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
Link To Document :
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