Skip Navigation

This Article
Right arrow FREE Full Text (Print PDF) Freely available
Right arrow FREE Full Text (Screen PDF)
Right arrow Comments: Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when Comments are posted
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 ISI Web of Science
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 arrow Search for citing articles in:
ISI Web of Science (38)
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Ng, S.-K.
Right arrow Articles by Tan, S.-H.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Ng, S.-K.
Right arrow Articles by Tan, S.-H.
Social Bookmarking
 Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

Bioinformatics Vol. 19 no. 8 2003
Pages 923-929
© 2003 Oxford University Press

Integrative approach for computationally inferring protein domain interactions

See-Kiong Ng *, Zhuo Zhang and Soon-Heng Tan

Laboratories for Information Technology, 21 Heng Mui Keng Terrace, Singapore 119613

Received on June 9, 2002 ; revised on November 11, 2002 ; accepted on November 11, 2002

Motivation: The current need for high-throughput protein interaction detection has resulted in interaction data being generated en masse through such experimental methods as yeast-two-hybrids and protein chips. Such data can be erroneous and they often do not provide adequate functional information for the detected interactions. Therefore, it is useful to develop an in silico approach to further validate and annotate the detected protein interactions.

Results: Given that protein–protein interactions involve physical interactions between protein domains, domain–domain interaction information can be useful for validating, annotating, and even predicting protein interactions. However, large-scale, experimentally determined domain–domain interaction data do not exist. Here, we describe an integrative approach to computationally derive putative domain interactions from multiple data sources, including protein interactions, protein complexes, and Rosetta Stone sequences. We further prove the usefulness of such an integrative approach by applying the derived domain interactions to predict and validate protein–protein interactions.

Availability: A database of putative protein domain interactions derived using the method described in this paper is available at http://interdom.lit.org.sg.

Contact: skng{at}lit.org.sg

* To whom correspondence should be addressed.


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
BioinformaticsHome page
M. Liu, X.-w. Chen, and R. Jothi
Knowledge-guided inference of domain-domain interactions from incomplete protein-protein interaction networks
Bioinformatics, October 1, 2009; 25(19): 2492 - 2499.
[Abstract] [Full Text] [PDF]


Home page
Nucleic Acids ResHome page
H. Blankenburg, F. Ramirez, J. Buch, and M. Albrecht
DASMIweb: online integration, analysis and assessment of distributed protein interaction data
Nucleic Acids Res., July 1, 2009; 37(suppl_2): W122 - W128.
[Abstract] [Full Text] [PDF]


Home page
BioinformaticsHome page
H. Blankenburg, R. D. Finn, A. Prlic, A. M. Jenkinson, F. Ramirez, D. Emig, S.-E. Schelhorn, J. Buch, T. Lengauer, and M. Albrecht
DASMI: exchanging, annotating and assessing molecular interaction data
Bioinformatics, May 15, 2009; 25(10): 1321 - 1328.
[Abstract] [Full Text] [PDF]


Home page
Proc. Natl. Acad. Sci. USAHome page
E. Akiva, Z. Itzhaki, and H. Margalit
Built-in loops allow versatility in domain-domain interactions: Lessons from self-interacting domains
PNAS, September 9, 2008; 105(36): 13292 - 13297.
[Abstract] [Full Text] [PDF]


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
P. Pagel, M. Oesterheld, O. Tovstukhina, N. Strack, V. Stumpflen, and D. Frishman
DIMA 2.0 predicted and known domain interactions
Nucleic Acids Res., January 11, 2008; 36(suppl_1): D651 - D655.
[Abstract] [Full Text] [PDF]


Home page
Nucleic Acids ResHome page
Y.-C. Chen, Y.-S. Lo, W.-C. Hsu, and J.-M. Yang
3D-partner: a web server to infer interacting partners and binding models
Nucleic Acids Res., July 13, 2007; 35(suppl_2): W561 - W567.
[Abstract] [Full Text] [PDF]


Home page
BioinformaticsHome page
M. D. Dyer, T. M. Murali, and B. W. Sobral
Computational prediction of host-pathogen protein protein interactions
Bioinformatics, July 1, 2007; 23(13): i159 - i166.
[Abstract] [Full Text] [PDF]


Home page
Nucleic Acids ResHome page
E. R. Jefferson, T. P. Walsh, T. J. Roberts, and G. J. Barton
SNAPPI-DB: a database and API of Structures, iNterfaces and Alignments for Protein-Protein Interactions
Nucleic Acids Res., January 12, 2007; 35(suppl_1): D580 - D589.
[Abstract] [Full Text] [PDF]


Home page
Proc. Natl. Acad. Sci. USAHome page
E. Sprinzak, Y. Altuvia, and H. Margalit
Colloquium Papers: Characterization and prediction of protein-protein interactions within and between complexes
PNAS, October 3, 2006; 103(40): 14718 - 14723.
[Abstract] [Full Text] [PDF]


Home page
BioinformaticsHome page
H. Li, J. Li, and L. Wong
Discovering motif pairs at interaction sites from protein sequences on a proteome-wide scale
Bioinformatics, April 15, 2006; 22(8): 989 - 996.
[Abstract] [Full Text] [PDF]


Home page
BioinformaticsHome page
D. Park, S. Lee, D. Bolser, M. Schroeder, M. Lappe, D. Oh, and J. Bhak
Comparative interactomics analysis of protein family interaction networks using PSIMAP (protein structural interactome map)
Bioinformatics, August 1, 2005; 21(15): 3234 - 3240.
[Abstract] [Full Text] [PDF]


Home page
BioinformaticsHome page
T. M. W. Nye, C. Berzuini, W. R. Gilks, M. M. Babu, and S. A. Teichmann
Statistical analysis of domains in interacting protein pairs
Bioinformatics, April 1, 2005; 21(7): 993 - 1001.
[Abstract] [Full Text] [PDF]


Home page
BioinformaticsHome page
H. Li and J. Li
Discovery of stable and significant binding motif pairs from PDB complexes and protein interaction datasets
Bioinformatics, February 1, 2005; 21(3): 314 - 324.
[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.