Integrated data modeling in high-throughput proteomics
by Jin, Shuangshuang, Ph.D., WASHINGTON STATE UNIVERSITY, 2007, 129 pages; 3301984

Abstract:

The purpose of this research project is to investigate the work flow in high-throughput quantitative proteomics. After data collection on complex protein mixtures subjected to proteolysis, liquid chromatography (LC) and mass spectrometry (MS), a long data reduction procedure beings that involves protein identification, protein abundance estimation, biological interpretation of differentially abundant proteins. The data reduction procedure contains many steps that are the subject of ongoing research in bioinformatics. This thesis research addresses the following issues: (1) protein database redundancy, (2) peptides from proteolysis that are found in more than one database entry, (3) separation of biological effects on protein abundance from variance due to instrument and processing effects, (4) data mining to relate observed global changes in an organisms proteome to biological processes perturbed by treatments.

 
AdviserJohn H. Miller
SchoolWASHINGTON STATE UNIVERSITY
SourceDAI/B 69-02, p. , May 2008
Source TypeDissertation
SubjectsComputer science
Publication Number3301984
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