Cloud Prediction of Protein Structure and Function with PredictProtein for DebianReport as inadecuate

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BioMed Research InternationalVolume 2013 2013, Article ID 398968, 6 pages

Research Article

TUM, Department of Informatics, Bioinformatics & Computational Biology-I12, Boltzmannstraß 3, 85748 Garching, Germany

Columbia 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

Biosof LLC, 10th Floor, 138 West 25th Street, New York, NY 10001, USA

WZW-Weihenstephan, Alte Akademie 8, Freising, Germany

Institute 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.


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.

Author: László Kaján, Guy Yachdav, Esmeralda Vicedo, Martin Steinegger, Milot Mirdita, Christof Angermüller, Ariane Böhm, Simo



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