An algorithm for protein structure prediction. sDFIRE outperforms other state-of-the-art energy functions in selecting near native structures and in the Pearson’s correlation coefficient between the energy score and structural accuracy of the model.
Department of Computer Science, University of New Orleans, New Orleans, LO, USA; Institute for Glycomics and School of Informatics and Communication, Technology, Griffith University, Brisbane, QLD, Australia
sDFIRE funding source(s)
Louisiana Board of Regents through the Board of Regents Support Fund; National Health and Medical Research Council of Australia and Australian Research Council’s Linkage Infrastructure, Equipment and Facilities funding scheme (grants No.1059775 and No.1083450); National Natural Science Foundation of China (grant No. 61271378)