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

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

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...

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書目詳細資料
Main Authors:	Peng, Hui, Wang, He, Kong, Weijia, Li, Jinyan, Goh, Wilson Wen Bin
其他作者:	Lee Kong Chian School of Medicine (LKCMedicine)
格式:	Article
語言:	English
出版:	2024
主題:	Medicine, Health and Life Sciences Proteomics Ensemble inference
在線閱讀:	https://hdl.handle.net/10356/178809
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!
機構:	Nanyang Technological University
語言:	English

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