments. Our results suggest that the combination of steady-state and time-series datasets may provide better prediction of RNA-to-RNA interactions, and may also reveal biological features that cannot be identified from dynamic or steady state information alone. Finally, we consider the experimental design of genomics experiments for gene regulatory network inference and show that network inference can be improved by incorporating steady-state measurements with time-series data.

  15. Plant Water Stress Affects Interactions Between an Invasive and a Naturalized Aphid Species on Cereal Crops.

    Science.gov (United States)

    Foote, N E; Davis, T S; Crowder, D W; Bosque-Pérez, N A; Eigenbrode, S D

    2017-06-01

    In cereal cropping systems of the Pacific Northwestern United States (PNW), climate change is projected to increase the frequency of drought during summer months, which could increase water stress for crop plants. Yet, it remains uncertain how interactions between herbivore species are affected by drought stress. Here, interactions between two cereal aphids present in PNW cereal systems, Metopolophium festucae (Theobald) subsp. cerealium (a newly invasive species) and Rhopalosiphum padi L. (a naturalized species), were tested relative to wheat water stress. When aphids were confined in leaf cages on wheat, asymmetrical facilitation occurred; per capita fecundity of R. padi was increased by 46% when M. festucae cerealium was also present, compared to when only R. padi was present. Imposed water stress did not influence this interaction. When aphids were confined on whole wheat plants, asymmetrical competition occurred; cocolonization inhibited M. festucae cerealium population growth but did not affect R. padi population growth. Under conditions of plant water stress, however, the inhibitory effect of R. padi on M. festucae cerealium was not observed. We conclude that beneficial effects of cocolonization on R. padi are due to a localized plant response to M. festucae cerealium feeding, and that cocolonization of plants is likely to suppress M. festucae cerealium populations under ample water conditions, but not when plants are water stressed. This suggests that plant responses to water stress alter the outcome of competition between herbivore species, with implications for the structure of pest communities on wheat during periods of drought. © The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America.

  16. Species interactions within a fouling diatom community: Roles of nutrients, initial inoculum and competitive strategies

    Digital Repository Service at National Institute of Oceanography (India)

    Mitbavkar, S.; Anil, A

    Diatoms constitute an important component of the fouling community. Although a lot of work has dealt with the fouling diatom community structure, work on the species interactions within the community is still meager. In this regard, a study...

  17. Role of Temporal Diversity in Inferring Social Ties Based on Spatio-Temporal Data

    OpenAIRE

    Desai, Deshana; Nisar, Harsh; Bhardawaj, Rishab

    2016-01-01

    The last two decades have seen a tremendous surge in research on social networks and their implications. The studies includes inferring social relationships, which in turn have been used for target advertising, recommendations, search customization etc. However, the offline experiences of human, the conversations with people and face-to-face interactions that govern our lives interactions have received lesser attention. We introduce DAIICT Spatio-Temporal Network (DSSN), a spatiotemporal data...

  18. Logical inference and evaluation

    International Nuclear Information System (INIS)

    Perey, F.G.

    1981-01-01

    Most methodologies of evaluation currently used are based upon the theory of statistical inference. It is generally perceived that this theory is not capable of dealing satisfactorily with what are called systematic errors. Theories of logical inference should be capable of treating all of the information available, including that not involving frequency data. A theory of logical inference is presented as an extension of deductive logic via the concept of plausibility and the application of group theory. Some conclusions, based upon the application of this theory to evaluation of data, are also given

  19. Evolutionary responses of native plant species to invasive plants : a review

    OpenAIRE

    Oduor, Ayub M. O.

    2013-01-01

    Strong competition from invasive plant species often leads to declines in abundances and may,in certain cases, cause localized extinctions of native plant species. Nevertheless, studies have shown that certain populations of native plant species can co-exist with invasive plant species, suggesting the possibility of adaptive evolutionary responses of those populations to the invasive plants. Empirical inference of evolutionary responses of the native plant species to invasive plants has invol...

  20. Effects of plant diversity on primary production and species interactions in brackish water angiosperm communities

    DEFF Research Database (Denmark)

    Salo, Tiina; Gustafsson, Camilla; Boström, Christoffer

    2009-01-01

    Research on plant biodiversity and ecosystem functioning has mainly focused on terrestrial ecosystems, and our understanding of how plant species diversity and interactions affect processes in marine ecosystems is still limited. To investigate if plant species richness and composition influence...... plant productivity in brackish water angiosperm communities, a 14 wk field experiment was conducted. Using a replacement design with a standardized initial aboveground biomass, shoots of Zostera marina, Potamogeton filiformis and P. perfoliatus were planted on a shallow, sandy bottom in replicated...

  1. Diet Segregation between Cohabiting Builder and Inquiline Termite Species.

    Directory of Open Access Journals (Sweden)

    Daniela Faria Florencio

    Full Text Available How do termite inquilines manage to cohabit termitaria along with the termite builder species? With this in mind, we analysed one of the several strategies that inquilines could use to circumvent conflicts with their hosts, namely, the use of distinct diets. We inspected overlapping patterns for the diets of several cohabiting Neotropical termite species, as inferred from carbon and nitrogen isotopic signatures for termite individuals. Cohabitant communities from distinct termitaria presented overlapping diet spaces, indicating that they exploited similar diets at the regional scale. When such communities were split into their components, full diet segregation could be observed between builders and inquilines, at regional (environment-wide and local (termitarium scales. Additionally, diet segregation among inquilines themselves was also observed in the vast majority of inspected termitaria. Inquiline species distribution among termitaria was not random. Environmental-wide diet similarity, coupled with local diet segregation and deterministic inquiline distribution, could denounce interactions for feeding resources. However, inquilines and builders not sharing the same termitarium, and thus not subject to potential conflicts, still exhibited distinct diets. Moreover, the areas of the builder's diet space and that of its inquilines did not correlate negatively. Accordingly, the diet areas of builders which hosted inquilines were in average as large as the areas of builders hosting no inquilines. Such results indicate the possibility that dietary partitioning by these cohabiting termites was not majorly driven by current interactive constraints. Rather, it seems to be a result of traits previously fixed in the evolutionary past of cohabitants.

  2. Species-environment interactions changed by introduced herbivores in an oceanic high-mountain ecosystem.

    Science.gov (United States)

    Seguí, Jaume; López-Darias, Marta; Pérez, Antonio J; Nogales, Manuel; Traveset, Anna

    2017-01-05

    Summit areas of oceanic islands constitute some of the most isolated ecosystems on earth, highly vulnerable to climate change and introduced species. Within the unique high-elevation communities of Tenerife (Canary Islands), reproductive success and thus long-term survival of species may depend on environmental suitability as well as threat by introduced herbivores. By experimentally modifying the endemic and vulnerable species Viola cheiranthifolia along its entire altitudinal occurrence range, we studied plant performance, autofertility, pollen limitation and visitation rate and the interactive effect of grazing by non-native rabbits on them. We assessed the grazing effects by recording (1) the proportion of consumed plants and flowers along the gradient, (2) comparing fitness traits of herbivore-excluded plants along the gradient, and (3) comparing fitness traits, autofertility and pollen limitation between plants excluded from herbivores with unexcluded plants at the same locality. Our results showed that V. cheiranthifolia performance is mainly affected by inter-annual and microhabitat variability along the gradient, especially in the lowest edge. Despite the increasingly adverse environmental conditions, the plant showed no pollen limitation with elevation, which is attributed to the increase in autofertility levels (≥ 50% of reproductive output) and decrease in competition for pollinators at higher elevations. Plant fitness is, however, extremely reduced owing to the presence of non-native rabbits in the area (consuming more than 75% of the individuals in some localities), which in turn change plant trait-environment interactions along the gradient. Taken together, these findings indicate that the elevational variation found on plant performance results from the combined action of non-native rabbits with the microhabitat variability, exerting intricate ecological influences that threaten the survival of this violet species. Published by Oxford University

  3. Evolutionary Inference across Eukaryotes Identifies Specific Pressures Favoring Mitochondrial Gene Retention.

    Science.gov (United States)

    Johnston, Iain G; Williams, Ben P

    2016-02-24

    Since their endosymbiotic origin, mitochondria have lost most of their genes. Although many selective mechanisms underlying the evolution of mitochondrial genomes have been proposed, a data-driven exploration of these hypotheses is lacking, and a quantitatively supported consensus remains absent. We developed HyperTraPS, a methodology coupling stochastic modeling with Bayesian inference, to identify the ordering of evolutionary events and suggest their causes. Using 2015 complete mitochondrial genomes, we inferred evolutionary trajectories of mtDNA gene loss across the eukaryotic tree of life. We find that proteins comprising the structural cores of the electron transport chain are preferentially encoded within mitochondrial genomes across eukaryotes. A combination of high GC content and high protein hydrophobicity is required to explain patterns of mtDNA gene retention; a model that accounts for these selective pressures can also predict the success of artificial gene transfer experiments in vivo. This work provides a general method for data-driven inference of the ordering of evolutionary and progressive events, here identifying the distinct features shaping mitochondrial genomes of present-day species. Copyright © 2016 Elsevier Inc. All rights reserved.

  4. Uberon, an integrative multi-species anatomy ontology

    Science.gov (United States)

    2012-01-01

    We present Uberon, an integrated cross-species ontology consisting of over 6,500 classes representing a variety of anatomical entities, organized according to traditional anatomical classification criteria. The ontology represents structures in a species-neutral way and includes extensive associations to existing species-centric anatomical ontologies, allowing integration of model organism and human data. Uberon provides a necessary bridge between anatomical structures in different taxa for cross-species inference. It uses novel methods for representing taxonomic variation, and has proved to be essential for translational phenotype analyses. Uberon is available at http://uberon.org PMID:22293552

  5. Belowground Plant–Herbivore Interactions Vary among Climate-Driven Range-Expanding Plant Species with Different Degrees of Novel Chemistry

    Directory of Open Access Journals (Sweden)

    Rutger A. Wilschut

    2017-10-01

    Full Text Available An increasing number of studies report plant range expansions to higher latitudes and altitudes in response to global warming. However, consequences for interactions with other species in the novel ranges are poorly understood. Here, we examine how range-expanding plant species interact with root-feeding nematodes from the new range. Root-feeding nematodes are ubiquitous belowground herbivores that may impact the structure and composition of natural vegetation. Because of their ecological novelty, we hypothesized that range-expanding plant species will be less suitable hosts for root-feeding nematodes than native congeneric plant species. In greenhouse and lab trials we compared nematode preference and performance of two root-feeding nematode species between range-expanding plant species and their congeneric natives. In order to understand differences in nematode preferences, we compared root volatile profiles of all range-expanders and congeneric natives. Nematode preferences and performances differed substantially among the pairs of range-expanders and natives. The range-expander that had the most unique volatile profile compared to its related native was unattractive and a poor host for nematodes. Other range-expanding plant species that differed less in root chemistry from native congeners, also differed less in nematode attraction and performance. We conclude that the three climate-driven range-expanding plant species studied varied considerably in their chemical novelty compared to their congeneric natives, and therefore affected native root-feeding nematodes in species-specific ways. Our data suggest that through variation in chemical novelty, range-expanding plant species may vary in their impacts on belowground herbivores in the new range.

  6. Inferring selection in the Anopheles gambiae species complex: an example from immune-related serine protease inhibitors

    Directory of Open Access Journals (Sweden)

    Little Tom J

    2009-06-01

    Full Text Available Abstract Background Mosquitoes of the Anopheles gambiae species complex are the primary vectors of human malaria in sub-Saharan Africa. Many host genes have been shown to affect Plasmodium development in the mosquito, and so are expected to engage in an evolutionary arms race with the pathogen. However, there is little conclusive evidence that any of these mosquito genes evolve rapidly, or show other signatures of adaptive evolution. Methods Three serine protease inhibitors have previously been identified as candidate immune system genes mediating mosquito-Plasmodium interaction, and serine protease inhibitors have been identified as hot-spots of adaptive evolution in other taxa. Population-genetic tests for selection, including a recent multi-gene extension of the McDonald-Kreitman test, were applied to 16 serine protease inhibitors and 16 other genes sampled from the An. gambiae species complex in both East and West Africa. Results Serine protease inhibitors were found to show a marginally significant trend towards higher levels of amino acid diversity than other genes, and display extensive genetic structuring associated with the 2La chromosomal inversion. However, although serpins are candidate targets for strong parasite-mediated selection, no evidence was found for rapid adaptive evolution in these genes. Conclusion It is well known that phylogenetic and population history in the An. gambiae complex can present special problems for the application of standard population-genetic tests for selection, and this may explain the failure of this study to detect selection acting on serine protease inhibitors. The pitfalls of uncritically applying these tests in this species complex are highlighted, and the future prospects for detecting selection acting on the An. gambiae genome are discussed.

  7. Phylogenetic relationships of the genus Phanerochaete inferred from the internal transcribed spacer region

    Science.gov (United States)

    Theodorus H. de Koker; Karen K. Nakasone; Jacques Haarhof; Harold H. Burdsall; Bernard J.H. Janse

    2003-01-01

    Phanerochaete is a genus of resupinate homobasidiomycetes that are saprophytic on woody debris and logs. Morphological studies in the past indicated that Phanerochaete is a heterogeneous assemblage of species. In this study the internal transcribed spacer (ITS) region of the nuclear ribosomal DNA was used to test the monophyly of the genus Phanerochaete and to infer...

  8. Hierarchical modeling and inference in ecology: The analysis of data from populations, metapopulations and communities

    Science.gov (United States)

    Royle, J. Andrew; Dorazio, Robert M.

    2008-01-01

    A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods. This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Hierarchical models represent a paradigm shift in the application of statistics to ecological inference problems because they combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The principles of hierarchical modeling are developed and applied to problems in population, metapopulation, community, and metacommunity systems. The book provides the first synthetic treatment of many recent methodological advances in ecological modeling and unifies disparate methods and procedures. The authors apply principles of hierarchical modeling to ecological problems, including * occurrence or occupancy models for estimating species distribution * abundance models based on many sampling protocols, including distance sampling * capture-recapture models with individual effects * spatial capture-recapture models based on camera trapping and related methods * population and metapopulation dynamic models * models of biodiversity, community structure and dynamics.

  9. Limitations of climatic data for inferring species boundaries: insights from speckled rattlesnakes.

    Directory of Open Access Journals (Sweden)

    Jesse M Meik

    Full Text Available Phenotypes, DNA, and measures of ecological differences are widely used in species delimitation. Although rarely defined in such studies, ecological divergence is almost always approximated using multivariate climatic data associated with sets of specimens (i.e., the "climatic niche"; the justification for this approach is that species-specific climatic envelopes act as surrogates for physiological tolerances. Using identical statistical procedures, we evaluated the usefulness and validity of the climate-as-proxy assumption by comparing performance of genetic (nDNA SNPs and mitochondrial DNA, phenotypic, and climatic data for objective species delimitation in the speckled rattlesnake (Crotalus mitchellii complex. Ordination and clustering patterns were largely congruent among intrinsic (heritable traits (nDNA, mtDNA, phenotype, and discordance is explained by biological processes (e.g., ontogeny, hybridization. In contrast, climatic data did not produce biologically meaningful clusters that were congruent with any intrinsic dataset, but rather corresponded to regional differences in atmospheric circulation and climate, indicating an absence of inherent taxonomic signal in these data. Surrogating climate for physiological tolerances adds artificial weight to evidence of species boundaries, as these data are irrelevant for that purpose. Based on the evidence from congruent clustering of intrinsic datasets, we recommend that three subspecies of C. mitchellii be recognized as species: C. angelensis, C. mitchellii, and C. Pyrrhus.

  10. Lower complexity bounds for lifted inference

    DEFF Research Database (Denmark)

    Jaeger, Manfred

    2015-01-01

    instances of the model. Numerous approaches for such “lifted inference” techniques have been proposed. While it has been demonstrated that these techniques will lead to significantly more efficient inference on some specific models, there are only very recent and still quite restricted results that show...... the feasibility of lifted inference on certain syntactically defined classes of models. Lower complexity bounds that imply some limitations for the feasibility of lifted inference on more expressive model classes were established earlier in Jaeger (2000; Jaeger, M. 2000. On the complexity of inference about...... that under the assumption that NETIME≠ETIME, there is no polynomial lifted inference algorithm for knowledge bases of weighted, quantifier-, and function-free formulas. Further strengthening earlier results, this is also shown to hold for approximate inference and for knowledge bases not containing...

  11. HitPredict version 4: comprehensive reliability scoring of physical protein-protein interactions from more than 100 species.

    Science.gov (United States)

    López, Yosvany; Nakai, Kenta; Patil, Ashwini

    2015-01-01

    HitPredict is a consolidated resource of experimentally identified, physical protein-protein interactions with confidence scores to indicate their reliability. The study of genes and their inter-relationships using methods such as network and pathway analysis requires high quality protein-protein interaction information. Extracting reliable interactions from most of the existing databases is challenging because they either contain only a subset of the available interactions, or a mixture of physical, genetic and predicted interactions. Automated integration of interactions is further complicated by varying levels of accuracy of database content and lack of adherence to standard formats. To address these issues, the latest version of HitPredict provides a manually curated dataset of 398 696 physical associations between 70 808 proteins from 105 species. Manual confirmation was used to resolve all issues encountered during data integration. For improved reliability assessment, this version combines a new score derived from the experimental information of the interactions with the original score based on the features of the interacting proteins. The combined interaction score performs better than either of the individual scores in HitPredict as well as the reliability score of another similar database. HitPredict provides a web interface to search proteins and visualize their interactions, and the data can be downloaded for offline analysis. Data usability has been enhanced by mapping protein identifiers across multiple reference databases. Thus, the latest version of HitPredict provides a significantly larger, more reliable and usable dataset of protein-protein interactions from several species for the study of gene groups. Database URL: http://hintdb.hgc.jp/htp. © The Author(s) 2015. Published by Oxford University Press.

  12. M-GCAT: interactively and efficiently constructing large-scale multiple genome comparison frameworks in closely related species

    Directory of Open Access Journals (Sweden)

    Messeguer Xavier

    2006-10-01

    Full Text Available Abstract Background Due to recent advances in whole genome shotgun sequencing and assembly technologies, the financial cost of decoding an organism's DNA has been drastically reduced, resulting in a recent explosion of genomic sequencing projects. This increase in related genomic data will allow for in depth studies of evolution in closely related species through multiple whole genome comparisons. Results To facilitate such comparisons, we present an interactive multiple genome comparison and alignment tool, M-GCAT, that can efficiently construct multiple genome comparison frameworks in closely related species. M-GCAT is able to compare and identify highly conserved regions in up to 20 closely related bacterial species in minutes on a standard computer, and as many as 90 (containing 75 cloned genomes from a set of 15 published enterobacterial genomes in an hour. M-GCAT also incorporates a novel comparative genomics data visualization interface allowing the user to globally and locally examine and inspect the conserved regions and gene annotations. Conclusion M-GCAT is an interactive comparative genomics tool well suited for quickly generating multiple genome comparisons frameworks and alignments among closely related species. M-GCAT is freely available for download for academic and non-commercial use at: http://alggen.lsi.upc.es/recerca/align/mgcat/intro-mgcat.html.

  13. Variations on Bayesian Prediction and Inference

    Science.gov (United States)

    2016-05-09

    inference 2.2.1 Background There are a number of statistical inference problems that are not generally formulated via a full probability model...problem of inference about an unknown parameter, the Bayesian approach requires a full probability 1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND...the problem of inference about an unknown parameter, the Bayesian approach requires a full probability model/likelihood which can be an obstacle

  14. Is the extremely rare Iberian endemic plant species Castrilanthemum debeauxii (Compositae, Anthemideae) a 'living fossil'? Evidence from a multi-locus species tree reconstruction.

    Science.gov (United States)

    Tomasello, Salvatore; Álvarez, Inés; Vargas, Pablo; Oberprieler, Christoph

    2015-01-01

    The present study provides results of multi-species coalescent species tree analyses of DNA sequences sampled from multiple nuclear and plastid regions to infer the phylogenetic relationships among the members of the subtribe Leucanthemopsidinae (Compositae, Anthemideae), to which besides the annual Castrilanthemum debeauxii (Degen, Hervier & É.Rev.) Vogt & Oberp., one of the rarest flowering plant species of the Iberian Peninsula, two other unispecific genera (Hymenostemma, Prolongoa), and the polyploidy complex of the genus Leucanthemopsis belong. Based on sequence information from two single- to low-copy nuclear regions (C16, D35, characterised by Chapman et al. (2007)), the multi-copy region of the nrDNA internal transcribed spacer regions ITS1 and ITS2, and two intergenic spacer regions of the cpDNA gene trees were reconstructed using Bayesian inference methods. For the reconstruction of a multi-locus species tree we applied three different methods: (a) analysis of concatenated sequences using Bayesian inference (MrBayes), (b) a tree reconciliation approach by minimizing the number of deep coalescences (PhyloNet), and (c) a coalescent-based species-tree method in a Bayesian framework ((∗)BEAST). All three species tree reconstruction methods unequivocally support the close relationship of the subtribe with the hitherto unclassified genus Phalacrocarpum, the sister-group relationship of Castrilanthemum with the three remaining genera of the subtribe, and the further sister-group relationship of the clade of Hymenostemma+Prolongoa with a monophyletic genus Leucanthemopsis. Dating of the (∗)BEAST phylogeny supports the long-lasting (Early Miocene, 15-22Ma) taxonomical independence and the switch from the plesiomorphic perennial to the apomorphic annual life-form assumed for the Castrilanthemum lineage that may have occurred not earlier than in the Pliocene (3Ma) when the establishment of a Mediterranean climate with summer droughts triggered evolution towards

  15. Early growth interactions between a mangrove and an herbaceous salt marsh species are not affected by elevated CO2 or drought

    Science.gov (United States)

    Howard, Rebecca J.; Stagg, Camille L.; Utomo, Herry S.

    2018-01-01

    Increasing atmospheric carbon dioxide (CO2) concentrations are likely to influence future distributions of plants and plant community structure in many regions of the world through effects on photosynthetic rates. In recent decades the encroachment of woody mangrove species into herbaceous marshes has been documented along the U.S. northern Gulf of Mexico coast. These species shifts have been attributed primarily to rising sea levels and warming winter temperatures, but the role of elevated CO2 and water availability may become more prominent drivers of species interactions under future climate conditions. Drought has been implicated as a major factor contributing to salt marsh vegetation dieback in this region. In this greenhouse study we examined the effects of CO2 concentration (∼380 ppm, ∼700 ppm) and water regime (drought, saturated, flooded) on early growth of Avicennia germinans, a C3 mangrove species, and Spartina alterniflora, a C4 grass. Plants were grown in monocultures and in a mixed-species assemblage. We found that neither species responded to elevated CO2 over the 10-month duration of the experiment, and there were few interactions between experimental factors. Two effects of water regime were documented: lower A. germinanspneumatophore biomass under drought conditions, and lower belowground biomass under flooded conditions regardless of planting assemblage. Evidence of interspecific interactions was noted. Competition for aboveground resources (e.g., light) was indicated by lower S. alterniflora stem biomass in mixed-species assemblage compared to biomass in S. alterniflora monocultures. Pneumatophore biomass of A. germinans was reduced when grown in monoculture compared to the mixed-species assemblage, indicating competition for belowground resources. These interactions provide insight into how these species may respond following major disturbance events that lead to vegetation dieback. Site variation in propagule availability

  16. Adaptability and phenotypic stability of common bean genotypes through Bayesian inference.

    Science.gov (United States)

    Corrêa, A M; Teodoro, P E; Gonçalves, M C; Barroso, L M A; Nascimento, M; Santos, A; Torres, F E

    2016-04-27

    This study used Bayesian inference to investigate the genotype x environment interaction in common bean grown in Mato Grosso do Sul State, and it also evaluated the efficiency of using informative and minimally informative a priori distributions. Six trials were conducted in randomized blocks, and the grain yield of 13 common bean genotypes was assessed. To represent the minimally informative a priori distributions, a probability distribution with high variance was used, and a meta-analysis concept was adopted to represent the informative a priori distributions. Bayes factors were used to conduct comparisons between the a priori distributions. The Bayesian inference was effective for the selection of upright common bean genotypes with high adaptability and phenotypic stability using the Eberhart and Russell method. Bayes factors indicated that the use of informative a priori distributions provided more accurate results than minimally informative a priori distributions. According to Bayesian inference, the EMGOPA-201, BAMBUÍ, CNF 4999, CNF 4129 A 54, and CNFv 8025 genotypes had specific adaptability to favorable environments, while the IAPAR 14 and IAC CARIOCA ETE genotypes had specific adaptability to unfavorable environments.

  17. Digest: Demographic inferences accounting for selection at linked sites†.

    Science.gov (United States)

    Simon, Alexis; Duranton, Maud

    2018-05-16

    Complex demography and selection at linked sites can generate spurious signatures of divergent selection. Unfortunately, many attempts at demographic inference consider overly simple models and neglect the effect of selection at linked sites. In this issue, Rougemont and Bernatchez (2018) applied an approximate Bayesian computation (ABC) framework that accounts for indirect selection to reveal a complex history of secondary contacts in Atlantic salmon (Salmo salar) that might explain a high rate of latitudinal clines in this species. © 2018 The Author(s). Evolution © 2018 The Society for the Study of Evolution.

  18. Inferring the gene network underlying the branching of tomato inflorescence.

    Directory of Open Access Journals (Sweden)

    Laura Astola

    Full Text Available The architecture of tomato inflorescence strongly affects flower production and subsequent crop yield. To understand the genetic activities involved, insight into the underlying network of genes that initiate and control the sympodial growth in the tomato is essential. In this paper, we show how the structure of this network can be derived from available data of the expressions of the involved genes. Our approach starts from employing biological expert knowledge to select the most probable gene candidates behind branching behavior. To find how these genes interact, we develop a stepwise procedure for computational inference of the network structure. Our data consists of expression levels from primary shoot meristems, measured at different developmental stages on three different genotypes of tomato. With the network inferred by our algorithm, we can explain the dynamics corresponding to all three genotypes simultaneously, despite their apparent dissimilarities. We also correctly predict the chronological order of expression peaks for the main hubs in the network. Based on the inferred network, using optimal experimental design criteria, we are able to suggest an informative set of experiments for further investigation of the mechanisms underlying branching behavior.

  19. Inferring Pre-shock Acoustic Field From Post-shock Pitot Pressure Measurement

    Science.gov (United States)

    Wang, Jian-Xun; Zhang, Chao; Duan, Lian; Xiao, Heng; Virginia Tech Team; Missouri Univ of Sci; Tech Team

    2017-11-01

    Linear interaction analysis (LIA) and iterative ensemble Kalman method are used to convert post-shock Pitot pressure fluctuations to static pressure fluctuations in front of the shock. The LIA is used as the forward model for the transfer function associated with a homogeneous field of acoustic waves passing through a nominally normal shock wave. The iterative ensemble Kalman method is then employed to infer the spectrum of upstream acoustic waves based on the post-shock Pitot pressure measured at a single point. Several test cases with synthetic and real measurement data are used to demonstrate the merits of the proposed inference scheme. The study provides the basis for measuring tunnel freestream noise with intrusive probes in noisy supersonic wind tunnels.

  20. Semantic Interaction for Sensemaking: Inferring Analytical Reasoning for Model Steering.

    Science.gov (United States)

    Endert, A; Fiaux, P; North, C

    2012-12-01

    Visual analytic tools aim to support the cognitively demanding task of sensemaking. Their success often depends on the ability to leverage capabilities of mathematical models, visualization, and human intuition through flexible, usable, and expressive interactions. Spatially clustering data is one effective metaphor for users to explore similarity and relationships between information, adjusting the weighting of dimensions or characteristics of the dataset to observe the change in the spatial layout. Semantic interaction is an approach to user interaction in such spatializations that couples these parametric modifications of the clustering model with users' analytic operations on the data (e.g., direct document movement in the spatialization, highlighting text, search, etc.). In this paper, we present results of a user study exploring the ability of semantic interaction in a visual analytic prototype, ForceSPIRE, to support sensemaking. We found that semantic interaction captures the analytical reasoning of the user through keyword weighting, and aids the user in co-creating a spatialization based on the user's reasoning and intuition.

  1. Unparalleled rates of species diversification in Europe

    Science.gov (United States)

    Valente, Luis M.; Savolainen, Vincent; Vargas, Pablo

    2010-01-01

    The most rapid species radiations have been reported from ‘evolutionary laboratories’, such as the Andes and the Cape of South Africa, leading to the prevailing view that diversification elsewhere has not been as dramatic. However, few studies have explicitly assessed rates of diversification in northern regions such as Europe. Here, we show that carnations (Dianthus, Caryophyllaceae), a well-known group of plants from temperate Eurasia, have diversified at the most rapid rate ever reported in plants or terrestrial vertebrates. Using phylogenetic methods, we found that the majority of species of carnations belong to a lineage that is remarkably species-rich in Europe, and arose at the rate of 2.2–7.6 species per million years. Unlike most previous studies that have inferred rates of diversification in young diverse groups, we use a conservative approach throughout that explicitly incorporates the uncertainties associated with phylogenetic inference, molecular dating and incomplete taxon sampling. We detected a shift in diversification rates of carnations coinciding with a period of increase in climatic aridity in the Pleistocene, suggesting a link between climate and biodiversity. This explosive radiation suggests that Europe, the continent with the world's best-studied flora, has been underestimated as a cradle of recent and rapid speciation. PMID:20106850

  2. The beta-diversity of species interactions: Untangling the drivers of geographic variation in plant-pollinator diversity and function across scales.

    Science.gov (United States)

    Burkle, Laura A; Myers, Jonathan A; Belote, R Travis

    2016-01-01

    Geographic patterns of biodiversity have long inspired interest in processes that shape the assembly, diversity, and dynamics of communities at different spatial scales. To study mechanisms of community assembly, ecologists often compare spatial variation in community composition (beta-diversity) across environmental and spatial gradients. These same patterns inspired evolutionary biologists to investigate how micro- and macro-evolutionary processes create gradients in biodiversity. Central to these perspectives are species interactions, which contribute to community assembly and geographic variation in evolutionary processes. However, studies of beta-diversity have predominantly focused on single trophic levels, resulting in gaps in our understanding of variation in species-interaction networks (interaction beta-diversity), especially at scales most relevant to evolutionary studies of geographic variation. We outline two challenges and their consequences in scaling-up studies of interaction beta-diversity from local to biogeographic scales using plant-pollinator interactions as a model system in ecology, evolution, and conservation. First, we highlight how variation in regional species pools may contribute to variation in interaction beta-diversity among biogeographic regions with dissimilar evolutionary history. Second, we highlight how pollinator behavior (host-switching) links ecological networks to geographic patterns of plant-pollinator interactions and evolutionary processes. Third, we outline key unanswered questions regarding the role of geographic variation in plant-pollinator interactions for conservation and ecosystem services (pollination) in changing environments. We conclude that the largest advances in the burgeoning field of interaction beta-diversity will come from studies that integrate frameworks in ecology, evolution, and conservation to understand the causes and consequences of interaction beta-diversity across scales. © 2016 Botanical

  3. Reproductive interference and fecundity affect competitive interactions of sibling species with low mating barriers: experimental and theoretical evidence.

    Science.gov (United States)

    Gebiola, M; Kelly, S E; Velten, L; Zug, R; Hammerstein, P; Giorgini, M; Hunter, M S

    2017-12-01

    When allopatric species with incomplete prezygotic isolation come into secondary contact, the outcome of their interaction is not easily predicted. The parasitoid wasp Encarsia suzannae (iES), infected by Cardinium inducing cytoplasmic incompatibility (CI), and its sibling species E. gennaroi (EG), not infected by bacterial endosymbionts, may have diverged because of the complementary action of CI and asymmetric hybrid incompatibilities. Whereas postzygotic isolation is now complete because of sterility of F1 hybrid progeny, prezygotic isolation is still incipient. We set up laboratory population cage experiments to evaluate the outcome of the interaction between ES and EG in two pairwise combinations: iES vs EG and cured ES (cES, where Cardinium was removed with antibiotics) vs EG. We also built a theoretical model aimed at exploring the role of life-history differences and asymmetric mating on competitive outcomes. In three of four cages in each treatment, ES dominated the interaction. We found evidence for reproductive interference, driven by asymmetric mating preferences, that gave a competitive edge to ES, the species that better discriminated against heterospecifics. However, we did not find the fecundity cost previously shown to be associated with Cardinium infection in iES. The model largely supported the experimental results. The finding of only a slight competitive edge of ES over EG in population cages suggests that in a more heterogeneous environment the species could coexist. This is supported by evidence that the two species coexist in sympatry, where preliminary data suggest reproductive character displacement may have reinforced postzygotic isolation.

  4. Species interactions can maintain resistance of subtidal algal habitats to an increasingly modified world

    Directory of Open Access Journals (Sweden)

    Laura J. Falkenberg

    2015-07-01

    Full Text Available Current trends in habitat loss have been forecast to accelerate under anticipated global change, thereby focusing conservation attention on identifying the circumstances under which key species interactions retard habitat loss. Urbanised coastlines are associated with broad-scale loss of kelp canopies and their replacement by less productive mats of algal turf, a trend predicted to accelerate under ocean acidification and warming (i.e. enhanced CO2 and temperature. Here we use kelp forests as a model system to test whether efforts to maintain key species interactions can maintain habitat integrity under forecasted conditions. First, we assessed whether increasing intensity of local human activity is associated with more extensive turf mats and sparser canopies via structured field observations. Second, we experimentally tested the hypothesis that intact canopies can resist turf expansion under enhanced CO2 and temperature in large mesocosms. In the field, there was a greater proportion of turf patches on urbanised coasts of South Australia than in agricultural and urban catchments in which there was a greater proportion of canopy-forming algae. Mesocosm experiments revealed this expansion of turfs is likely to accelerate under increases in CO2 and temperature, but may be limited by the presence of intact canopies. We note that even in the presence of canopy, increases in CO2 and temperature facilitate greater turf covers than occurs under contemporary conditions. The influence of canopy would likely be due to shading of the understorey turfs which, in turn, can modify their photosynthetic activity. These results suggest that resistance of habitat to change under human-dominated conditions may be managed via the retention of key species and their interactions. Management that directly reduces the disturbance of habitat-forming organisms (e.g. harvesting or reverses loss through restoration may, therefore, reinforce habitat resistance in an

  5. Assessing the putative roles of X-autosome and X-Y interactions in hybrid male sterility of the Drosophila bipectinata species complex.

    Science.gov (United States)

    Mishra, Paras Kumar; Singh, Bashisth Narayan

    2007-07-01

    Interspecific F1 hybrid males of the Drosophila bipectinata species complex are sterile, while females are fertile, following Haldane's rule. A backcross scheme involving a single recessive visible marker on the X chromosome has been used to assess the putative roles of X-autosome and X-Y interactions in hybrid male sterility in the D. bipectinata species complex. The results suggest that X-Y interactions are playing the major role in hybrid male sterility in the crosses D. bipectinata x D. parabipectinata and D. bipectinata x D. pseudoananassae, while X-autosome interactions are largely involved in hybrid male sterility in the crosses D. malerkotliana x D. bipectinata and D. malerkotliana x D. parabipectinata. However, by using this single marker it is not possible to rule out the involvement of autosome-autosome interactions in hybrid male sterility. These findings also lend further support to the phylogenetic relationships among 4 species of the D. bipectinata complex.

  6. Inferring the role of transcription factors in regulatory networks

    Directory of Open Access Journals (Sweden)

    Le Borgne Michel

    2008-05-01

    Full Text Available Abstract Background Expression profiles obtained from multiple perturbation experiments are increasingly used to reconstruct transcriptional regulatory networks, from well studied, simple organisms up to higher eukaryotes. Admittedly, a key ingredient in developing a reconstruction method is its ability to integrate heterogeneous sources of information, as well as to comply with practical observability issues: measurements can be scarce or noisy. In this work, we show how to combine a network of genetic regulations with a set of expression profiles, in order to infer the functional effect of the regulations, as inducer or repressor. Our approach is based on a consistency rule between a network and the signs of variation given by expression arrays. Results We evaluate our approach in several settings of increasing complexity. First, we generate artificial expression data on a transcriptional network of E. coli extracted from the literature (1529 nodes and 3802 edges, and we estimate that 30% of the regulations can be annotated with about 30 profiles. We additionally prove that at most 40.8% of the network can be inferred using our approach. Second, we use this network in order to validate the predictions obtained with a compendium of real expression profiles. We describe a filtering algorithm that generates particularly reliable predictions. Finally, we apply our inference approach to S. cerevisiae transcriptional network (2419 nodes and 4344 interactions, by combining ChIP-chip data and 15 expression profiles. We are able to detect and isolate inconsistencies between the expression profiles and a significant portion of the model (15% of all the interactions. In addition, we report predictions for 14.5% of all interactions. Conclusion Our approach does not require accurate expression levels nor times series. Nevertheless, we show on both data, real and artificial, that a relatively small number of perturbation experiments are enough to determine

  7. Adaptive Inference on General Graphical Models

    OpenAIRE

    Acar, Umut A.; Ihler, Alexander T.; Mettu, Ramgopal; Sumer, Ozgur

    2012-01-01

    Many algorithms and applications involve repeatedly solving variations of the same inference problem; for example we may want to introduce new evidence to the model or perform updates to conditional dependencies. The goal of adaptive inference is to take advantage of what is preserved in the model and perform inference more rapidly than from scratch. In this paper, we describe techniques for adaptive inference on general graphs that support marginal computation and updates to the conditional ...

  8. Phylogeography of five Polytrichum species within Europe

    NARCIS (Netherlands)

    Van der Velde, M; Bijlsma, R

    Using allozymes and microsatellites we have analysed the genetic structure among European populations for several Polytrichum species to infer relevant factors, such as historical events or gene flow, that have shaped their genetic structure. As we observed low levels of genetic differentiation

  9. Confronting species distribution model predictions with species functional traits.

    Science.gov (United States)

    Wittmann, Marion E; Barnes, Matthew A; Jerde, Christopher L; Jones, Lisa A; Lodge, David M

    2016-02-01

    Species distribution models are valuable tools in studies of biogeography, ecology, and climate change and have been used to inform conservation and ecosystem management. However, species distribution models typically incorporate only climatic variables and species presence data. Model development or validation rarely considers functional components of species traits or other types of biological data. We implemented a species distribution model (Maxent) to predict global climate habitat suitability for Grass Carp (Ctenopharyngodon idella). We then tested the relationship between the degree of climate habitat suitability predicted by Maxent and the individual growth rates of both wild (N = 17) and stocked (N = 51) Grass Carp populations using correlation analysis. The Grass Carp Maxent model accurately reflected the global occurrence data (AUC = 0.904). Observations of Grass Carp growth rate covered six continents and ranged from 0.19 to 20.1 g day(-1). Species distribution model predictions were correlated (r = 0.5, 95% CI (0.03, 0.79)) with observed growth rates for wild Grass Carp populations but were not correlated (r = -0.26, 95% CI (-0.5, 0.012)) with stocked populations. Further, a review of the literature indicates that the few studies for other species that have previously assessed the relationship between the degree of predicted climate habitat suitability and species functional traits have also discovered significant relationships. Thus, species distribution models may provide inferences beyond just where a species may occur, providing a useful tool to understand the linkage between species distributions and underlying biological mechanisms.

  10. Inferring Person-to-person Proximity Using WiFi Signals

    DEFF Research Database (Denmark)

    Sapiezynski, Piotr; Stopczynski, Arkadiusz; Wind, David Kofoed

    2017-01-01

    phone towers, Bluetooth beacons, and WiFi networks as proxies for location. However, while mobility is an important aspect of human behavior, understanding complex social systems requires studying not only the movement of individuals, but also their interactions. Sensing social interactions on a large...... scale is a technical challenge and many commonly used approaches—including RFID badges or Bluetooth scanning—offer only limited scalability. Here we show that it is possible, in a scalable and robust way, to accurately infer person-to-person physical proximity from the lists of WiFi access points...... measured by smartphones carried by the two individuals. Based on a longitudinal dataset of approximately 800 participants with ground-truth interactions collected over a year, we show that our model performs better than the current state-of-the-art. Our results demonstrate the value of WiFi signals...

  11. Use of abundance of one species as a surrogate for abundance of others

    Science.gov (United States)

    Samuel A. Cushman; Kevin S. McKelvey; Barry R. Noon; Kevin McGarigal

    2010-01-01

    Indicator species concepts have a long history in conservation biology. Arguments in favor of these approaches generally stress expediency and assume efficacy. We tested the premise that the abundance patterns of one species can be used to infer those of other species. Our data consisted of 72,495 bird observations on 55 species across 1046 plots distributed across 30...

  12. Empathy and Prosocial Behaviours. Insights from Intra- and Inter-species Interactions

    Directory of Open Access Journals (Sweden)

    Maria elide Vanutelli

    2015-04-01

    Full Text Available It has been suggested that “sharing the same body” between the observer and the observed subject allows for a direct form of understanding and emotional attuning by a process of simulation. Then, what happens when we don’t share the same body? The aim of the present paper is to review available evidence of intra- and inter-species empathic and prosocial behaviours, with respect to within-human, within-animals and cross-specifies interactions. Similarities and differences will be evaluated using a comparative perspective, and some possible moral and ethical implications for human-animal interactions will be discussed. According to Charles Darwin’s work, the perceived differences between human and animal empathy could be more quantitative than qualitative, suggesting a common affective core which allows both categories to mirror and tune to conspecifics’ feelings, where in the case of humans it can be integrated with more complex cognitive processes.

