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Whole-proteome prediction of protein function via graph-theoretic analysis of interaction maps
Author(s) -
Elebieva,
Kam Jim,
Amit Agarwal,
Bernard Chazelle,
Mona Singh
Publication year - 2005
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/bti1054
Subject(s) - proteome , graph , computational biology , function (biology) , computer science , protein function prediction , protein function , theoretical computer science , chemistry , bioinformatics , biology , biochemistry , microbiology and biotechnology , gene
Determining protein function is one of the most important problems in the post-genomic era. For the typical proteome, there are no functional annotations for one-third or more of its proteins. Recent high-throughput experiments have determined proteome-scale protein physical interaction maps for several organisms. These physical interactions are complemented by an abundance of data about other types of functional relationships between proteins, including genetic interactions, knowledge about co-expression and shared evolutionary history. Taken together, these pairwise linkages can be used to build whole-proteome protein interaction maps.

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