Deep in the Bowel: Highly Interpretable Neural Encoder-Decoder Networks Predict Gut Metabolites from Gut Microbiome

Deep in the Bowel: Highly Interpretable Neural Encoder-Decoder Networks Predict Gut Metabolites from Gut Microbiome

Abstract Background Technological advances in next-generation sequencing (NGS) and chromatographic assays [e.g., liquid chromatography mass spectrometry (LC-MS)] have made it possible to identify thousands of microbe and metabolite species, and to measure their relative abundance. In this paper, we...

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Bibliographic Details
Main Authors: Vuong Le, Thomas P. Quinn, Truyen Tran, Svetha Venkatesh
Format: Article
Language:English
Published: BMC 2020-07-01
Series:BMC Genomics
Subjects:
Metabolomics
Multi-omics
Machine learning
Deep learning
Interpretability
Online Access:http://link.springer.com/article/10.1186/s12864-020-6652-7

Internet

http://link.springer.com/article/10.1186/s12864-020-6652-7

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