Email updates

Keep up to date with the latest news and content from BMC Bioinformatics and BioMed Central.

This article is part of the supplement: Proceedings of the 11th Annual Bioinformatics Open Source Conference (BOSC) 2010

Open Access Proceedings

The Musite open-source framework for phosphorylation-site prediction

Jianjiong Gao and Dong Xu*

Author Affiliations

Department of Computer Science, C.S. Bond Life Sciences Center, University of Missouri, Columbia, Missouri 65211, USA

For all author emails, please log on.

BMC Bioinformatics 2010, 11(Suppl 12):S9  doi:10.1186/1471-2105-11-S12-S9

Published: 21 December 2010

Abstract

Background

With the rapid accumulation of phosphoproteomics data, phosphorylation-site prediction is becoming an increasingly active research area. More than a dozen phosphorylation-site prediction tools have been released in the past decade. However, there is currently no open-source framework specifically designed for phosphorylation-site prediction except Musite.

Results

Here we present the Musite open-source framework for building applications to perform machine learning based phosphorylation-site prediction. Musite was implemented with six modules loosely coupled with each other. With its well-designed Java application programming interface (API), Musite can be easily extended to integrate various sources of biological evidence for phosphorylation-site prediction.

Conclusions

Released under the GNU GPL open source license, Musite provides an open and extensible framework for phosphorylation-site prediction. The software with its source code is available at

    http://musite.sourceforge.net
.