[Gene coexpression networks: concepts and applications].

Q4 Biochemistry, Genetics and Molecular Biology
Biologie Aujourd''hui Pub Date : 2024-01-01 Epub Date: 2025-01-27 DOI:10.1051/jbio/2024009
Charles Durand, Pierre Charbord
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引用次数: 0

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.

基因共表达网络:概念和应用。
高通量组学数据的出现和新算法的产生为生物学家提供了在系统生物学背景下探索生命过程的机会,旨在揭示基因相互作用,复杂细胞功能背后的网络。在本文中,我们讨论了两种基因网络重建方法,即Steve Horvath及其合作者于2008年开发的WGCNA(加权基因相关网络分析)和herv Isambert及其团队于2017年和2024年开发的MIIC(多元信息归纳因果关系)。这两种方法是互补的,WGCNA产生无向网络,其中大多数基因与基因之间的相互作用是间接的,而MIIC揭示了直接的相互作用和一些因果关系。我们根据自己的工作来说明这些方面,旨在确定造血干细胞在早期发育阶段间充质基质细胞支持活性的基因相互作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Biologie Aujourd''hui
Biologie Aujourd''hui Biochemistry, Genetics and Molecular Biology-Biochemistry, Genetics and Molecular Biology (all)
CiteScore
0.30
自引率
0.00%
发文量
9
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