transbioZI/BioMMex: BioMM: Biological-informed Multi-stage Machine learning framework for phenotype prediction using omics data

The identification of reproducible biological patterns from high-dimensional omics data is a key factor in understanding the biology of complex disease or traits. Incorporating prior biological knowledge into machine learning is an important step in advancing such research. We have proposed a biologically informed multi-stage machine learing framework termed BioMM specifically for phenotype prediction based on omics-scale data where we can evaluate different machine learning models with prior biological meta information.

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Package details

AuthorJunfang Chen and Emanuel Schwarz
Bioconductor views Classification GO Genetics Pathways Regression Software
MaintainerJunfang Chen <>
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
transbioZI/BioMMex documentation built on Jan. 27, 2023, 4:14 a.m.