Protein domain recurrence and order can enhance prediction of protein functions.

Citation data:

Bioinformatics (Oxford, England), ISSN: 1367-4811, Vol: 28, Issue: 18, Page: i444-i450

Publication Year:
2012
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Citations 18
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Repository URL:
http://hdl.handle.net/10754/325434
PMID:
22962465
DOI:
10.1093/bioinformatics/bts398
PMCID:
PMC3436825; 3436825
Author(s):
Abdel Messih, Mario A.; Chitale, Meghana; Bajic, Vladimir B.; Kihara, Daisuke; Gao, Xin
Publisher(s):
Oxford University Press (OUP); Oxford University Press
Tags:
Biochemistry, Genetics and Molecular Biology; Computer Science; Mathematics; Medicine; protein; Bayes theorem; physiology; protein tertiary structure; sequence analysis; statistical model; Bayes Theorem; Models, Statistical; Protein Structure, Tertiary; Proteins; Sequence Analysis, Protein
article description
Burgeoning sequencing technologies have generated massive amounts of genomic and proteomic data. Annotating the functions of proteins identified in this data has become a big and crucial problem. Various computational methods have been developed to infer the protein functions based on either the sequences or domains of proteins. The existing methods, however, ignore the recurrence and the order of the protein domains in this function inference.