Understanding transcriptome methylation using machine learning

Understanding transcriptome methylation using machine learning

Dr. Yufei Huang, Professor  UTSA Electrical and Computer Engineering

Transcriptome methylation is an exciting, emerging area that studies methylation in the transcriptome. In contrast to well-established DNA methylation, transcriptome methylation is largely an uncharted territory. In this talk, I will report our recent effort in developing machine learning tools to predict transcriptome wide N6-methyl-adenosine (m6A) methylation sites, context specific differential m6A methylation sites, and driver m6A sites from high throughput sequencing data. I will also report how we use these tools to elucidate the dynamics of transcriptome wide m6A methylation in the course of Kaposi’s sarcoma-associated herpesvirus (KSHV) infection of mammalian cells. I will conclude the talk with discussion on the outlook and future directions of this area.

Friday, November 10th

FLN 4.01.20

4:00 – 5:00 PM