Literature DB >> 11861907

Interaction generality, a measurement to assess the reliability of a protein-protein interaction.

Rintaro Saito1, Harukazu Suzuki, Yoshihide Hayashizaki.   

Abstract

Here we introduce the 'interaction generality' measure, a new method for computationally assessing the reliability of protein-protein interactions obtained in biological experiments. This measure is basically the number of proteins involved in a given interaction and also adopts the idea that interactions observed in a complicated interaction network are likely to be true positives. Using a group of yeast protein-protein interactions identified in various biological experiments, we show that interactions with low generalities are more likely to be reproducible in other independent assays. We constructed more reliable networks by eliminating interactions whose generalities were above a particular threshold. The rate of interactions with common cellular roles increased from 63% in the unadjusted estimates to 79% in the refined networks. As a result, the rate of cross-talk between proteins with different cellular roles decreased, enabling very clear predictions of the functions of some unknown proteins. The results suggest that the interaction generality measure will make interaction data more useful in all organisms and may yield insights into the biological roles of the proteins studied.

Entities:  

Mesh:

Substances:

Year:  2002        PMID: 11861907      PMCID: PMC101243          DOI: 10.1093/nar/30.5.1163

Source DB:  PubMed          Journal:  Nucleic Acids Res        ISSN: 0305-1048            Impact factor:   16.971


  33 in total

1.  Assessment of prediction accuracy of protein function from protein--protein interaction data.

Authors:  H Hishigaki; K Nakai; T Ono; A Tanigami; T Takagi
Journal:  Yeast       Date:  2001-04       Impact factor: 3.239

2.  The large-scale organization of metabolic networks.

Authors:  H Jeong; B Tombor; R Albert; Z N Oltvai; A L Barabási
Journal:  Nature       Date:  2000-10-05       Impact factor: 49.962

3.  A Java applet for visualizing protein-protein interaction.

Authors:  R Mrowka
Journal:  Bioinformatics       Date:  2001-07       Impact factor: 6.937

4.  Two-hybrid system and false positives. Approaches to detection and elimination.

Authors:  I G Serebriiskii; E A Golemis
Journal:  Methods Mol Biol       Date:  2001

5.  Protein-protein interaction panel using mouse full-length cDNAs.

Authors:  H Suzuki; Y Fukunishi; I Kagawa; R Saito; H Oda; T Endo; S Kondo; H Bono; Y Okazaki; Y Hayashizaki
Journal:  Genome Res       Date:  2001-10       Impact factor: 9.043

6.  Integrated genomic and proteomic analyses of a systematically perturbed metabolic network.

Authors:  T Ideker; V Thorsson; J A Ranish; R Christmas; J Buhler; J K Eng; R Bumgarner; D R Goodlett; R Aebersold; L Hood
Journal:  Science       Date:  2001-05-04       Impact factor: 47.728

Review 7.  Protein--protein interaction maps: a lead towards cellular functions.

Authors:  P Legrain; J Wojcik; J M Gauthier
Journal:  Trends Genet       Date:  2001-06       Impact factor: 11.639

8.  Predicting protein--protein interactions from primary structure.

Authors:  J R Bock; D A Gough
Journal:  Bioinformatics       Date:  2001-05       Impact factor: 6.937

9.  A relationship between gene expression and protein interactions on the proteome scale: analysis of the bacteriophage T7 and the yeast Saccharomyces cerevisiae.

Authors:  A Grigoriev
Journal:  Nucleic Acids Res       Date:  2001-09-01       Impact factor: 16.971

10.  Multiple functional interactions between components of the Lsm2-Lsm8 complex, U6 snRNA, and the yeast La protein.

Authors:  B K Pannone; S D Kim; D A Noe; S L Wolin
Journal:  Genetics       Date:  2001-05       Impact factor: 4.562

View more
  37 in total

1.  Assessing experimentally derived interactions in a small world.

Authors:  Debra S Goldberg; Frederick P Roth
Journal:  Proc Natl Acad Sci U S A       Date:  2003-04-03       Impact factor: 11.205

2.  The mammalian protein-protein interaction database and its viewing system that is linked to the main FANTOM2 viewer.

Authors:  Harukazu Suzuki; Rintaro Saito; Mutsumi Kanamori; Chikatoshi Kai; Christian Schönbach; Takeshi Nagashima; Junko Hosaka; Yoshihide Hayashizaki
Journal:  Genome Res       Date:  2003-06       Impact factor: 9.043

3.  Computational approaches to protein-protein interaction.

Authors:  Giacomo Franzot; Oliviero Carugo
Journal:  J Struct Funct Genomics       Date:  2003

4.  The interactome as a tree--an attempt to visualize the protein-protein interaction network in yeast.

Authors:  Hongchao Lu; Xiaopeng Zhu; Haifeng Liu; Geir Skogerbø; Jingfen Zhang; Yong Zhang; Lun Cai; Yi Zhao; Shiwei Sun; Jingyi Xu; Dongbo Bu; Runsheng Chen
Journal:  Nucleic Acids Res       Date:  2004-09-08       Impact factor: 16.971

Review 5.  Embryonic stem cell interactomics: the beginning of a long road to biological function.

Authors:  Maram Yousefi; Vahid Hajihoseini; Woojin Jung; Batol Hosseinpour; Hassan Rassouli; Bonghee Lee; Hossein Baharvand; KiYoung Lee; Ghasem Hosseini Salekdeh
Journal:  Stem Cell Rev Rep       Date:  2012-12       Impact factor: 5.739

6.  Predicting protein-protein interactions in Arabidopsis thaliana through integration of orthology, gene ontology and co-expression.

Authors:  Stefanie De Bodt; Sebastian Proost; Klaas Vandepoele; Pierre Rouzé; Yves Van de Peer
Journal:  BMC Genomics       Date:  2009-06-29       Impact factor: 3.969

7.  Predicting direct protein interactions from affinity purification mass spectrometry data.

Authors:  Ethan Dh Kim; Ashish Sabharwal; Adrian R Vetta; Mathieu Blanchette
Journal:  Algorithms Mol Biol       Date:  2010-10-29       Impact factor: 1.405

8.  Assessing reliability of protein-protein interactions by integrative analysis of data in model organisms.

Authors:  Xiaotong Lin; Mei Liu; Xue-wen Chen
Journal:  BMC Bioinformatics       Date:  2009-04-29       Impact factor: 3.169

9.  A large-scale protein protein interaction analysis in Synechocystis sp. PCC6803.

Authors:  Shusei Sato; Yoshikazu Shimoda; Akiko Muraki; Mitsuyo Kohara; Yasukazu Nakamura; Satoshi Tabata
Journal:  DNA Res       Date:  2007-11-13       Impact factor: 4.458

10.  A core-attachment based method to detect protein complexes in PPI networks.

Authors:  Min Wu; Xiaoli Li; Chee-Keong Kwoh; See-Kiong Ng
Journal:  BMC Bioinformatics       Date:  2009-06-02       Impact factor: 3.169

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.