  13. Dense gene physical maps of the non-model species Drosophila subobscura.

    Science.gov (United States)

    Orengo, Dorcas J; Puerma, Eva; Papaceit, Montserrat; Segarra, Carmen; Aguadé, Montserrat

    2017-06-01

    The comparative analysis of genetic and physical maps as well as of whole genome sequences had revealed that in the Drosophila genus, most structural rearrangements occurred within chromosomal elements as a result of paracentric inversions. Genome sequence comparison would seem the best method to estimate rates of chromosomal evolution, but the high-quality reference genomes required for this endeavor are still scanty. Here, we have obtained dense physical maps for Muller elements A, C, and E of Drosophila subobscura, a species with an extensively studied rich and adaptive chromosomal polymorphism. These maps are based on 462 markers: 115, 236, and 111 markers for elements A, C, and E, respectively. The availability of these dense maps will facilitate genome assembly and will thus greatly contribute to obtaining a good reference genome, which is a required step for D. subobscura to attain the model species status. The comparative analysis of these physical maps and those obtained from the D. pseudoobscura and D. melanogaster genomes allowed us to infer the number of fixed inversions and chromosomal evolutionary rates for each pairwise comparison. For all three elements, rates inferred from the more closely related species were higher than those inferred from the more distantly related species, which together with results of relative-rate tests point to an acceleration in the D. subobscura lineage at least for elements A and E.

  14. Effective network inference through multivariate information transfer estimation

    Science.gov (United States)

    Dahlqvist, Carl-Henrik; Gnabo, Jean-Yves

    2018-06-01

    Network representation has steadily gained in popularity over the past decades. In many disciplines such as finance, genetics, neuroscience or human travel to cite a few, the network may not directly be observable and needs to be inferred from time-series data, leading to the issue of separating direct interactions between two entities forming the network from indirect interactions coming through its remaining part. Drawing on recent contributions proposing strategies to deal with this problem such as the so-called "global silencing" approach of Barzel and Barabasi or "network deconvolution" of Feizi et al. (2013), we propose a novel methodology to infer an effective network structure from multivariate conditional information transfers. Its core principal is to test the information transfer between two nodes through a step-wise approach by conditioning the transfer for each pair on a specific set of relevant nodes as identified by our algorithm from the rest of the network. The methodology is model free and can be applied to high-dimensional networks with both inter-lag and intra-lag relationships. It outperforms state-of-the-art approaches for eliminating the redundancies and more generally retrieving simulated artificial networks in our Monte-Carlo experiments. We apply the method to stock market data at different frequencies (15 min, 1 h, 1 day) to retrieve the network of US largest financial institutions and then document how bank's centrality measurements relate to bank's systemic vulnerability.

  15. Inference of Time-Evolving Coupled Dynamical Systems in the Presence of Noise

    Science.gov (United States)

    Stankovski, Tomislav; Duggento, Andrea; McClintock, Peter V. E.; Stefanovska, Aneta

    2012-07-01

    A new method is introduced for analysis of interactions between time-dependent coupled oscillators, based on the signals they generate. It distinguishes unsynchronized dynamics from noise-induced phase slips and enables the evolution of the coupling functions and other parameters to be followed. It is based on phase dynamics, with Bayesian inference of the time-evolving parameters achieved by shaping the prior densities to incorporate knowledge of previous samples. The method is tested numerically and applied to reveal and quantify the time-varying nature of cardiorespiratory interactions.

  16. The inference from a single case: moral versus scientific inferences in implementing new biotechnologies.

    Science.gov (United States)

    Hofmann, B

    2008-06-01

    Are there similarities between scientific and moral inference? This is the key question in this article. It takes as its point of departure an instance of one person's story in the media changing both Norwegian public opinion and a brand-new Norwegian law prohibiting the use of saviour siblings. The case appears to falsify existing norms and to establish new ones. The analysis of this case reveals similarities in the modes of inference in science and morals, inasmuch as (a) a single case functions as a counter-example to an existing rule; (b) there is a common presupposition of stability, similarity and order, which makes it possible to reason from a few cases to a general rule; and (c) this makes it possible to hold things together and retain order. In science, these modes of inference are referred to as falsification, induction and consistency. In morals, they have a variety of other names. Hence, even without abandoning the fact-value divide, there appear to be similarities between inference in science and inference in morals, which may encourage communication across the boundaries between "the two cultures" and which are relevant to medical humanities.

  17. Dinoflagellate phylogeny as inferred from heat shock protein 90 and ribosomal gene sequences.

    Directory of Open Access Journals (Sweden)

    Mona Hoppenrath

    2010-10-01

    Full Text Available Interrelationships among dinoflagellates in molecular phylogenies are largely unresolved, especially in the deepest branches. Ribosomal DNA (rDNA sequences provide phylogenetic signals only at the tips of the dinoflagellate tree. Two reasons for the poor resolution of deep dinoflagellate relationships using rDNA sequences are (1 most sites are relatively conserved and (2 there are different evolutionary rates among sites in different lineages. Therefore, alternative molecular markers are required to address the deeper phylogenetic relationships among dinoflagellates. Preliminary evidence indicates that the heat shock protein 90 gene (Hsp90 will provide an informative marker, mainly because this gene is relatively long and appears to have relatively uniform rates of evolution in different lineages.We more than doubled the previous dataset of Hsp90 sequences from dinoflagellates by generating additional sequences from 17 different species, representing seven different orders. In order to concatenate the Hsp90 data with rDNA sequences, we supplemented the Hsp90 sequences with three new SSU rDNA sequences and five new LSU rDNA sequences. The new Hsp90 sequences were generated, in part, from four additional heterotrophic dinoflagellates and the type species for six different genera. Molecular phylogenetic analyses resulted in a paraphyletic assemblage near the base of the dinoflagellate tree consisting of only athecate species. However, Noctiluca was never part of this assemblage and branched in a position that was nested within other lineages of dinokaryotes. The phylogenetic trees inferred from Hsp90 sequences were consistent with trees inferred from rDNA sequences in that the backbone of the dinoflagellate clade was largely unresolved.The sequence conservation in both Hsp90 and rDNA sequences and the poor resolution of the deepest nodes suggests that dinoflagellates reflect an explosive radiation in morphological diversity in their recent

  18. Chasing Ecological Interactions.

    Science.gov (United States)

    Jordano, Pedro

    2016-09-01

    Basic research on biodiversity has concentrated on individual species-naming new species, studying distribution patterns, and analyzing their evolutionary relationships. Yet biodiversity is more than a collection of individual species; it is the combination of biological entities and processes that support life on Earth. To understand biodiversity we must catalog it, but we must also assess the ways species interact with other species to provide functional support for the Tree of Life. Ecological interactions may be lost well before the species involved in those interactions go extinct; their ecological functions disappear even though they remain. Here, I address the challenges in studying the functional aspects of species interactions and how basic research is helping us address the fast-paced extinction of species due to human activities.

  19. Introductory statistical inference

    CERN Document Server

    Mukhopadhyay, Nitis

    2014-01-01

    This gracefully organized text reveals the rigorous theory of probability and statistical inference in the style of a tutorial, using worked examples, exercises, figures, tables, and computer simulations to develop and illustrate concepts. Drills and boxed summaries emphasize and reinforce important ideas and special techniques.Beginning with a review of the basic concepts and methods in probability theory, moments, and moment generating functions, the author moves to more intricate topics. Introductory Statistical Inference studies multivariate random variables, exponential families of dist

  20. Hierarchical species distribution models

    Science.gov (United States)

    Hefley, Trevor J.; Hooten, Mevin B.

    2016-01-01

    Determining the distribution pattern of a species is important to increase scientific knowledge, inform management decisions, and conserve biodiversity. To infer spatial and temporal patterns, species distribution models have been developed for use with many sampling designs and types of data. Recently, it has been shown that count, presence-absence, and presence-only data can be conceptualized as arising from a point process distribution. Therefore, it is important to understand properties of the point process distribution. We examine how the hierarchical species distribution modeling framework has been used to incorporate a wide array of regression and theory-based components while accounting for the data collection process and making use of auxiliary information. The hierarchical modeling framework allows us to demonstrate how several commonly used species distribution models can be derived from the point process distribution, highlight areas of potential overlap between different models, and suggest areas where further research is needed.

  1. Inferring the interaction structure of resistance to antimicrobials.

    Science.gov (United States)

    Zawack, Kelson; Love, Will; Lanzas, Cristina; Booth, James G; Gröhn, Yrjö T

    2018-04-01

    The growth of antimicrobial resistance presents a significant threat to human and animal health. Of particular concern is multi-drug resistance, as this increases the chances an infection will be untreatable by any antibiotic. In order to understand multi-drug resistance, it is essential to understand the association between drug resistances. Pairwise associations characterize the connectivity between resistances and are useful in making decisions about courses of treatment, or the design of drug cocktails. Higher-order associations, interactions, which tie together groups of drugs can suggest commonalities in resistance mechanism and lead to their identification. To capture interactions, we apply log-linear models of contingency tables to analyze publically available data on the resistance of Escheresia coli isolated from chicken and turkey meat by the National Antimicrobial Resistance Monitoring System. Standard large sample and conditional exact testing approaches for assessing significance of parameters in these models breakdown due to structured patterns inherent to antimicrobial resistance. To address this, we adopt a Bayesian approach which reveals that E. coli resistance associations can be broken into two subnetworks. The first subnetwork is characterized by a hierarchy of β-lactams which is consistent across the chicken and turkey datasets. Tier one in this hierarchy is a near equivalency between amoxicillin-clavulanic acid, ceftriaxone and cefoxitin. Susceptibility to tier one then implies susceptibility to ceftiofur. The second subnetwork is characterized by more complex interactions between a variety of drug classes that vary between the chicken and turkey datasets. Copyright © 2018 Elsevier B.V. All rights reserved.

  2. Pathogenomic inference of virulence-associated genes in Leptospira interrogans.

    Directory of Open Access Journals (Sweden)

    Jason S Lehmann

    Full Text Available Leptospirosis is a globally important, neglected zoonotic infection caused by spirochetes of the genus Leptospira. Since genetic transformation remains technically limited for pathogenic Leptospira, a systems biology pathogenomic approach was used to infer leptospiral virulence genes by whole genome comparison of culture-attenuated Leptospira interrogans serovar Lai with its virulent, isogenic parent. Among the 11 pathogen-specific protein-coding genes in which non-synonymous mutations were found, a putative soluble adenylate cyclase with host cell cAMP-elevating activity, and two members of a previously unstudied ∼15 member paralogous gene family of unknown function were identified. This gene family was also uniquely found in the alpha-proteobacteria Bartonella bacilliformis and Bartonella australis that are geographically restricted to the Andes and Australia, respectively. How the pathogenic Leptospira and these two Bartonella species came to share this expanded gene family remains an evolutionary mystery. In vivo expression analyses demonstrated up-regulation of 10/11 Leptospira genes identified in the attenuation screen, and profound in vivo, tissue-specific up-regulation by members of the paralogous gene family, suggesting a direct role in virulence and host-pathogen interactions. The pathogenomic experimental design here is generalizable as a functional systems biology approach to studying bacterial pathogenesis and virulence and should encourage similar experimental studies of other pathogens.

  3. Active inference, communication and hermeneutics.

    Science.gov (United States)

    Friston, Karl J; Frith, Christopher D

    2015-07-01

    Hermeneutics refers to interpretation and translation of text (typically ancient scriptures) but also applies to verbal and non-verbal communication. In a psychological setting it nicely frames the problem of inferring the intended content of a communication. In this paper, we offer a solution to the problem of neural hermeneutics based upon active inference. In active inference, action fulfils predictions about how we will behave (e.g., predicting we will speak). Crucially, these predictions can be used to predict both self and others--during speaking and listening respectively. Active inference mandates the suppression of prediction errors by updating an internal model that generates predictions--both at fast timescales (through perceptual inference) and slower timescales (through perceptual learning). If two agents adopt the same model, then--in principle--they can predict each other and minimise their mutual prediction errors. Heuristically, this ensures they are singing from the same hymn sheet. This paper builds upon recent work on active inference and communication to illustrate perceptual learning using simulated birdsongs. Our focus here is the neural hermeneutics implicit in learning, where communication facilitates long-term changes in generative models that are trying to predict each other. In other words, communication induces perceptual learning and enables others to (literally) change our minds and vice versa. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  4. A phylogenetic perspective on the individual species-area relationship in temperate and tropical tree communities.

    Science.gov (United States)

    Yang, Jie; Swenson, Nathan G; Cao, Min; Chuyong, George B; Ewango, Corneille E N; Howe, Robert; Kenfack, David; Thomas, Duncan; Wolf, Amy; Lin, Luxiang

    2013-01-01

    Ecologists have historically used species-area relationships (SARs) as a tool to understand the spatial distribution of species. Recent work has extended SARs to focus on individual-level distributions to generate individual species area relationships (ISARs). The ISAR approach quantifies whether individuals of a species tend have more or less species richness surrounding them than expected by chance. By identifying richness 'accumulators' and 'repellers', respectively, the ISAR approach has been used to infer the relative importance of abiotic and biotic interactions and neutrality. A clear limitation of the SAR and ISAR approaches is that all species are treated as evolutionarily independent and that a large amount of work has now shown that local tree neighborhoods exhibit non-random phylogenetic structure given the species richness. Here, we use nine tropical and temperate forest dynamics plots to ask: (i) do ISARs change predictably across latitude?; (ii) is the phylogenetic diversity in the neighborhood of species accumulators and repellers higher or lower than that expected given the observed species richness?; and (iii) do species accumulators, repellers distributed non-randomly on the community phylogenetic tree? The results indicate no clear trend in ISARs from the temperate zone to the tropics and that the phylogenetic diversity surrounding the individuals of species is generally only non-random on very local scales. Interestingly the distribution of species accumulators and repellers was non-random on the community phylogenies suggesting the presence of phylogenetic signal in the ISAR across latitude.

  5. Species interactions in the western Baltic Sea: With focus on the ecological role of whiting

    DEFF Research Database (Denmark)

    Ross, Stine Dalmann

    , which potentially prey on and compete for food with whiting. Here, the growth dynamics and feeding ecology of whiting in the western Baltic Sea is investigated and discussed in an ecosystem context. Furthermore, the diet of the harbour porpoise is examined and the interactions between whiting, cod......, implementation of the models in strategic management advice for commercially important fish stocks and protected marine mammals is not common practice. This is due to the lack of sufficient information about species interactions including knowledge about the diet, food intake and growth dynamics. This thesis...

  6. Ontology Mapping Neural Network: An Approach to Learning and Inferring Correspondences among Ontologies

    Science.gov (United States)

    Peng, Yefei

    2010-01-01

    An ontology mapping neural network (OMNN) is proposed in order to learn and infer correspondences among ontologies. It extends the Identical Elements Neural Network (IENN)'s ability to represent and map complex relationships. The learning dynamics of simultaneous (interlaced) training of similar tasks interact at the shared connections of the…

  7. Short-range interactions between surfactants, silica species and EDTA⁴- salt during self-assembly of siliceous mesoporous molecular sieve: a UV Raman study.

    Science.gov (United States)

    Song, Jiayin; Liu, Liping; Li, Peng; Xiong, Guang

    2012-11-01

    The effects of surfactants, counterions and additive salts on the formation of siliceous mesoporous molecular sieves during self-assembly process were investigated by UV Raman spectroscopy, X-ray diffraction (XRD) and transmission electron microscopy (TEM) techniques. The surfactant molecules experience the rearrangement after adding the silica species and adjusting the pH value. The obvious change of the Raman bands related to the surfactants supports a cooperative interaction between surfactant and inorganic species during self-assembly process. The addition of EDTANa(4) to the system induces the interaction between the COO(-) groups of EDTA(4-) and silanol groups of silica and a strong interaction between the EDTA(4-) and the N(+)(CH(3))(3) groups of the surfactant. The above interactions may be the main reason for the salt effect. The new information from the change of the chemical bonds allows for a further analysis to the interactions of different salts between surfactants and silica species at molecular level. Copyright © 2012 Elsevier B.V. All rights reserved.

  8. Species delimitation of the Hyphydrus ovatus complex in western Palaearctic with an update of species distributions (Coleoptera, Dytiscidae

    Directory of Open Access Journals (Sweden)

    Johannes Bergsten

    2017-06-01

    Full Text Available The species status of Hyphydrus anatolicus Guignot, 1957 and H. sanctus Sharp, 1882, previously often confused with the widespread H. ovatus (Linnaeus, 1760, are tested with molecular and morphological characters. Cytochrome c oxidase subunit 1 (CO1 was sequenced for 32 specimens of all three species. Gene-trees were inferred with parsimony, time-free bayesian and strict clock bayesian analyses. The GMYC model was used to estimate species limits. All three species were reciprocally monophyletic with CO1 and highly supported. The GMYC species delimitation analysis unequivocally delimited the three species with no other than the three species solution included in the confidence interval. A likelihood ratio test rejected the one-species null model. Important morphological characters distinguishing the species are provided and illustrated. New distributional data are given for the following species: Hyphydrus anatolicus from Slovakia and Ukraine, and H. aubei Ganglbauer, 1891, and H. sanctus from Turkey.

  9. Dental biofilm: ecological interactions in health and disease.

    Science.gov (United States)

    Marsh, P D; Zaura, Egija

    2017-03-01

    The oral microbiome is diverse and exists as multispecies microbial communities on oral surfaces in structurally and functionally organized biofilms. To describe the network of microbial interactions (both synergistic and antagonistic) occurring within these biofilms and assess their role in oral health and dental disease. PubMed database was searched for studies on microbial ecological interactions in dental biofilms. The search results did not lend themselves to systematic review and have been summarized in a narrative review instead. Five hundred and forty-seven original research articles and 212 reviews were identified. The majority (86%) of research articles addressed bacterial-bacterial interactions, while inter-kingdom microbial interactions were the least studied. The interactions included physical and nutritional synergistic associations, antagonism, cell-to-cell communication and gene transfer. Oral microbial communities display emergent properties that cannot be inferred from studies of single species. Individual organisms grow in environments they would not tolerate in pure culture. The networks of multiple synergistic and antagonistic interactions generate microbial inter-dependencies and give biofilms a resilience to minor environmental perturbations, and this contributes to oral health. If key environmental pressures exceed thresholds associated with health, then the competitiveness among oral microorganisms is altered and dysbiosis can occur, increasing the risk of dental disease. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  10. Integrative inference of population history in the Ibero-Maghrebian endemic Pleurodeles waltl (Salamandridae).

    Science.gov (United States)

    Gutiérrez-Rodríguez, Jorge; Barbosa, A Márcia; Martínez-Solano, Íñigo

    2017-07-01

    Inference of population histories from the molecular signatures of past demographic processes is challenging, but recent methodological advances in species distribution models and their integration in time-calibrated phylogeographic studies allow detailed reconstruction of complex biogeographic scenarios. We apply an integrative approach to infer the evolutionary history of the Iberian ribbed newt (Pleurodeles waltl), an Ibero-Maghrebian endemic with populations north and south of the Strait of Gibraltar. We analyzed an extensive multilocus dataset (mitochondrial and nuclear DNA sequences and ten polymorphic microsatellite loci) and found a deep east-west phylogeographic break in Iberian populations dating back to the Plio-Pleistocene. This break is inferred to result from vicariance associated with the formation of the Guadalquivir river basin. In contrast with previous studies, North African populations showed exclusive mtDNA haplotypes, and formed a monophyletic clade within the Eastern Iberian lineage in the mtDNA genealogy. On the other hand, microsatellites failed to recover Moroccan populations as a differentiated genetic cluster. This is interpreted to result from post-divergence gene flow based on the results of IMA2 and Migrate analyses. Thus, Moroccan populations would have originated after overseas dispersal from the Iberian Peninsula in the Pleistocene, with subsequent gene flow in more recent times, implying at least two trans-marine dispersal events. We modeled the distribution of the species and of each lineage, and projected these models back in time to infer climatically favourable areas during the mid-Holocene, the last glacial maximum (LGM) and the last interglacial (LIG), to reconstruct more recent population dynamics. We found minor differences in climatic favourability across lineages, suggesting intraspecific niche conservatism. Genetic diversity was significantly correlated with the intersection of environmental favourability in the LIG and

  11. Optimization methods for logical inference

    CERN Document Server

    Chandru, Vijay

    2011-01-01

    Merging logic and mathematics in deductive inference-an innovative, cutting-edge approach. Optimization methods for logical inference? Absolutely, say Vijay Chandru and John Hooker, two major contributors to this rapidly expanding field. And even though ""solving logical inference problems with optimization methods may seem a bit like eating sauerkraut with chopsticks. . . it is the mathematical structure of a problem that determines whether an optimization model can help solve it, not the context in which the problem occurs."" Presenting powerful, proven optimization techniques for logic in

  12. Inference in `poor` languages

    Energy Technology Data Exchange (ETDEWEB)

    Petrov, S.

    1996-10-01

    Languages with a solvable implication problem but without complete and consistent systems of inference rules (`poor` languages) are considered. The problem of existence of finite complete and consistent inference rule system for a ``poor`` language is stated independently of the language or rules syntax. Several properties of the problem arc proved. An application of results to the language of join dependencies is given.

