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Seminar: Network-based Analysis of Protein Mass Spectrometry Expression Data
Paul Price
Anastasia Gurinovich
Ph.D. Candidate
Supervisory Committee: Dr. Wolfgang Banzhaf, Dr. Lourdes Pena-Castillo and Dr. Andrew Lang Network-based Analysis of Protein Mass Spectrometry Expression Data Department of Computer Science Friday, August 24, 2012, 11:00 a.m., Room EN 2022

Abstract With the introduction and development of high-through put proteomics experimental techniques, in particular mass spectrometry, an increasing amount of protein expression data is available for analysis. Proteomics is often considered as the next level in understanding biological processes after genomics. One of the reasons is that protein expression levels are direct measures of cell machinery, unlike mRNAs which represent intermediate gene products that are subject to regulation and degradation. Abundance of computational and statistical methods for gene expression data analysis is available and can be partly employed for the protein expression data analysis. However, proteomics data is much more complex than genomics data, because of the nature of proteomes that undergo constant changes and variations. This proposal reviews the material necessary for conducting a network-based analysis of protein expression data. Networks (or graphs) are natural models to represent proteomics data with proteins being nodes and edges being the connections between them. Moreover, network-based approaches have been proven to be successful in the analysis of molecular biology data. In partial fulfilment of the requirements for the degree of Doctor of Philosophy.
Aug 17th, 2012

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