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2016 | OriginalPaper | Chapter

Microbiome Data Mining for Microbial Interactions and Relationships

Authors : Xingpeng Jiang, Xiaohua Hu

Published in: Big Data Analytics

Publisher: Springer India

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Abstract

The study of how microbial species coexist and interact in a host-associated environment or a natural environment is crucial to advance basic microbiology science and the understanding of human health and diseases. Researchers have started to infer common interspecies interactions and species–phenotype relations such as competitive and cooperative interactions leveraging to big microbiome data. These endeavors have facilitated the discovery of previously unknown principles of microbial world and expedited the understanding of the disease mechanism. In this review, we will summarize current computational efforts in microbiome data mining for discovering microbial interactions and relationships including dimension reduction and data visualization, association analysis, microbial network reconstruction, as well as dynamic modeling and simulations.

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Title: Microbiome Data Mining for Microbial Interactions and Relationships
Authors: Xingpeng Jiang
Xiaohua Hu
Publisher: Springer India
Book: Big Data Analytics
Print ISBN: 978-81-322-3626-9

Electronic ISBN: 978-81-322-3628-3

Copyright Year: 2016
DOI: https://doi.org/10.1007/978-81-322-3628-3_12

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Abstract

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