Factors determining nestedness in complex networks.
Ontology highlight
ABSTRACT:
SUBMITTER: Jonhson S
PROVIDER: S-EPMC3777946 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description: Not available
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Project description:Nestedness is a statistical measure used to interpret bipartite interaction data in several ecological and evolutionary contexts, e.g. biogeography (species-site relationships) and species interactions (plant-pollinator and host-parasite networks). Multiple methods have been used to evaluate nestedness, which differ in how the metrics for nestedness are determined. Furthermore, several different null models have been used to calculate statistical significance of nestedness scores. The profusion of measures and null models, many of which give conflicting results, is problematic for comparison of nestedness across different studies. We developed the FALCON software package to allow easy and efficient comparison of nestedness scores and statistical significances for a given input network, using a selection of the more popular measures and null models from the current literature. FALCON currently includes six measures and five null models for nestedness in binary networks, and two measures and four null models for nestedness in weighted networks. The FALCON software is designed to be efficient and easy to use. FALCON code is offered in three languages (R, MATLAB, Octave) and is designed to be modular and extensible, enabling users to easily expand its functionality by adding further measures and null models. FALCON provides a robust methodology for comparing the strength and significance of nestedness in a given bipartite network using multiple measures and null models. It includes an "adaptive ensemble" method to reduce undersampling of the null distribution when calculating statistical significance. It can work with binary or weighted input networks. FALCON is a response to the proliferation of different nestedness measures and associated null models in the literature. It allows easy and efficient calculation of nestedness scores and statistical significances using different methods, enabling comparison of results from different studies and thereby supporting theoretical study of the causes and implications of nestedness in different biological contexts.
| S-EPMC4244763 | biostudies-other
Project description:Theoretical studies have indicated that nestedness and modularity-non-random structural patterns of ecological networks-influence the stability of ecosystems against perturbations; as such, climate change and human activity, as well as other sources of environmental perturbations, affect the nestedness and modularity of ecological networks. However, the effects of climate change and human activities on ecological networks are poorly understood. Here, we used a spatial analysis approach to examine the effects of climate change and human activities on the structural patterns of food webs and mutualistic networks, and found that ecological network structure is globally affected by climate change and human impacts, in addition to current climate. In pollination networks, for instance, nestedness increased and modularity decreased in response to increased human impacts. Modularity in seed-dispersal networks decreased with temperature change (i.e., warming), whereas food web nestedness increased and modularity declined in response to global warming. Although our findings are preliminary owing to data-analysis limitations, they enhance our understanding of the effects of environmental change on ecological communities.
| S-EPMC4913940 | biostudies-literature
Project description:Biological networks pervade nature. They describe systems throughout all levels of biological organization, from molecules regulating metabolism to species interactions that shape ecosystem dynamics. The network thinking revealed recurrent organizational patterns in complex biological systems, such as the formation of semi-independent groups of connected elements (modularity) and non-random distributions of interactions among elements. Other structural patterns, such as nestedness, have been primarily assessed in ecological networks formed by two non-overlapping sets of elements; information on its occurrence on other levels of organization is lacking. Nestedness occurs when interactions of less connected elements form proper subsets of the interactions of more connected elements. Only recently these properties began to be appreciated in one-mode networks (where all elements can interact) which describe a much wider variety of biological phenomena. Here, we compute nestedness in a diverse collection of one-mode networked systems from six different levels of biological organization depicting gene and protein interactions, complex phenotypes, animal societies, metapopulations, food webs and vertebrate metacommunities. Our findings suggest that nestedness emerge independently of interaction type or biological scale and reveal that disparate systems can share nested organization features characterized by inclusive subsets of interacting elements with decreasing connectedness. We primarily explore the implications of a nested structure for each of these studied systems, then theorize on how nested networks are assembled. We hypothesize that nestedness emerges across scales due to processes that, although system-dependent, may share a general compromise between two features: specificity (the number of interactions the elements of the system can have) and affinity (how these elements can be connected to each other). Our findings suggesting occurrence of nestedness throughout biological scales can stimulate the debate on how pervasive nestedness may be in nature, while the theoretical emergent principles can aid further research on commonalities of biological networks.
