Ensemble of decision tree reveals potential miRNA-disease associations.

ABSTRACT: In recent years, increasing associations between microRNAs (miRNAs) and human diseases have been identified. Based on accumulating biological data, many computational models for potential miRNA-disease associations inference have been developed, which saves time and expenditure on experimental studies, making great contributions to researching molecular mechanism of human diseases and developing new drugs for disease treatment. In this paper, we proposed a novel computational method named Ensemble of Decision Tree based MiRNA-Disease Association prediction (EDTMDA), which innovatively built a computational framework integrating ensemble learning and dimensionality reduction. For each miRNA-disease pair, the feature vector was extracted by calculating the statistical measures, graph theoret

SUBMITTER: Chen X 

PROVIDER: S-EPMC6675125 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature