BioinformaticsbioRxivPreprint
Quality control-based signal drift correction and interpretations of metabolomics/proteomics data using random forest regression
Hemi Luan, Fenfen Ji, Yu Chen, Zongwei Cai
The paper develops a quality control-based random forest regression method to correct signal drift in metabolomics and proteomics data, improving precision and statistical accuracy.
6 citations