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LS-GKM: a new gkm-SVM for large-scale datasets.

ABSTRACT:

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.

SUBMITTER: Lee D

PROVIDER: S-EPMC4937189 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature

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LS-GKM: a new gkm-SVM for large-scale datasets.

Lee Dongwon D

Bioinformatics (Oxford, England) 20160315 14

<h4>Unlabelled</h4>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 ...[more]

PMID: 27153584

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