ABSTRACT
The convergence of artificial intelligence (AI) and machine learning (ML) with the field of RNA biology has ushered in a new era of scientific discovery, providing unprecedented insights into the complexities of RNA regulation at the molecular level. By analysing large datasets and incorporating domain knowledge, AI/ML provides unique opportunities to decode RNA biology, characterising the composition and structure of RNA, uncovering RNA functions, deciphering the intricate regulatory networks that control their activity, and assessing their relevance and changes in disease. In this talk, I will provide an overview of my early and more recent applications of AI/ML to RNA biology and share future directions for using AI/ML to tackle key challenges in RNA research and biomedical applications.

BIOGRAPHY
Eduardo Eyras’ career in Computational Biology began in 2001 at the Sanger Institute, creating early tools for alternative splicing prediction while contributing to multiple international genome projects. From 2006, as an ICREA Professor at Pompeu Fabra University, he pioneered machine learning approaches in RNA biology. Since 2019, as EMBL Australia Group Leader at ANU, his team develops AI-based methods for RNA biology, with a strong focus on long-read sequencing, RNA modifications, and protein-RNA interactions. Beyond research, he mentors early-career scientists, fosters interdisciplinary collaborations, and contributes to national initiatives in RNA technology and high-performance computing. His goal is to contribute with tools and discoveries that improve human health while nurturing the next generation of scientists.