Extraction of Temporal Networks from Term Co-Occurrences in Online Textual Sources

A stream of unstructured news can be a valuable source of hidden relations between different entities, such as financial institutions, countries, or persons. We present an approach to continuously collect online news, recognize relevant entities in them, and extract time-varying networks. The nodes of the network are the entities, and the links are their co-occurrences. We present a method to estimate the significance of co-occurrences, and a benchmark model against which their robustness is evaluated. The approach is applied to a large set of financial news, collected over a period of two years. The entities we consider are 50 countries which issue sovereign bonds, and which are insured by Credit Default Swaps (CDS) in turn. We compare the country co-occurrence networks to the CDS networks constructed from the correlations between the CDS. The results show relatively small, but significant overlap between the networks extracted from the news and those from the CDS correlations.     

Phenocopy--a strategy to qualify chemical compounds during hit-to-lead and/or lead optimization

A phenocopy is defined as an environmentally induced phenotype of one individual which is identical to the genotype-determined phenotype of another individual. The phenocopy phenomenon has been translated to the drug discovery process as phenotypes produced by the treatment of biological systems with new chemical entities (NCE) may resemble environmentally induced phenotypic modifications. Various new chemical entities exerting inhibition of the kinase activity of Transforming Growth Factor β Receptor I (TGF-βR1) were qualified by high-throughput RNA expression profiling. This chemical genomics approach resulted in a precise time-dependent insight to the TGF-β biology and allowed furthermore a comprehensive analysis of each NCE's off-target effects. The evaluation of off-target effects by the phenocopy approach allows a more accurate and integrated view on optimized compounds, supplementing classical biological evaluation parameters such as potency and selectivity. It has therefore the potential to become a novel method for ranking compounds during various drug discovery phases.     

Mining relational paths in integrated biomedical data

Much life science and biology research requires an understanding of complex relationships between biological entities (genes, compounds, pathways, diseases, and so on). There is a wealth of data on such relationships in publicly available datasets and publications, but these sources are overlapped and distributed so that finding pertinent relational data is increasingly difficult. Whilst most public datasets have associated tools for searching, there is a lack of searching methods that can cross data sources and that in particular search not only based on the biological entities themselves but also on the relationships between them. In this paper, we demonstrate how graph-theoretic algorithms for mining relational paths can be used together with a previous integrative data resource we developed called Chem2Bio2RDF to extract new biological insights about the relationships between such entities. In particular, we use these methods to investigate the genetic basis of side-effects of thiazolinedione drugs, and in particular make a hypothesis for the recently discovered cardiac side-effects of Rosiglitazone (Avandia) and a prediction for Pioglitazone which is backed up by recent clinical studies.     

Predation,competition, and co-occurrences of Boeckella and Calamoecia (Copepoda: Calanoida) in Western Australia

Patterns of co-occurrences of Boeckella and Calamoeciafound in Western Australia are documented. Patterns are analyzed inrelation to size of organisms and to geographical distributions oforganisms. Deviations from randomness in the number ofmulti-species assemblages suggest that biotic interactionsinfluence co-occurrences, but size relationships in severalco-occurring pairs indicate that competition for resources is nota factor influencing co-occurrence. Laboratory experimentsdemonstrate that the large Boeckella triarticulata consumesimmature stages of the small Calamoecia tasmanica butprovides a partial refuge for C. tasmanica when theplanktivorous fish Gambusia, which consumes Boeckellamore rapidly than Calamoecia, is present. These resultsindicate that co-occurrence patterns may be related to theintensity of predation by fish: in the absence of fish predation,Boeckella can prevent invasion of Calamoecia, whilemoderate predation by fish will reduce Boeckella density,consequently allowing Calamoecia to invade.     

