GeneSrF
Gene selection with random forests.
Info
Members (researchers): Ramon Díaz Uriarte
Research Groups: Bioinformatics and Computational Biology in Cancer Evolution
Contact Email: ramon.diaz@iib.uam.es
Tool Repository: http://genesrf.iib.uam.es/
Documentation: http://genesrf.iib.uam.es/help/genesrf-help.html
Publications DOI: doi:10.1186/1471-2105-8-328
No Institution assigned.
Application domain: Artificial Intelligence, Computational Techniques, Data Analysis, Frequentist analysis, High-performance Computing, Machine Learning in Biology, Multivariate statistics, Non-parametric statistics, Parallel Computing, RNA Sequencing (RNA-seq), Statistical Methods for Biology, Transcriptomics
Technical details
Type of application
- Web-service
Software compatibility
- Linux
- Mac
- Windows
Hardware requirements
Programming language
- Python
- R
Type of containerization
- None
Wrapper type
- None
Input file formats
- csv
Output file formats
- csv
- Other