LE-MDCAP: A Computational Model to Prioritize Causal miRNA-Disease Associations.

ABSTRACT: MicroRNAs (miRNAs) are associated with various complex human diseases and some miRNAs can be directly involved in the mechanisms of disease. Identifying disease-causative miRNAs can provide novel insight in disease pathogenesis from a miRNA perspective and facilitate disease treatment. To date, various computational models have been developed to predict general miRNA-disease associations, but few models are available to further prioritize causal miRNA-disease associations from non-causal associations. Therefore, in this study, we constructed a Levenshtein-Distance-Enhanced miRNA-disease Causal Association Predictor (LE-MDCAP), to predict potential causal miRNA-disease associations. Specifically, Levenshtein distance matrixes covering the sequence, expression and functional miRNA similariti

SUBMITTER: Huang Z 

PROVIDER: S-EPMC8706837 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature