LS GKM: a new gkm SVM for large scale datasets
UNLABELLED gkm SVM is a sequence based method for predicting and detecting the regulatory vocabulary encoded in functional DNA elements, and is a commonly used tool for studying gene regulatory mechanisms. Here we introduce new software, LS GKM, which removes several limitations of our previous releases, enabling training on much larger scale (LS) datasets. LS GKM also provides additional advanced gapped k mer based kernel functions. With these improvements, LS GKM achieves considerably higher accuracy than the original gkm SVM. AVAILABILITY AND IMPLEMENTATION C/C source codes and related scripts are freely available from http:/github.com/Dongwon Lee/lsgkm/ and supported on Linux and Mac OS X. CONTACT dwlee@jhu.edu SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Bioinform.