msBayesImpute: A Versatile Framework for Addressing Missing Values in Biomedical Mass Spectrometry Proteomics Data
Jiaojiao He, Barbara Helm, Franziska Gödtel, Katharina Buchner, Marcel Schilling, Marc Andre Schneider, Laura Valentina Klotz, Jana M. Braunger, Hauke Winter, Britta Velten, Ursula Klingmüller, Junyan Lu
msBayesImpute improves missing value handling in proteomics data by integrating Bayesian factorization and probabilistic dropout models, outperforming existing methods in imputation and normalization.
Communications Chemistry · Jul 7, 2026Peer-reviewedBioinformatics