A Computational Strategy to Analyze Label-Free Temporal Bottom-Up Proteomics Data
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- 作者：Xiuxia Du ; Stephen J. Callister ; Nathan P. Manes ; Joshua N. Adkins ; Roxana A. Alexandridis ; Xiaohua Zeng ; Jung Hyeob Roh ; William E. Smith ; Timothy J. Donohue ; Samuel Kaplan ; Richard D. Smith ; Mary S.
- 刊名：Journal of Proteome Research
- 出版年：2008
- 出版时间：July 2008
- 年：2008
- 卷：7
- 期：7
- 页码：2595 - 2604
- 全文大小：3324K
- 年卷期：v.7,no.7(July 2008)
- ISSN：1535-3907
文摘
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.