Nurse plant effects on plant species richness in drylands: The role of grazing,rainfall and species specificity

The outcome of plant–plant interactions depends on environmental (e.g. grazing and climatic conditions) and species-specific attributes (e.g. life strategy and dispersal mode of the species involved). However, the joint effects of such factors on pairwise plant–plant interactions, and how they modulate the role of these interactions at the community level, have not been addressed before. We assessed how these species-specific (life strategy and dispersal) and environmental (grazing and rainfall) factors affected the co-occurrence of 681 plant species pairs on open woodlands in south-eastern Australia. Species-specific attributes affected the co-occurrence of most species pairs, with higher co-occurrence levels dominating for drought-intolerant species. The dispersal mechanism only affected drought-tolerant beneficiaries, with more positive co-occurrences for vertebrate-dispersed species. Conversely, the percentage of facilitated species at the community scale declined under higher rainfall availabilities. A significant grazing × rainfall interaction on the percentage of facilitated species suggests that grazing-mediated protection was important under low to moderate, but not high, rainfall availabilities. This study improves our ability to predict changes in plant–plant interactions along environmental gradients, and their effect on community species richness, by highlighting that: (1) species-specific factors were more important than environmental conditions as drivers of a large amount (～37%) of the pairwise co-occurrences evaluated; (2) grazing and rainfall interaction drive the co-occurrence among different species in the studied communities, and (3) the effect of nurse plants on plant species richness will depend on the relative dominance of particular dispersal mechanisms or life strategies prone to be facilitated.     

Male hosts drive infracommunity structure of ectoparasites

We studied the co-occurrence of flea species in infracommunities of 16 rodents from four regions (South Africa, Tanzania, central Europe and western Siberia) using null models, and predicted that flea co-occurrences will be expressed more strongly in male than in female hosts. We examined patterns of co-occurrence (measured as the C score) in infracommunities of fleas that are parasitic on male and female hosts by comparing co-occurrence frequencies with those expected by chance. When a significant degree of nonrandomness in flea co-occurrences was detected, it indicated aggregative infracommunity structure. In Tanzanian rodents, no significant flea co-occurrences were detected in either male or female hosts. In a South African rodent, significant flea co-occurrences were not detected in males, but were found in females in some localities. In Palaearctic rodents, significant nonrandomness was detected either equally for males and females or more frequently in males than in females. Meta-analyses demonstrated that the frequency of the detection of nonrandomness in flea co-occurrences was significantly higher in male than in female hosts. The values of the standardized effect size (SES) for the C score differed significantly among host species, but not between host genders. When the Palaearctic hosts were analyzed separately, the effects of both host gender and species appeared to be significant, with the SES values for the C score in males being smaller than those in females. The strength of the gender difference in the manifestation of flea community structure increased with increasing gender difference in flea species richness, and with decreasing gender difference in flea prevalence for the Palaearctic hosts. We conclude that male hosts are the main drivers of flea infracommunity structure. However, the manifestation of gender bias in flea community structure varies among host species, and is likely determined by the pattern of species-specific spatial behavior.     

A theory for species co-occurrence in interaction networks

The study of species co-occurrences has been central in community ecology since the foundation of the discipline. Co-occurrence data are, nevertheless, a neglected source of information to model species distributions and biogeographers are still debating about the impact of biotic interactions on species distributions across geographical scales. We argue that a theory of species co-occurrence in ecological networks is needed to better inform interpretation of co-occurrence data, to formulate hypotheses for different community assembly mechanisms, and to extend the analysis of species distributions currently focused on the relationship between occurrences and abiotic factors. The main objective of this paper is to provide the first building blocks of a general theory for species co-occurrences. We formalize the problem with definitions of the different probabilities that are studied in the context of co-occurrence analyses. We analyze three species interactions modules and conduct multi-species simulations in order to document five principles influencing the associations between species within an ecological network: (i) direct interactions impact pairwise co-occurrence, (ii) indirect interactions impact pairwise co-occurrence, (iii) pairwise co-occurrence rarely are symmetric, (iv) the strength of an association decreases with the length of the shortest path between two species, and (v) the strength of an association decreases with the number of interactions a species is experiencing. Our analyses reveal the difficulty of the interpretation of species interactions from co-occurrence data. We discuss whether the inference of the structure of interaction networks is feasible from co-occurrence data. We also argue that species distributions models could benefit from incorporating conditional probabilities of interactions within the models as an attempt to take into account the contribution of biotic interactions to shaping individual distributions of species.     

