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Data Analysis for Gut Microbiota and Health

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Healthcare and Big Data Management

Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 1028))

Abstract

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.

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Authors and Affiliations

  1. School of Computer, Central China Normal University, Wuhan, Hubei, 430079, China

    Xingpeng Jiang & Xiaohua Hu

  2. College of Computing & Informatics, Drexel University, Philadelphia, PA, 19104, USA

    Xiaohua Hu

Authors
  1. Xingpeng Jiang
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  2. Xiaohua Hu
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Correspondence to Xingpeng Jiang .

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Editors and Affiliations

  1. Center for Systems Biology, Soochow University, Suzhou, Jiangsu, China

    Bairong Shen

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© 2017 Springer Nature Singapore Pte Ltd.

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Jiang, X., Hu, X. (2017). Data Analysis for Gut Microbiota and Health. In: Shen, B. (eds) Healthcare and Big Data Management. Advances in Experimental Medicine and Biology, vol 1028. Springer, Singapore. https://doi.org/10.1007/978-981-10-6041-0_5

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