A Computational Strategy to Analyze Label-Free Temporal Bottom-Up Proteomics Data

@article{citeulike:2735812, abstract = {Abstract: 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.}, address = {Fundamental and Computational Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, Department of Bacteriology, University of WisconsinMadison, Madison, Wisconsin 53706, and Department of Microbiology \& Molecular Genetics, Medical School, University of TexasHouston, Houston, Texas 77225}, author = {Du, Xiuxia and Callister, Stephen J. and Manes, Nathan P. and Adkins, Joshua N. and Alexandridis, Roxana A. and Zeng, Xiaohua and Roh, Jung H. and Smith, William E. and Donohue, Timothy J. and Kaplan, Samuel and Smith, Richard D. and Lipton, Mary S. }, citeulike-article-id = {2735812}, doi = {10.1021/pr0704837}, journal = {J. Proteome Res.}, month = {April}, posted-at = {2008-05-15 10:27:49}, priority = {2}, title = {A Computational Strategy to Analyze Label-Free Temporal Bottom-Up Proteomics Data}, url = {http://dx.doi.org/10.1021/pr0704837}, year = {2008} }

TY - JOUR ID - citeulike:2735812 L3 - citeulike-article-id:2735812 TI - A Computational Strategy to Analyze Label-Free Temporal Bottom-Up Proteomics Data JF - J. Proteome Res. AD - Fundamental and Computational Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, Department of Bacteriology, University of WisconsinMadison, Madison, Wisconsin 53706, and Department of Microbiology & Molecular Genetics, Medical School, University of TexasHouston, Houston, Texas 77225 N2 - Abstract: 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. AU - Du, Xiuxia AU - Callister, Stephen AU - Manes, Nathan AU - Adkins, Joshua AU - Alexandridis, Roxana AU - Zeng, Xiaohua AU - Roh, Jung AU - Smith, William AU - Donohue, Timothy AU - Kaplan, Samuel AU - Smith, Richard AU - Lipton, Mary PY - 2008/04/29/ UR - http://dx.doi.org/10.1021/pr0704837 ER -