Optimizing differential expression analysis for proteomics data via high-performing rules and ensemble inference

• المؤلفون الرئيسيون: Peng, Hui, Wang, He, Kong, Weijia, Li, Jinyan, Goh, Wilson Wen Bin
• مؤلفون آخرون: Lee Kong Chian School of Medicine (LKCMedicine)
• التنسيق: مقال
• اللغة: English
• منشور في: 2024
• الموضوعات: Medicine, Health and Life Sciences; Proteomics; Ensemble inference
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/178809

Identification of differentially expressed proteins in a proteomics workflow typically encompasses five key steps: raw data quantification, expression matrix construction, matrix normalization, missing value imputation (MVI), and differential expression analysis. The plethora of options in each step...