Spatial co-occurrence networks predict the feeding histories of polyphagous arthropod predators at field scales

In agricultural systems, polyphagous beetles and spiders are abundant components of the beneficial arthropod community. Although data on the dietary ranges of these groups is increasing, remarkably little is understood regarding how individuals interact with their prey at small spatial scales. We demonstrate the utility of a spatially-explicit network model that integrates predator behaviour using predator-prey co-occurrences. Three co-occurrence matrices, one each for June, July and August, were generated using Vortis suction sample data collected from an 80 point grid imposed on a field of winter wheat. Heuristic predator-prey linkages, based on positive spatial co-occurrence, were imposed on these three matrices to create networks. It was found that primary consumers were highly aggregated and showed a strong tendency to co-occur. This contrasted with patterns of predator–predator or predator–prey co-occurrences that either aggregated to their prey or were weak and more scattered. These patterns could not be explained by either competition for resources or body size differences. Procrustean methods indicated that the networks were temporally dynamic, consistently achieving rates of turnover >60%. A negative relationship was found between decreasing predator–prey co-occurrence in the network and the number of prey positives in the guts of those predators. For large polyphagous beetles, the closer they were to their prey at the field scale, the more likely they were to have eaten them. This simple underlying relationship suggests that spatial co-occurrence networks can be used to predict feeding behaviour and could make a valuable contribution to food web structuring.     

Species co-occurrences in ectoparasite infracommunities: Accounting for confounding factors associated with space,time, and host community composition

1. We explored patterns of co-occurrence of ectoparasite species on individual hosts from Central Europe (Slovakia) and South America (Argentina) within and between higher taxa while controlling for confounding factors associated with variation between host individuals and host species, as well as spatial and temporal variation. We used a recently developed statistical approach, the hierarchical modelling of species communities. 2. Although the probability of pairwise associations of the majority of species in both regions did not differ from random, all significant species associations in Slovakia were positive, whereas the only three significant species associations in Argentina were negative. On average, associations between ectoparasite species belonging to different higher taxa were positive in Slovakia and negative in Argentina. 3. At the host species level, both positive and negative associations between species were detected in all higher taxa. This was also true for ectoparasite co-occurrences in the same site, habitat, or year; although the number of co-occurring species pairs with high posterior probability was much greater in Slovakia than in Argentina. 4. We conclude that consideration of species co-occurrences across the entire multi-host assemblage and control for confounding spatial and temporal factors provided important insights into parasite community structure.     

A Genome-Wide Gene Function Prediction Resource for Drosophila melanogaster

Predicting gene functions by integrating large-scale biological data remains a challenge for systems biology. Here we present a resource for Drosophila melanogaster gene function predictions. We trained function-specific classifiers to optimize the influence of different biological datasets for each functional category. Our model predicted GO terms and KEGG pathway memberships for Drosophila melanogaster genes with high accuracy, as affirmed by cross-validation, supporting literature evidence, and large-scale RNAi screens. The resulting resource of prioritized associations between Drosophila genes and their potential functions offers a guide for experimental investigations.     

Compound co-occurrence and biosynthetic inference

Zavarin suggested that co-occurrence of terpenoids in plants provides an indication of likely biosynthetic relationships when enzymatic and tracer results are unavailable to determine the matter. Zavarin's proposal is here evaluated with data from another class of secondary metabolites, the glucosinolates, where biosynthetic pathways are well known. Three datasets from taxa of Cakile and Streptanthus (Cruciferae) were analyzed statistically with SPSS programs. Pair-wise comparisons of compounds tested their assignment to one of three possible categories: related by one-carbon chain extension; related by cleavage of terminal methylthio-group to produce a double bond; or no close relationship. While one dataset showed a tendency for chain-extended compounds to correlate significantly, the data exhibited no strong indication overall that co-occurring compounds were any more likely to be biosynthetically linked than not. Furthermore, contrasting positive and negative correlations for biosynthetically related pairs indicated that co-occurrence did not track mechanisms of biosynthesis. Hence, compound co-occurrence by itself provides no clear guide to biosynthetic relationships. By analogy, similar results can be expected for other classes of diverse secondary metabolites such as flavonoids and terpenoids.     

