Benchmark study of feature selection strategies for multi-omics data.

Yingxia Li Ulrich Robert Mansmann Shangming Du Roman Hornung

Published in: BMC bioinformatics (2022)

We recommend the permutation importance of random forests and the filter method mRMR for feature selection using multi-omics data, where, however, mRMR is considerably more computationally costly.

Keyphrases

machine learning
electronic health record
big data
single cell
deep learning
climate change
data analysis