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QAcon

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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

Interface:
Web user interface
Input data:
A protein sequence.
Version:
1.0
Source code URL:
http://cactus.rnet.missouri.edu/QAcon/QACON1.0.tar.gz
Restrictions to use:
None
Computer skills:
Basic
Stability:
Stable
Maintained:
Yes

QAcon support

Maintainer

  • Jianlin Cheng <>

Credits

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Publications

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).

Link to literature

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