|Summary:||Tool suite uses a support vector machine (SVM) with kmer sequence features to identify predictive combinations of short transcription factor binding sites which determine the tissue specificity of the original NGS assay.|
- Deployment page
- Information gained from kmer-SVM can be used as an additional source of confidence in genomic experiments by recovering known binding sites, and can also reveal novel sequence features and possible cooperative mechanisms to be tested experimentally.
- A tutorial on using the web server and a Galaxy Tool Shed repository are also available.
- [Email](mailto:kmersvm DOT team AT gmail DOT com)
- kmer-SVM: a web server for identifying predictive regulatory sequence features in genomic data sets. Christopher Fletez-Brant; Dongwon Lee; Andrew S. McCallion; Michael A. Beer *Nucleic Acids Research* 2013; doi: 10.1093/nar/gkt519
- Kmer-SVM tagged publications in the Galaxy Publication library
- This project is a collaboration between Christopher Fletez-Brant and Dongown Lee respectively of the McCallion Lab of the McKusick-Nathans Institute of Genetic Medicine at the Johns Hopkins University School of Medicine and the Beer Lab of the Johns Hopkins University Department of Biomedical Engineering.