  13. Biotic and abiotic factors investigated in two Drosophila species – evidence of both negative and positive fitness effects of interactions on performance

    DEFF Research Database (Denmark)

    Ørsted, Michael; Schou, Mads Fristrup; Kristensen, Torsten Nygård

    2017-01-01

    more informative descriptions of complex interactions we implemented re-conceptualised definitions of synergism and antagonism. We found approximately equal proportions of synergistic and antagonistic interactions in both species, however the effects of interactions on performance differed between...

  14. Inference of gene regulatory networks with sparse structural equation models exploiting genetic perturbations.

    Directory of Open Access Journals (Sweden)

    Xiaodong Cai

    Full Text Available Integrating genetic perturbations with gene expression data not only improves accuracy of regulatory network topology inference, but also enables learning of causal regulatory relations between genes. Although a number of methods have been developed to integrate both types of data, the desiderata of efficient and powerful algorithms still remains. In this paper, sparse structural equation models (SEMs are employed to integrate both gene expression data and cis-expression quantitative trait loci (cis-eQTL, for modeling gene regulatory networks in accordance with biological evidence about genes regulating or being regulated by a small number of genes. A systematic inference method named sparsity-aware maximum likelihood (SML is developed for SEM estimation. Using simulated directed acyclic or cyclic networks, the SML performance is compared with that of two state-of-the-art algorithms: the adaptive Lasso (AL based scheme, and the QTL-directed dependency graph (QDG method. Computer simulations demonstrate that the novel SML algorithm offers significantly better performance than the AL-based and QDG algorithms across all sample sizes from 100 to 1,000, in terms of detection power and false discovery rate, in all the cases tested that include acyclic or cyclic networks of 10, 30 and 300 genes. The SML method is further applied to infer a network of 39 human genes that are related to the immune function and are chosen to have a reliable eQTL per gene. The resulting network consists of 9 genes and 13 edges. Most of the edges represent interactions reasonably expected from experimental evidence, while the remaining may just indicate the emergence of new interactions. The sparse SEM and efficient SML algorithm provide an effective means of exploiting both gene expression and perturbation data to infer gene regulatory networks. An open-source computer program implementing the SML algorithm is freely available upon request.

  15. PHI-base: a new interface and further additions for the multi-species pathogen–host interactions database

    Science.gov (United States)

    Urban, Martin; Cuzick, Alayne; Rutherford, Kim; Irvine, Alistair; Pedro, Helder; Pant, Rashmi; Sadanadan, Vidyendra; Khamari, Lokanath; Billal, Santoshkumar; Mohanty, Sagar; Hammond-Kosack, Kim E.

    2017-01-01

    The pathogen–host interactions database (PHI-base) is available at www.phi-base.org. PHI-base contains expertly curated molecular and biological information on genes proven to affect the outcome of pathogen–host interactions reported in peer reviewed research articles. In addition, literature that indicates specific gene alterations that did not affect the disease interaction phenotype are curated to provide complete datasets for comparative purposes. Viruses are not included. Here we describe a revised PHI-base Version 4 data platform with improved search, filtering and extended data display functions. A PHIB-BLAST search function is provided and a link to PHI-Canto, a tool for authors to directly curate their own published data into PHI-base. The new release of PHI-base Version 4.2 (October 2016) has an increased data content containing information from 2219 manually curated references. The data provide information on 4460 genes from 264 pathogens tested on 176 hosts in 8046 interactions. Prokaryotic and eukaryotic pathogens are represented in almost equal numbers. Host species belong ∼70% to plants and 30% to other species of medical and/or environmental importance. Additional data types included into PHI-base 4 are the direct targets of pathogen effector proteins in experimental and natural host organisms. The curation problems encountered and the future directions of the PHI-base project are briefly discussed. PMID:27915230

  16. EI: A Program for Ecological Inference

    Directory of Open Access Journals (Sweden)

    Gary King

    2004-09-01

    Full Text Available The program EI provides a method of inferring individual behavior from aggregate data. It implements the statistical procedures, diagnostics, and graphics from the book A Solution to the Ecological Inference Problem: Reconstructing Individual Behavior from Aggregate Data (King 1997. Ecological inference, as traditionally defined, is the process of using aggregate (i.e., "ecological" data to infer discrete individual-level relationships of interest when individual-level data are not available. Ecological inferences are required in political science research when individual-level surveys are unavailable (e.g., local or comparative electoral politics, unreliable (racial politics, insufficient (political geography, or infeasible (political history. They are also required in numerous areas of ma jor significance in public policy (e.g., for applying the Voting Rights Act and other academic disciplines ranging from epidemiology and marketing to sociology and quantitative history.

  17. Helminth community structure and diet of three Afrotropical anuran species: a test of the interactive-versus-isolationist parasite communities hypothesis

    Directory of Open Access Journals (Sweden)

    G. C. Akani

    2011-09-01

    Full Text Available The interactive-versus-isolationist hypothesis predicts that parasite communities should be depauperated and weakly structured by interspecific competition in amphibians. A parasitological survey was carried out to test this hypothesis using three anuran species from Nigeria, tropical Africa (one Bufonidae; two Ranidae. High values of parasite infection parameters were found in all three species, which were infected by nematodes, cestodes and trematodes. Nonetheless, the parasite communities of the three anurans were very depauperated in terms of number of species (4 to 6. Interspecific competition was irrelevant in all species, as revealed by null models and Monte Carlo permutations. Cluster analyses revealed that, in terms of parasite community composition, the two Ranidae were similar, whereas the Bufonidae was more different. However, when prevalence, intensity, and abundance of parasites are combined into a multivariate analysis, each anuran species was clearly spaced apart from the others, thus revealing considerable species-specific differences in terms of their parasite communities. All anurans were generalists and probably opportunistic in terms of dietary habits, and showed no evidence of interspecific competition for food. Overall, our data are widely consistent with expectations driven from the interactive-versus-isolationist parasite communities hypothesis.

  18. Ecological modeling from time-series inference: insight into dynamics and stability of intestinal microbiota.

    Directory of Open Access Journals (Sweden)

    Richard R Stein

    Full Text Available The intestinal microbiota is a microbial ecosystem of crucial importance to human health. Understanding how the microbiota confers resistance against enteric pathogens and how antibiotics disrupt that resistance is key to the prevention and cure of intestinal infections. We present a novel method to infer microbial community ecology directly from time-resolved metagenomics. This method extends generalized Lotka-Volterra dynamics to account for external perturbations. Data from recent experiments on antibiotic-mediated Clostridium difficile infection is analyzed to quantify microbial interactions, commensal-pathogen interactions, and the effect of the antibiotic on the community. Stability analysis reveals that the microbiota is intrinsically stable, explaining how antibiotic perturbations and C. difficile inoculation can produce catastrophic shifts that persist even after removal of the perturbations. Importantly, the analysis suggests a subnetwork of bacterial groups implicated in protection against C. difficile. Due to its generality, our method can be applied to any high-resolution ecological time-series data to infer community structure and response to external stimuli.

  19. Ecological modeling from time-series inference: insight into dynamics and stability of intestinal microbiota.

    Science.gov (United States)

    Stein, Richard R; Bucci, Vanni; Toussaint, Nora C; Buffie, Charlie G; Rätsch, Gunnar; Pamer, Eric G; Sander, Chris; Xavier, João B

    2013-01-01

    The intestinal microbiota is a microbial ecosystem of crucial importance to human health. Understanding how the microbiota confers resistance against enteric pathogens and how antibiotics disrupt that resistance is key to the prevention and cure of intestinal infections. We present a novel method to infer microbial community ecology directly from time-resolved metagenomics. This method extends generalized Lotka-Volterra dynamics to account for external perturbations. Data from recent experiments on antibiotic-mediated Clostridium difficile infection is analyzed to quantify microbial interactions, commensal-pathogen interactions, and the effect of the antibiotic on the community. Stability analysis reveals that the microbiota is intrinsically stable, explaining how antibiotic perturbations and C. difficile inoculation can produce catastrophic shifts that persist even after removal of the perturbations. Importantly, the analysis suggests a subnetwork of bacterial groups implicated in protection against C. difficile. Due to its generality, our method can be applied to any high-resolution ecological time-series data to infer community structure and response to external stimuli.

  20. Connectivity in the yeast cell cycle transcription network: inferences from neural networks.

    Directory of Open Access Journals (Sweden)

    Christopher E Hart

    2006-12-01

    Full Text Available A current challenge is to develop computational approaches to infer gene network regulatory relationships based on multiple types of large-scale functional genomic data. We find that single-layer feed-forward artificial neural network (ANN models can effectively discover gene network structure by integrating global in vivo protein:DNA interaction data (ChIP/Array with genome-wide microarray RNA data. We test this on the yeast cell cycle transcription network, which is composed of several hundred genes with phase-specific RNA outputs. These ANNs were robust to noise in data and to a variety of perturbations. They reliably identified and ranked 10 of 12 known major cell cycle factors at the top of a set of 204, based on a sum-of-squared weights metric. Comparative analysis of motif occurrences among multiple yeast species independently confirmed relationships inferred from ANN weights analysis. ANN models can capitalize on properties of biological gene networks that other kinds of models do not. ANNs naturally take advantage of patterns of absence, as well as presence, of factor binding associated with specific expression output; they are easily subjected to in silico "mutation" to uncover biological redundancies; and they can use the full range of factor binding values. A prominent feature of cell cycle ANNs suggested an analogous property might exist in the biological network. This postulated that "network-local discrimination" occurs when regulatory connections (here between MBF and target genes are explicitly disfavored in one network module (G2, relative to others and to the class of genes outside the mitotic network. If correct, this predicts that MBF motifs will be significantly depleted from the discriminated class and that the discrimination will persist through evolution. Analysis of distantly related Schizosaccharomyces pombe confirmed this, suggesting that network-local discrimination is real and complements well-known enrichment of

  1. Interfacial Interaction of Titania Nanoparticles and Ligated Uranyl Species: A Relativistic DFT Investigation.

    Science.gov (United States)

    Zhao, Hong-Bo; Zheng, Ming; Schreckenbach, Georg; Pan, Qing-Jiang

    2017-03-06

    To understand interfacial behavior of actinides adsorbed onto mineral surfaces and unravel their structure-property relationship, the structures, electronic properties, and energetics of various ligated uranyl species adsorbed onto TiO 2 surface nanoparticle clusters (SNCs) were examined using relativistic density functional theory. Rutile (110) and anatase (101) titania surfaces, experimentally known to be stable, were fully optimized. For the former, models studied include clean and water-free Ti 27 O 64 H 20 (dry), partially hydrated (Ti 27 O 64 H 20 )(H 2 O) 8 (sol) and proton-saturated [(Ti 27 O 64 H 20 )(H 2 O) 8 (H) 2 ] 2+ (sat), while defect-free and defected anatase SNCs involving more than 38 TiO 2 units were considered. The aquouranyl sorption onto rutile SNCs is energetically preferred, with interaction energies of -8.54, -10.36, and -2.39 eV, respectively. Energy decomposition demonstrates that the sorption is dominated by orbital attractive interactions and modified by steric effects. Greater hydrogen-bonding involvement leads to increased orbital interactions (i.e., more negative energy) from dry to sol/sat complexes, while much larger steric interaction in the sat complex significantly reduces the sorption interaction (i.e., more positive energy). For dry SNC, adsorbates were varied from aquo to aquo-carbonato, to carbonato, to hydroxo uranyl species. Longer U-O surf /U-Ti distances and more positive sorption energies were calculated upon introducing carbonato and hydroxo ligands, indicative of weaker uranyl sorption onto the substrate. This is consistent with experimental observations that the uranyl sorption rate decreases upon raising solution pH value or adding carbon dioxide. Anatase SNCs adsorbing aquouranyl are even more exothermic, because more bonds are formed than in the case of rutile. Moreover, the anatase sorption can be tuned by surface defects as well as its Ti and O stoichiometry. All the aquouranyl-SNC complexes show similar

  2. Prokaryotic Phylogenies Inferred from Whole-Genome Sequence and Annotation Data

    Directory of Open Access Journals (Sweden)

    Wei Du

    2013-01-01

    Full Text Available Phylogenetic trees are used to represent the evolutionary relationship among various groups of species. In this paper, a novel method for inferring prokaryotic phylogenies using multiple genomic information is proposed. The method is called CGCPhy and based on the distance matrix of orthologous gene clusters between whole-genome pairs. CGCPhy comprises four main steps. First, orthologous genes are determined by sequence similarity, genomic function, and genomic structure information. Second, genes involving potential HGT events are eliminated, since such genes are considered to be the highly conserved genes across different species and the genes located on fragments with abnormal genome barcode. Third, we calculate the distance of the orthologous gene clusters between each genome pair in terms of the number of orthologous genes in conserved clusters. Finally, the neighbor-joining method is employed to construct phylogenetic trees across different species. CGCPhy has been examined on different datasets from 617 complete single-chromosome prokaryotic genomes and achieved applicative accuracies on different species sets in agreement with Bergey's taxonomy in quartet topologies. Simulation results show that CGCPhy achieves high average accuracy and has a low standard deviation on different datasets, so it has an applicative potential for phylogenetic analysis.

  3. Landscape-scale evaluation of asymmetric interactions between Brown Trout and Brook Trout using two-species occupancy models

    Science.gov (United States)

    Wagner, Tyler; Jefferson T. Deweber,; Jason Detar,; John A. Sweka,

    2013-01-01

    Predicting the distribution of native stream fishes is fundamental to the management and conservation of many species. Modeling species distributions often consists of quantifying relationships between species occurrence and abundance data at known locations with environmental data at those locations. However, it is well documented that native stream fish distributions can be altered as a result of asymmetric interactions between dominant exotic and subordinate native species. For example, the naturalized exotic Brown Trout Salmo trutta has been identified as a threat to native Brook Trout Salvelinus fontinalis in the eastern United States. To evaluate large-scale patterns of co-occurrence and to quantify the potential effects of Brown Trout presence on Brook Trout occupancy, we used data from 624 stream sites to fit two-species occupancy models. These models assumed that asymmetric interactions occurred between the two species. In addition, we examined natural and anthropogenic landscape characteristics we hypothesized would be important predictors of occurrence of both species. Estimated occupancy for Brook Trout, from a co-occurrence model with no landscape covariates, at sites with Brown Trout present was substantially lower than sites where Brown Trout were absent. We also observed opposing patterns for Brook and Brown Trout occurrence in relation to percentage forest, impervious surface, and agriculture within the network catchment. Our results are consistent with other studies and suggest that alterations to the landscape, and specifically the transition from a forested catchment to one that contains impervious surface or agriculture, reduces the occurrence probability of wild Brook Trout. Our results, however, also suggest that the presence of Brown Trout results in lower occurrence probability of Brook Trout over a range of anthropogenic landscape characteristics, compared with streams where Brown Trout were absent.

  4. Phylogenetic diversity and relationships among species of genus ...

    African Journals Online (AJOL)

    Fifty six Nicotiana species were used to construct phylogenetic trees and to asses the genetic relationships between them. Genetic distances estimated from RAPD analysis was used to construct phylogenetic trees using Phylogenetic Inference Package (PHYLIP). Since phylogenetic relationships estimated for closely ...

  5. Uncovering transcriptional interactions via an adaptive fuzzy logic approach

    Directory of Open Access Journals (Sweden)

    Chen Chung-Ming

    2009-12-01

    Full Text Available Abstract Background To date, only a limited number of transcriptional regulatory interactions have been uncovered. In a pilot study integrating sequence data with microarray data, a position weight matrix (PWM performed poorly in inferring transcriptional interactions (TIs, which represent physical interactions between transcription factors (TF and upstream sequences of target genes. Inferring a TI means that the promoter sequence of a target is inferred to match the consensus sequence motifs of a potential TF, and their interaction type such as AT or RT is also predicted. Thus, a robust PWM (rPWM was developed to search for consensus sequence motifs. In addition to rPWM, one feature extracted from ChIP-chip data was incorporated to identify potential TIs under specific conditions. An interaction type classifier was assembled to predict activation/repression of potential TIs using microarray data. This approach, combining an adaptive (learning fuzzy inference system and an interaction type classifier to predict transcriptional regulatory networks, was named AdaFuzzy. Results AdaFuzzy was applied to predict TIs using real genomics data from Saccharomyces cerevisiae. Following one of the latest advances in predicting TIs, constrained probabilistic sparse matrix factorization (cPSMF, and using 19 transcription factors (TFs, we compared AdaFuzzy to four well-known approaches using over-representation analysis and gene set enrichment analysis. AdaFuzzy outperformed these four algorithms. Furthermore, AdaFuzzy was shown to perform comparably to 'ChIP-experimental method' in inferring TIs identified by two sets of large scale ChIP-chip data, respectively. AdaFuzzy was also able to classify all predicted TIs into one or more of the four promoter architectures. The results coincided with known promoter architectures in yeast and provided insights into transcriptional regulatory mechanisms. Conclusion AdaFuzzy successfully integrates multiple types of

  6. Study on the interaction of U(VI) species with natural organic matters in KURT groundwater

    Energy Technology Data Exchange (ETDEWEB)

    Jung, Euo Chang; Baik, Min Hoon; Cho, Hye Ryun; Kim, Hee Kyung; Cha, Wansik [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2017-06-15

    The interaction of U(VI) (hexavalent uranium) species with natural organic matter (NOM) in KURT (KAERI Underground Research Tunnel) groundwater is investigated using a laser spectroscopic technique. The luminescence spectra of the NOM are observed in the ultraviolet and blue wavelength regions by irradiating a laser beam at 266 nm in groundwater. The luminescence spectra of U(VI) species in groundwater containing uranium concentrations of 0.034-0.788 mg·L-1 are measured in the green-colored wavelength region. The luminescence characteristics (peak wavelengths and lifetime) of U(VI) in the groundwater agree well with those of Ca{sub 2}UO{sub 2}(CO{sub 3}){sub 3}(aq) in a standard solution prepared in a laboratory. The luminescence intensities of U(VI) in the groundwater are weaker than those of Ca{sub 2}UO{sub 2}(CO{sub 3}){sub 3}(aq) in the standard solution at the same uranium concentrations. The luminescence intensities of Ca{sub 2}UO{sub 2}(CO{sub 3}){sub 3}(aq) in the standard solution mixed with the groundwater are also weaker than those of Ca{sub 2}UO{sub 2}(CO{sub 3}){sub 3}(aq) in the standard solution at the same uranium concentrations. These results can be ascribed to calcium-U(VI)-carbonate species interacting with NOM and forming non-radiative U(VI) complexes in groundwater.

  7. Inferring network topology from complex dynamics

    International Nuclear Information System (INIS)

    Shandilya, Srinivas Gorur; Timme, Marc

    2011-01-01

    Inferring the network topology from dynamical observations is a fundamental problem pervading research on complex systems. Here, we present a simple, direct method for inferring the structural connection topology of a network, given an observation of one collective dynamical trajectory. The general theoretical framework is applicable to arbitrary network dynamical systems described by ordinary differential equations. No interference (external driving) is required and the type of dynamics is hardly restricted in any way. In particular, the observed dynamics may be arbitrarily complex; stationary, invariant or transient; synchronous or asynchronous and chaotic or periodic. Presupposing a knowledge of the functional form of the dynamical units and of the coupling functions between them, we present an analytical solution to the inverse problem of finding the network topology from observing a time series of state variables only. Robust reconstruction is achieved in any sufficiently long generic observation of the system. We extend our method to simultaneously reconstructing both the entire network topology and all parameters appearing linear in the system's equations of motion. Reconstruction of network topology and system parameters is viable even in the presence of external noise that distorts the original dynamics substantially. The method provides a conceptually new step towards reconstructing a variety of real-world networks, including gene and protein interaction networks and neuronal circuits.

  8. Caught in the Same Net? Small-Scale Fishermen's Perceptions of Fisheries Interactions with Sea Turtles and Other Protected Species

    Directory of Open Access Journals (Sweden)

    Aliki Panagopoulou

    2017-06-01

    Full Text Available Small-scale fisheries are responsible for high numbers of animals caught as bycatch, such as turtles, cetaceans, and seals. Bycatch and its associated mortality is a major conservation challenge for these species and is considered undesirable by fishermen. To gain insights on the impact of bycatch on small-scale fishermen and put it in context with other financial and environmental challenges they face, we conducted questionnaire-based interviews on fishermen working on Crete, Greece. We investigated fishermen's perceptions of sea turtle and other protected species interactions, and the impacts of such interactions on their profession and livelihoods. Our results indicate a connection between declining fish stocks, related increased fishing effort, and reported increased frequency of interactions between fishermen and sea turtles. Respondents believed that their livelihoods were endangered by industrial fishing and environmental problems, but thought that combined interactions with turtles and other marine megafauna species were a larger problem. Responses suggested that extending compensation to fishermen may be a good conservation intervention. Small-scale fishermen hold a wealth of knowledge about the marine environment and its resources. This may be of help to researchers and policy makers as it could be used to achieve a better managed, sustainable fishery. Including small-scale fishermen in the process of developing regulations will both enhance those regulations and increase compliance with them.

  9. Diversification of the silverspot butterflies (Nymphalidae) in the Neotropics inferred from multi-locus DNA sequences.

