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 ------------- * 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.