期刊
JOURNAL OF PROTEOME RESEARCH
卷 7, 期 7, 页码 2595-2604出版社
AMER CHEMICAL SOC
DOI: 10.1021/pr0704837
关键词
protein abundance dynamics; bottom-up proteomics; normalization; missing-value imputation; significance analysis
资金
- NIAID NIH HHS [Y1-AI-4894-01] Funding Source: Medline
- NIGMS NIH HHS [R01 GM015590, R01 GM075273-02, GM075273, R01 GM075273, GM15590] Funding Source: Medline
Biological systems are in a continual state of flux, which necessitates an understanding of the dynamic nature of protein abundances. The study of protein abundance dynamics has become feasible with recent improvements in mass spectrometry-based quantitative proteomics. However, a number of challenges still remain related to how best to extract biological information from dynamic proteomics data, for example, challenges related to extraneous variability, missing abundance values, and the identification of significant temporal patterns. This paper describes a strategy that addresses these issues and demonstrates its values for analyzing temporal bottom-up proteomics data using data from a Rhodobacter sphaeroides 2.4.1 time-course study.
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