Would you like to see your presentation here, made available to a global audience of researchers?
Add your own presentation or have us affordably record your next conference.
MicroRNAs (miRNAs) are critical regulators of gene expression. The co-expressed miRNAs, miR-24 and miR-27, are known to restrain T helper 2 (Th2) cell differentiation and the production of cytokines like Interleukin-4 (IL-4), which are central to allergic diseases. However, a comprehensive map of their target network is incomplete. High-throughput sequencing of RNA isolated by crosslinking immunoprecipitation (HITS-CLIP) can identify miRNA targets transcriptome-wide, but analyzing these large datasets to find differential targets between conditions remains a major computational challenge. To address this, we developed DeepRNA-Reg, a novel deep learning algorithm designed for high-fidelity comparative analysis of HITS-CLIP experiments.
