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This repository contains R implementation of the algorithms proposed in "Path2Surv: Pathway/gene set-based survival analysis using multiple kernel learning", which is appearing in Bioinformatics. run_survival_random_forest_tcga.R shows how to replicate random forest experiments on TCGA cohorts. run_survival_svm_tcga.R shows how to replicate support vector machine experiments on TCGA cohorts. run_survival_group_lasso_mkl_tcga.R shows how to replicate group Lasso MKL experiments on TCGA cohorts. Path2Surv methods ----------------- * survival_helper.R => helper functions * solve_survival_svm_cplex.R => survival support vector machine solver using CPLEX optimization software * single_kernel_survival_train.R => training procedure for survival support vector machine * single_kernel_survival_test.R => test procedure for survival support vector machine * group_lasso_multiple_kernel_survival_train.R => training procedure for group Lasso MKL * group_lasso_multiple_kernel_survival_test.R => test procedure for group Lasso MKL If you use any of the algorithms implemented in this repository, please cite the following paper: Onur Dereli, Ceyda Oguz, and Mehmet Gonen. Path2Surv: Pathway/gene set-based survival analysis using multiple kernel learning. Bioinformatics, 35(24):5137-5145, 2019.
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Pathway/Gene Set-Based Survival Analysis
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