JSON
Skwark MJ, Elofsson A
Bioinformatics 29 (14) 1817-1818 [2013-07-15; online 2013-05-14]
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. The source code for PconsD is freely available at http://d.pcons.net/. Supplementary benchmarking data are also available there. arne@bioinfo.se Supplementary data are available at Bioinformatics online.
PubMed 23677942
DOI 10.1093/bioinformatics/btt272
Crossref 10.1093/bioinformatics/btt272
pii: btt272