Information theory provides a comprehensive framework for the evaluation of protein structure predictions

Protein structure prediction has a number of important ad hoc similarity measures for evaluating predictions, but would benefit from a measure that is able to provide a common framework for a broad range of comparisons. Here we show that a mutual information-like measure can provide a comprehensive framework for evaluating protein structure prediction of all types. We discuss the concept of information, its application to secondary structure, and the obstacle to applying it to 3D structure. On the basis of the insights from the secondary structure case, we present an approach to work around the 3D difficulties, and develop a method to measure the mutual information provided by a 3D structure prediction. We integrate the evaluation of all types of protein structure prediction into a single framework, and compare the amount of information provided by various prediction methods, including secondary structure prediction. Within this broadened framework, the idea that structure is better preserved than sequence during evolution is evaluated quantitatively for the globin family. A nearly perfect sequence match in the globin family corresponds to about 300 bits of information, whereas a nearly perfect structural match for the same two proteins corresponds to about 2500 bits of information, where bits of information describes the probability of obtaining a match of similar closeness by chance. Mutual information provides both a theoretical basis for evaluating structure similarity and an explanatory surround for existing similarity measures.     

A metacommunity framework for enhancing the effectiveness of biological monitoring strategies

Because of inadequate knowledge and funding, the use of biodiversity indicators is often suggested as a way to support management decisions. Consequently, many studies have analyzed the performance of certain groups as indicator taxa. However, in addition to knowing whether certain groups can adequately represent the biodiversity as a whole, we must also know whether they show similar responses to the main structuring processes affecting biodiversity. Here we present an application of the metacommunity framework for evaluating the effectiveness of biodiversity indicators. Although the metacommunity framework has contributed to a better understanding of biodiversity patterns, there is still limited discussion about its implications for conservation and biomonitoring. We evaluated the effectiveness of indicator taxa in representing spatial variation in macroinvertebrate community composition in Atlantic Forest streams, and the processes that drive this variation. We focused on analyzing whether some groups conform to environmental processes and other groups are more influenced by spatial processes, and on how this can help in deciding which indicator group or groups should be used. We showed that a relatively small subset of taxa from the metacommunity would represent 80% of the variation in community composition shown by the entire metacommunity. Moreover, this subset does not have to be composed of predetermined taxonomic groups, but rather can be defined based on random subsets. We also found that some random subsets composed of a small number of genera performed better in responding to major environmental gradients. There were also random subsets that seemed to be affected by spatial processes, which could indicate important historical processes. We were able to integrate in the same theoretical and practical framework, the selection of biodiversity surrogates, indicators of environmental conditions, and more importantly, an explicit integration of environmental and spatial processes into the selection approach.     

The metacommunity concept: a framework for multi-scale community ecology

The metacommunity concept is an important way to think about linkages between different spatial scales in ecology. Here we review current understanding about this concept. We first investigate issues related to its definition as a set of local communities that are linked by dispersal of multiple potentially interacting species. We then identify four paradigms for metacommunities: the patch‐dynamic view, the species‐sorting view, the mass effects view and the neutral view, that each emphasizes different processes of potential importance in metacommunities. These have somewhat distinct intellectual histories and we discuss elements related to their potential future synthesis. We then use this framework to discuss why the concept is useful in modifying existing ecological thinking and illustrate this with a number of both theoretical and empirical examples. As ecologists strive to understand increasingly complex mechanisms and strive to work across multiple scales of spatio‐temporal organization, concepts like the metacommunity can provide important insights that frequently contrast with those that would be obtained with more conventional approaches based on local communities alone.     

A comprehensive framework for global patterns in biodiversity

The present study proposes to reconcile the different spatial and temporal scales of regional species production and local constraint on species richness. Although interactions between populations rapidly achieve equilibrium and limit membership in ecological communities locally, these interactions occur over heterogeneous environments within large regions, where the populations of species are stably regulated through competition and habitat selection. Consequently, exclusion of species from a region depends on long‐term regional‐scale environmental change or evolutionary change among interacting populations, bringing species production and extinction onto the same scale and establishing a link between local and regional processes.     

metacom: an R package for the analysis of metacommunity structure

Metacommunity theory is an extension of metapopulation theory with the goal of understanding how ecological communities vary through space and time. One off‐shoot of metacommunity theory deals with understanding how community structure varies along biotic or environmental gradients. The Elements of Metacommunity Structure framework is a three‐tiered analysis of metacommunity structure that enables the user to identify metacommunity properties that arise in site‐by‐species incidence matrices. These properties can then be related to underlying variables that influence species distributions. The EMS framework is now implemented in metacom, an open source R package that allows for the analysis and plotting of metacommunities.     

