AI in Life Sciences
Custom Machine-Learning Models for Genomes and Evolution
PD Dr. Katharina Hoff and Prof. Dr. Mario Stanke
Biological sequences such as genomes and proteins can be thought of as texts written in a language that was not invented by humans. While methods from so-called natural language processing have brought powerful new tools to biology, the most accurate approaches often are tailored to the specific rules of life’s code. In this talk, we will present machine-learning methods to uncover the locations of genes and their exon–intron structures in genomes, and to reconstruct where insertions and deletions have occurred during evolution, as well as distinguishing the underlying mutational processes that shape genetic variation.