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Using protein structural and contact information with machine learning techniques. QAcon is a single-model quality assessment method utilizing structural features, physicochemical properties, and residue contact predictions. It is based on machine learning and various protein features, which is ranked as one of the best single-model quality assessment methods according to the critical assessment of techniques for protein structure prediction (CASP) official evaluation results.

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QAcon classification

QAcon specifications

Software type:
Package
Restrictions to use:
None
Computer skills:
Basic
Stability:
Stable
Interface:
Web user interface
Input data:
A Protein sequence (one plain sequence, no headers)
Version:
1.0
Source code URL:
http://cactus.rnet.missouri.edu/QAcon/QACON1.0.tar.gz

Credits

Publications

  • (Cao et al., 2016) QAcon: single model quality assessment using protein structural and contact information with machine learning techniques. Bioinformatics.
    DOI: 10.1093/bioinformatics/btw694

Institution(s)

Department of Computer Science, Pacific Lutheran University, WA, USA; Department of Computer Science, University of Missouri, Columbia, MO, USA; Department of Electrical Engineering and Computer Science, Wichita State University, Wichita, KS, USA; Department of Electrical and Computer Engineering, University of Missouri, Columbia, MO, USA; Informatics Institute, University of Missouri, Columbia, MO, USA

Funding source(s)

The work is supported by US National Institutes of Health (NIH) grant (R01GM093123).

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