Literature DB >> 17055769

The value of high quality protein-protein interaction networks for systems biology.

Ulrich Stelzl1, Erich E Wanker.   

Abstract

Protein-protein interaction (PPI) networks contain a large amount of useful information for the functional characterization of proteins and promote the understanding of the complex molecular relationships that determine the phenotype of a cell. Recently, large human interaction maps have been generated with high throughput technologies such as the yeast two-hybrid system. However, they are static and incomplete and do not provide immediate clues about the cellular processes that convert genetic information into complex phenotypes. Refined multiple-aspect PPI screening and confirmation strategies will have to be put in place to increase the validity of interaction maps. Integration of interaction data with other qualitative and quantitative information (e.g. protein expression or localization data), will be required to construct networks of protein function that reflect dynamic processes in the cell. In this way, combined PPI networks can become valuable resources for a systems-level understanding of cellular processes and complex phenotypes.

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Year:  2006        PMID: 17055769     DOI: 10.1016/j.cbpa.2006.10.005

Source DB:  PubMed          Journal:  Curr Opin Chem Biol        ISSN: 1367-5931            Impact factor:   8.822


  33 in total

1.  High-sensitivity detection and quantitative analysis of native protein-protein interactions and multiprotein complexes by flow cytometry.

Authors:  Adam G Schrum; Diana Gil; Elaine P Dopfer; David L Wiest; Laurence A Turka; Wolfgang W A Schamel; Ed Palmer
Journal:  Sci STKE       Date:  2007-06-05

2.  Mapping of protein-protein interaction sites by the 'absence of interference' approach.

Authors:  Arunkumar Dhayalan; Tomasz P Jurkowski; Heike Laser; Richard Reinhardt; Da Jia; Xiaodong Cheng; Albert Jeltsch
Journal:  J Mol Biol       Date:  2007-12-23       Impact factor: 5.469

Review 3.  Proof of concept: network and systems biology approaches aid in the discovery of potent anticancer drug combinations.

Authors:  Asfar S Azmi; Zhiwei Wang; Philip A Philip; Ramzi M Mohammad; Fazlul H Sarkar
Journal:  Mol Cancer Ther       Date:  2010-11-01       Impact factor: 6.261

4.  Walking the interactome for prioritization of candidate disease genes.

Authors:  Sebastian Köhler; Sebastian Bauer; Denise Horn; Peter N Robinson
Journal:  Am J Hum Genet       Date:  2008-03-27       Impact factor: 11.025

5.  Large-scale de novo prediction of physical protein-protein association.

Authors:  Antigoni Elefsinioti; Ömer Sinan Saraç; Anna Hegele; Conrad Plake; Nina C Hubner; Ina Poser; Mihail Sarov; Anthony Hyman; Matthias Mann; Michael Schroeder; Ulrich Stelzl; Andreas Beyer
Journal:  Mol Cell Proteomics       Date:  2011-08-11       Impact factor: 5.911

6.  Categorizing biases in high-confidence high-throughput protein-protein interaction data sets.

Authors:  Xueping Yu; Joseph Ivanic; Vesna Memisević; Anders Wallqvist; Jaques Reifman
Journal:  Mol Cell Proteomics       Date:  2011-08-29       Impact factor: 5.911

Review 7.  Building Bridges Between Structural and Network-Based Systems Biology.

Authors:  Christos T Chasapis
Journal:  Mol Biotechnol       Date:  2019-03       Impact factor: 2.695

8.  Increased entropy of signal transduction in the cancer metastasis phenotype.

Authors:  Andrew E Teschendorff; Simone Severini
Journal:  BMC Syst Biol       Date:  2010-07-30

9.  Application of an integrated physical and functional screening approach to identify inhibitors of the Wnt pathway.

Authors:  Bryan W Miller; Garnet Lau; Chris Grouios; Emanuela Mollica; Miriam Barrios-Rodiles; Yongmei Liu; Alessandro Datti; Quaid Morris; Jeffrey L Wrana; Liliana Attisano
Journal:  Mol Syst Biol       Date:  2009-10-13       Impact factor: 11.429

10.  Interactome and Gene Ontology provide congruent yet subtly different views of a eukaryotic cell.

Authors:  Antonio Marco; Ignacio Marín
Journal:  BMC Syst Biol       Date:  2009-07-15
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