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In silico two‐hybrid system for the selection of physically interacting protein pairs
Author(s) -
Pazos Florencio,
Valencia Alfonso
Publication year - 2002
Publication title -
proteins: structure, function, and bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.699
H-Index - 191
eISSN - 1097-0134
pISSN - 0887-3585
DOI - 10.1002/prot.10074
Subject(s) - in silico , computer science , sequence (biology) , selection (genetic algorithm) , computational biology , basis (linear algebra) , simple (philosophy) , artificial intelligence , protein–protein interaction , interaction network , machine learning , data mining , theoretical computer science , biology , genetics , mathematics , gene , philosophy , geometry , epistemology
Deciphering the interaction links between proteins has become one of the main tasks of experimental and bioinformatic methodologies. Reconstruction of complex networks of interactions in simple cellular systems by integrating predicted interaction networks with available experimental data is becoming one of the most demanding needs in the postgenomic era. On the basis of the study of correlated mutations in multiple sequence alignments, we propose a new method (in silico two‐hybrid, i2h) that directly addresses the detection of physically interacting protein pairs and identifies the most likely sequence regions involved in the interactions. We have applied the system to several test sets, showing that it can discriminate between true and false interactions in a significant number of cases. We have also analyzed a large collection of E. coli protein pairs as a first step toward the virtual reconstruction of its complete interaction network. Proteins 2002;47:219–227. © 2002 Wiley‐Liss, Inc.