Prediction of contact matrix for protein–protein interaction
Author(s) -
Álvaro González,
Li Liao,
Cathy Wu
Publication year - 2013
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/btt076
Subject(s) - domain (mathematical analysis) , sequence (biology) , feature vector , position (finance) , markov chain , computer science , matrix (chemical analysis) , support vector machine , dimension (graph theory) , protein–protein interaction , hidden markov model , artificial intelligence , computational biology , pattern recognition (psychology) , algorithm , mathematics , machine learning , biology , chemistry , combinatorics , genetics , mathematical analysis , finance , chromatography , economics
Prediction of protein-protein interaction has become an important part of systems biology in reverse engineering the biological networks for better understanding the molecular biology of the cell. Although significant progress has been made in terms of prediction accuracy, most computational methods only predict whether two proteins interact but not their interacting residues-the information that can be very valuable for understanding the interaction mechanisms and designing modulation of the interaction. In this work, we developed a computational method to predict the interacting residue pairs-contact matrix for interacting protein domains, whose rows and columns correspond to the residues in the two interacting domains respectively and whose values (1 or 0) indicate whether the corresponding residues (do or do not) interact.
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