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 | 1.5.9 |
Package repository | View on GitHub |
Installation |
Install the latest version of this package by entering the following in R:
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.