Skip Navigation



Bioinformatics Advance Access published online on November 11, 2004
Bioinformatics, doi:10.1093/bioinformatics/bti135
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:
21/7/1020    most recent
bti135v1
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 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 Kifer, I.
Right arrow Articles by Linial, M.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Kifer, I.
Right arrow Articles by Linial, M.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

Received December 19, 2003
Revised October 18, 2004
Accepted November 2, 2004

Article

Predicting fold novelty based on ProtoNet hierarchical classification

Ilona Kifer 1, Ori Sasson 2, and Michal Linial 3*

1 Department of Biological Chemistry, Institute of Life Sciences, Jerusalem 91904, Israel; School of Computer Science and Engineering, The Hebrew University, Jerusalem 91904, Israel
2 School of Computer Science and Engineering, The Hebrew University, Jerusalem 91904, Israel
3 Department of Biological Chemistry, Institute of Life Sciences, Jerusalem 91904, Israel

* To whom correspondence should be addressed.
Michal Linial, E-mail: michall{at}cc.huji.ac.il


  Abstract

Motivation: Structural genomics projects aim to solve a large number of protein structures with the ultimate objective of representing the entire protein space. The computational challenge is to identify and prioritise a small set of proteins with new, currently unknown superfamilies or folds.

Results: We develop a method that assigns each protein a likelihood of it belonging to a new, yet undetermined structural superfamily. The method relies on a variant of ProtoNet, an automatic hierarchical classification scheme of all protein sequences from SwissProt. Our results show that proteins that are remote from solved structures in the ProtoNet hierarchy are more likely to belong to new superfamilies. The results are validated against SCOP releases from recent years that account for about half of the solved structures known to date. We show that our new method and the representation of ProtoNet are superior in detecting new targets, compared to our previous method using ProtoMap classification. Furthermore, our method outperforms PSI-BLAST search in detecting potential new superfamilies.

Availability: An interactive tool implementing this method, named ProTarget is available at http://www.protarget.cs.huji.ac.il. It can be used interactively to retrieve a list of candidate proteins for Structural Genomics projects.

Supplement: Supplementary material is available at http://www.protarget.cs.huji.ac.il/supplement.


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
Y. Loewenstein and M. Linial
Connect the dots: exposing hidden protein family connections from the entire sequence tree
Bioinformatics, August 15, 2008; 24(16): i193 - i199.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
Y. Loewenstein, E. Portugaly, M. Fromer, and M. Linial
Efficient algorithms for accurate hierarchical clustering of huge datasets: tackling the entire protein space
Bioinformatics, July 1, 2008; 24(13): i41 - i49.
[Abstract] [Full Text] [PDF]

Home page
 Nucleic Acids ResHome page
O. Sasson and M. Linial
ProTarget: automatic prediction of protein structure novelty
Nucleic Acids Res., July 1, 2005; 33(suppl_2): W81 - W84.
[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.