Brief Communication: Identifying the target mRNAs of microRNAs in colorectal cancer
Computational Biology and Chemistry
Discovery of functional miRNA-mRNA regulatory modules with computational methods
Journal of Biomedical Informatics
A tripartite clustering analysis on microRNA, gene and disease model
Proceedings of the 2nd ACM Conference on Bioinformatics, Computational Biology and Biomedicine
Computers in Biology and Medicine
Computers in Biology and Medicine
| Hi-index | 3.84 |
Motivation: MicroRNAs (miRNAs) are small endogenous RNAs that can play important regulatory roles via the RNA-interference pathway by targeting mRNAs for cleavage or translational repression. We propose a computational method to predict miRNA regulatory modules (MRMs) or groups of miRNAs and target genes that are believed to participate cooperatively in post-transcriptional gene regulation. Results: We tested our method with the human genes and miRNAs, predicting 431 MRMs. We analyze a module with genes: BTG2, WT1, PPM1D, PAK7 and RAB9B, and miRNAs: miR-15a and miR-16. Review of the literature and annotation with Gene Ontology terms reveal that the roles of these genes can indeed be closely related in specific biological processes, such as gene regulation involved in breast, renal and prostate cancers. Furthermore, it has been reported that miR-15a and miR-16 are deleted together in certain types of cancer, suggesting a possible connection between these miRNAs and cancers. Given that most known functionalities of miRNAs are related to negative gene regulation, extending our approach and exploiting the insight thus obtained may provide clues to achieving practical accuracy in the reverse-engineering of gene regulatory networks. Availability: A list of predicted modules is available from the authors upon request. Contact: sryoon@stanford.edu