Identification of microbial interaction network: zero-inflated latent Ising model based approach
Abstract Background Throughout their lifespans, humans continually interact with the microbial world, including those organisms which live in and on the human body. Research in this domain has revealed the extensive links between the human-associated microbiota and health. In particular, the microbi...
Main Authors: | , , , , , , , |
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Format: | Article |
Language: | English |
Published: |
BMC
2020-10-01
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Series: | BioData Mining |
Subjects: | |
Online Access: | http://link.springer.com/article/10.1186/s13040-020-00226-7 |