Talk 7.6: 3:15PM–4:15PM
| Session Name: | Biomedical Applications and Artificial Perception |
| Session Time: | 3:15PM–4:15PM |
| Author Name: | Jim C Huang |
| Author Email: | jim@psi.toronto.edu |
| Talk Title: | Computational Discovery of Functional MicroRNA Targets in Cancer |
| Slides: | 7-6.ppt |
| Abstract: | Micro (mi) RNAs are short noncoding transcripts that post-transcriptionally regulate gene expression by sequence-specific interaction. Hundreds of miRNAs have been identified in humans with thousands of predicted mRNA targets. However, despite rapid advances in miRNA identification, accurate determination of targets has slowed their functional characterization in animals. Here we present a novel computational method called GenMiR++ to discover a regulatory network of functional miRNA-mRNA interactions using sequence and expression data. Using this method, we find that tissue-specific patterns of expression of miRNA-targeted genes are surprisingly predictive of whether miRNA-mRNA interactions are functional in other tissues. We show that our targetting network is an improvement over predictions generated using solely sequence-based approaches and directly demonstrate its biological relevance by exploring miRNA misregulation in retinoblastoma. We found that downregulation of let-7b in retinoblastoma correlated with elevated levels of GenMiR targets, including CDC25A and BCL7A, which were reduced in response to let-7b. Our miRNA regulatory network provides a large-scale resource of functional targets that will accelerate exposition of miRNA biological roles in cancer. |
| Research Group: | Communications |
| Degree Program: | Ph.D. |
| Author Bio: | Jim C. Huang is a Ph.D. candidate in the Probabilistic and Statistical Inference Group in the Electrical and Computer Engineering Department at the University of Toronto. He obtained his B.Eng. with great distinction in Electrical Engineering at McGill University in 2004 and has recently interned with the Machine Learning and Perception group at Microsoft Research Cambridge in the UK. His current research interests span the fields of machine learning and applications thereof to problems in bioinformatics and computer vision. |