Network Analysis in Microbiome Research: Methods, Tools, and Applications.

Jiajun Liu, Yixue Li, Tao Huang

Journal: Methods in molecular biology (Clifton, N.J.) 2026;3033():105-115

PMID: 42108293

Abstract

The human microbiome operates as a complex, interconnected ecosystem where microbial interactions dictate community stability, host health, and disease progression. Understanding these dynamics requires moving beyond simple taxonomic catalogs to systems-level network analyses. This chapter reviews network methodologies in microbiome research, progressing from traditional correlation-based approaches to advanced artificial intelligence techniques. We systematically cover co-occurrence, protein-protein interaction, metabolic, multi-omics integrated, and evolutionary transmission networks. Computational tools-spanning general platforms and specialized pipelines-are compared alongside topology metrics and community detection algorithms. Furthermore, we highlight the integration of graph neural networks and protein language models, discussing current challenges in data standardization, model interpretability, and the merging of mechanistic and data-driven paradigms.

Address: Department of Artificial Intelligence and Digital Health, CAS Engineering Laboratory for Nutrition, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.; Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.; Department of Artificial Intelligence and Digital Health, CAS Engineering Laboratory for Nutrition, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China. [email protected].; Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China. [email protected].; Guangzhou National Laboratory, Guangzhou, China. [email protected].; GMU-GIBH Joint School of Life Sciences, The Guangdong-Hong Kong-Macau Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou Laboratory, Guangzhou Medical University, Guangzhou, China. [email protected].; Key Laboratory of Systems Health Science of Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, China. [email protected].; Department of Artificial Intelligence and Digital Health, CAS Engineering Laboratory for Nutrition, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China. [email protected].; Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China. [email protected].

DOI: 10.1007/978-1-0716-5264-0_6

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MeSH Terms: Humans, Microbiota, Computational Biology, Algorithms