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Article
P.R.E.S.S. – An R-package for Exploring Residual-Level Protein Structural Statistics
Journal of Bioinformatics and Computational Biology
  • Yuanyuan Huang, Iowa State University
  • Steve Bonett, Iowa State University
  • Andrzej Klockowski, Iowa State University
  • Robert Jernigan, Iowa State University
  • Zhijun Wu, Iowa State University
Document Type
Article
Publication Version
Accepted Manuscript
Publication Date
6-1-2012
DOI
10.1142/S0219720012420073
Abstract

P.R.E.S.S. is an R package developed to allow researchers to get access to and manipulate on a large set of statistical data on protein residue-level structural properties such as residue-level virtual bond lengths, virtual bond angles, and virtual torsion angles. A large set of high-resolution protein structures are downloaded and surveyed. Their residue-level structural properties are calculated and documented. The statistical distributions and correlations of these properties can be queried and displayed. Tools are also provided for modeling and analyzing a given structure in terms of its residue-level structural properties. In particular, new tools for computing residue-level statistical potentials and displaying residue-level Ramachandran-like plots are developed for structural analysis and refinement. P.R.E.S.S. will be released in R as an open source software package, with a user-friendly GUI, accessible and executable by a public user in any R environment.

Comments

This is a manuscript of an Electronic version of an article published as Journal of Bioinformatics and Computational Biology 10, no. 03 (2012): 1242007, DOI: 10.1142/S0219720012420073. © copyright World Scientific Publishing Company, http://www.worldscientific.com/worldscinet/jbcb.

Copyright Owner
World Scientific Publishing Company
Language
en
File Format
application/pdf
Citation Information
Yuanyuan Huang, Steve Bonett, Andrzej Klockowski, Robert Jernigan, et al.. "P.R.E.S.S. – An R-package for Exploring Residual-Level Protein Structural Statistics" Journal of Bioinformatics and Computational Biology Vol. 10 Iss. 3 (2012) p. 1242007
Available at: http://works.bepress.com/robert-jernigan/40/