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Updated: May 30, 2025

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
Published on: October 19, 2021
[Gene coexpression networks: concepts and applications]
Charles Durand1, Pierre Charbord1
1Sorbonne Université, CNRS, Inserm U1156, Institut de Biologie Paris Seine, Laboratoire de Biologie du Développement/UMR7622, 9 Quai St-Bernard, 75005 Paris, France.
Abstract:
The advent of high-throughput omics data and the generation of new algorithms provide the biologists with the opportunity to explore living processes in the context of systems biology aiming at revealing the gene interactions, the networks underlying complex cellular functions. In this article, we discuss two methods for gene network reconstruction, WGCNA (Weighted Gene Correlation Network Analysis) developed by Steve Horvath and collaborators in 2008, and MIIC (Multivariate Information-based Inductive Causation) developed by Hervé Isambert and his team in 2017 and 2024. These two methods are complementary, WGCNA generating undirected networks in which most gene-to-gene interactions are indirect, while MIIC reveals direct interactions and some causal links. We illustrate these aspects according to our own work aiming at identifying the gene interactions underlying the hematopoietic stem cell supportive activity of mesenchymal stromal cells at an early developmental stage.
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