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Bioinformatics Advance Access published online on September 5, 2006
Bioinformatics, doi:10.1093/bioinformatics/btl444
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© The Author (2006). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
Received June 23, 2006
Accepted August 15, 2006

Applications note

SEBINI: software environment for biological network inference

Ronald C. Taylor 1 *, Anuj Shah 1, Charles Treatman 2, and Meridith Blevins 3

1 Computational Biology & Bioinformatics Group, Pacific Northwest National Laboratory, Richland, Washington, USA
2 Oberlin College, Oberlin, Ohio, USA
3 Case Western Reserve University, Cleveland, Ohio, USA

* To whom correspondence should be addressed.
Ronald C. Taylor, E-mail: ronald.taylor{at}pnl.gov


  Abstract

Summary: The Software Environment for BIological Network Inference (SEBINI) has been created to provide an interactive environment for the deployment and evaluation of algorithms used to reconstruct the structure of biological regulatory and interaction networks. SEBINI can be used to compare and train network inference methods on artificial networks and simulated gene expression perturbation data. It also allows the analysis within the same framework of experimental high-throughput expression data using the suite of (trained) inference methods; hence SEBINI should be useful to software developers wishing to evaluate, compare, refine, or combine inference techniques, and to bioinformaticians analyzing experimental data. SEBINI provides a platform that aids in more accurate reconstruction of biological networks, with less effort, in less time.

Availability: A demonstration web site is located at https://www.emsl.pnl.gov/NIT/NIT.html. The Java source code and PostgreSQL database schema are available freely for non-commercial use.

Associate Editor: Alvis Brazma
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