BDVAL is an acronym for Biomarker Discovery and VALidation. BDVAL is an open source project for biomarker discovery in high-throughput datasets. The program is distributed under the GNU General Public License (GPL). See the download page for the most recent distribution. BDVal can process microarray and proteomics datasets to discover and validate biomarkers.

• BDVal directly supports many kinds of classifiers: it can train weka and libSVM classifiers.
• BDVal supports various feature selection strategy and validation protocols: SVM weights (Support Vector Machine), recursive feature elimination, genetic algorithm wrappers, T-Test, Fold-Change, and any sensible combination of these strategies. Leave one out, stratified cross validation with random repeats are all supported.
• BDVal leverages biological information: gene lists and pathway information can be used during for a priori feature selection or feature aggregation.
• BDVal is a high-performance program: it takes advantage of multi-threaded machines transparently.
• BDVal is highly portable: it runs on a laptop computer or a multi-processor SMP machine without recompilation (thanks to Java)
• BDVal output is fully reproducible: all steps of discovery and validation are automated. Random seeds can be controlled. The program generates detailed validation statistics and detailed model information output. Results are fully reproducible.
• BDVal is robust: the program has been used in the MAQC-II community evaluation of biomarker discovery approaches.

Flexibility and modularity of the BDVAL software design allows various feature selection methods to be combined easily. Feature selection strategies can be automated.