- Added residue eta calculation (average eta per residue). - New struct-based API. - Cache optimized svm training data (svm problems structs). - Fixed memory leaks in svm training. - Added -nthreads option to set the number of threads to use at runtime. - Atom IDs are output next to eta values. - Shows progress while constructing svm problem structs (can take a long time for large trajectories). - Added failure handling to large memory allocations. - Added functions for freeing svm data. - Added regression test. View License
S. Varma, M. Botlani and R.E. Leighty, Discerning intersecting fusion-activation pathways in the Nipah virus using machine learning. Proteins. 82: 3241-3254 (2014) View
R.E. Leighty and S. Varma, Quantifying changes in intrinsic molecular motion using support vector machines. J Chem. Theory and Comput. 9: 868-875 (2013) View
P. Dutta, A. Siddiqui, M. Botlani and S. Varma, Stimulation of Nipah Fusion: Small Intradomain Changes Trigger Extensive Interdomain Rearrangements. Biophys. J. 111: 1621–1630 (2016) View
First stable release. View License
N. Duro, M. Gjika, A. Siddiqui, H.L. Scott and S. Varma, POPC bilayers supported on nanoporous substrates: specific effects of silica-type surface hydroxylation and charge density. Langmuir. 32: 6766–6774 (2016) View