Dissertation
Integrated data modeling in high-throughput proteomices
Washington State University
Doctor of Philosophy (PhD), Washington State University
12/2007
DOI:
https://doi.org/10.7273/000005770
Abstract
The purpose of this research project is to investigate the work flow in highthroughput
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.
Metrics
Details
- Title
- Integrated data modeling in high-throughput proteomices
- Creators
- Shuangshuang Jin
- Contributors
- John H Miller (Chair) - Washington State University, School of Engineering and Applied Sciences (TRIC)Donald J. Lynch (Committee Member)ROBERT R LEWIS (Committee Member)
- Awarding Institution
- Washington State University
- Academic Unit
- School of Electrical Engineering and Computer Science
- Theses and Dissertations
- Doctor of Philosophy (PhD), Washington State University
- Publisher
- Washington State University
- Number of pages
- 129
- Identifiers
- 99901054762901842
- Language
- English
- Resource Type
- Dissertation