Using functional diversity patterns to explore metacommunity dynamics: a framework for understanding local and regional influences on community structure

The metacommunity concept, describing how local and regional scale processes interact to structure communities, has been successfully applied to patterns of taxonomic diversity. Functional diversity has proved useful for understanding local scale processes, but has less often been applied to understanding regional scale processes. Here, we explore functional diversity patterns within a metacommunity context to help elucidate how local and regional scale processes influence community assembly. We detail how each of the four metacommunity perspectives (species sorting, mass effects, patch dynamics, neutral) predict different patterns of functional beta‐ and alpha‐diversity and spatial structure along two key gradients: dispersal limitation and environmental conditions. We then apply this conceptual model to a case study from alpine tundra plant communities. We sampled species composition in 17 ‘sky islands’ of alpine tundra in the Colorado Rocky Mountains, USA that differed in geographic isolation and area (key factors related to dispersal limitation) and temperature and elevation (key environmental factors). We quantified functional diversity in each site based on specific leaf area, leaf area, stomatal conductance, plant height and chlorophyll content. We found that colder high elevation sites were functionally more similar to each other (decreased functional beta‐diversity) and had lower functional alpha‐diversity. Geographic isolation and area did not influence functional beta‐ or alpha‐diversity. These results suggest a strong role for environmental conditions structuring alpine plant communities, patterns consistent with the species sorting metacommunity perspective. Incorporating functional diversity into metacommunity theory can help elucidate how local and regional factors structure communities and provide a framework for observationally examining the role of metacommunity dynamics in systems where experimental approaches are less tractable.     

A process‐based metacommunity framework linking local and regional scale community ecology

The metacommunity concept has the potential to integrate local and regional dynamics within a general community ecology framework. To this end, the concept must move beyond the discrete archetypes that have largely defined it (e.g. neutral vs. species sorting) and better incorporate local scale species interactions and coexistence mechanisms. Here, we present a fundamental reconception of the framework that explicitly links local coexistence theory to the spatial processes inherent to metacommunity theory, allowing for a continuous range of competitive community dynamics. These dynamics emerge from the three underlying processes that shape ecological communities: (1) density‐independent responses to abiotic conditions, (2) density‐dependent biotic interactions and (3) dispersal. Stochasticity is incorporated in the demographic realisation of each of these processes. We formalise this framework using a simulation model that explores a wide range of competitive metacommunity dynamics by varying the strength of the underlying processes. Using this model and framework, we show how existing theories, including the traditional metacommunity archetypes, are linked by this common set of processes. We then use the model to generate new hypotheses about how the three processes combine to interactively shape diversity, functioning and stability within metacommunities.     

A mathematical framework for protein structure comparison

Comparison of protein structures is important for revealing the evolutionary relationship among proteins, predicting protein functions and predicting protein structures. Many methods have been developed in the past to align two or multiple protein structures. Despite the importance of this problem, rigorous mathematical or statistical frameworks have seldom been pursued for general protein structure comparison. One notable issue in this field is that with many different distances used to measure the similarity between protein structures, none of them are proper distances when protein structures of different sequences are compared. Statistical approaches based on those non-proper distances or similarity scores as random variables are thus not mathematically rigorous. In this work, we develop a mathematical framework for protein structure comparison by treating protein structures as three-dimensional curves. Using an elastic Riemannian metric on spaces of curves, geodesic distance, a proper distance on spaces of curves, can be computed for any two protein structures. In this framework, protein structures can be treated as random variables on the shape manifold, and means and covariance can be computed for populations of protein structures. Furthermore, these moments can be used to build Gaussian-type probability distributions of protein structures for use in hypothesis testing. The covariance of a population of protein structures can reveal the population-specific variations and be helpful in improving structure classification. With curves representing protein structures, the matching is performed using elastic shape analysis of curves, which can effectively model conformational changes and insertions/deletions. We show that our method performs comparably with commonly used methods in protein structure classification on a large manually annotated data set.     

