Prioritizes candidate miRNA-disease pairs for further biological experiment validation. IRWRMDA is a computational model developed to infer potential associations between miRNAs and investigated diseases. This method achieves reliable prediction performance with under the curve in leave one out cross validation framework. It can also provide data sources such as miRNA expression data, disease-related miRNA-environmental factor interactions, and disease-related miRNA-target interactions to enhance the robustness of SPYSMDA.
School of Electronics and Information Engineering, Tongji University, Shanghai, China
IRWRMDA funding source(s)
Supported by the grants of the National Science Foundation of China 61472282, 61520106006, 31571364, U1611265, 61672203, 61402334, 61472280, 61532008, 61472173, 61572447, 61373098 and 61672382; China Postdoctoral Science Foundation, Grant 2016M601646.