Genome Research

Home Help [Feedback] [For Subscribers] [Archive] [Search] [Contents]
QUICK SEARCH:   [advanced]


     

This Article
Right arrow Full Text
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
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 Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Mott, R.
Right arrow Articles by Ponting, C. P.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Mott, R.
Right arrow Articles by Ponting, C. P.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati  
What's this?

Vol. 12, Issue 8, 1168-1174, August 2002

LETTER
Predicting Protein Cellular Localization Using a Domain Projection Method

Richard Mott,1,5 Jörg Schultz,2,3 Peer Bork,3 and Chris P. Ponting4

1 Wellcome Trust Centre for Human Genetics, Oxford OX3 7BN, United Kingdom; 2 Max-Planck-Institute for Molecular Genetics, 14195 Berlin, Germany; 3 European Molecular Biology Laboratory, 69012 Heidelberg, Germany, and Max Delbruk Centrum Berlin-Buch, 13092 Berlin, Germany; 4 Medical Research Council Functional Genetics Unit, Department of Human Anatomy and Genetics, University of Oxford, Oxford OX1 3QX, United Kingdom

We investigate the co-occurrence of domain families in eukaryotic proteins to predict protein cellular localization. Approximately half (300) of SMART domains form a "small-world network", linked by no more than seven degrees of separation. Projection of the domains onto two-dimensional space reveals three clusters that correspond to cellular compartments containing secreted, cytoplasmic, and nuclear proteins. The projection method takes into account the existence of "bridging" domains, that is, instances where two domains might not occur with each other but frequently co-occur with a third domain; in such circumstances the domains are neighbors in the projection. While the majority of domains are specific to a compartment ("locale"), and hence may be used to localize any protein that contains such a domain, a small subset of domains either are present in multiple locales or occur in transmembrane proteins. Comparison with previously annotated proteins shows that SMART domain data used with this approach can predict, with 92% accuracy, the localizations of 23% of eukaryotic proteins. The coverage and accuracy will increase with improvements in domain database coverage. This method is complementary to approaches that use amino-acid composition or identify sorting sequences; these methods may be combined to further enhance prediction accuracy.

5 Corresponding author.

12:1168-1174 ©2002 by Cold Spring Harbor Laboratory Press  ISSN 1088-9051/02 $5.00
Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati    What's this?


This article has been cited by other articles:


Home page
 Brief Funct Genomic ProteomicHome page
R. Casadio, P. L. Martelli, and A. Pierleoni
The prediction of protein subcellular localization from sequence: a shortcut to functional genome annotation
Brief Funct Genomic Proteomic, February 18, 2008; (2008) eln003v1.
[Abstract] [Full Text] [PDF]

Home page
 Nucleic Acids ResHome page
D. Wilson, V. Charoensawan, S. K. Kummerfeld, and S. A. Teichmann
DBD--taxonomically broad transcription factor predictions: new content and functionality
Nucleic Acids Res., January 18, 2008; 36(suppl_1): D88 - D92.
[Abstract] [Full Text] [PDF]

Home page
 Nucleic Acids ResHome page
S. Lee, B. Lee, I. Jang, S. Kim, and J. Bhak
Localizome: a server for identifying transmembrane topologies and TM helices of eukaryotic proteins utilizing domain information.
Nucleic Acids Res., July 1, 2006; 34(Web Server issue): W99 - W103.
[Abstract] [Full Text] [PDF]

Home page
 Nucleic Acids ResHome page
C. Guda
pTARGET: a web server for predicting protein subcellular localization.
Nucleic Acids Res., July 1, 2006; 34(Web Server issue): W210 - W213.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
H. Luz and M. Vingron
Family specific rates of protein evolution
Bioinformatics, May 15, 2006; 22(10): 1166 - 1171.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
C. Guda and S. Subramaniam
TARGET: a new method for predicting protein subcellular localization in eukaryotes
Bioinformatics, November 1, 2005; 21(21): 3963 - 3969.
[Abstract] [Full Text] [PDF]

Home page
 Protein Sci.Home page
A. Bernsel and G. Von Heijne
Improved membrane protein topology prediction by domain assignments
Protein Sci., July 1, 2005; 14(7): 1723 - 1728.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
V. Atalay and R. Cetin-Atalay
Implicit motif distribution based hybrid computational kernel for sequence classification
Bioinformatics, April 15, 2005; 21(8): 1429 - 1436.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
V. Arnau, S. Mars, and I. Marín
Iterative Cluster Analysis of Protein Interaction Data
Bioinformatics, February 1, 2005; 21(3): 364 - 378.
[Abstract] [Full Text] [PDF]

Home page
 Nucleic Acids ResHome page
Y. Chen, Y. Zhang, Y. Yin, G. Gao, S. Li, Y. Jiang, X. Gu, and J. Luo
SPD--a web-based secreted protein database
Nucleic Acids Res., January 1, 2005; 33(suppl_1): D169 - D173.
[Abstract] [Full Text] [PDF]

Home page
 Genome Res.Home page
M. S. Scott, D. Y. Thomas, and M. T. Hallett
Predicting Subcellular Localization via Protein Motif Co-Occurrence
Genome Res., October 1, 2004; 14(10a): 1957 - 1966.
[Abstract] [Full Text] [PDF]

Home page
 Genome Res.Home page
Y. Ye and A. Godzik
Comparative Analysis of Protein Domain Organization
Genome Res., March 1, 2004; 14(3): 343 - 353.
[Abstract] [Full Text] [PDF]


Home Help [Feedback] [For Subscribers] [Archive] [Search] [Contents]
Genes Dev. Learn. Mem.
Protein Science RNA Genome Res.