    Science.gov (United States)

    Massardo, Darli; Fornel, Rodrigo; Kronforst, Marcus; Gonçalves, Gislene Lopes; Moreira, Gilson Rudinei Pires

    2015-01-01

    The tribe Heliconiini (Lepidoptera: Nymphalidae) is a diverse group of butterflies distributed throughout the Neotropics, which has been studied extensively, in particular the genus Heliconius. However, most of the other lineages, such as Dione, which are less diverse and considered basal within the group, have received little attention. Basic information, such as species limits and geographical distributions remain uncertain for this genus. Here we used multilocus DNA sequence data and the geographical distribution analysis across the entire range of Dione in the Neotropical region in order to make inferences on the evolutionary history of this poorly explored lineage. Bayesian time-tree reconstruction allows inferring two major diversification events in this tribe around 25mya. Lineages thought to be ancient, such as Dione and Agraulis, are as recent as Heliconius. Dione formed a monophyletic clade, sister to the genus Agraulis. Dione juno, D. glycera and D. moneta were reciprocally monophyletic and formed genetic clusters, with the first two more close related than each other in relation to the third. Divergence time estimates support the hypothesis that speciation in Dione coincided with both the rise of Passifloraceae (the host plants) and the uplift of the Andes. Since the sister species D. glycera and D. moneta are specialized feeders on passion-vine lineages that are endemic to areas located either within or adjacent to the Andes, we inferred that they co-speciated with their host plants during this vicariant event. Copyright © 2014 Elsevier Inc. All rights reserved.

  10. The role of biotic interactions in plant community assembly: What is the community species pool?

    Science.gov (United States)

    Švamberková, Eva; Vítová, Alena; Lepš, Jan

    2017-11-01

    Differences in plant species composition between a community and its species pool are considered to reflect the effect of community filters. If we define the species pool as a set of species able to reach a site and form a viable population in a given abiotic environment (i.e. to pass the dispersal and abiotic filter), the difference in species composition should correspond to the effect of biotic interactions. However, most of the operational definitions of the species pool are based on co-occurrence patterns and thus also reflect the effect of biotic relationships, including definitions based on functional plant traits, Ellenberg indicator values or Beals index. We conducted two seed introduction experiments in an oligotrophic wet meadow with the aim of demonstrating that many species excluded, according to the above definitions, from a species pool are in fact able to establish there successfully if competition is removed. In sowing experiments, we studied the establishment and survival of species after the removal of competition (i.e. in artificial gaps) and in intact vegetation. We also investigated inter-annual variability of seed germination and seedling establishment and competitive exclusion of sown species. The investigated species also included those from very different habitats (i.e. species with very low corresponding Beals index or Ellenberg indicator values that were different from the target community weighted mean). Many of these species were able to grow in the focal wet meadow if competition was removed, but they did not establish and survive in the intact community. These species are thus not limited by abiotic conditions, but by the biotic filter. We also recorded a great inter-annual variability in seed germination and seedling establishment. Competitive exclusion of species with different ecological requirements could be quite fast (one and half seasons) in some species, but some non-resident species were able to survive several seasons; the

  11. An Inference Language for Imaging

    DEFF Research Database (Denmark)

    Pedemonte, Stefano; Catana, Ciprian; Van Leemput, Koen

    2014-01-01

    We introduce iLang, a language and software framework for probabilistic inference. The iLang framework enables the definition of directed and undirected probabilistic graphical models and the automated synthesis of high performance inference algorithms for imaging applications. The iLang framewor...

  12. Phylogenetic relationships in the genus Leonardoxa (Leguminosae: Caesalpinioideae) inferred from chloroplast trnL intron and trnL-trnF intergenic spacer sequences.

    Science.gov (United States)

    Brouat, Carine; Gielly, Ludovic; McKey, Doyle

    2001-01-01

    The African genus LEONARDOXA: (Leguminosae: Caesalpinioideae) comprises two Congolean species and a group of four mostly allopatric subspecies principally located in Cameroon and clustered together in the L. africana complex. LEONARDOXA: provides a good opportunity to investigate the evolutionary history of ant-plant mutualisms, as it exhibits various grades of ant-plant interactions from diffuse to obligate and symbiotic associations. We present in this paper the first molecular phylogenetic study of this genus. We sequenced both the chloroplast DNA trnL intron (677 aligned base pairs [bp]) and trnL-trnF intergene spacer (598 aligned bp). Inferred phylogenetic relationships suggested first that the genus is paraphyletic. The L. africana complex is clearly separated from the two Congolean species, and the integrity of the genus is thus in question. In the L. africana complex, our data showed a lack of congruence between clades suggested by morphological and chloroplast characters. This, and the low level of molecular divergence found between subspecies, suggests gene flow and introgressive events in the L. africana complex.

  13. Sapling performance along resource gradients drives tree species distributions within and across tropical forests

    NARCIS (Netherlands)

    Sterck, F.J.; Markesteijn, L.; Toledo, M.; Schieving, F.; Poorter, L.

    2014-01-01

    Niche differentiation is a major hypothesized determinant of species distributions, but its practical importance is heavily debated and its underlying mechanisms are poorly understood. Trait-based approaches have been used to infer niche differentiation and predict species distributions. For

  14. Yakima River Species Interactions Studies; Yakima/Klickitat Fisheries Project Monitoring and Evaluation, 2004-2005 Annual Report.

    Energy Technology Data Exchange (ETDEWEB)

    Pearsons, Todd N.; Temple, Gabriel M.; Fritts, Anthony L. (Washington Department of Fish and Wildlife, Olympia, WA)

    2005-05-01

    This report is intended to satisfy two concurrent needs: (1) provide a contract deliverable from the Washington Department of Fish and Wildlife (WDFW) to the Bonneville Power Administration (BPA), with emphasis on identification of salient results of value to ongoing Yakima/Klickitat Fisheries Project (YKFP) planning, and (2) summarize results of research that have broader scientific relevance. This is the thirteenth of a series of progress reports that address species interactions research and supplementation monitoring of fishes in response to supplementation of salmon and steelhead in the upper Yakima River basin (Hindman et al. 1991; McMichael et al. 1992; Pearsons et al. 1993; Pearsons et al. 1994; Pearsons et al. 1996; Pearsons et al. 1998, Pearsons et al. 1999, Pearsons et al. 2001a, Pearsons et al. 2001b, Pearsons et al. 2002, Pearsons et al. 2003, Pearsons et al. 2004). Journal articles and book chapters have also been published from our work (McMichael 1993; Martin et al. 1995; McMichael et al. 1997; McMichael and Pearsons 1998; McMichael et al. 1998; Pearsons and Fritts 1999; McMichael et al. 1999; McMichael et al. 1999; Pearsons and Hopley 1999; Ham and Pearsons 2000; Ham and Pearsons 2001; Amaral et al. 2001; McMichael and Pearsons 2001; Pearsons 2002, Fritts and Pearsons 2004, Pearsons et al. in press, Major et al. in press). This progress report summarizes data collected between January 1, 2004 and December 31, 2004. These data were compared to findings from previous years to identify general trends and make preliminary comparisons. Interactions between fish produced as part of the YKFP, termed target species or stocks, and other species or stocks (non-target taxa) may alter the population status of non-target species or stocks. This may occur through a variety of mechanisms, such as competition, predation, and interbreeding (Pearsons et al. 1994; Busack et al. 1997; Pearsons and Hopley 1999). Furthermore, the success of a supplementation program may

  15. Inference

    DEFF Research Database (Denmark)

    Møller, Jesper

    2010-01-01

    Chapter 9: This contribution concerns statistical inference for parametric models used in stochastic geometry and based on quick and simple simulation free procedures as well as more comprehensive methods based on a maximum likelihood or Bayesian approach combined with markov chain Monte Carlo...... (MCMC) techniques. Due to space limitations the focus is on spatial point processes....

  16. Feature Inference Learning and Eyetracking

    Science.gov (United States)

    Rehder, Bob; Colner, Robert M.; Hoffman, Aaron B.

    2009-01-01

    Besides traditional supervised classification learning, people can learn categories by inferring the missing features of category members. It has been proposed that feature inference learning promotes learning a category's internal structure (e.g., its typical features and interfeature correlations) whereas classification promotes the learning of…

  17. Learning from instructional explanations: effects of prompts based on the active-constructive-interactive framework.

    Science.gov (United States)

    Roelle, Julian; Müller, Claudia; Roelle, Detlev; Berthold, Kirsten

    2015-01-01

    Although instructional explanations are commonly provided when learners are introduced to new content, they often fail because they are not integrated into effective learning activities. The recently introduced active-constructive-interactive framework posits an effectiveness hierarchy in which interactive learning activities are at the top; these are then followed by constructive and active learning activities, respectively. Against this background, we combined instructional explanations with different types of prompts that were designed to elicit these learning activities and tested the central predictions of the active-constructive-interactive framework. In Experiment 1, N = 83 students were randomly assigned to one of four combinations of instructional explanations and prompts. To test the active learning hypothesis, the learners received either (1) complete explanations and engaging prompts designed to elicit active activities or (2) explanations that were reduced by inferences and inference prompts designed to engage learners in constructing the withheld information. Furthermore, in order to explore how interactive learning activities can be elicited, we gave the learners who had difficulties in constructing the prompted inferences adapted remedial explanations with either (3) unspecific engaging prompts or (4) revision prompts. In support of the active learning hypothesis, we found that the learners who received reduced explanations and inference prompts outperformed the learners who received complete explanations and engaging prompts. Moreover, revision prompts were more effective in eliciting interactive learning activities than engaging prompts. In Experiment 2, N = 40 students were randomly assigned to either (1) a reduced explanations and inference prompts or (2) a reduced explanations and inference prompts plus adapted remedial explanations and revision prompts condition. In support of the constructive learning hypothesis, the learners who received

  18. Bayesian Inference of Forces Causing Cytoplasmic Streaming in Caenorhabditis elegans Embryos and Mouse Oocytes.

    Science.gov (United States)

    Niwayama, Ritsuya; Nagao, Hiromichi; Kitajima, Tomoya S; Hufnagel, Lars; Shinohara, Kyosuke; Higuchi, Tomoyuki; Ishikawa, Takuji; Kimura, Akatsuki

    2016-01-01

    Cellular structures are hydrodynamically interconnected, such that force generation in one location can move distal structures. One example of this phenomenon is cytoplasmic streaming, whereby active forces at the cell cortex induce streaming of the entire cytoplasm. However, it is not known how the spatial distribution and magnitude of these forces move distant objects within the cell. To address this issue, we developed a computational method that used cytoplasm hydrodynamics to infer the spatial distribution of shear stress at the cell cortex induced by active force generators from experimentally obtained flow field of cytoplasmic streaming. By applying this method, we determined the shear-stress distribution that quantitatively reproduces in vivo flow fields in Caenorhabditis elegans embryos and mouse oocytes during meiosis II. Shear stress in mouse oocytes were predicted to localize to a narrower cortical region than that with a high cortical flow velocity and corresponded with the localization of the cortical actin cap. The predicted patterns of pressure gradient in both species were consistent with species-specific cytoplasmic streaming functions. The shear-stress distribution inferred by our method can contribute to the characterization of active force generation driving biological streaming.

  19. A ReaxFF-based molecular dynamics study of the mechanisms of interactions between reactive oxygen plasma species and the Candida albicans cell wall

    Science.gov (United States)

    Zhao, T.; Shi, L.; Zhang, Y. T.; Zou, L.; Zhang, L.

    2017-10-01

    Atmospheric pressure non-equilibrium plasmas have attracted significant attention and have been widely used to inactivate pathogens, yet the mechanisms underlying the interactions between plasma-generated species and bio-organisms have not been elucidated clearly. In this paper, reactive molecular dynamics simulations are employed to investigate the mechanisms of interactions between reactive oxygen plasma species (O, OH, and O2) and β-1,6-glucan (a model for the C. albicans cell wall) from a microscopic point of view. Our simulations show that O and OH species can break structurally important C-C and C-O bonds, while O2 molecules exhibit only weak, non-bonded interactions with β-1,6-glucan. Hydrogen abstraction from hydroxyl or CH groups occurs first in all bond cleavage mechanisms. This is followed by a cascade of bond cleavage and double bond formation events. These lead to the destruction of the fungal cell wall. O and OH have similar effects related to their bond cleavage mechanisms. Our simulation results provide fundamental insights into the mechanisms underlying the interactions between reactive oxygen plasma species and the fungal cell wall of C. albicans at the atomic level.

  20. An assessment of machine and statistical learning approaches to inferring networks of protein-protein interactions

    Directory of Open Access Journals (Sweden)

    Browne Fiona

    2006-12-01

    Full Text Available Protein-protein interactions (PPI play a key role in many biological systems. Over the past few years, an explosion in availability of functional biological data obtained from high-throughput technologies to infer PPI has been observed. However, results obtained from such experiments show high rates of false positives and false negatives predictions as well as systematic predictive bias. Recent research has revealed that several machine and statistical learning methods applied to integrate relatively weak, diverse sources of large-scale functional data may provide improved predictive accuracy and coverage of PPI. In this paper we describe the effects of applying different computational, integrative methods to predict PPI in Saccharomyces cerevisiae. We investigated the predictive ability of combining different sets of relatively strong and weak predictive datasets. We analysed several genomic datasets ranging from mRNA co-expression to marginal essentiality. Moreover, we expanded an existing multi-source dataset from S. cerevisiae by constructing a new set of putative interactions extracted from Gene Ontology (GO- driven annotations in the Saccharomyces Genome Database. Different classification techniques: Simple Naive Bayesian (SNB, Multilayer Perceptron (MLP and K-Nearest Neighbors (KNN were evaluated. Relatively simple classification methods (i.e. less computing intensive and mathematically complex, such as SNB, have been proven to be proficient at predicting PPI. SNB produced the “highest” predictive quality obtaining an area under Receiver Operating Characteristic (ROC curve (AUC value of 0.99. The lowest AUC value of 0.90 was obtained by the KNN classifier. This assessment also demonstrates the strong predictive power of GO-driven models, which offered predictive performance above 0.90 using the different machine learning and statistical techniques. As the predictive power of single-source datasets became weaker MLP and SNB performed

  1. Occurrence and evolutionary inferences about Kranz anatomy in Cyperaceae (Poales

    Directory of Open Access Journals (Sweden)

    SHIRLEY MARTINS

    2015-12-01

    Full Text Available ABSTRACT Cyperaceae is an angiosperm family with the greatest diversity of species with Kranz anatomy. Four different types of Kranz anatomy (chlorocyperoid, eleocharoid, fimbristyloid and rhynchosporoid have been described for this angiosperm family, and the occurrence and structural characteristics of these types are important to trace evolutionary hypotheses. The purpose of this study was to examine the available data on Cyperaceae Kranz anatomy, emphasizing taxonomy, geographic distribution, habitat and anatomy, to infer the potential origin of the Kranz anatomy in this family. The results showed that the four types of Kranz anatomy (associated with C4 photosynthesis in Cyperaceae emerged numerous times in unrelated phylogenetic groups. However, the convergence of these anatomical types, except rhynchosporoid, was observed in certain groups. Thus, the diverse origin of these species might result from different environmental pressures that promote photorespiration. Greater variation in occurrence of Kranz anatomy and anatomical types was observed inEleocharis, whose emergence of the C4 pathway was recent compared with other genera in the family, and the species of this genus are located in aquatic environments.

  2. Patterns of contemporary hybridization inferred from paternity analysis in a four-oak-species forest

    Directory of Open Access Journals (Sweden)

    Gailing Oliver

    2009-12-01

    Full Text Available Abstract Background Few studies address the issue of hybridization in a more than two-species context. The species-rich Quercus complex is one of the systems which can offer such an opportunity. To investigate the contemporary pattern of hybridization we sampled and genotyped 320 offspring from a natural mixed forest comprising four species of the European white oak complex: Quercus robur, Q. petraea, Q. pubescens, and Q. frainetto. Results A total of 165 offspring were assigned unambiguously to one of the pollen donors within the study plot. The minimum amount of effective pollen originating from outside the plot varied markedly among the seed parents, ranging from 0.18 to 0.87. The majority of the successful matings (64.1% occurred between conspecific individuals indicating the existence of reproductive barriers between oak species. However, the isolation was not complete since we found strong evidence for both first-generation (8.4% and later-generation hybrids (27.5%. Only two out of eight seed parents, belonging to Q. petraea and Q. robur, showed a high propensity to hybridize with Q. pubescens and Q. petraea, respectively. Significant structure of the effective pollen pools (Φpt = 0.069, P = 0.01 was detected in our sample. However, no support was found for the isolation by distance hypothesis. The proportion of hybrids was much higher (79% in the seed generation when compared to the adult tree generation. Conclusion First-generation hybrids were observed only between three out of six possible species combinations. Hybrids between one pair of species preferred to mate with one of their parental species. The observation of first and later-generation hybrids in higher frequency in acorns than in adults might be explained by selection against hybrid genotypes, the history of this uneven-aged forest or past introgression between species.

  3. Species interactions slow warming-induced upward shifts of treelines on the Tibetan Plateau

    Science.gov (United States)

    Liang, Eryuan; Wang, Yafeng; Piao, Shilong; Lu, Xiaoming; Camarero, Jesús Julio; Zhu, Haifeng; Zhu, Liping; Ciais, Philippe; Peñuelas, Josep

    2016-01-01

    The alpine treeline is commonly regarded as being sensitive to climatic warming because regeneration and growth of trees at treeline generally are limited by low temperature. The alpine treelines of the Tibetan Plateau (TP) occur at the highest elevations (4,900 m above sea level) in the Northern Hemisphere. Ongoing climatic warming is expected to shift treelines upward. Studies of treeline dynamics at regional and local scales, however, have yielded conflicting results, indicating either unchanging treeline elevations or upward shifts. To reconcile this conflict, we reconstructed in detail a century of treeline structure and tree recruitment at sites along a climatic gradient of 4 °C and mean annual rainfall of 650 mm on the eastern TP. Species interactions interacted with effects of warming on treeline and could outweigh them. Densification of shrubs just above treeline inhibited tree establishment, and slowed upward movement of treelines on a time scale of decades. Interspecific interactions are major processes controlling treeline dynamics that may account for the absence of an upward shift at some TP treelines despite continued climatic warming. PMID:27044083

  4. Species interactions slow warming-induced upward shifts of treelines on the Tibetan Plateau.

    Science.gov (United States)

    Liang, Eryuan; Wang, Yafeng; Piao, Shilong; Lu, Xiaoming; Camarero, Jesús Julio; Zhu, Haifeng; Zhu, Liping; Ellison, Aaron M; Ciais, Philippe; Peñuelas, Josep

    2016-04-19

    The alpine treeline is commonly regarded as being sensitive to climatic warming because regeneration and growth of trees at treeline generally are limited by low temperature. The alpine treelines of the Tibetan Plateau (TP) occur at the highest elevations (4,900 m above sea level) in the Northern Hemisphere. Ongoing climatic warming is expected to shift treelines upward. Studies of treeline dynamics at regional and local scales, however, have yielded conflicting results, indicating either unchanging treeline elevations or upward shifts. To reconcile this conflict, we reconstructed in detail a century of treeline structure and tree recruitment at sites along a climatic gradient of 4 °C and mean annual rainfall of 650 mm on the eastern TP. Species interactions interacted with effects of warming on treeline and could outweigh them. Densification of shrubs just above treeline inhibited tree establishment, and slowed upward movement of treelines on a time scale of decades. Interspecific interactions are major processes controlling treeline dynamics that may account for the absence of an upward shift at some TP treelines despite continued climatic warming.

  5. Forward and backward inference in spatial cognition.

    Directory of Open Access Journals (Sweden)

    Will D Penny

    Full Text Available This paper shows that the various computations underlying spatial cognition can be implemented using statistical inference in a single probabilistic model. Inference is implemented using a common set of 'lower-level' computations involving forward and backward inference over time. For example, to estimate where you are in a known environment, forward inference is used to optimally combine location estimates from path integration with those from sensory input. To decide which way to turn to reach a goal, forward inference is used to compute the likelihood of reaching that goal under each option. To work out which environment you are in, forward inference is used to compute the likelihood of sensory observations under the different hypotheses. For reaching sensory goals that require a chaining together of decisions, forward inference can be used to compute a state trajectory that will lead to that goal, and backward inference to refine the route and estimate control signals that produce the required trajectory. We propose that these computations are reflected in recent findings of pattern replay in the mammalian brain. Specifically, that theta sequences reflect decision making, theta flickering reflects model selection, and remote replay reflects route and motor planning. We also propose a mapping of the above computational processes onto lateral and medial entorhinal cortex and hippocampus.

  6. Ecological multiplex interactions determine the role of species for parasite spread amplification.

    Science.gov (United States)

    Stella, Massimo; Selakovic, Sanja; Antonioni, Alberto; Andreazzi, Cecilia

    2018-04-23

    Despite their potential interplay, multiple routes of many disease transmissions are often investigated separately. As an unifying framework for understanding parasite spread through interdependent transmission paths, we present the 'ecomultiplex' model, where the multiple transmission paths among a diverse community of interacting hosts are represented as a spatially explicit multiplex network. We adopt this framework for designing and testing potential control strategies for T. cruzi spread in two empirical host communities. We show that the ecomultiplex model is an efficient and low data-demanding method to identify which species enhances parasite spread and should thus be a target for control strategies. We also find that the interplay between predator-prey and host-parasite interactions leads to a phenomenon of parasite amplification, in which top predators facilitate T. cruzi spread, offering a mechanistic interpretation of previous empirical findings. Our approach can provide novel insights in understanding and controlling parasite spreading in real-world complex systems. © 2018, Stella et al.

  7. Feeding behavior and trophic interaction of three shark species in the Galapagos Marine Reserve

    Directory of Open Access Journals (Sweden)

    Diego Páez-Rosas

    2018-05-01

    Full Text Available There is great concern about the future of sharks in Ecuador because of the lack of biological knowledge of most species that inhabit the region. This paper analyzes the feeding behavior of the pelagic thresher shark (Alopias pelagicus, the blue shark (Prionace glauca and the silky shark (Carcharhinus falciformis through the use of stable isotopes of carbon and nitrogen (δ13C and δ15N, with the aim of determining the degree of interaction between these species in the Galapagos Marine Reserve. No interspecific differences were found in use of oceanic vs. inshore feeding areas (δ13C: Kruskal–Wallis test, p = 0.09. The position in the hierarchy of the food web where A. pelagicus feeds differed from that of the other species (δ15N: Kruskal–Wallis test, p = 0.01. There were no significant differences in δ13C and δ15N values between males and females of the three species (Student’s t-test, p > 0.05, which suggests that both sexes have a similar feeding behavior. A specialist strategy was observed in P. glauca (trophic niche breadth TNB = 0.69, while the other species were found to be generalist (A. pelagicus TNB = 1.50 and C. falciformis TNB = 1.09. The estimated trophic level (TL varied between the three species. C. falciformis occupied the highest trophic level (TL = 4.4, making it a quaternary predator in the region. The results of this study coincide with the identified behavior in these predators in other areas of the tropical Pacific (Colombia and Mexico, and suggest a pelagic foraging strategy with differential consumption of prey between the three species. These ecological aspects can provide timely information when implementing in conservation measures for these shark species in the Tropical Pacific and Galapagos Marine Reserve.

  8. Feeding behavior and trophic interaction of three shark species in the Galapagos Marine Reserve.

    Science.gov (United States)

    Páez-Rosas, Diego; Insuasti-Zarate, Paul; Riofrío-Lazo, Marjorie; Galván-Magaña, Felipe

    2018-01-01

    There is great concern about the future of sharks in Ecuador because of the lack of biological knowledge of most species that inhabit the region. This paper analyzes the feeding behavior of the pelagic thresher shark ( Alopias pelagicus ), the blue shark ( Prionace glauca ) and the silky shark ( Carcharhinus falciformis ) through the use of stable isotopes of carbon and nitrogen ( δ 13 C and δ 15 N), with the aim of determining the degree of interaction between these species in the Galapagos Marine Reserve. No interspecific differences were found in use of oceanic vs. inshore feeding areas ( δ 13 C: Kruskal-Wallis test, p = 0.09). The position in the hierarchy of the food web where A. pelagicus feeds differed from that of the other species ( δ 15 N: Kruskal-Wallis test, p = 0.01). There were no significant differences in δ 13 C and δ 15 N values between males and females of the three species (Student's t -test, p  > 0.05), which suggests that both sexes have a similar feeding behavior. A specialist strategy was observed in P. glauca (trophic niche breadth TNB = 0.69), while the other species were found to be generalist ( A. pelagicus TNB = 1.50 and C. falciformis TNB = 1.09). The estimated trophic level (TL) varied between the three species. C. falciformis occupied the highest trophic level (TL = 4.4), making it a quaternary predator in the region. The results of this study coincide with the identified behavior in these predators in other areas of the tropical Pacific (Colombia and Mexico), and suggest a pelagic foraging strategy with differential consumption of prey between the three species. These ecological aspects can provide timely information when implementing in conservation measures for these shark species in the Tropical Pacific and Galapagos Marine Reserve.

  9. PHI-base: a new interface and further additions for the multi-species pathogen-host interactions database.

    Science.gov (United States)

    Urban, Martin; Cuzick, Alayne; Rutherford, Kim; Irvine, Alistair; Pedro, Helder; Pant, Rashmi; Sadanadan, Vidyendra; Khamari, Lokanath; Billal, Santoshkumar; Mohanty, Sagar; Hammond-Kosack, Kim E

    2017-01-04

    The pathogen-host interactions database (PHI-base) is available at www.phi-base.org PHI-base contains expertly curated molecular and biological information on genes proven to affect the outcome of pathogen-host interactions reported in peer reviewed research articles. In addition, literature that indicates specific gene alterations that did not affect the disease interaction phenotype are curated to provide complete datasets for comparative purposes. Viruses are not included. Here we describe a revised PHI-base Version 4 data platform with improved search, filtering and extended data display functions. A PHIB-BLAST search function is provided and a link to PHI-Canto, a tool for authors to directly curate their own published data into PHI-base. The new release of PHI-base Version 4.2 (October 2016) has an increased data content containing information from 2219 manually curated references. The data provide information on 4460 genes from 264 pathogens tested on 176 hosts in 8046 interactions. Prokaryotic and eukaryotic pathogens are represented in almost equal numbers. Host species belong ∼70% to plants and 30% to other species of medical and/or environmental importance. Additional data types included into PHI-base 4 are the direct targets of pathogen effector proteins in experimental and natural host organisms. The curation problems encountered and the future directions of the PHI-base project are briefly discussed. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  10. Inferring topologies of complex networks with hidden variables.

    Science.gov (United States)

    Wu, Xiaoqun; Wang, Weihan; Zheng, Wei Xing

    2012-10-01

    Network topology plays a crucial role in determining a network's intrinsic dynamics and function, thus understanding and modeling the topology of a complex network will lead to greater knowledge of its evolutionary mechanisms and to a better understanding of its behaviors. In the past few years, topology identification of complex networks has received increasing interest and wide attention. Many approaches have been developed for this purpose, including synchronization-based identification, information-theoretic methods, and intelligent optimization algorithms. However, inferring interaction patterns from observed dynamical time series is still challenging, especially in the absence of knowledge of nodal dynamics and in the presence of system noise. The purpose of this work is to present a simple and efficient approach to inferring the topologies of such complex networks. The proposed approach is called "piecewise partial Granger causality." It measures the cause-effect connections of nonlinear time series influenced by hidden variables. One commonly used testing network, two regular networks with a few additional links, and small-world networks are used to evaluate the performance and illustrate the influence of network parameters on the proposed approach. Application to experimental data further demonstrates the validity and robustness of our method.

  11. Inference of protein diffusion probed via fluorescence correlation spectroscopy

    Science.gov (United States)

    Tsekouras, Konstantinos

    2015-03-01

    Fluctuations are an inherent part of single molecule or few particle biophysical data sets. Traditionally, ``noise'' fluctuations have been viewed as a nuisance, to be eliminated or minimized. Here we look on how statistical inference methods - that take explicit advantage of fluctuations - have allowed us to draw an unexpected picture of single molecule diffusional dynamics. Our focus is on the diffusion of proteins probed using fluorescence correlation spectroscopy (FCS). First, we discuss how - in collaboration with the Bustamante and Marqusee labs at UC Berkeley - we determined using FCS data that individual enzymes are perturbed by self-generated catalytic heat (Riedel et al, Nature, 2014). Using the tools of inference, we found how distributions of enzyme diffusion coefficients shift in the presence of substrate revealing that enzymes performing highly exothermic reactions dissipate heat by transiently accelerating their center of mass following a catalytic reaction. Next, when molecules diffuse in the cell nucleus they often appear to diffuse anomalously. We analyze FCS data - in collaboration with Rich Day at the IU Med School - to propose a simple model for transcription factor binding-unbinding in the nucleus to show that it may give rise to apparent anomalous diffusion. Here inference methods extract entire binding affinity distributions for the diffusing transcription factors, allowing us to precisely characterize their interactions with different components of the nuclear environment. From this analysis, we draw key mechanistic insight that goes beyond what is possible by simply fitting data to ``anomalous diffusion'' models.

  12. A formal model of interpersonal inference

    Directory of Open Access Journals (Sweden)

    Michael eMoutoussis

    2014-03-01

    Full Text Available Introduction: We propose that active Bayesian inference – a general framework for decision-making – can equally be applied to interpersonal exchanges. Social cognition, however, entails special challenges. We address these challenges through a novel formulation of a formal model and demonstrate its psychological significance. Method: We review relevant literature, especially with regards to interpersonal representations, formulate a mathematical model and present a simulation study. The model accommodates normative models from utility theory and places them within the broader setting of Bayesian inference. Crucially, we endow people's prior beliefs, into which utilities are absorbed, with preferences of self and others. The simulation illustrates the model's dynamics and furnishes elementary predictions of the theory. Results: 1. Because beliefs about self and others inform both the desirability and plausibility of outcomes, in this framework interpersonal representations become beliefs that have to be actively inferred. This inference, akin to 'mentalising' in the psychological literature, is based upon the outcomes of interpersonal exchanges. 2. We show how some well-known social-psychological phenomena (e.g. self-serving biases can be explained in terms of active interpersonal inference. 3. Mentalising naturally entails Bayesian updating of how people value social outcomes. Crucially this includes inference about one’s own qualities and preferences. Conclusion: We inaugurate a Bayes optimal framework for modelling intersubject variability in mentalising during interpersonal exchanges. Here, interpersonal representations are endowed with explicit functional and affective properties. We suggest the active inference framework lends itself to the study of psychiatric conditions where mentalising is distorted.

  13. Distributional Inference

    NARCIS (Netherlands)

    Kroese, A.H.; van der Meulen, E.A.; Poortema, Klaas; Schaafsma, W.

    1995-01-01

    The making of statistical inferences in distributional form is conceptionally complicated because the epistemic 'probabilities' assigned are mixtures of fact and fiction. In this respect they are essentially different from 'physical' or 'frequency-theoretic' probabilities. The distributional form is

  14. Interactive Effects of Nitrogen and Climate Change on Biodiversity

    Science.gov (United States)

    Porter, E. M.; Bowman, W. D.; Clark, C. M.; Compton, J. E.; Pardo, L. H.; Soong, J.

    2011-12-01

    Biodiversity has been described as the diversity of life on earth within species, between species and in ecosystems. Biodiversity contributes to regulating ecosystem services like climate, flood, disease, and water quality regulation. Biodiversity also supports and sustains ecosystem services that provide material goods like food, fiber, fuel, timber and water, and to non-material benefits like educational, recreational, spiritual, and aesthetic ecosystem services. The Millennium Ecosystem Assessment estimated that the rate of biodiversity loss due to human activity in the last 50 years has been more rapid than at any other time in human history, and that many of the drivers of biodiversity loss are increasing. The strongest drivers of biodiversity loss include habitat loss, overexploitation, invasive species, climate change, and pollution, including pollution from reactive nitrogen. Of these stressors, climate change and reactive nitrogen from anthropogenic activities are causing some of the most rapid changes. Climate change is causing warming trends that result in consistent patterns of poleward and elevational range shifts of flora and fauna, causing changes in biodiversity. Warming has also resulted in changes in phenology, particularly the earlier onset of spring events, migration, and lengthening of the growing season, disrupting predator-prey and plant-pollinator interactions. In addition to warming, elevated carbon dioxide by itself can affect biodiversity by influencing plant growth, soil water, tissue stoichiometry, and trophic interactions. Nitrogen enrichment also impacts ecosystems and biodiversity in a variety of ways. Nitrogen enhances plant growth, but has been shown to favor invasive, fast-growing species over native species adapted to low nitrogen conditions. Although there have been a limited number of empirical studies on climate change and nitrogen interactions, inferences can be drawn from observed responses to each stressor by itself. For

  15. Continuous Integrated Invariant Inference, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The proposed project will develop a new technique for invariant inference and embed this and other current invariant inference and checking techniques in an...

  16. Estimating uncertainty of inference for validation

    Energy Technology Data Exchange (ETDEWEB)

    Booker, Jane M [Los Alamos National Laboratory; Langenbrunner, James R [Los Alamos National Laboratory; Hemez, Francois M [Los Alamos National Laboratory; Ross, Timothy J [UNM

    2010-09-30

    We present a validation process based upon the concept that validation is an inference-making activity. This has always been true, but the association has not been as important before as it is now. Previously, theory had been confirmed by more data, and predictions were possible based on data. The process today is to infer from theory to code and from code to prediction, making the role of prediction somewhat automatic, and a machine function. Validation is defined as determining the degree to which a model and code is an accurate representation of experimental test data. Imbedded in validation is the intention to use the computer code to predict. To predict is to accept the conclusion that an observable final state will manifest; therefore, prediction is an inference whose goodness relies on the validity of the code. Quantifying the uncertainty of a prediction amounts to quantifying the uncertainty of validation, and this involves the characterization of uncertainties inherent in theory/models/codes and the corresponding data. An introduction to inference making and its associated uncertainty is provided as a foundation for the validation problem. A mathematical construction for estimating the uncertainty in the validation inference is then presented, including a possibility distribution constructed to represent the inference uncertainty for validation under uncertainty. The estimation of inference uncertainty for validation is illustrated using data and calculations from Inertial Confinement Fusion (ICF). The ICF measurements of neutron yield and ion temperature were obtained for direct-drive inertial fusion capsules at the Omega laser facility. The glass capsules, containing the fusion gas, were systematically selected with the intent of establishing a reproducible baseline of high-yield 10{sup 13}-10{sup 14} neutron output. The deuterium-tritium ratio in these experiments was varied to study its influence upon yield. This paper on validation inference is the

  17. Magnetic interactions as a stabilizing factor of semiquinone species of lawsone by metal complexation

    International Nuclear Information System (INIS)

    Valle-Bourrouet, Grettel; Ugalde-Saldivar, Victor M.; Gomez, Martin; Ortiz-Frade, Luis A.; Gonzalez, Ignacio; Frontana, Carlos

    2010-01-01

    Changes in electrochemical reactivity for lawsone anions (lawsone, 2-hydroxy-1,4-naphthoquinone, HLw) being coordinated to a series of metallic ions in dimethylsulfoxide solution were evaluated. Upon performing cyclic voltammetry experiments for metal complexes of this quinone with pyridine (Py) - structural formula M(II)(Lw - ) 2 (Py) 2 ; M: Co(II), Ni(II), Zn(II) - it was found that the reduction of coordinated Lw - units occurs during the first and second electron uptake in the analyzed compounds. The stability of the electrogenerated intermediates for each complex depends on the d electron configuration in each metal center and is determined by magnetic interactions with the available spins considering an octahedral conformation for all the compounds. This was evidenced by in situ spectroelectrochemical-ESR measurements in the Zn(II) complex in which due to the lack of magnetic interaction owing to its electron configuration, the structure of the coordinated anion radical species was determined. Successive reduction of the associated Lw - units leads to partial dissociation of the complex, determined by the identification of free radical dianion structures in solution. These results show some insights on how metal-lawsone complexation can modify the solution reactivity and stability of the electrogenerated radical species.

  18. Magnetic interactions as a stabilizing factor of semiquinone species of lawsone by metal complexation

    Energy Technology Data Exchange (ETDEWEB)

    Valle-Bourrouet, Grettel [Universidad de Costa Rica, Escuela de Quimica, San Jose (Costa Rica); Ugalde-Saldivar, Victor M. [Facultad de Quimica, Universidad Nacional Autonoma de Mexico, Ciudad Universitaria, C.P. 04510, Mexico, D.F. (Mexico); Gomez, Martin [Departamento de Sistemas Biologicos, Universidad Autonoma Metropolitana-Xochimilco, C.P. 04960, Mexico, D.F. (Mexico); Ortiz-Frade, Luis A. [Centro de Investigacion y Desarrollo Tecnologico en Electroquimica, Parque Tecnologico Queretaro, Sanfandila, 76703, Pedro Escobedo, Queretaro (Mexico); Gonzalez, Ignacio [Universidad Autonoma Metropolitana - Iztapalapa, Departamento de Quimica, Area de Electroquimica, Apartado postal 55-534, 09340, Mexico, D.F. (Mexico); Frontana, Carlos, E-mail: ultrabuho@yahoo.com.m [Departamento de Quimica, Centro de Investigacion y Estudios Avanzados, Av. Instituto Politecnico Nacional No. 2508 Col. San Pedro Zacatenco, C.P. 07360, Mexico, D.F. (Mexico)

    2010-12-01

    Changes in electrochemical reactivity for lawsone anions (lawsone, 2-hydroxy-1,4-naphthoquinone, HLw) being coordinated to a series of metallic ions in dimethylsulfoxide solution were evaluated. Upon performing cyclic voltammetry experiments for metal complexes of this quinone with pyridine (Py) - structural formula M(II)(Lw{sup -}){sub 2}(Py){sub 2}; M: Co(II), Ni(II), Zn(II) - it was found that the reduction of coordinated Lw{sup -} units occurs during the first and second electron uptake in the analyzed compounds. The stability of the electrogenerated intermediates for each complex depends on the d electron configuration in each metal center and is determined by magnetic interactions with the available spins considering an octahedral conformation for all the compounds. This was evidenced by in situ spectroelectrochemical-ESR measurements in the Zn(II) complex in which due to the lack of magnetic interaction owing to its electron configuration, the structure of the coordinated anion radical species was determined. Successive reduction of the associated Lw{sup -} units leads to partial dissociation of the complex, determined by the identification of free radical dianion structures in solution. These results show some insights on how metal-lawsone complexation can modify the solution reactivity and stability of the electrogenerated radical species.

  19. Modeling invasive alien plant species in river systems: Interaction with native ecosystem engineers and effects on hydro-morphodynamic processes

    Science.gov (United States)

    van Oorschot, M.; Kleinhans, M. G.; Geerling, G. W.; Egger, G.; Leuven, R. S. E. W.; Middelkoop, H.

    2017-08-01

    Invasive alien plant species negatively impact native plant communities by out-competing species or changing abiotic and biotic conditions in their introduced range. River systems are especially vulnerable to biological invasions, because waterways can function as invasion corridors. Understanding interactions of invasive and native species and their combined effects on river dynamics is essential for developing cost-effective management strategies. However, numerical models for simulating long-term effects of these processes are lacking. This paper investigates how an invasive alien plant species affects native riparian vegetation and hydro-morphodynamics. A morphodynamic model has been coupled to a dynamic vegetation model that predicts establishment, growth and mortality of riparian trees. We introduced an invasive alien species with life-history traits based on Japanese Knotweed (Fallopia japonica), and investigated effects of low- and high propagule pressure on invasion speed, native vegetation and hydro-morphodynamic processes. Results show that high propagule pressure leads to a decline in native species cover due to competition and the creation of unfavorable native colonization sites. With low propagule pressure the invader facilitates native seedling survival by creating favorable hydro-morphodynamic conditions at colonization sites. With high invader abundance, water levels are raised and sediment transport is reduced during the growing season. In winter, when the above-ground invader biomass is gone, results are reversed and the floodplain is more prone to erosion. Invasion effects thus depend on seasonal above- and below ground dynamic vegetation properties and persistence of the invader, on the characteristics of native species it replaces, and the combined interactions with hydro-morphodynamics.

  20. Power-Law Kinetics and Determinant Criteria for the Preclusion of Multistationarity in Networks of Interacting Species

    DEFF Research Database (Denmark)

    Wiuf, Carsten Henrik; Feliu, Elisenda

    2013-01-01

    is derived from the determinant of the Jacobian of the species formation rate function. Using this characterization, we further derive similar determinant criteria applicable to general sets of kinetics. The criteria are conceptually simple, computationally tractable, and easily implemented. Our approach...... embraces and extends previous work on multistationarity, such as work in relation to chemical reaction networks with dynamics defined by mass-action or noncatalytic kinetics, and also work based on graphical analysis of the interaction graph associated with the system. Further, we interpret the criteria...... and how the species influence each reaction. We characterize families of so-called power-law kinetics for which the associated species formation rate function is injective within each stoichiometric class and thus the network cannot exhibit multistationarity. The criterion for power-law kinetics...

