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BioMed Research International
Volume 2013 (2013), Article ID 398968, 6 pages
http://dx.doi.org/10.1155/2013/398968
Research Article

Cloud Prediction of Protein Structure and Function with PredictProtein for Debian

1TUM, Department of Informatics, Bioinformatics & Computational Biology-I12, Boltzmannstraß 3, 85748 Garching, Germany
2Columbia University, Department of Biochemistry and Molecular Biophysics and New York Consortium on Membrane Protein Structure (NYCOMPS), 701 West 168th Street, New York, NY 10032, USA
3Biosof LLC, 10th Floor, 138 West 25th Street, New York, NY 10001, USA
4WZW-Weihenstephan, Alte Akademie 8, Freising, Germany
5Institute for Advanced Study (TUM-IAS), Lichtenbergstraß 2a, 85748 Garching, Germany

Received 4 January 2013; Accepted 5 July 2013

Academic Editor: Ching-Hsien (Robert) Hsu

Copyright © 2013 László Kaján et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

We report the release of PredictProtein for the Debian operating system and derivatives, such as Ubuntu, Bio-Linux, and Cloud BioLinux. The PredictProtein suite is available as a standard set of open source Debian packages. The release covers the most popular prediction methods from the Rost Lab, including methods for the prediction of secondary structure and solvent accessibility (profphd), nuclear localization signals (predictnls), and intrinsically disordered regions (norsnet). We also present two case studies that successfully utilize PredictProtein packages for high performance computing in the cloud: the first analyzes protein disorder for whole organisms, and the second analyzes the effect of all possible single sequence variants in protein coding regions of the human genome.