Evidence of stochasticity driving anuran metacommunity structure in the Pantanal wetlands

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Hydrological connectivity determining metacommunity structure of planktonic heterotrophic flagellates

Dispersal potential of organisms is directly related to the hydrological connectivity among habitats. We investigated if the relative role of the environmental and spatial components in structuring the heterotrophic flagellates depends on the degree of hydrological connectivity. Samplings were performed in aquatic environments of the Paraná River floodplain, which differ in their degree of connectivity: lotic environments, connected lakes and isolated lakes (temporarily connected to the main river only during floods). We expect that communities in isolated lakes would be more subject to dispersal limitation, while in connected lakes and lotic environments the communities would be regulated mainly by environmental variables (species sorting). We sampled in the pelagic region of 23 environments during the low water period in 2014. The results of pRDA revealed that the contributions of environmental and spatial factors differed between the types of environments. The greater contribution of the environmental variables in structuring the flagellates metacommunity, regardless of the type of environment, may be related to the elevated dispersal capacity of microorganisms. The spatial component was also significant in the isolated lakes. Our results support the idea that microorganism communities are mainly structured by environmental factors, although the spatial component seems important when lakes are isolated.     

Dispersal abilities of riverine freshwater mussels influence metacommunity structure

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Beyond connectivity: how the structure of dispersal influences metacommunity dynamics

Dispersal within metacommunities can play a major role in species persistence by promoting asynchrony between communities. Understanding this role is crucial both for explaining species coexistence and managing landscapes that are increasingly fragmented by human activities. Here, we demonstrate that spatial patterning of dispersal connections can drastically alter both the tendency toward asynchrony and the effect of asynchrony on metacommunity dynamics commonly used to infer the potential for persistence. We also demonstrate that changes in dispersal connections in strictly homogeneous predator-prey metacommunities can generate an extremely rich variety of dynamics even when previously investigated properties of connectivity such as the magnitude and distribution of dispersal among patches are held constant. Furthermore, the dynamics we observe depend strongly on initial conditions. Our results illustrate the effectiveness of measures of spatial structure for predicting asynchrony and its effects on community dynamics, providing a deeper understanding of the relationship between spatial structure and species persistence in metacommunities.     

Predicting food‐web structure with metacommunity models

Synthesis Metacommunity theory aims to elucidate the relative influence of local and regional‐scale processes in generating diversity patterns across the landscape. Metacommunity research has focused largely on assemblages of competing organisms within a single trophic level. Here, we test the ability of metacommunity models to predict the network structure of the aquatic food web found in the leaves of the northern pitcher plant Sarracenia purpurea. The species‐sorting and patch‐dynamics models most accurately reproduced nine food web properties, suggesting that local‐scale interactions play an important role in structuring Sarracenia food webs. Our approach can be applied to any well‐resolved food web for which data are available from multiple locations. The metacommunity framework explores the relative influence of local and regional‐scale processes in generating diversity patterns across the landscape. Metacommunity models and empirical studies have focused mostly on assemblages of competing organisms within a single trophic level. Studies of multi‐trophic metacommunities are predominantly restricted to simplified trophic motifs and rarely consider entire food webs. We tested the ability of the patch‐dynamics, species‐sorting, mass‐effects, and neutral metacommunity models, as well as three hybrid models, to reproduce empirical patterns of food web structure and composition in the complex aquatic food web found in the northern pitcher plant Sarracenia purpurea. We used empirical data to determine regional species pools and estimate dispersal probabilities, simulated local food‐web dynamics, dispersed species from regional pools into local food webs at rates based on the assumptions of each metacommunity model, and tested their relative fits to empirical data on food‐web structure. The species‐sorting and patch‐dynamics models most accurately reproduced nine food web properties, suggesting that local‐scale interactions were important in structuring Sarracenia food webs. However, differences in dispersal abilities were also important in models that accurately reproduced empirical food web properties. Although the models were tested using pitcher‐plant food webs, the approach we have developed can be applied to any well‐resolved food web for which data are available from multiple locations.     

