Integration of Multiple Genomic and Phenotype Data to Infer Novel miRNA-Disease Associations.

ABSTRACT: MicroRNAs (miRNAs) play an important role in the development and progression of human diseases. The identification of disease-associated miRNAs will be helpful for understanding the molecular mechanisms of diseases at the post-transcriptional level. Based on different types of genomic data sources, computational methods for miRNA-disease association prediction have been proposed. However, individual source of genomic data tends to be incomplete and noisy; therefore, the integration of various types of genomic data for inferring reliable miRNA-disease associations is urgently needed. In this study, we present a computational framework, CHNmiRD, for identifying miRNA-disease associations by integrating multiple genomic and phenotype data, including protein-protein interaction data, gene onto

SUBMITTER: Shi H 

PROVIDER: S-EPMC4743935 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature