LADE Meeting

Abstract

Recent advancements in deep learning, particularly in sequence modeling, have revolutionized our ability to analyze and understand complex biological data, paving the way for advancements in precision medicine, drug discovery, and synthetic biology. Potential applications range from predicting the clinical impact of mutations in the human genome to designing entirely new organisms from scratch. In this talk, we will look at some recently developed models for studying of DNA and protein sequences. Later, we will explore the possibility of examining and comparing the representations emerging from the intermediate layers of these models using current analytical techniques.