Allows users to identify the miRNA signature associated with the survival time of patients with lung adenocarcinoma. SVR-LUAD is based on support vector regression (SVR) and uses an inheritable bi-objective combinatorial genetic algorithm (IBCGA) to identify informative miRNAs associated with the estimation of lung adenocarcinoma survival time. The algorithm was tested using lung adenocarcinoma patients obtained from the TCGA database.
Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, Taiwan; Department of Biological Science and Technology, National Chiao Tung University, Hsinchu, Taiwan
SVR-LUAD funding source(s)
Supported by the National Science Council of Taiwan (MOST-105-2627-M-009-008- and MOST-105-2221-E-009-138-MY2-); “Center for Bioinformatics Research of Aiming for the Top University Program” of National Chiao Tung University; and the Ministry of Education, Taiwan, R.O.C. for the project 105W962.