DocumentCode
3410583
Title
SRPVS: a new motif searching algorithm for protein analysis
Author
Huang, Xiaolu ; AIi, H. ; Sadanandam, Anguraj ; Singh, Rakesh
Author_Institution
Nebraska Univ., Omaha, NE, USA
fYear
2004
fDate
16-19 Aug. 2004
Firstpage
674
Lastpage
675
Abstract
In some protein sequence regions, when two sequences share similar amino acid composition, they also share the same biological structure regardless of the sequence order. Traditional protein analysis tools, since they are sequence order dependent, cannot detect such a sequence order relaxing similarity. In this study, a more flexible protein comparison algorithm, the similar enriched Parikh vector searching (SRPVS) algorithm is designed to detect sequence similarity in a local-sequence-order-flexible manner. In SRPVS, a peptide sequence is broken into a group of Parikh vectors of predefined word sizes, and then similar enriched Parikh vectors (SRPV) are searched between the two sequences and an order score is assigned to each pair of SRPV to reflect the order difference between the two sequences. A test has shown that SRPVS can detect shuffled protein sequence regions that share biological structure between two protein sequences.
Keywords
biology computing; molecular biophysics; proteins; search problems; SRPVS algorithm; amino acid composition; biological structure; motif searching algorithm; order score; peptide sequence; protein analysis; protein sequence regions; sequence order relaxing similarity; similar enriched Parikh vector searching algorithm; Algorithm design and analysis; Amino acids; Biology; Computer science; Data structures; Neoplasms; Pathology; Peptides; Protein sequence; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Systems Bioinformatics Conference, 2004. CSB 2004. Proceedings. 2004 IEEE
Print_ISBN
0-7695-2194-0
Type
conf
DOI
10.1109/CSB.2004.1332543
Filename
1332543
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