ArticlePeerJ2015
Identifying communities from multiplex biological networks.
Article in PeerJ, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
- Modeling roles and trade-offs in multiplex networks.Nature communications · 2026Article
- Multilayer network approaches to omics data integration in digital twins for cancer research.Frontiers in systems biology · 2026Review
- Quantifying the diverse contributions of hierarchical muscle interactions to motor function.iScience · 2025Article
- RWRtoolkit: multi-omic network analysis using random walks on multiplex networks in any species.GigaScience · 2025Article
- Lung Tissue Multilayer Network Analysis Uncovers the Molecular Heterogeneity of Chronic Obstructive Pulmonary Disease.American journal of respiratory and critical care medicine · 2024Article
- An integrative network-based approach to identify driving gene communities in chronic obstructive pulmonary disease.NPJ systems biology and applications · 2024Article
- Rare disease research workflow using multilayer networks elucidates the molecular determinants of severity in Congenital Myasthenic Syndromes.Nature communications · 2024Article
- Random walk with restart on multilayer networks: from node prioritisation to supervised link prediction and beyond.BMC bioinformatics · 2024Article
- scMLC: an accurate and robust multiplex community detection method for single-cell multi-omics data.Briefings in bioinformatics · 2024Article
- Article
- Gene communities in co-expression networks across different tissues.PLoS computational biology · 2023Article
- scPCOR-seq enables co-profiling of chromatin occupancy and RNAs in single cells.Communications biology · 2022Article
- Comparing protein-protein interaction networks of SARS-CoV-2 and (H1N1) influenza using topological features.Scientific reports · 2022Article
- Using dual-network-analyser for communities detecting in dual networks.BMC bioinformatics · 2022Article
- A multi-objective genetic algorithm to find active modules in multiplex biological networks.PLoS computational biology · 2021Article
- The multilayer community structure of medulloblastoma.iScience · 2021Article
- Modularity in Biological Networks.Frontiers in genetics · 2021Review
- Inferring Functional Epigenetic Modules by Integrative Analysis of Multiple Heterogeneous Networks.Frontiers in genetics · 2021Article
- Computational biology approaches for mapping transcriptional regulatory networks.Computational and structural biotechnology journal · 2021Review
- A propagation-based seed-centric local community detection for multilayer environment: The case study of colon adenocarcinoma.PloS one · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Various biological networks can be constructed, each featuring gene/protein relationships of different meanings (e.g., protein interactions or gene co-expression). However, this diversity is classically not considered and the different interaction categories are usually aggregated in a single network. The multiplex framework, where biological relationships are represented by different network layers reflecting the various nature of interactions, is expected to retain more information. Here we assessed aggregation, consensus and multiplex-modularity approaches to detect communities from multiple network sources. By simulating random networks, we demonstrated that the multiplex-modularity method outperforms the aggregation and consensus approaches when network layers are incomplete or heterogeneous in density. Application to a multiplex biological network containing 4 layers of physical or functional interactions allowed recovering communities more accurately annotated than their aggregated counterparts. Overall, taking into account the multiplexity of biological networks leads to better-defined functional modules. A user-friendly graphical software to detect communities from multiplex networks, and corresponding C source codes, are available at GitHub (https://github.com/gilles-didier/MolTi).
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.