Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/15961
Title: Algorithms for peptide and PTM identification using Tandem mass spectrometry
Authors: NING KANG
Keywords: Heurisitc Algorithm, Peptide identification, Post translational modifications, Tandem mass spectrometry, Multi-charge
Issue Date: 11-Jul-2008
Source: NING KANG (2008-07-11). Algorithms for peptide and PTM identification using Tandem mass spectrometry. ScholarBank@NUS Repository.
Abstract: This dissertation focuses on my work in the analysis of biological sequences, with special concentration on algorithms for peptide and PTM identification using tandem mass spectrometry. The main concern for algorithms in peptide identification is achieving fast and accurate peptide identification by mass spectrometry. The main results of this study is a set of database search and De Novo algorithms for peptide identification based on "extended spectrum graph" and machine learning techniques such as SOM. I have designed a set of heuristic algorithms for identification of peptide sequences from mass spectrometry, with focus on multi-charge spectrum. Then I have described peptide identification algorithms that are based on transformation of spectra to high dimensional vectors. Using the SOM and MPRQ technique, these algorithms then transformed the peptide sequence similarity to 2D point similarity on SOM map, and performed multiple simultaneous queries for candidate peptides efficiently.
URI: http://scholarbank.nus.edu.sg/handle/10635/15961
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