nec-research/microbiome-mvib
Microbiome-based disease prediction with multimodal variational information bottlenecks, Grazioli et al., PLOS Computational Biology 2022
This project helps medical researchers and computational biologists predict diseases using microbiome data. It takes strain-level marker profiles and species-relative abundance profiles as input. The output is a disease prediction, which can help in understanding disease mechanisms or developing diagnostic tools.
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Use this if you are a medical researcher or computational biologist working with microbiome data and need to predict disease states or understand the microbial features associated with them.
Not ideal if you do not have both strain-level marker and species-relative abundance profiles, or if your primary goal is not disease prediction from microbiome data.
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Language
Python
License
MIT
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Last pushed
Apr 12, 2022
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