  1. Evolutionary and domestication history of Cucurbita (pumpkin and squash) species inferred from 44 nuclear loci.

    Science.gov (United States)

    Kates, Heather R; Soltis, Pamela S; Soltis, Douglas E

    2017-06-01

    Phylogenetics can facilitate the study of plant domestication by resolving sister relationships between crops and their wild relatives, thereby identifying the ancestors of cultivated plants. Previous phylogenetic studies of the six Cucurbita crop lineages (pumpkins and squashes) and their wild relatives suggest histories of deep coalescence that complicate uncovering the genetic origins of the six crop taxa. We investigated the evolution of wild and domesticated Cucurbita using the most comprehensive and robust molecular-based phylogeny for Cucurbita to date based on 44 loci derived from introns of single-copy nuclear genes. We discovered novel relationships among Cucurbita species and recovered the first Cucurbita tree with well-supported resolution within species. Cucurbita comprises a clade of mesophytic annual species that includes all six crop taxa and a grade of xerophytic perennial species that represent the ancestral xerophytic habit of the genus. Based on phylogenetic resolution within-species we hypothesize that the magnitude of domestication bottlenecks varies among Cucurbita crop lineages. Our phylogeny clarifies how wild Cucurbita species are related to the domesticated taxa. We find close relationships between two wild species and crop lineages not previously identified. Expanded geographic sampling of key wild species is needed for improved understanding of the evolution of domesticated Cucurbita. Copyright © 2017 Elsevier Inc. All rights reserved.

  2. Social interaction with non-averse group-mates modifies a learned food aversion in single- and mixed-species groups of tamarins (Saguinus fuscicollis and S. labiatus).

    Science.gov (United States)

    Prescott, M J; Buchanan-Smith, H M; Smith, A C

    2005-04-01

    For social species, being a member of a cohesive group and performing activities as a coordinated unit appear to provide a mechanism for the efficient transmission of information about food. Social learning about food palatability was investigated in two captive primates, Saguinus fuscicollis and S. labiatus, which form stable and cohesive mixed-species groups in the wild. We explored whether an induced food aversion toward a preferred food is modified during and after social interaction with non-averse conspecifics or congeners. Sets of intra- and interspecific pairs were presented with two foods, one of which was considered distasteful by one of the pairs (the other was palatable), and their behavior was compared pre-interaction, during interaction, and post-interaction. For the aversely-conditioned individuals of both species, the change in social context corresponded to a change in their preference for the food that they considered unpalatable, regardless of whether they had interacted with a conspecific or congeneric pair, and the change in food preference was maintained post-interaction. In a control condition, in which averse individuals did not have the opportunity to interact with non-averse animals, S. fuscicollis sampled the preferred food, but not as quickly as when given the opportunity to interact. We conclude that the social learning demonstrated here may allow individual tamarins to track environmental change, such as fruit ripening, more efficiently than asocial learning alone, because social learners can more quickly and safely focus on appropriate behavior by sharing up-to-date foraging information. Furthermore, since the behavior of congeners, as well as conspecifics, acts to influence food choice in a more adaptive direction, social learning about food palatability may be an advantage of mixed-species group formation to tamarins of both species. Copyright 2005 Wiley-Liss, Inc

  3. Quantum-Like Representation of Non-Bayesian Inference

    Science.gov (United States)

    Asano, M.; Basieva, I.; Khrennikov, A.; Ohya, M.; Tanaka, Y.

    2013-01-01

    This research is related to the problem of "irrational decision making or inference" that have been discussed in cognitive psychology. There are some experimental studies, and these statistical data cannot be described by classical probability theory. The process of decision making generating these data cannot be reduced to the classical Bayesian inference. For this problem, a number of quantum-like coginitive models of decision making was proposed. Our previous work represented in a natural way the classical Bayesian inference in the frame work of quantum mechanics. By using this representation, in this paper, we try to discuss the non-Bayesian (irrational) inference that is biased by effects like the quantum interference. Further, we describe "psychological factor" disturbing "rationality" as an "environment" correlating with the "main system" of usual Bayesian inference.

  4. Bayesian Inference Methods for Sparse Channel Estimation

    DEFF Research Database (Denmark)

    Pedersen, Niels Lovmand

    2013-01-01

    This thesis deals with sparse Bayesian learning (SBL) with application to radio channel estimation. As opposed to the classical approach for sparse signal representation, we focus on the problem of inferring complex signals. Our investigations within SBL constitute the basis for the development...... of Bayesian inference algorithms for sparse channel estimation. Sparse inference methods aim at finding the sparse representation of a signal given in some overcomplete dictionary of basis vectors. Within this context, one of our main contributions to the field of SBL is a hierarchical representation...... analysis of the complex prior representation, where we show that the ability to induce sparse estimates of a given prior heavily depends on the inference method used and, interestingly, whether real or complex variables are inferred. We also show that the Bayesian estimators derived from the proposed...

  5. Statistical inference an integrated Bayesianlikelihood approach

    CERN Document Server

    Aitkin, Murray

    2010-01-01

    Filling a gap in current Bayesian theory, Statistical Inference: An Integrated Bayesian/Likelihood Approach presents a unified Bayesian treatment of parameter inference and model comparisons that can be used with simple diffuse prior specifications. This novel approach provides new solutions to difficult model comparison problems and offers direct Bayesian counterparts of frequentist t-tests and other standard statistical methods for hypothesis testing.After an overview of the competing theories of statistical inference, the book introduces the Bayes/likelihood approach used throughout. It pre

  6. Population dynamics of three songbird species in a nestbox population in Central Europe show effects of density, climate and competitive interactions

    NARCIS (Netherlands)

    Smallegange, I.M.; van der Meer, J.; Fiedler, W.

    2011-01-01

    Unravelling the contributions of density-dependent and density-independent factors in determining species population dynamics is a challenge, especially if the two factors interact. One approach is to apply stochastic population models to long-term data, yet few studies have included interactions

  7. Streptococcus massiliensis in the human mouth: a phylogenetic approach for the inference of bacterial habitats.

    Science.gov (United States)

    Póntigo, F; Silva, C; Moraga, M; Flores, S V

    2015-12-29

    Streptococcus is a diverse bacterial lineage. Species of this genus occupy a myriad of environments inside humans and other animals. Despite the elucidation of several of these habitats, many remain to be identified. Here, we explore a methodological approach to reveal unknown bacterial environments. Specifically, we inferred the phylogeny of the Mitis group by analyzing the sequences of eight genes. In addition, information regarding habitat use of species belonging to this group was obtained from the scientific literature. The oral cavity emerged as a potential, previously unknown, environment of Streptococcus massiliensis. This phylogeny-based prediction was confirmed by species-specific polymerase chain reaction (PCR) amplification. We propose employing a similar approach, i.e., use of bibliographic data and molecular phylogenetics as predictive methods, and species-specific PCR as confirmation, in order to reveal other unknown habitats in further bacterial taxa.

  8. Statistical Models for Inferring Vegetation Composition from Fossil Pollen

    Science.gov (United States)

    Paciorek, C.; McLachlan, J. S.; Shang, Z.

    2011-12-01

    Fossil pollen provide information about vegetation composition that can be used to help understand how vegetation has changed over the past. However, these data have not traditionally been analyzed in a way that allows for statistical inference about spatio-temporal patterns and trends. We build a Bayesian hierarchical model called STEPPS (Spatio-Temporal Empirical Prediction from Pollen in Sediments) that predicts forest composition in southern New England, USA, over the last two millenia based on fossil pollen. The critical relationships between abundances of tree taxa in the pollen record and abundances in actual vegetation are estimated using modern (Forest Inventory Analysis) data and (witness tree) data from colonial records. This gives us two time points at which both pollen and direct vegetation data are available. Based on these relationships, and incorporating our uncertainty about them, we predict forest composition using fossil pollen. We estimate the spatial distribution and relative abundances of tree species and draw inference about how these patterns have changed over time. Finally, we describe ongoing work to extend the modeling to the upper Midwest of the U.S., including an approach to infer tree density and thereby estimate the prairie-forest boundary in Minnesota and Wisconsin. This work is part of the PalEON project, which brings together a team of ecosystem modelers, paleoecologists, and statisticians with the goal of reconstructing vegetation responses to climate during the last two millenia in the northeastern and midwestern United States. The estimates from the statistical modeling will be used to assess and calibrate ecosystem models that are used to project ecological changes in response to global change.

  9. Multi-species interactions impact the accumulation of weathered 2,2-bis (p-chlorophenyl)-1,1-dichloroethylene (p,p'-DDE) from soil

    International Nuclear Information System (INIS)

    Kelsey, Jason W.; White, Jason C.

    2005-01-01

    The impact of interactions between the earthworms Eisenia foetida and Lumbricus terrestris and the plants Cucurbita pepo and Cucurbita maxima on the uptake of weathered p,p'-DDE from soil was determined. Although some combinations of earthworm and plant species caused significant changes in the p,p'-DDE burden in both organisms, the effects were species specific. Contaminant bioconcentration in C. pepo was increased slightly by E. foetida and by 3-fold when the plant was grown with L. terrestris. E. foetida had no effect on the contaminant BCF by C. maxima, but L. terrestris caused a 2-fold reduction in p,p'-DDE uptake by the plant. Contaminant levels in E. foetida and L. terrestris were unaffected by C. pepo. When grown with C. maxima, the concentration of p,p'-DDE decreased by approximately 4-fold and 7-fold in E. foetida and L. terrestris, respectively. The data suggest that the prediction of contaminant bioavailability should consider interactions among species. - Interactions between earthworms and plants affect both the phytoextraction and bioaccumulation of p,p'-DDE in soil

  10. Species associations in a species-rich subtropical forest were not well-explained by stochastic geometry of biodiversity.

    Science.gov (United States)

    Wang, Qinggang; Bao, Dachuan; Guo, Yili; Lu, Junmeng; Lu, Zhijun; Xu, Yaozhan; Zhang, Kuihan; Liu, Haibo; Meng, Hongjie; Jiang, Mingxi; Qiao, Xiujuan; Huang, Handong

    2014-01-01

    The stochastic dilution hypothesis has been proposed to explain species coexistence in species-rich communities. The relative importance of the stochastic dilution effects with respect to other effects such as competition and habitat filtering required to be tested. In this study, using data from a 25-ha species-rich subtropical forest plot with a strong topographic structure at Badagongshan in central China, we analyzed overall species associations and fine-scale species interactions between 2,550 species pairs. The result showed that: (1) the proportion of segregation in overall species association analysis at 2 m neighborhood in this plot followed the prediction of the stochastic dilution hypothesis that segregations should decrease with species richness but that at 10 m neighborhood was higher than the prediction. (2) The proportion of no association type was lower than the expectation of stochastic dilution hypothesis. (3) Fine-scale species interaction analyses using Heterogeneous Poisson processes as null models revealed a high proportion (47%) of significant species effects. However, the assumption of separation of scale of this method was not fully met in this plot with a strong fine-scale topographic structure. We also found that for species within the same families, fine-scale positive species interactions occurred more frequently and negative ones occurred less frequently than expected by chance. These results suggested effects of environmental filtering other than species interaction in this forest. (4) We also found that arbor species showed a much higher proportion of significant fine-scale species interactions (66%) than shrub species (18%). We concluded that the stochastic dilution hypothesis only be partly supported and environmental filtering left discernible spatial signals in the spatial associations between species in this species-rich subtropical forest with a strong topographic structure.

  11. Species associations in a species-rich subtropical forest were not well-explained by stochastic geometry of biodiversity.

    Directory of Open Access Journals (Sweden)

    Qinggang Wang

    Full Text Available The stochastic dilution hypothesis has been proposed to explain species coexistence in species-rich communities. The relative importance of the stochastic dilution effects with respect to other effects such as competition and habitat filtering required to be tested. In this study, using data from a 25-ha species-rich subtropical forest plot with a strong topographic structure at Badagongshan in central China, we analyzed overall species associations and fine-scale species interactions between 2,550 species pairs. The result showed that: (1 the proportion of segregation in overall species association analysis at 2 m neighborhood in this plot followed the prediction of the stochastic dilution hypothesis that segregations should decrease with species richness but that at 10 m neighborhood was higher than the prediction. (2 The proportion of no association type was lower than the expectation of stochastic dilution hypothesis. (3 Fine-scale species interaction analyses using Heterogeneous Poisson processes as null models revealed a high proportion (47% of significant species effects. However, the assumption of separation of scale of this method was not fully met in this plot with a strong fine-scale topographic structure. We also found that for species within the same families, fine-scale positive species interactions occurred more frequently and negative ones occurred less frequently than expected by chance. These results suggested effects of environmental filtering other than species interaction in this forest. (4 We also found that arbor species showed a much higher proportion of significant fine-scale species interactions (66% than shrub species (18%. We concluded that the stochastic dilution hypothesis only be partly supported and environmental filtering left discernible spatial signals in the spatial associations between species in this species-rich subtropical forest with a strong topographic structure.

  12. Extensive range overlap between heliconiine sister species: evidence for sympatric speciation in butterflies?

    Science.gov (United States)

    Rosser, Neil; Kozak, Krzysztof M; Phillimore, Albert B; Mallet, James

    2015-06-30

    Sympatric speciation is today generally viewed as plausible, and some well-supported examples exist, but its relative contribution to biodiversity remains to be established. We here quantify geographic overlap of sister species of heliconiine butterflies, and use age-range correlations and spatial simulations of the geography of speciation to infer the frequency of sympatric speciation. We also test whether shifts in mimetic wing colour pattern, host plant use and climate niche play a role in speciation, and whether such shifts are associated with sympatry. Approximately a third of all heliconiine sister species pairs exhibit near complete range overlap, and analyses of the observed patterns of range overlap suggest that sympatric speciation contributes 32%-95% of speciation events. Müllerian mimicry colour patterns and host plant choice are highly labile traits that seem to be associated with speciation, but we find no association between shifts in these traits and range overlap. In contrast, climatic niches of sister species are more conserved. Unlike birds and mammals, sister species of heliconiines are often sympatric and our inferences using the most recent comparative methods suggest that sympatric speciation is common. However, if sister species spread rapidly into sympatry (e.g. due to their similar climatic niches), then assumptions underlying our methods would be violated. Furthermore, although we find some evidence for the role of ecology in speciation, ecological shifts did not show the associations with range overlap expected under sympatric speciation. We delimit species of heliconiines in three different ways, based on "strict and " "relaxed" biological species concepts (BSC), as well as on a surrogate for the widely-used "diagnostic" version of the phylogenetic species concept (PSC). We show that one reason why more sympatric speciation is inferred in heliconiines than in birds may be due to a different culture of species delimitation in the two

  13. Inference Attacks and Control on Database Structures

    Directory of Open Access Journals (Sweden)

    Muhamed Turkanovic

    2015-02-01

    Full Text Available Today’s databases store information with sensitivity levels that range from public to highly sensitive, hence ensuring confidentiality can be highly important, but also requires costly control. This paper focuses on the inference problem on different database structures. It presents possible treats on privacy with relation to the inference, and control methods for mitigating these treats. The paper shows that using only access control, without any inference control is inadequate, since these models are unable to protect against indirect data access. Furthermore, it covers new inference problems which rise from the dimensions of new technologies like XML, semantics, etc.

  14. Some limitations of public sequence data for phylogenetic inference (in plants).

    Science.gov (United States)

    Hinchliff, Cody E; Smith, Stephen Andrew

    2014-01-01

    The GenBank database contains essentially all of the nucleotide sequence data generated for published molecular systematic studies, but for the majority of taxa these data remain sparse. GenBank has value for phylogenetic methods that leverage data-mining and rapidly improving computational methods, but the limits imposed by the sparse structure of the data are not well understood. Here we present a tree representing 13,093 land plant genera--an estimated 80% of extant plant diversity--to illustrate the potential of public sequence data for broad phylogenetic inference in plants, and we explore the limits to inference imposed by the structure of these data using theoretical foundations from phylogenetic data decisiveness. We find that despite very high levels of missing data (over 96%), the present data retain the potential to inform over 86.3% of all possible phylogenetic relationships. Most of these relationships, however, are informed by small amounts of data--approximately half are informed by fewer than four loci, and more than 99% are informed by fewer than fifteen. We also apply an information theoretic measure of branch support to assess the strength of phylogenetic signal in the data, revealing many poorly supported branches concentrated near the tips of the tree, where data are sparse and the limiting effects of this sparseness are stronger. We argue that limits to phylogenetic inference and signal imposed by low data coverage may pose significant challenges for comprehensive phylogenetic inference at the species level. Computational requirements provide additional limits for large reconstructions, but these may be overcome by methodological advances, whereas insufficient data coverage can only be remedied by additional sampling effort. We conclude that public databases have exceptional value for modern systematics and evolutionary biology, and that a continued emphasis on expanding taxonomic and genomic coverage will play a critical role in developing

  15. A mental architecture modeling of inference of sensory stimuli to the teaching of the deaf

    Directory of Open Access Journals (Sweden)

    Rubens Santos Guimaraes

    2016-10-01

    Full Text Available The transmission and retention of knowledge rests on the cognitive faculty of the concepts linked to it. The repeatability of your applications builds a solid foundation for Education, according to cultural and behavioral standards set by the Society. This cognitive ability to infer on what we observe and perceive, regarded as intrinsic human beings, independent of their physical capacity. This article presents a conceptual model Mental Architecture Digitized – AMD, enabling reproduce inferences about sensory stimuli deaf, focused on the implementation of a web system that aims to improve the teaching and learning of students with hearing disability. In this proposal, we evaluate the contextual aspects experienced by learners during the interactions between the constituent elements of a study session, based on experiments with two deaf students enrolled in regular high school. The results allow us to infer the potential of a computer communications environment to expand the possibilities of social inclusion of these students.

  16. NetCooperate: a network-based tool for inferring host-microbe and microbe-microbe cooperation.

    Science.gov (United States)

    Levy, Roie; Carr, Rogan; Kreimer, Anat; Freilich, Shiri; Borenstein, Elhanan

    2015-05-17

    Host-microbe and microbe-microbe interactions are often governed by the complex exchange of metabolites. Such interactions play a key role in determining the way pathogenic and commensal species impact their host and in the assembly of complex microbial communities. Recently, several studies have demonstrated how such interactions are reflected in the organization of the metabolic networks of the interacting species, and introduced various graph theory-based methods to predict host-microbe and microbe-microbe interactions directly from network topology. Using these methods, such studies have revealed evolutionary and ecological processes that shape species interactions and community assembly, highlighting the potential of this reverse-ecology research paradigm. NetCooperate is a web-based tool and a software package for determining host-microbe and microbe-microbe cooperative potential. It specifically calculates two previously developed and validated metrics for species interaction: the Biosynthetic Support Score which quantifies the ability of a host species to supply the nutritional requirements of a parasitic or a commensal species, and the Metabolic Complementarity Index which quantifies the complementarity of a pair of microbial organisms' niches. NetCooperate takes as input a pair of metabolic networks, and returns the pairwise metrics as well as a list of potential syntrophic metabolic compounds. The Biosynthetic Support Score and Metabolic Complementarity Index provide insight into host-microbe and microbe-microbe metabolic interactions. NetCooperate determines these interaction indices from metabolic network topology, and can be used for small- or large-scale analyses. NetCooperate is provided as both a web-based tool and an open-source Python module; both are freely available online at http://elbo.gs.washington.edu/software_netcooperate.html.

  17. Studies on interaction of colloidal silver nanoparticles (SNPs) with five different bacterial species.

    Science.gov (United States)

    Khan, S Sudheer; Mukherjee, Amitava; Chandrasekaran, N

    2011-10-01

    Silver nanoparticles (SNPs) are being increasingly used in many consumer products like textile fabrics, cosmetics, washing machines, food and drug products owing to its excellent antimicrobial properties. Here we have studied the adsorption and toxicity of SNPs on bacterial species such as Pseudomonas aeruginosa, Micrococcus luteus, Bacillus subtilis, Bacillus barbaricus and Klebsiella pneumoniae. The influence of zeta potential on the adsorption of SNPs on bacterial cell surface was investigated at acidic, neutral and alkaline pH and with varying salt (NaCl) concentrations (0.05, 0.1, 0.5, 1 and 1.5 M). The survival rate of bacterial species decreased with increase in adsorption of SNPs. Maximum adsorption and toxicity was observed at pH 5, and NaCl concentration of 0.5 M, there by resulting in less toxicity. The zeta potential study suggests that, the adsorption of SNPs on the cell surface was related to electrostatic force of attraction. The equilibrium and kinetics of the adsorption process were also studied. The adsorption equilibrium isotherms fitted well to the Langmuir model. The kinetics of adsorption fitted best to pseudo-first-order. These findings form a basis for interpreting the interaction of nanoparticles with environmental bacterial species. Copyright © 2011 Elsevier B.V. All rights reserved.

  18. Type Inference with Inequalities

    DEFF Research Database (Denmark)

    Schwartzbach, Michael Ignatieff

    1991-01-01

    of (monotonic) inequalities on the types of variables and expressions. A general result about systems of inequalities over semilattices yields a solvable form. We distinguish between deciding typability (the existence of solutions) and type inference (the computation of a minimal solution). In our case, both......Type inference can be phrased as constraint-solving over types. We consider an implicitly typed language equipped with recursive types, multiple inheritance, 1st order parametric polymorphism, and assignments. Type correctness is expressed as satisfiability of a possibly infinite collection...