Co-occurrence of ectoparasites on rodent hosts: null model analyses of data from three continents

We studied patterns of species co-occurrence in communities of ectoparasitic arthropods (ixodid ticks, mesostigmate mites and fleas) harboured by rodent hosts from South Africa ( Rhabdomys pumilio ), South America ( Scapteromys aquaticus and Oxymycterus rufus ) and west Siberia ( Apodemus agrarius , Microtus gregalis , Microtus oeconomus and Myodes rutilus ) using null models. We compared frequencies of co-occurrences of parasite species or higher taxa across host individuals with those expected by chance. When non-randomness of parasite co-occurrences was detected, positive but not negative co-occurrences of parasite species or higher taxa prevailed (except for a single sample of mesostigmate mites from O. rufus ). Frequency of detection of non-randomness of parasite co-occurrences differed among parasite taxa, being higher in fleas and lower in mites and ticks. This frequency differed also among host species independent of parasite taxon, being highest in Microtus species and lowest in O. rufus and S. aquaticus . We concluded that the pattern of species co-occurrence in ectoparasite communities on rodent hosts is predominantly positive, depends on life history of parasites and may be affected to a great extent by life history of a host.     

Chemical genomics in plant biology

Chemical genomics is a newly emerged and rapidly progressing field in biology, where small chemical molecules bind specifically and reversibly to protein(s) to modulate their function(s), leading to the delineation and subsequent unravelling of biological processes. This approach overcomes problems like lethality and redundancy of classical genetics. Armed with the powerful techniques of combinatorial synthesis, high-throughput screening and target discovery chemical genomics expands its scope to diverse areas in biology. The well-established genetic system of Arabidopsis model allows chemical genomics to enter into the realm of plant biology exploring signaling pathways of growth regulators, endomembrane signaling cascades, plant defense mechanisms and many more events.     

Assessing drug target association using semantic linked data

The rapidly increasing amount of public data in chemistry and biology provides new opportunities for large-scale data mining for drug discovery. Systematic integration of these heterogeneous sets and provision of algorithms to data mine the integrated sets would permit investigation of complex mechanisms of action of drugs. In this work we integrated and annotated data from public datasets relating to drugs, chemical compounds, protein targets, diseases, side effects and pathways, building a semantic linked network consisting of over 290,000 nodes and 720,000 edges. We developed a statistical model to assess the association of drug target pairs based on their relation with other linked objects. Validation experiments demonstrate the model can correctly identify known direct drug target pairs with high precision. Indirect drug target pairs (for example drugs which change gene expression level) are also identified but not as strongly as direct pairs. We further calculated the association scores for 157 drugs from 10 disease areas against 1683 human targets, and measured their similarity using a [Formula: see text] score matrix. The similarity network indicates that drugs from the same disease area tend to cluster together in ways that are not captured by structural similarity, with several potential new drug pairings being identified. This work thus provides a novel, validated alternative to existing drug target prediction algorithms. The web service is freely available at: http://chem2bio2rdf.org/slap.     

Diurnal foraging ant–tree co-occurrence networks are similar between canopy and understorey in a Neotropical rain forest

Discussion of the vertical stratification of organisms in tropical forests has traditionally focused on species distribution. Most studies have shown that, due to differences in abiotic conditions and resource distribution, species can be distributed along the vertical gradient according to their ecophysiological needs. However, the network structure between distinct vertical strata remains little-explored. To fill this gap in knowledge, we used baits to sample ants in the canopy and understorey trees of a Mexican tropical rain forest to record the ant–tree co-occurrences. We examined the ant–tree co-occurrences in the canopy and understorey using complementary network metrics (i.e., specialization, interaction diversity, modularity, and nestedness). In addition, we evaluated co-occurrence patterns between ant species on trees, using C-score analysis. In general, we found no differences in the network structure, although the interaction diversity was greater in the understorey than in the canopy networks. We also observed that co-occurrence networks of each vertical stratum featured four ant species in the central core of highly co-occurring species, with three species unique to each stratum. Moreover, we found a similar trend toward ant species segregation in the both strata. These findings reveal a similar pattern of ant–ant co-occurrences in both vertical strata, probably due to the presence of arboreal-nesting ants in the understorey. Overall, we showed that despite the marked differences in species composition and environmental conditions between understorey and canopy strata, ant–tree co-occurrences in these habitats could be governed by similar mechanisms, related to dominance and resource monopolization by ants.     

