scispace - formally typeset
Search or ask a question
Topic

Interaction network

About: Interaction network is a research topic. Over the lifetime, 2700 publications have been published within this topic receiving 113372 citations.


Papers
More filters
Posted ContentDOI
16 Aug 2017-bioRxiv
TL;DR: The network of pairwise competitive interactions in a model community consisting of 20 strains of naturally co-occurring soil bacteria is investigated and it is found that the interaction network is strongly hierarchical and lacks significant non-transitive motifs, a result that is robust across multiple environments.
Abstract: Microbial communities are typically incredibly diverse, and this diversity is thought to play a key role in community function. However, explaining how this diversity can be maintained is a major challenge in ecology. Temporal fluctuations and spatial structure in the environment likely play a key role, but it has also been suggested that the structure of interactions within the community may act as a stabilizing force for species diversity. In particular, if competitive interactions are non-transitive as in the classic rock-paper-scissors game, they can contribute to the maintenance of species diversity; on the other hand, if they are predominantly hierarchical, any observed diversity must be maintained via other mechanisms. Here, we investigate the network of pairwise competitive interactions in a model community consisting of 20 strains of naturally co-occurring soil bacteria. We find that the interaction network is strongly hierarchical and lacks significant non-transitive motifs, a result that is robust across multiple environments. Moreover, in agreement with recently proposed community assembly rules, the full 20-strain competition resulted in extinction of all but three of the most highly competitive strains, indicating that higher order interactions do not play a major role in structuring this community. The lack of non-transitivity and higher order interactions in vitro indicates that other factors, such as temporal or spatial heterogeneity, must be at play in enabling these strains to coexist in nature.

34 citations

Journal ArticleDOI
TL;DR: Results of the intervention scores indicate that the method proposed in this study can provide new effective combinations of Chinese herbal medicines for T2DM, and can effectively promote the modernization and development of TCM.

34 citations

Journal ArticleDOI
TL;DR: A new approach for visualizing and analyzing the dynamic spread on the host network of the local perturbations induced by viral proteins is found, which confirms that potyvirus protein-protein interaction networks are highly connected, with some proteins playing the role of hubs.
Abstract: One of the central interests of Virology is the identification of host factors that contribute to virus infection. Despite tremendous efforts, the list of factors identified remains limited. With omics techniques, the focus has changed from identifying and thoroughly characterizing individual host factors to the simultaneous analysis of thousands of interactions, framing them on the context of protein-protein interaction networks and of transcriptional regulatory networks. This new perspective is allowing the identification of direct and indirect viral targets. Such information is available for several members of the Potyviridae family, one of the largest and more important families of plant viruses. After collecting information on virus protein-protein interactions from different potyviruses, we have processed it and used it for inferring a protein-protein interaction network. All proteins are connected into a single network component. Some proteins show a high degree and are highly connected while others are much less connected, with the network showing a significant degree of dissortativeness. We have attempted to integrate this virus protein-protein interaction network into the largest protein-protein interaction network of Arabidopsis thaliana, a susceptible laboratory host. To make the interpretation of data and results easier, we have developed a new approach for visualizing and analyzing the dynamic spread on the host network of the local perturbations induced by viral proteins. We found that local perturbations can reach the entire host protein-protein interaction network, although the efficiency of this spread depends on the particular viral proteins. By comparing the spread dynamics among viral proteins, we found that some proteins spread their effects fast and efficiently by attacking hubs in the host network while other proteins exert more local effects. Our findings confirm that potyvirus protein-protein interaction networks are highly connected, with some proteins playing the role of hubs. Several topological parameters depend linearly on the protein degree. Some viral proteins focus their effect in only host hubs while others diversify its effect among several proteins at the first step. Future new data will help to refine our model and to improve our predictions.

34 citations

Journal ArticleDOI
TL;DR: A novel framework based on WeChat-like interaction network to analyze manipulative and non-cooperative behaviors in the LSGDM problems is introduced and the efficiency of this novel approach for coping with manipulative andNon- cooperative behaviors is demonstrated.

34 citations

Journal ArticleDOI
TL;DR: An analysis of protein interaction network data via the comparison of models of network evolution to the observed data is presented and a preference for a duplication-divergence with linear preferential attachment model is found in the majority of the interaction datasets considered.
Abstract: We present an analysis of protein interaction network data via the comparison of models of network evolution to the observed data We take a Bayesian approach and perform posterior density estimation using an approximate Bayesian computation with sequential Monte Carlo method Our approach allows us to perform model selection over a selection of potential network growth models The methodology we apply uses a distance defined in terms of graph spectra which captures the network data more naturally than previously used summary statistics such as the degree distribution Furthermore, we include the effects of sampling into the analysis, to properly correct for the incompleteness of existing datasets, and have analysed the performance of our method under various degrees of sampling We consider a number of models focusing not only on the biologically relevant class of duplication models, but also including models of scale-free network growth that have previously been claimed to describe such data We find a preference for a duplication-divergence with linear preferential attachment model in the majority of the interaction datasets considered We also illustrate how our method can be used to perform multi-model inference of network parameters to estimate properties of the full network from sampled data

34 citations


Network Information
Related Topics (5)
Genome
74.2K papers, 3.8M citations
83% related
Regulation of gene expression
85.4K papers, 5.8M citations
81% related
Cluster analysis
146.5K papers, 2.9M citations
80% related
Gene
211.7K papers, 10.3M citations
79% related
Transcription factor
82.8K papers, 5.4M citations
78% related
Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202337
202290
2021183
2020221
2019201
2018163