Machine Learning for Evolutionary Genomics Data

9:00 - 10:00 (1h)

Keynote: Generative adversarial networks, transfer learning, and interpretability for evolutionary inference

Sara Mathieson

10:00 - 11:00 (1h)

Predictions on a single sequence

Laurent Jacob

› Illuminating the functional landscape of the dark proteome across the Animal Tree of Life through natural language processing models - Gemma I. Martínez-Redondo, Institute of Evolutionary Biology (CSIC-UPF), Passeig marítim de la Barceloneta 37-49, 08003 Barcelona, Spain 10:00-10:30 (30min)

› Deciphering Deep Phylogeny and Evolution of Protein Families through Protein Language Models - Ivan Koludarov, Institut für Informatik 10:30-11:00 (30min)

11:00 - 11:30 (30min)

Coffee break

11:30 - 13:30 (2h)

Predictions on a single sequence

Laurent Jacob

› Classification of the evolutionary origin of orphan genes using machine learning approaches - Nikolaos Vakirlis, Biomedical Sciences Research Centre Alexander Fleming [Vari, Greece] 11:30-12:00 (30min)

› Unsupervised learning as a tool to retrieve genomes from undersampled taxa: Fast and slow evolution in myxozoans - Claudia Weber, Wellcome Sanger Institute 12:00-12:30 (30min)

› Long context windows improve deep learning methods for predicting genomic regulation - Ian Holmes, University of California [Berkeley], Calico Life Sciences LLC, Lawrence Berkeley National Laboratory [Berkeley] 12:30-13:00 (30min)

› Interpreting artificial neural networks for detecting genome-wide association signals for complex traits - Burak Yelmen, Institute of Genomics [Tartu, Estonia], LISN 13:00-13:30 (30min)

13:30 - 14:30 (1h)

Lunch

14:30 - 17:30 (3h)

Hike at Sroumpoulas

Planning