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This repository contains Matlab and R implementations of the algorithms proposed in "Integrating gene set analysis and nonlinear predictive modeling of disease phenotypes using a Bayesian multitask formulation", which is appearing in BMC Bioinformatics.

SBMKL methods
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* sbmkl_supervised_classification_variational_train.m => training procedure for binary classification in Matlab
* sbmkl_supervised_classification_variational_test.m => test procedure for binary classification in Matlab
* sbmkl_supervised_classification_variational_train.R => training procedure for binary classification in R
* sbmkl_supervised_classification_variational_test.R => test procedure for binary classification in R
* sbmtmkl_supervised_classification_variational_train.m => training procedure for multitask binary classification in Matlab
* sbmtmkl_supervised_classification_variational_test.m => test procedure for multitask binary classification in Matlab
* sbmtmkl_supervised_classification_variational_train.R => training procedure for multitask binary classification in R
* sbmtmkl_supervised_classification_variational_test.R => test procedure for multitask binary classification in R

If you use any of the algorithms implemented in this repository, please cite the following paper:

Mehmet Gonen. Integrating gene set analysis and nonlinear predictive modeling of disease phenotypes using a Bayesian multitask formulation. BMC Bioinformatics, 17(Suppl 16):1311, 2016.