Title
Rapid and accurate generation of peptide sequence tags with a graph search approach
Abstract
Protein peptide identification from a tandem mass spectrum (MS/MS) is a challenging task. Previous approaches for peptide identification with database search are time consuming due to huge search space. De novo sequencing approaches which derive a peptide sequence directly from a MS/MS spectrum usually are of high complexities and the accuracies of the approaches highly depend on the quality of the spectra. In this paper, we developed an accurate and efficient algorithm for peptide identification. Our work consisted of the following steps. Firstly, we found a pair of complementary mass peaks that are b-ion and y-ion, respectively. We then used the two mass peaks as two tree nodes and extend the trees such that in the end the nodes of the trees are elements of a b-ion set and a yion set, respectively. Secondly, we applied breadth first search to the trees to generate peptide sequence tags. Finally, we designed a weight function to evaluate the reliabilities of the tags and rank the tags. Our experiment on 2620 experimental MS/MS spectra with one PTM showed that our algorithm achieved better accuracy than other approaches with higher efficiency.
Year
DOI
Venue
2011
10.1007/978-3-642-21260-4_25
ISBRA
Keywords
Field
DocType
complementary mass peak,ms spectrum,graph search approach,peptide identification,protein peptide identification,database search,experimental ms,accurate generation,mass peak,huge search space,peptide sequence tag,peptide sequence,post translational modification,weight function,search space,spectrum,breadth first search
Tandem,Graph,Weight function,Computer science,Database search engine,Breadth-first search,Peptide,Mass spectrum,Bioinformatics,Peptide sequence
Conference
Volume
ISSN
Citations 
6674
0302-9743
0
PageRank 
References 
Authors
0.34
6
6
Name
Order
Citations
PageRank
Hui Li135.46
Lauren Scott2121.14
Chun-Mei Liu324541.30
Mugizi Rwebangira451.51
Legand Burge5299.60
William Southerland6156.23