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Nucleic Acids Research 2005 33(Web Server Issue):W324-W325; doi:10.1093/nar/gki401
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© The Author 2005. Published by Oxford University Press. All rights reserved
The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions{at}oupjournals.org


Article

BIOVERSE: enhancements to the framework for structural, functional and contextual modeling of proteins and proteomes

Jason McDermott, Michal Guerquin, Zach Frazier, Aaron N. Chang and Ram Samudrala*

Department of Microbiology, University of Washington Seattle, WA, USA

*To whom correspondence should be addressed. Tel: +1 206 732 6122; Fax: +1 206 732 6055; Email: ram{at}compbio.washington.edu

Received February 14, 2005. Revised March 16, 2005. Accepted March 16, 2005.

We have made a number of enhancements to the previously described Bioverse web server and computational biology framework (http://bioverse.compbio.washington.edu). In this update, we provide an overview of the new features available that include: (i) expansion of the number of organisms represented in the Bioverse and addition of new data sources and novel prediction techniques not available elsewhere, including network-based annotation; (ii) reengineering the database backend and supporting code resulting in significant speed, search and ease-of use improvements; and (iii) creation of a stateful and dynamic web application frontend to improve interface speed and usability. Integrated Java-based applications also allow dynamic visualization of real and predicted protein interaction networks.


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An integrative approach for predicting interactions of protein regions
Bioinformatics, August 15, 2008; 24(16): i35 - i41.
[Abstract] [Full Text] [PDF]



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