dc.contributor.advisor | MacCoss, Michael J | en_US |
dc.contributor.author | Finney, Gregory L. | en_US |
dc.date.accessioned | 2012-08-10T20:25:50Z | |
dc.date.available | 2012-08-10T20:25:50Z | |
dc.date.issued | 2012-08-10 | |
dc.date.submitted | 2012 | en_US |
dc.identifier.other | Finney_washington_0250E_10114.pdf | en_US |
dc.identifier.uri | http://hdl.handle.net/1773/20263 | |
dc.description | Thesis (Ph.D.)--University of Washington, 2012 | en_US |
dc.description.abstract | The comparative measurement of protein abundance is a powerful method to detect changes in the biological dynamics of cells and tissues. Shotgun proteomics has proven to be a method where a wide range of proteins can be characterized in a single experiment by analysis of their peptide digests using micro-capillary liquid chromatography coupled to mass spectrometry (μLC-MS). We have the CRAWDAD software tool for label-free relative quantitation between samples using peptide signals in μLC-MS data associated with their identifications from MS/MS data. CRAWDAD discovers features for quantification in μLC-MS data, lowers chromatographic and signal variance across replicates, and finds statistically significant changes in peptide abundance between samples. We have applied this tool toward model systems of induced expression of the <italic>Lac</italic> operator in <italic>E. coli</italic> to qualitatively assess the protein changes detected. A controlled set of changes using an <italic>E. coli</italic> protein digest spiked in at changing levels over a constant background of human proteins assesses the precision and accuracy of the detected changes in peptide and protein levels, and showed our results to be superior to label-free quantitation using spectral counting. | en_US |
dc.format.mimetype | application/pdf | en_US |
dc.language.iso | en_US | en_US |
dc.rights | Copyright is held by the individual authors. | en_US |
dc.subject | Bioinformatics; Genomics; Label-Free; Mass Spectrometry; Proteomics; Retention Time Alignment | en_US |
dc.subject.other | Bioinformatics | en_US |
dc.subject.other | Biochemistry | en_US |
dc.subject.other | Analytical chemistry | en_US |
dc.subject.other | Genetics | en_US |
dc.title | Tools and Analyses for Differential Label-Free Proteomics Using Mass Spectrometry | en_US |
dc.type | Thesis | en_US |
dc.embargo.terms | No embargo | en_US |