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Book chapter
Microbiome Data Mining for Microbial Interactions and Relationships
Big Data Analytics, pp 221-235
13 Oct 2016
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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2 citations in Scopus
Details
- Title
- Microbiome Data Mining for Microbial Interactions and Relationships
- Creators
- Xingpeng Jiang - Central China Normal UniversityXiaohua Hu - Central China Normal University
- Publication Details
- Big Data Analytics, pp 221-235
- Publisher
- Springer India; New Delhi
- Resource Type
- Book chapter
- Language
- English
- Academic Unit
- Information Science; Obstetrics and Gynecology
- Scopus ID
- 2-s2.0-85018606236
- Other Identifier
- 991019173562204721