| S-EPMC5293200 | biostudies-literature
Project description:Plant-pollinator networks have been repeatedly reported as cumulative ones that are described with >1 years observations. However, such cumulative networks are composed of pairwise interactions recorded at different periods, and thus may not be able to reflect the reality of species interactions in nature (e.g., early-flowering plants typically do not compete for shared pollinators with late-flowering plants, but they are assumed to do so in accumulated networks). Here, we examine the monthly sampling structure of an alpine plant-pollinator bipartite network over a two-year period to determine whether relative species abundance and species traits better explain the network structure of monthly networks than yearly ones. Although community composition and species abundance varied from one month to another, the monthly networks (as well as the yearly networks described with annual pooled data) had a highly nested structure, in which specialists directly interact with generalist partners. Moreover, relative species abundance predicted the nestedness in both the monthly and yearly networks and accounted for a statistically significant percentage of the variation (i.e., 20%-44%) in the pairwise interactions of monthly networks, but not yearly networks. The combination of relative species abundance and species traits (but not species traits only) showed a similar prediction power in terms of both network nestedness and pairwise interaction frequencies. Considering the previously recognized structural pattern and associated mechanisms of plant-pollinator networks, we propose that relative species abundance may be an important factor influencing both nestedness and interaction frequency of pollination networks.
| S-EPMC6816544 | biostudies-literature
Project description:Nestedness and modularity are measures of ecological networks whose causative effects are little understood. We analyzed antagonistic plant-herbivore bipartite networks using common gardens in two contrasting environments comprised of aspen trees with differing evolutionary histories of defence against herbivores. These networks were tightly connected owing to a high level of specialization of arthropod herbivores that spend a large proportion of the life cycle on aspen. The gardens were separated by ten degrees of latitude with resultant differences in abiotic conditions. We evaluated network metrics and reported similar connectance between gardens but greater numbers of links per species in the northern common garden. Interaction matrices revealed clear nestedness, indicating subsetting of the bipartite interactions into specialist divisions, in both the environmental and evolutionary aspen groups, although nestedness values were only significant in the northern garden. Variation in plant vulnerability, measured as the frequency of herbivore specialization in the aspen population, was significantly partitioned by environment (common garden) but not by evolutionary origin of the aspens. Significant values of modularity were observed in all network matrices. Trait-matching indicated that growth traits, leaf morphology, and phenolic metabolites affected modular structure in both the garden and evolutionary groups, whereas extra-floral nectaries had little influence. Further examination of module configuration revealed that plant vulnerability explained considerable variance in web structure. The contrasting conditions between the two gardens resulted in bottom-up effects of the environment, which most strongly influenced the overall network architecture, however, the aspen groups with dissimilar evolutionary history also showed contrasting degrees of nestedness and modularity. Our research therefore shows that, while evolution does affect the structure of aspen-herbivore bipartite networks, the role of environmental variations is a dominant constraint.
| S-EPMC4541994 | biostudies-literature
Project description:Registration of patients referred for colon investigation by barium enema, CT colonography and colonoscopy in two hospitals and one radiology centre in Telemark, Norway, for a period of minimum six months. Indications, delay and results of procedure will be recorded.Hypothesis: Choice of procedure for colon investigation is not based solely on clinical indication, but factors like delay, patient preference, lack of knowledge about the the procedures by the referring physician may have a decisive influence. The study will also analyse the correlation between patients symptoms, clinical findings and laboratory results and major pathology findings by colon investigation. Further, delay from patient´s first symptoms to finally diagnosis by colon investigation will also be registered and analysed.
