Journal
BIOINFORMATICS
Volume 29, Issue 14, Pages 1817-1818Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btt272
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Funding
- Swedish Research Council [VR-NT 2009-5072, VR-M 2010-3555]
- SSF (the Foundation for Strategic Research)
- Vinnova through the Vinnova-JSP program
- EU [FP7-HEALTH-F4-2007-201924]
- TranSys, a Marie Curie ITN [FP7-PEOPLE-2007-ITN-215524]
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Clustering methods are often needed for accurately assessing the quality of modeled protein structures. Recent blind evaluation of quality assessment methods in CASP10 showed that there is little difference between many different methods as far as ranking models and selecting best model are concerned. When comparing many models, the computational cost of the model comparison can become significant. Here, we present PconsD, a fast, stream-computing method for distance-driven model quality assessment that runs on consumer hardware. PconsD is at least one order of magnitude faster than other methods of comparable accuracy.
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