Literature DB >> 12127457

Computational methods for the prediction of protein interactions.

Alfonso Valencia1, Florencio Pazos.   

Abstract

Establishing protein interaction networks is crucial for understanding cellular operations. Detailed knowledge of the 'interactome', the full network of protein-protein interactions, in model cellular systems should provide new insights into the structure and properties of these systems. Parallel to the first massive application of experimental techniques to the determination of protein interaction networks and protein complexes, the first computational methods, based on sequence and genomic information, have emerged.

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Year:  2002        PMID: 12127457     DOI: 10.1016/s0959-440x(02)00333-0

Source DB:  PubMed          Journal:  Curr Opin Struct Biol        ISSN: 0959-440X            Impact factor:   6.809


  95 in total

1.  Development of unified statistical potentials describing protein-protein interactions.

Authors:  Hui Lu; Long Lu; Jeffrey Skolnick
Journal:  Biophys J       Date:  2003-03       Impact factor: 4.033

2.  TopNet: a tool for comparing biological sub-networks, correlating protein properties with topological statistics.

Authors:  Haiyuan Yu; Xiaowei Zhu; Dov Greenbaum; John Karro; Mark Gerstein
Journal:  Nucleic Acids Res       Date:  2004-01-14       Impact factor: 16.971

3.  HPr kinase/phosphorylase, the sensor enzyme of catabolite repression in Gram-positive bacteria: structural aspects of the enzyme and the complex with its protein substrate.

Authors:  Sylvie Nessler; Sonia Fieulaine; Sandrine Poncet; Anne Galinier; Josef Deutscher; Joël Janin
Journal:  J Bacteriol       Date:  2003-07       Impact factor: 3.490

4.  Computational approaches to protein-protein interaction.

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

Review 5.  Tools used to study how protein complexes are assembled in signaling cascades.

Authors:  Susan Dwane; Patrick A Kiely
Journal:  Bioeng Bugs       Date:  2011-09-01

Review 6.  Proteome-wide prediction of protein-protein interactions from high-throughput data.

Authors:  Zhi-Ping Liu; Luonan Chen
Journal:  Protein Cell       Date:  2012-06-22       Impact factor: 14.870

7.  Using manifold embedding for assessing and predicting protein interactions from high-throughput experimental data.

Authors:  Zhu-Hong You; Ying-Ke Lei; Jie Gui; De-Shuang Huang; Xiaobo Zhou
Journal:  Bioinformatics       Date:  2010-09-03       Impact factor: 6.937

8.  Identification of interface residues in protease-inhibitor and antigen-antibody complexes: a support vector machine approach.

Authors:  Changhui Yan; Vasant Honavar; Drena Dobbs
Journal:  Neural Comput Appl       Date:  2004-06-01       Impact factor: 5.606

9.  Structural Modeling of GR Interactions with the SWI/SNF Chromatin Remodeling Complex and C/EBP.

Authors:  Serena Muratcioglu; Diego M Presman; John R Pooley; Lars Grøntved; Gordon L Hager; Ruth Nussinov; Ozlem Keskin; Attila Gursoy
Journal:  Biophys J       Date:  2015-08-13       Impact factor: 4.033

10.  Assessing predictions of protein-protein interaction: the CAPRI experiment.

Authors:  Joël Janin
Journal:  Protein Sci       Date:  2005-02       Impact factor: 6.725

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