| 2036222 | ecrin-mdr-crc
Project description:The physiological determinants of high-intensity exercise tolerance are important for both elite human performance and morbidity, mortality and disease in clinical settings. The asymptote of the hyperbolic relation between external power and time to task failure, critical power, represents the threshold intensity above which systemic and intramuscular metabolic homeostasis can no longer be maintained. After ~ 60 years of research into the phenomenon of critical power, a clear understanding of its physiological determinants has emerged. The purpose of the present review is to critically examine this contemporary evidence in order to explain the physiological underpinnings of critical power. Evidence demonstrating that alterations in convective and diffusive oxygen delivery can impact upon critical power is first addressed. Subsequently, evidence is considered that shows that rates of muscle oxygen utilisation, inferred via the kinetics of pulmonary oxygen consumption, can influence critical power. The data reveal a clear picture that alterations in the rates of flux along every step of the oxygen transport and utilisation pathways influence critical power. It is also clear that critical power is influenced by motor unit recruitment patterns. On this basis, it is proposed that convective and diffusive oxygen delivery act in concert with muscle oxygen utilisation rates to determine the intracellular metabolic milieu and state of fatigue within the myocytes. This interacts with exercising muscle mass and motor unit recruitment patterns to ultimately determine critical power.
| S-EPMC9935749 | biostudies-literature
Project description:Many vector-borne pathogens rely on antigenic variation to prolong infections and increase their likelihood of onward transmission. This immune evasion strategy often involves mutually exclusive switching between members of gene families that encode functionally similar but antigenically different variants during the course of a single infection. Studies of different pathogens have suggested that switching between variant genes is non-random and that genes have intrinsic probabilities of being activated or silenced. These factors could create a hierarchy of gene expression with important implications for both infection dynamics and the acquisition of protective immunity. Inferring complete switching networks from gene transcription data is problematic, however, because of the high dimensionality of the system and uncertainty in the data. Here we present a statistically rigorous method for analysing temporal gene transcription data to reconstruct an underlying switching network. Using artificially generated transcription profiles together with in vitro var gene transcript data from two Plasmodium falciparum laboratory strains, we show that instead of relying on data from long-term parasite cultures, accuracy can be greatly improved by using transcription time courses of several parasite populations from the same isolate, each starting with different variant distributions. The method further provides explicit indications about the reliability of the resulting networks and can thus be used to test competing hypotheses with regards to the underlying switching pathways. Our results demonstrate that antigenic switch pathways can be determined reliably from short gene transcription profiles assessing multiple time points, even when subject to moderate levels of experimental error. This should yield important new information about switching patterns in antigenically variable organisms and might help to shed light on the molecular basis of antigenic variation.
| S-EPMC3382232 | biostudies-literature
Project description:BACKGROUND:Aetiology of transient global amnesia (TGA) remains uncertain, though many have been proposed, including ischaemic, migrainous or epileptic pathologies. METHODS:We attempted to determine risk factors for TGA, as well as prognostic factors that may cause recurrence. We evaluated clinical history, family history and magnetic resonance diffusion-weighted imaging (DWI) studies of 93 prospective patients with TGA. Patients were followed from 2004 to 2016. Fifteen of 93 (16%) patients experienced a recurrence of TGA. RESULTS:Among precipitating events, physical activities inducing Valsalva-like manoeuvres were most common, followed by emotional stress. Eighty-four patients had possible comorbidities or risk factors for TGA, though no single risk factor was ubiquitous. Risk factors associated with recurrence were head injury (isolated vs. recurrent, 16.7% vs. 53.5%, p <?0.01), depression (isolated vs. recurrent, 15.4% vs 46.7%, p =?0.01) and family history of dementia (isolated vs. recurrent, 20.5% vs. 46.7%, p =?0.03). Of 15 patients with confirmed recurrent TGA, two developed dementia and four subjective memory impairment. DWI lesions were observed in 24 patients and were located anywhere within the hippocampus. CONCLUSIONS:DWI lesions were not significantly associated with outcomes (recurrence, subjective memory impairment, dementia). We have found that depression, previous head injury and family history of dementia may predict TGA recurrence.
| S-EPMC7060647 | biostudies-literature