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Activity Number:
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657
- Bayesian and Empirical Bayes
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Type:
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Contributed
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Date/Time:
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Thursday, August 1, 2019 : 10:30 AM to 12:20 PM
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Sponsor:
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IMS
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Abstract #306547
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Presentation
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Title:
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Information Content of High-Order Associations of the Human Gut Microbiota Network
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Author(s):
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Weston Viles* and Juliette C. Madan and Hongzhe Li and Jason H Moore and Margaret R. Karagas and Anne G. Hoen
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Companies:
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University of Southern Maine and The Geisel School of Medicine at Dartmouth and University of Pennsylvania and University of Pennsylvania and The Geisel School of Medicine at Dartmouth and The Geisel School of Medicine at Dartmouth
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Keywords:
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Networks;
Learning;
Information;
Microbiome;
Ecosystem
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Abstract:
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Microbiomics research is the study of relationships between the microbial communities of the microbiota and the physiology of its human host. This relationship is fundamentally linked to the state the host's microbiota ecosystem and properties of its components. We define a procedure for estimating ecologically-associated subsets of its constituents' microbial sequence data. Our optimization procedure applied to the a class of maximum entropy models produces interpretable estimates for the relative change in predictability of microbial states as a function of local interaction complexity.
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Authors who are presenting talks have a * after their name.
