Literature DB >> 10977076

Integrative analysis of protein interaction data.

M Fellenberg1, K Albermann, A Zollner, H W Mewes, J Hani.   

Abstract

We have developed a method for the integrative analysis of protein interaction data. It comprises clustering, visualization and data integration components. The method is generally applicable for all sequenced organisms. Here, we describe in detail the combination of protein interaction data in the yeast Saccharomyces cerevisiae with the functional classification of all yeast proteins. We evaluate the utility of the method by comparison with experimental data and deduce hypotheses about the functional role of so far uncharacterized proteins. Further applications of the integrative analysis method are discussed. The method presented here is powerful and flexible. We show that it is capable of mining large-scale data sets.

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Year:  2000        PMID: 10977076

Source DB:  PubMed          Journal:  Proc Int Conf Intell Syst Mol Biol        ISSN: 1553-0833


  11 in total

1.  Networking proteins in yeast.

Authors:  T R Hazbun; S Fields
Journal:  Proc Natl Acad Sci U S A       Date:  2001-04-10       Impact factor: 11.205

2.  Relating whole-genome expression data with protein-protein interactions.

Authors:  Ronald Jansen; Dov Greenbaum; Mark Gerstein
Journal:  Genome Res       Date:  2002-01       Impact factor: 9.043

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

Authors:  Rintaro Saito; Harukazu Suzuki; Yoshihide Hayashizaki
Journal:  Nucleic Acids Res       Date:  2002-03-01       Impact factor: 16.971

4.  Functional modules by relating protein interaction networks and gene expression.

Authors:  Sabine Tornow; H W Mewes
Journal:  Nucleic Acids Res       Date:  2003-11-01       Impact factor: 16.971

5.  The PEDANT genome database.

Authors:  Dmitrij Frishman; Martin Mokrejs; Denis Kosykh; Gabi Kastenmüller; Grigory Kolesov; Igor Zubrzycki; Christian Gruber; Birgitta Geier; Andreas Kaps; Kaj Albermann; Andreas Volz; Christian Wagner; Matthias Fellenberg; Klaus Heumann; Hans-Werner Mewes
Journal:  Nucleic Acids Res       Date:  2003-01-01       Impact factor: 16.971

6.  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

7.  A comprehensive two-hybrid analysis to explore the yeast protein interactome.

Authors:  T Ito; T Chiba; R Ozawa; M Yoshida; M Hattori; Y Sakaki
Journal:  Proc Natl Acad Sci U S A       Date:  2001-03-13       Impact factor: 11.205

8.  On the number of protein-protein interactions in the yeast proteome.

Authors:  Andrei Grigoriev
Journal:  Nucleic Acids Res       Date:  2003-07-15       Impact factor: 16.971

9.  A regression-based K nearest neighbor algorithm for gene function prediction from heterogeneous data.

Authors:  Zizhen Yao; Walter L Ruzzo
Journal:  BMC Bioinformatics       Date:  2006-03-20       Impact factor: 3.169

10.  System-based proteomic analysis of the interferon response in human liver cells.

Authors:  Wei Yan; Hookeun Lee; Eugene C Yi; David Reiss; Paul Shannon; Bartlomiej K Kwieciszewski; Carlos Coito; Xiao-jun Li; Andrew Keller; Jimmy Eng; Timothy Galitski; David R Goodlett; Ruedi Aebersold; Michael G Katze
Journal:  Genome Biol       Date:  2004-07-22       Impact factor: 13.583

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