Skip Navigation



Bioinformatics Advance Access published online on October 27, 2004
Bioinformatics, doi:10.1093/bioinformatics/bti086
Bioinformatics © Oxford University Press 2004; all rights reserved
This Article
Right arrow Advance Access manuscript (PDF) Freely available
Right arrow All Versions of this Article:
21/7/993    most recent
bti086v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Nye, T. M. W.
Right arrow Articles by Teichmann, S. A.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Nye, T. M. W.
Right arrow Articles by Teichmann, S. A.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

Received June 3, 2004
Revised September 1, 2004
Accepted October 5, 2004

Article

Statistical analysis of domains in interacting protein pairs

Tom M. W. Nye 1*, Carlo Berzuini 2, Walter R. Gilks 1, M. Madan Babu 3, and Sarah A. Teichmann 3

1 Medical Research Council Biostatistics Unit, Cambridge, UK
2 Medical Research Council Biostatistics Unit, Cambridge, UK; Dipartimento di Informatica e Sistemistica, Università di Pavia, Italy
3 Medical Research Council Laboratory of Molecular Biology, Cambridge, UK

* To whom correspondence should be addressed.
Tom M. W. Nye, E-mail: thomas.nye{at}mrc-bsu.cam.ac.uk


  Abstract

Motivation: Several methods have recently been developed to analyse large-scale sets of physical interactions between proteins in terms of physical contacts between the constituent domains, often with a view to predicting new pairwise interactions. Our aim is to combine genomic interaction data, in which domain-domain contacts are not explicitly reported, with the domain-level structure of individual proteins, in order to learn about the structure of interacting protein pairs. Our approach is driven by the need to assess the evidence for physical contacts between domains in a statistically rigorous way.

Results: We develop a statistical approach that assigns p-values to pairs of domain superfamilies, measuring the strength of evidence within a set of protein interactions that domains from these superfamilies form contacts. A set of p-values is calculated for SCOP superfamily pairs, based on a pooled dataset of interactions from yeast. These p-values can be used to predict which domains come into contact in an interacting protein pair. This predictive scheme is tested against protein complexes in the Protein Quaternary Structure (PQS) database, and is used to predict domain-domain contacts within 705 interacting protein pairs taken from our pooled dataset.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 Nucleic Acids ResHome page
J. Guo, X. Wu, D.-Y. Zhang, and K. Lin
Genome-wide inference of protein interaction sites: lessons from the yeast high-quality negative protein-protein interaction dataset
Nucleic Acids Res., April 1, 2008; 36(6): 2002 - 2011.
[Abstract] [Full Text] [PDF]

Home page
 Nucleic Acids ResHome page
B. Raghavachari, A. Tasneem, T. M. Przytycka, and R. Jothi
DOMINE: a database of protein domain interactions
Nucleic Acids Res., January 11, 2008; 36(suppl_1): D656 - D661.
[Abstract] [Full Text] [PDF]

Home page
 Nucleic Acids ResHome page
F. P. Davis, H. Braberg, M.-Y. Shen, U. Pieper, A. Sali, and M.S. Madhusudhan
Protein complex compositions predicted by structural similarity
Nucleic Acids Res., May 31, 2006; 34(10): 2943 - 2952.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
J. Espadaler, O. Romero-Isart, R. M. Jackson, and B. Oliva
Prediction of protein-protein interactions using distant conservation of sequence patterns and structure relationships
Bioinformatics, August 15, 2005; 21(16): 3360 - 3368.
[Abstract] [Full Text] [PDF]


Disclaimer:
Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.