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      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.
| Package details | |
|---|---|
| Author | Junfang Chen and Emanuel Schwarz | 
| Bioconductor views | Classification GO Genetics Pathways Regression Software | 
| Maintainer | Junfang Chen <junfang.chen33@gmail.com> | 
| License | GPL-3 | 
| Version | 1.6.0 | 
| Package repository | View on Bioconductor | 
| Installation | Install the latest version of this package by entering the following in R:  | 
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