EU-OPENSCREEN—chemical tools for the study of plant biology and resistance mechanisms

EU-OPENSCREEN is an academic research infrastructure initiative in Europe for enabling researchers in all life sciences to take advantage of chemical biology approaches to their projects. In a collaborative effort of national networks in 16 European countries, EU-OPENSCREEN will develop novel chemical compounds with external users to address questions in, among other fields, systems and network biology (directed and selective perturbation of signalling pathways), structural biology (compound-target interactions at atomic resolution), pharmacology (early drug discovery and toxicology) and plant biology (response of wild or crop plants to environmental and agricultural substances). EU-OPENSCREEN supports all stages of a tool development project, including assay adaptation, high-throughput screening and chemical optimisation of the ‘hit’ compounds. All tool compounds and data will be made available to the scientific community. EU-OPENSCREEN integrates high-capacity screening platforms throughout Europe, which share a rationally selected compound collection comprising up to 300,000 (commercial and proprietary compounds collected from European chemists). By testing systematically this chemical collection in hundreds of assays originating from very different biological themes, the screening process generates enormous amounts of information about the biological activities of the substances and thereby steadily enriches our understanding of how and where they act.     

Explaining co-occurrence among helminth species of lesser snow geese (Chen caerulescens) during their winter and spring migration

The digestive tracts of 771 lesser snow geese (Chen caerulescens) collected from January to May 1983 from 12 locations (27 samples) were examined for helminth parasites to determine whether parasite species present in wintering geese or in spring migrants occurred independently of each other. Nine helminth species were identified. Seven had mean prevalences >5% and were the focus of this study. Six of those species were waterfowl generalists, one was a goose specialist. Our primary objective was to assess the potential contribution of factors, other than species interactions, in determining patterns of co-occurrence between helminth species. There were few negative relationships between helminth species, regardless of whether presence-absence or abundance data were used. However, some species pairs showed recurrent and significant co-occurrences. There were similar and significant effects of timing of sampling, host gender, and host age, on prevalence and mean abundance of particular species. Co-occurrences were found for those species that showed seasonal declines in prevalence, for those expected to have high colonizing ability based on host age profiles (using abundance data), and for abundant species that may have shared vectors or environmental conditions favorable for transmission. Thus, similarities between parasites in their abundance, transmission biology, and phenology seem sufficient to explain species co-occurrences without invoking other processes such as species interactions. Received: 18 March 1996 / Accepted: 20 April 1999     

Small zebrafish in a big chemical pond

The number of possible small organic molecules of different structure is virtually limitless. One of the main goals of chemical biologists is to identify, from this “chemical space”, entities that affect biological processes or systems in a specific manner. This can lead to a better understanding of the regulation and components of various biological machineries, as well as provide insights into efficacious therapeutic targets and drug candidates. However, the challenges confronting chemical biologists are multiple. How do we efficiently identify compounds that possess desirable activities without unwanted off‐target effects? Once a candidate compound has been found, how do we determine its mode of action? In this Prospects piece, we call attention to recent studies using embryonic and larval zebrafish to illustrate the breadth and depth of questions in chemical biology that may be addressed using this model, and hope that they can serve as catalysts for future investigational ideas. J. Cell. Biochem. 113: 2208–2216, 2012. © 2012 Wiley Periodicals, Inc.     

Enrichment and Training Improve Cognition in Rats with Cortical Malformations

Children with malformations of cortical development (MCD) frequently have associated cognitive impairments which reduce quality of life. We hypothesized that cognitive deficits associated with MCD can be improved with environmental manipulation or additional training. The E17 methylazoxymethanol acetate (MAM) exposure model bears many anatomical hallmarks seen in human MCDs as well as similar behavioral and cognitive deficits. We divided control and MAM exposed Sprague-Dawley rats into enriched and non-enriched groups and tested performance in the Morris water maze. Another group similarly divided underwent sociability testing and also underwent Magnetic Resonance Imaging (MRI) scans pre and post enrichment. A third group of control and MAM rats without enrichment were trained until they reached criterion on the place avoidance task. MAM rats had impaired performance on spatial tasks and enrichment improved performance of both control and MAM animals. Although MAM rats did not have a deficit in sociability they showed similar improvement with enrichment as controls. MRI revealed a whole brain volume decrease with MAM exposure, and an increase in both MAM and control enriched volumes in comparison to non-enriched animals. In the place avoidance task, MAM rats required approximately 3 times as long to reach criterion as control animals, but with additional training were able to reach control performance. Environmental manipulation and additional training can improve cognition in a rodent MCD model. We therefore suggest that patients with MCD may benefit from appropriate alterations in educational strategies, social interaction and environment. These factors should be considered in therapeutic strategies.