  19. Applying a multiobjective metaheuristic inspired by honey bees to phylogenetic inference.

    Science.gov (United States)

    Santander-Jiménez, Sergio; Vega-Rodríguez, Miguel A

    2013-10-01

    The development of increasingly popular multiobjective metaheuristics has allowed bioinformaticians to deal with optimization problems in computational biology where multiple objective functions must be taken into account. One of the most relevant research topics that can benefit from these techniques is phylogenetic inference. Throughout the years, different researchers have proposed their own view about the reconstruction of ancestral evolutionary relationships among species. As a result, biologists often report different phylogenetic trees from a same dataset when considering distinct optimality principles. In this work, we detail a multiobjective swarm intelligence approach based on the novel Artificial Bee Colony algorithm for inferring phylogenies. The aim of this paper is to propose a complementary view of phylogenetics according to the maximum parsimony and maximum likelihood criteria, in order to generate a set of phylogenetic trees that represent a compromise between these principles. Experimental results on a variety of nucleotide data sets and statistical studies highlight the relevance of the proposal with regard to other multiobjective algorithms and state-of-the-art biological methods. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  20. Spatially explicit inference for open populations: estimating demographic parameters from camera-trap studies.

    Science.gov (United States)

    Gardner, Beth; Reppucci, Juan; Lucherini, Mauro; Royle, J Andrew

    2010-11-01

    We develop a hierarchical capture-recapture model for demographically open populations when auxiliary spatial information about location of capture is obtained. Such spatial capture-recapture data arise from studies based on camera trapping, DNA sampling, and other situations in which a spatial array of devices records encounters of unique individuals. We integrate an individual-based formulation of a Jolly-Seber type model with recently developed spatially explicit capture-recapture models to estimate density and demographic parameters for survival and recruitment. We adopt a Bayesian framework for inference under this model using the method of data augmentation which is implemented in the software program WinBUGS. The model was motivated by a camera trapping study of Pampas cats Leopardus colocolo from Argentina, which we present as an illustration of the model in this paper. We provide estimates of density and the first quantitative assessment of vital rates for the Pampas cat in the High Andes. The precision of these estimates is poor due likely to the sparse data set. Unlike conventional inference methods which usually rely on asymptotic arguments, Bayesian inferences are valid in arbitrary sample sizes, and thus the method is ideal for the study of rare or endangered species for which small data sets are typical.

  1. Inference in models with adaptive learning

    NARCIS (Netherlands)

    Chevillon, G.; Massmann, M.; Mavroeidis, S.

    2010-01-01

    Identification of structural parameters in models with adaptive learning can be weak, causing standard inference procedures to become unreliable. Learning also induces persistent dynamics, and this makes the distribution of estimators and test statistics non-standard. Valid inference can be

  2. Genes, communities & invasive species: understanding the ecological and evolutionary dynamics of host-pathogen interactions.

    Science.gov (United States)

    Burdon, J J; Thrall, P H; Ericson, L

    2013-08-01

    Reciprocal interactions between hosts and pathogens drive ecological, epidemiological and co-evolutionary trajectories, resulting in complex patterns of diversity at population, species and community levels. Recent results confirm the importance of negative frequency-dependent rather than 'arms-race' processes in the evolution of individual host-pathogen associations. At the community level, complex relationships between species abundance and diversity dampen or alter pathogen impacts. Invasive pathogens challenge these controls reflecting the earliest stages of evolutionary associations (akin to arms-race) where disease effects may be so great that they overwhelm the host's and community's ability to respond. Viewing these different stabilization/destabilization phases as a continuum provides a valuable perspective to assessment of the role of genetics and ecology in the dynamics of both natural and invasive host-pathogen associations. Copyright © 2013 Elsevier Ltd. All rights reserved.

  3. Phylogeny of the Celastreae (Celastraceae) and the relationships of Catha edulis (qat) inferred from morphological characters and nuclear and plastid genes.

    Science.gov (United States)

    Simmons, Mark P; Cappa, Jennifer J; Archer, Robert H; Ford, Andrew J; Eichstedt, Dedra; Clevinger, Curtis C

    2008-08-01

    The phylogeny of Celastraceae tribe Celastreae, which includes about 350 species of trees and shrubs in 15 genera, was inferred in a simultaneous analysis of morphological characters together with nuclear (ITS and 26S rDNA) and plastid (matK, trnL-F) genes. A strong correlation was found between the geography of the species sampled and their inferred relationships. Species of Maytenus and Gymnosporia from different regions were resolved as polyphyletic groups. Maytenus was resolved in three lineages (New World, African, and Austral-Pacific), while Gymnosporia was resolved in two lineages (New World and Old World). Putterlickia was resolved as nested within the Old World Gymnosporia. Catha edulis (qat, khat) was resolved as sister to the clade of Allocassine, Cassine, Lauridia, and Maurocenia. Gymnosporia cassinoides, which is reportedly chewed as a stimulant in the Canary Islands, was resolved as a derived member of Gymnosporia and is more closely related to Lydenburgia and Putterlickia than it is to Catha. Therefore, all eight of these genera are candidates for containing cathinone- and/or cathine-related alkaloids.

  4. Inferring Person-to-person Proximity Using WiFi Signals

    DEFF Research Database (Denmark)

    Sapiezynski, Piotr; Stopczynski, Arkadiusz; Wind, David Kofoed

    2017-01-01

    scale is a technical challenge and many commonly used approaches—including RFID badges or Bluetooth scanning—offer only limited scalability. Here we show that it is possible, in a scalable and robust way, to accurately infer person-to-person physical proximity from the lists of WiFi access points...... measured by smartphones carried by the two individuals. Based on a longitudinal dataset of approximately 800 participants with ground-truth interactions collected over a year, we show that our model performs better than the current state-of-the-art. Our results demonstrate the value of WiFi signals...

  5. IDENTIFICATION OF SEQUENCE SPECIFIC PCR PRIMERS FOR DETECTION OF THE TOXIGENIC FUNGAL SPECIES STACHYBOTRYS CHARTARUM

    Science.gov (United States)

    The nucleotide sequence of a 936 bp segment of the nuclear rRNA gene operon was determined for the toxigenic fungal species Stachybotrys chartarum and for other species of Stachybotrys and the related genus Memnoniella. This information was used to infer the phylogenitic relati...

  6. Fiducial inference - A Neyman-Pearson interpretation

    NARCIS (Netherlands)

    Salome, D; VonderLinden, W; Dose,; Fischer, R; Preuss, R

    1999-01-01

    Fisher's fiducial argument is a tool for deriving inferences in the form of a probability distribution on the parameter space, not based on Bayes's Theorem. Lindley established that in exceptional situations fiducial inferences coincide with posterior distributions; in the other situations fiducial

  7. Uncertainty in prediction and in inference

    NARCIS (Netherlands)

    Hilgevoord, J.; Uffink, J.

    1991-01-01

    The concepts of uncertainty in prediction and inference are introduced and illustrated using the diffraction of light as an example. The close re-lationship between the concepts of uncertainty in inference and resolving power is noted. A general quantitative measure of uncertainty in

  8. Comparative Genomics of the Bacterial Genus Streptococcus Illuminates Evolutionary Implications of Species Groups

    Science.gov (United States)

    Gao, Xiao-Yang; Zhi, Xiao-Yang; Li, Hong-Wei; Klenk, Hans-Peter; Li, Wen-Jun

    2014-01-01

    Members of the genus Streptococcus within the phylum Firmicutes are among the most diverse and significant zoonotic pathogens. This genus has gone through considerable taxonomic revision due to increasing improvements of chemotaxonomic approaches, DNA hybridization and 16S rRNA gene sequencing. It is proposed to place the majority of streptococci into “species groups”. However, the evolutionary implications of species groups are not clear presently. We use comparative genomic approaches to yield a better understanding of the evolution of Streptococcus through genome dynamics, population structure, phylogenies and virulence factor distribution of species groups. Genome dynamics analyses indicate that the pan-genome size increases with the addition of newly sequenced strains, while the core genome size decreases with sequential addition at the genus level and species group level. Population structure analysis reveals two distinct lineages, one including Pyogenic, Bovis, Mutans and Salivarius groups, and the other including Mitis, Anginosus and Unknown groups. Phylogenetic dendrograms show that species within the same species group cluster together, and infer two main clades in accordance with population structure analysis. Distribution of streptococcal virulence factors has no obvious patterns among the species groups; however, the evolution of some common virulence factors is congruous with the evolution of species groups, according to phylogenetic inference. We suggest that the proposed streptococcal species groups are reasonable from the viewpoints of comparative genomics; evolution of the genus is congruent with the individual evolutionary trajectories of different species groups. PMID:24977706

  9. Evolution of opercle shape in cichlid fishes from Lake Tanganyika - adaptive trait interactions in extant and extinct species flocks.

    Science.gov (United States)

    Wilson, Laura A B; Colombo, Marco; Sánchez-Villagra, Marcelo R; Salzburger, Walter

    2015-11-20

    Phenotype-environment correlations and the evolution of trait interactions in adaptive radiations have been widely studied to gain insight into the dynamics underpinning rapid species diversification. In this study we explore the phenotype-environment correlation and evolution of operculum shape in cichlid fishes using an outline-based geometric morphometric approach combined with stable isotope indicators of macrohabitat and trophic niche. We then apply our method to a sample of extinct saurichthyid fishes, a highly diverse and near globally distributed group of actinopterygians occurring throughout the Triassic, to assess the utility of extant data to inform our understanding of ecomorphological evolution in extinct species flocks. A series of comparative methods were used to analyze shape data for 54 extant species of cichlids (N = 416), and 6 extinct species of saurichthyids (N = 44). Results provide evidence for a relationship between operculum shape and feeding ecology, a concentration in shape evolution towards present along with evidence for convergence in form, and significant correlation between the major axes of shape change and measures of gut length and body elongation. The operculum is one of few features that can be compared in extant and extinct groups, enabling reconstruction of phenotype-environment interactions and modes of evolutionary diversification in deep time.

  10. Data-driven Inference and Investigation of Thermosphere Dynamics and Variations

    Science.gov (United States)

    Mehta, P. M.; Linares, R.

    2017-12-01

    This paper presents a methodology for data-driven inference and investigation of thermosphere dynamics and variations. The approach uses data-driven modal analysis to extract the most energetic modes of variations for neutral thermospheric species using proper orthogonal decomposition, where the time-independent modes or basis represent the dynamics and the time-depedent coefficients or amplitudes represent the model parameters. The data-driven modal analysis approach combined with sparse, discrete observations is used to infer amplitues for the dynamic modes and to calibrate the energy content of the system. In this work, two different data-types, namely the number density measurements from TIMED/GUVI and the mass density measurements from CHAMP/GRACE are simultaneously ingested for an accurate and self-consistent specification of the thermosphere. The assimilation process is achieved with a non-linear least squares solver and allows estimation/tuning of the model parameters or amplitudes rather than the driver. In this work, we use the Naval Research Lab's MSIS model to derive the most energetic modes for six different species, He, O, N2, O2, H, and N. We examine the dominant drivers of variations for helium in MSIS and observe that seasonal latitudinal variation accounts for about 80% of the dynamic energy with a strong preference of helium for the winter hemisphere. We also observe enhanced helium presence near the poles at GRACE altitudes during periods of low solar activity (Feb 2007) as previously deduced. We will also examine the storm-time response of helium derived from observations. The results are expected to be useful in tuning/calibration of the physics-based models.

  11. Species boundaries of Gulf of Mexico vestimentiferans (Polychaeta, Siboglinidae) inferred from mitochondrial genes

    Science.gov (United States)

    Pia Miglietta, Maria; Hourdez, Stephane; Cowart, Dominique A.; Schaeffer, Stephen W.; Fisher, Charles

    2010-11-01

    At least six morphospecies of vestimentiferan tubeworms are associated with cold seeps in the Gulf of Mexico (GOM). The physiology and ecology of the two best-studied species from depths above 1000 m in the upper Louisiana slope (Lamellibrachia luymesi and Seepiophila jonesi) are relatively well understood. The biology of one rare species from the upper slope (escarpiid sp. nov.) and three morphospecies found at greater depths in the GOM (Lamellibrachia sp. 1, L. sp. 2, and Escarpia laminata) are not as well understood. Here we address species distributions and boundaries of cold-seep tubeworms using phylogenetic hypotheses based on two mitochondrial genes. Fragments of the mitochondrial large ribosomal subunit rDNA (16S) and cytochrome oxidase subunit I (COI) genes were sequenced for 167 vestimentiferans collected from the GOM and analyzed in the context of other seep vestimentiferans for which sequence data were available. The analysis supported five monophyletic clades of vestimentiferans in the GOM. Intra-clade variation in both genes was very low, and there was no apparent correlation between the within-clade diversity and collection depth or location. Two of the morphospecies of Lamellibrachia from different depths in the GOM could not be distinguished by either mitochondrial gene. Similarly, E. laminata could not be distinguished from other described species of Escarpia from either the west coast of Africa or the eastern Pacific using COI. We suggest that the mitochondrial COI and 16S genes have little utility as barcoding markers for seep vestimentiferan tubeworms.

  12. Functional indicators of response mechanisms to nitrogen deposition, ozone, and their interaction in two Mediterranean tree species.

    Directory of Open Access Journals (Sweden)

    Lina Fusaro

    Full Text Available The effects of nitrogen (N deposition, tropospheric ozone (O3 and their interaction were investigated in two Mediterranean tree species, Fraxinus ornus L. (deciduous and Quercus ilex L. (evergreen, having different leaf habits and resource use strategies. An experiment was conducted under controlled condition to analyse how nitrogen deposition affects the ecophysiological and biochemical traits, and to explore how the nitrogen-induced changes influence the response to O3. For both factors we selected realistic exposures (20 kg N ha-1 yr-1 and 80 ppb h for nitrogen and O3, respectively, in order to elucidate the mechanisms implemented by the plants. Nitrogen addition resulted in higher nitrogen concentration at the leaf level in F. ornus, whereas a slight increase was detected in Q. ilex. Nitrogen enhanced the maximum rate of assimilation and ribulose 1,5-bisphosphate regeneration in both species, whereas it influenced the light harvesting complex only in the deciduous F. ornus that was also affected by O3 (reduced assimilation rate and accelerated senescence-related processes. Conversely, Q. ilex developed an avoidance mechanism to cope with O3, confirming a substantial O3 tolerance of this species. Nitrogen seemed to ameliorate the harmful effects of O3 in F. ornus: the hypothesized mechanism of action involved the production of nitrogen oxide as the first antioxidant barrier, followed by enzymatic antioxidant response. In Q. ilex, the interaction was not detected on gas exchange and photosystem functionality; however, in this species, nitrogen might stimulate an alternative antioxidant response such as the emission of volatile organic compounds. Antioxidant enzyme activity was lower in plants treated with both O3 and nitrogen even though reactive oxygen species production did not differ between the treatments.

  13. Path-space variational inference for non-equilibrium coarse-grained systems

    International Nuclear Information System (INIS)

    Harmandaris, Vagelis; Kalligiannaki, Evangelia; Katsoulakis, Markos; Plecháč, Petr

    2016-01-01

    In this paper we discuss information-theoretic tools for obtaining optimized coarse-grained molecular models for both equilibrium and non-equilibrium molecular simulations. The latter are ubiquitous in physicochemical and biological applications, where they are typically associated with coupling mechanisms, multi-physics and/or boundary conditions. In general the non-equilibrium steady states are not known explicitly as they do not necessarily have a Gibbs structure. The presented approach can compare microscopic behavior of molecular systems to parametric and non-parametric coarse-grained models using the relative entropy between distributions on the path space and setting up a corresponding path-space variational inference problem. The methods can become entirely data-driven when the microscopic dynamics are replaced with corresponding correlated data in the form of time series. Furthermore, we present connections and generalizations of force matching methods in coarse-graining with path-space information methods. We demonstrate the enhanced transferability of information-based parameterizations to different observables, at a specific thermodynamic point, due to information inequalities. We discuss methodological connections between information-based coarse-graining of molecular systems and variational inference methods primarily developed in the machine learning community. However, we note that the work presented here addresses variational inference for correlated time series due to the focus on dynamics. The applicability of the proposed methods is demonstrated on high-dimensional stochastic processes given by overdamped and driven Langevin dynamics of interacting particles.

  14. Path-space variational inference for non-equilibrium coarse-grained systems

    Energy Technology Data Exchange (ETDEWEB)

    Harmandaris, Vagelis, E-mail: harman@uoc.gr [Department of Mathematics and Applied Mathematics, University of Crete (Greece); Institute of Applied and Computational Mathematics (IACM), Foundation for Research and Technology Hellas (FORTH), IACM/FORTH, GR-71110 Heraklion (Greece); Kalligiannaki, Evangelia, E-mail: ekalligian@tem.uoc.gr [Department of Mathematics and Applied Mathematics, University of Crete (Greece); Katsoulakis, Markos, E-mail: markos@math.umass.edu [Department of Mathematics and Statistics, University of Massachusetts at Amherst (United States); Plecháč, Petr, E-mail: plechac@math.udel.edu [Department of Mathematical Sciences, University of Delaware, Newark, Delaware (United States)

    2016-06-01

    In this paper we discuss information-theoretic tools for obtaining optimized coarse-grained molecular models for both equilibrium and non-equilibrium molecular simulations. The latter are ubiquitous in physicochemical and biological applications, where they are typically associated with coupling mechanisms, multi-physics and/or boundary conditions. In general the non-equilibrium steady states are not known explicitly as they do not necessarily have a Gibbs structure. The presented approach can compare microscopic behavior of molecular systems to parametric and non-parametric coarse-grained models using the relative entropy between distributions on the path space and setting up a corresponding path-space variational inference problem. The methods can become entirely data-driven when the microscopic dynamics are replaced with corresponding correlated data in the form of time series. Furthermore, we present connections and generalizations of force matching methods in coarse-graining with path-space information methods. We demonstrate the enhanced transferability of information-based parameterizations to different observables, at a specific thermodynamic point, due to information inequalities. We discuss methodological connections between information-based coarse-graining of molecular systems and variational inference methods primarily developed in the machine learning community. However, we note that the work presented here addresses variational inference for correlated time series due to the focus on dynamics. The applicability of the proposed methods is demonstrated on high-dimensional stochastic processes given by overdamped and driven Langevin dynamics of interacting particles.

  15. Polynomial Chaos Surrogates for Bayesian Inference

    KAUST Repository

    Le Maitre, Olivier

    2016-01-06

    The Bayesian inference is a popular probabilistic method to solve inverse problems, such as the identification of field parameter in a PDE model. The inference rely on the Bayes rule to update the prior density of the sought field, from observations, and derive its posterior distribution. In most cases the posterior distribution has no explicit form and has to be sampled, for instance using a Markov-Chain Monte Carlo method. In practice the prior field parameter is decomposed and truncated (e.g. by means of Karhunen- Lo´eve decomposition) to recast the inference problem into the inference of a finite number of coordinates. Although proved effective in many situations, the Bayesian inference as sketched above faces several difficulties requiring improvements. First, sampling the posterior can be a extremely costly task as it requires multiple resolutions of the PDE model for different values of the field parameter. Second, when the observations are not very much informative, the inferred parameter field can highly depends on its prior which can be somehow arbitrary. These issues have motivated the introduction of reduced modeling or surrogates for the (approximate) determination of the parametrized PDE solution and hyperparameters in the description of the prior field. Our contribution focuses on recent developments in these two directions: the acceleration of the posterior sampling by means of Polynomial Chaos expansions and the efficient treatment of parametrized covariance functions for the prior field. We also discuss the possibility of making such approach adaptive to further improve its efficiency.

  16. Multilocus Phylogeography and Species Delimitation in the Cumberland Plateau Salamander, Plethodon kentucki: Incongruence among Data Sets and Methods.

    Directory of Open Access Journals (Sweden)

    Shawn R Kuchta

    Full Text Available Species are a fundamental unit of biodiversity, yet can be challenging to delimit objectively. This is particularly true of species complexes characterized by high levels of population genetic structure, hybridization between genetic groups, isolation by distance, and limited phenotypic variation. Previous work on the Cumberland Plateau Salamander, Plethodon kentucki, suggested that it might constitute a species complex despite occupying a relatively small geographic range. To examine this hypothesis, we sampled 135 individuals from 43 populations, and used four mitochondrial loci and five nuclear loci (5693 base pairs to quantify phylogeographic structure and probe for cryptic species diversity. Rates of evolution for each locus were inferred using the multidistribute package, and time calibrated gene trees and species trees were inferred using BEAST 2 and *BEAST 2, respectively. Because the parameter space relevant for species delimitation is large and complex, and all methods make simplifying assumptions that may lead them to fail, we conducted an array of analyses. Our assumption was that strongly supported species would be congruent across methods. Putative species were first delimited using a Bayesian implementation of the GMYC model (bGMYC, Geneland, and Brownie. We then validated these species using the genealogical sorting index and BPP. We found substantial phylogeographic diversity using mtDNA, including four divergent clades and an inferred common ancestor at 14.9 myr (95% HPD: 10.8-19.7 myr. By contrast, this diversity was not corroborated by nuclear sequence data, which exhibited low levels of variation and weak phylogeographic structure. Species trees estimated a far younger root than did the mtDNA data, closer to 1.0 myr old. Mutually exclusive putative species were identified by the different approaches. Possible causes of data set discordance, and the problem of species delimitation in complexes with high levels of popu