ArticleFrontiers in microbiology2022
Application of a maximal-clique based community detection algorithm to gut microbiome data reveals driver microbes during influenza A virus infection.
Article in Frontiers in microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 10 citations in OpenAlex.
- MiCoDe: a web tool for performing microbiome community detection using a Bayesian weighted stochastic block model.Bioinformatics (Oxford, England) · 2025Article
- A Generalized Bayesian Stochastic Block Model for Microbiome Community Detection.Statistics in medicine · 2025Article
- Prenatal metal exposures and childhood gut microbial signatures are associated with depression score in late childhood.The Science of the total environment · 2024Article
- Temperature-dependent trophic associations modulate soil bacterial communities along latitudinal gradients.The ISME journal · 2024Article
- Time series cluster analysis reveals individual assignment of microbiota in captive tiger (Ecology and evolution · 2023Article
- Lower gut abundance ofFrontiers in cellular and infection microbiology · 2023Article
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Authors and funding
11 authors at 3 institutions in 1 country.
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Abstract
Influenza A Virus (IAV) infection followed by bacterial pneumonia often leads to hospitalization and death in individuals from high risk groups. Following infection, IAV triggers the process of viral RNA replication which in turn disrupts healthy gut microbial community, while the gut microbiota plays an instrumental role in protecting the host by evolving colonization resistance. Although the underlying mechanisms of IAV infection have been unraveled, the underlying complex mechanisms evolved by gut microbiota in order to induce host immune response following IAV infection remain evasive. In this work, we developed a novel Maximal-Clique based Community Detection algorithm for Weighted undirected Networks (MCCD-WN) and compared its performance with other existing algorithms using three sets of benchmark networks. Moreover, we applied our algorithm to gut microbiome data derived from fecal samples of both healthy and IAV-infected pigs over a sequence of time-points. The results we obtained from the real-life IAV dataset unveil the role of the microbial families
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