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|Title:||De novo peptide sequencing for mass spectra based on multi-charge strong tags|
|Citation:||Ning, K.,Chong, K.F.,Leong, H.W. (2007). De novo peptide sequencing for mass spectra based on multi-charge strong tags. Series on Advances in Bioinformatics and Computational Biology 5 : 287-296. ScholarBank@NUS Repository.|
|Abstract:||This paper presents an improved algorithm for de novo sequencing of multi-charge mass spectra. Recent work based on the analysis of multi-charge mass spectra showed that taking advantage of multi-charge information can lead to higher accuracy (sensitivity and specificity) in peptide sequencing. A simple de novo algorithm, called GBST (Greedy algorithm with Best Strong Tag) was proposed and was shown to produce good results for spectra with charge > 2. In this paper, we analyze some of the shortcomings of GBST. We then present a new algorithm GST-SPC, by extending the GBST algorithm in two directions. First, we use a larger set of multi-charge strong tags and show that this improves the theoretical upper bound on performance. Second, we give an algorithm that computes a peptide sequence that is optimal with respect to shared peaks count from among all sequences that are derived from multi-charge strong tags. Experimental results demonstrate the improvement of GST-SPC over GBST.|
|Source Title:||Series on Advances in Bioinformatics and Computational Biology|
|Appears in Collections:||Staff Publications|
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