Data Analysis for Gut Microbiota and Health

• Published in: Advances in experimental medicine and biology Vol. 1028; pp. 79 - 87
• Main Authors: Jiang, Xingpeng, Hu, Xiaohua
• Format: Book Chapter Journal Article
• Language: English
• Published: Singapore Springer Singapore 01.01.2017
• Series: Advances in Experimental Medicine and Biology
• Subjects: Data analysis; Data Mining; Diseases; Gastrointestinal Microbiome; Health; Humans; Microbes; Microbiome; Microbiota; Statistics as Topic; Data analysis; Microbiota; Data mining; Microbes; Diseases; Microbiome
• ISBN: 9789811060403; 9811060401
• ISSN: 0065-2598; 2214-8019
• DOI: 10.1007/978-981-10-6041-0_5

In recent years, data mining and analysis of high-throughput sequencing of microbiomes and metagenomic data enable researchers to discover biological knowledge by characterizing the composition and variation of species across environmental samples and to accumulate a huge amount of data, making it feasible to infer the complex principle of species interactions. The interactions of microbes in a microbial community play an important role in microbial ecological system. Data mining provides diverse approachs to identify the correlations between disease and microbes and how microbial species coexist and interact in a host-associated or natural environment. This is not only important to advance basic microbiology science and other related fields but also important to understand the impacts of microbial communities on human health and diseases.