title: gkmSVM: an R package for gapped-kmer SVM.
abstract: We present a new R package for training gapped-kmer SVM classifiers for DNA and protein sequences. We describe an improved algorithm for kernel matrix calculation that speeds run time by about 2 to 5-fold over our original gkmSVM algorithm. This package supports several sequence kernels, including: gkmSVM, kmer-SVM, mismatch kernel and wildcard kernel.
  
  
  
  gkmSVM package is freely available through the Comprehensive R Archive Network (CRAN), for Linux, Mac OS and Windows platforms. The C ++ implementation is available at www.beerlab.org/gkmsvm
  
  
  
  mghandi@gmail.com or mbeer@jhu.edu
  
  
  
  Supplementary data are available at Bioinformatics online.
authors.affiliation: The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
authors.forename: Mahmoud
authors.initials: M
authors.lastname: Ghandi
authors.affiliation: School of Mathematics, Statistics, and Computer Science, College of Science, University of Tehran, Tehran, Iran.
authors.forename: Morteza
authors.initials: M
authors.lastname: Mohammad-Noori
authors.affiliation: Department of Engineering Science, College of Engineering, University of Tehran, and Institute for Research in Fundamental Sciences (IPM), Tehran, Iran.
authors.forename: Narges
authors.initials: N
authors.lastname: Ghareghani
authors.affiliation: McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, MD, USA.
authors.forename: Dongwon
authors.initials: D
authors.lastname: Lee
authors.affiliation: The Broad Institute of MIT and Harvard, Cambridge, MA, USA Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
authors.forename: Levi
authors.initials: L
authors.lastname: Garraway
authors.affiliation: McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, MD, USA Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
authors.forename: Michael A
authors.initials: MA
authors.lastname: Beer
mesh_terms: D000465:Algorithms; D017422:Sequence Analysis, DNA / Q000379:methods*; D020539:Sequence Analysis, Protein / Q000379:methods*; D012984:Software; D060388:Support Vector Machine