Bat metacommunity structure on Caribbean islands and the role of endemics

Aim We evaluate characteristics of species ranges (i.e. coherence, species turnover and range boundary clumping) to determine the structure of bat metacommunities and metaensembles from Caribbean islands. We evaluate the effects of endemic species on that structure, and quantify associations between island characteristics and latent environmental gradients that structure these metacommunities and metaensembles. Location Sixty‐five Caribbean islands throughout the Bahamas, Greater Antilles and Lesser Antilles. Methods Metacommunity structure is an emergent property of a set of ecological communities at different sites defined by species distributions across geographic or environmental gradients. We analysed elements of metacommunity structure (coherence, range turnover and range boundary clumping) to determine the best‐fit pattern for metacommunities from all Caribbean islands, as well as from the Bahamas, the Greater Antilles and the Lesser Antilles separately. For each island group, analyses were conducted for all bats and for each of two broadly defined guilds (i.e. carnivores and herbivores). In addition, analyses were conducted for all species and for a subset in which endemic species were removed from the fauna. Spearman rank correlations identified island characteristics (area, elevation, latitude, longitude) that were associated significantly with island scores for ordination axes based on reciprocal averaging. Results Metacommunity structure for all bats and for carnivores was similar for each island group, with Clementsian distributions (i.e. discrete communities with groups of species replacing other groups of species along the gradient) for all islands, the Bahamas and the Lesser Antilles, but with nested distributions for the Greater Antilles. Herbivore distributions were random for the Bahamas, but were Clementsian for all other island groups. Removal of endemic species affected the best‐fit model of metacommunity structure in only 3 of 12 cases. In general, ordination scores for islands were correlated with longitude or latitude, but not with island area or elevation. Main conclusions Characteristics of bat species ranges and associated metacommunity structure were primarily dependent on the number and geographic arrangement of primary sources of colonization, and not on interspecific interactions, species‐specific levels of environmental tolerance, or the physical characteristics of islands. Endemic species did not greatly affect metacommunity structure in Caribbean bats.     

A framework for clinical evaluation of diagnostic technologies.

Most new diagnostic technologies have not been adequately assessed to determine whether their application improves health. Comprehensive evaluation of diagnostic technologies includes establishing technologic capability and determining the range of possible uses, diagnostic accuracy, impact on the health care provider, therapeutic impact and impact on patient outcome. Guidelines to determine whether each of these criteria have been met adequately are presented. Diagnostic technologies should be disseminated only if they are less expensive, produce fewer untoward effects and are at least as accurate as existing methods, if they eliminate the need for other investigations without loss of accuracy, or if they lead to institution of effective therapy. Establishing patient benefit often requires a randomized controlled trial in which patients receive the new test or an alternative diagnostic strategy. Other study designs are logistically less difficult but may not provide accurate assessment of benefit. Rigorous assessment of diagnostic technologies is needed for efficient use of health care resources.     

A comprehensive framework for prioritizing variants in exome sequencing studies of Mendelian diseases

Exome sequencing strategy is promising for finding novel mutations of human monogenic disorders. However, pinpointing the casual mutation in a small number of samples is still a big challenge. Here, we propose a three-level filtration and prioritization framework to identify the casual mutation(s) in exome sequencing studies. This efficient and comprehensive framework successfully narrowed down whole exome variants to very small numbers of candidate variants in the proof-of-concept examples. The proposed framework, implemented in a user-friendly software package, named KGGSeq (http://statgenpro.psychiatry.hku.hk/kggseq), will play a very useful role in exome sequencing-based discovery of human Mendelian disease genes.     

A comprehensive system for evaluation of remote sequence similarity detection

Background  

Accurate and sensitive performance evaluation is crucial for both effective development of better structure prediction methods based on sequence similarity, and for the comparative analysis of existing methods. Up to date, there has been no satisfactory comprehensive evaluation method that (i) is based on a large and statistically unbiased set of proteins with clearly defined relationships; and (ii) covers all performance aspects of sequence-based structure predictors, such as sensitivity and specificity, alignment accuracy and coverage, and structure template quality.     

Inferring species roles in metacommunity structure from species co-occurrence networks

A long-standing question in community ecology is what determines the identity of species that coexist across local communities or metacommunity assembly. To shed light upon this question, we used a network approach to analyse the drivers of species co-occurrence patterns. In particular, we focus on the potential roles of body size and trophic status as determinants of metacommunity cohesion because of their link to resource use and dispersal ability. Small-sized individuals at low-trophic levels, and with limited dispersal potential, are expected to form highly linked subgroups, whereas large-size individuals at higher trophic positions, and with good dispersal potential, will foster the spatial coupling of subgroups and the cohesion of the whole metacommunity. By using modularity analysis, we identified six modules of species with similar responses to ecological conditions and high co-occurrence across local communities. Most species either co-occur with species from a single module or are connectors of the whole network. Among the latter are carnivorous species of intermediate body size, which by virtue of their high incidence provide connectivity to otherwise isolated communities playing the role of spatial couplers. Our study also demonstrates that the incorporation of network tools to the analysis of metacommunity ecology can help unveil the mechanisms underlying patterns and processes in metacommunity assembly.