iLoops: a protein-protein interaction prediction server based on structural features

被引：29

作者：

Planas-Iglesias, Joan ^{[1
]}

Marin-Lopez, Manuel A. ^{[1
]}

Bonet, Jaume ^{[1
]}

Garcia-Garcia, Javier ^{[1
]}

Oliva, Baldo ^{[1
]}

机构：

[1] Univ Pompeu Fabra, Struct Bioinformat Lab, Barcelona 08003, Spain

来源：

BIOINFORMATICS | 2013年 / 29卷 / 18期

关键词：

DATABASE; NETWORKS; PAIRS;

D O I：

10.1093/bioinformatics/btt401

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

Protein-protein interactions play a critical role in many biological processes. Despite that, the number of servers that provide an easy and comprehensive method to predict them is still limited. Here, we present iLoops, a web server that predicts whether a pair of proteins can interact using local structural features. The inputs of the server are as follows: (i) the sequences of the query proteins and (ii) the pairs to be tested. Structural features are assigned to the query proteins by sequence similarity. Pairs of structural features (formed by loops or domains) are classified according to their likelihood to favor or disfavor a protein-protein interaction, depending on their observation in known interacting and non-interacting pairs. The server evaluates the putative interaction using a random forest classifier.

引用

页码：2360 / 2362

页数：3

共 19 条

[1] InterPreTS: protein Interaction Prediction through Tertiary Structure [J].

Aloy, P ;

Russell, RB .

BIOINFORMATICS, 2003, 19 (01) :161-162

[2] Gapped BLAST and PSI-BLAST: a new generation of protein database search programs [J].

Altschul, SF ;

Madden, TL ;

Schaffer, AA ;

Zhang, JH ;

Zhang, Z ;

Miller, W ;

Lipman, DJ .

NUCLEIC ACIDS RESEARCH, 1997, 25 (17) :3389-3402

[3] Data growth and its impact on the SCOP database: new developments [J].

Andreeva, Antonina ;

Howorth, Dave ;

Chandonia, John-Marc ;

Brenner, Steven E. ;

Hubbard, Tim J. P. ;

Chothia, Cyrus ;

Murzin, Alexey G. .

NUCLEIC ACIDS RESEARCH, 2008, 36 :D419-D425

[4] Choosing negative examples for the prediction of protein-protein interactions [J].

Ben-Hur, A ;

Noble, WS .

BMC BIOINFORMATICS, 2006, 7 (Suppl 1)

[5]

Braun P, 2009, NAT METHODS, V6, P91, DOI [10.1038/NMETH.1281, 10.1038/nmeth.1281]

[6] ArchDB: automated protein loop classification as a tool for structural genomics [J].

Espadaler, J ;

Fernandez-Fuentes, N ;

Hermoso, A ;

Querol, E ;

Aviles, FX ;

Sternberg, MJE ;

Oliva, B .

NUCLEIC ACIDS RESEARCH, 2004, 32 :D185-D188

[7] Biana: a software framework for compiling biological interactions and analyzing networks [J].

Garcia-Garcia, Javier ;

Guney, Emre ;

Aragues, Ramon ;

Planas-Iglesias, Joan ;

Oliva, Baldo .

BMC BIOINFORMATICS, 2010, 11

[8]

Hall M., 2009, SIGKDD Explorations, V11, P10, DOI DOI 10.1145/1656274.1656278

[9] A Bayesian networks approach for predicting protein-protein interactions from genomic data [J].

Jansen, R ;

Yu, HY ;

Greenbaum, D ;

Kluger, Y ;

Krogan, NJ ;

Chung, SB ;

Emili, A ;

Snyder, M ;

Greenblatt, JF ;

Gerstein, M .

SCIENCE, 2003, 302 (5644) :449-453

[10] Predictome: a database of putative functional links between proteins [J].

Mellor, JC ;

Yanai, I ;

Clodfelter, KH ;

Mintseris, J ;

DeLisi, C .

NUCLEIC ACIDS RESEARCH, 2002, 30 (01) :306-309

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