Planning

Week Mon. 13 Tue. 14 Wed. 15 List

	Mon. 13	Tue. 14	Wed. 15
09:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00	Introduction 9:45 - 10:00 (15min) Introduction Keynote: Harnessing AI in phylogenomics 10:00 - 11:00 (1h) Keynote: Harnessing AI in phylogenomics Tal Pupko Realistic data simulation 11:00 - 11:30 (30min) Realistic data simulation Franz Baumdicker › Assessing usefulness of artificial genomes via local ancestry inference - Antoine Szatkownik, Laboratoire Interdisciplinaire des Sciences du Numérique 11:00-11:30 (30min) Coffee break 11:30 - 12:00 (30min) Coffee break Realistic data simulation 12:00 - 13:00 (1h) Realistic data simulation Franz Baumdicker › Simulations of Sequence Evolution: How (Un)realistic They Are and Why - Johanna Trost, Université Claude Bernard Lyon 1 - Julia Haag, Heidelberg Institute for Theoretical Studies - Dimitri Höhler, Heidelberg Institute for Theoretical Studies - Laurent Jacob, Sorbonne Université 12:00-12:30 (30min) › Fitting Indel Evolution Model Parameters to PFam Protein Alignments with a GPU-accelerated Framework - Annabel Large, Department of Bioengineering; University of California, Berkeley, Joint Bioengineering Graduate Group; University of California, Berkeley and University of California, San Francisco 12:30-13:00 (30min) Lunch 13:00 - 14:30 (1h30) Lunch Keynote: Deep learning for the phylogenetic inference of species diversification 14:30 - 15:30 (1h) Keynote: Deep learning for the phylogenetic inference of species diversification Hélène Morlon Phylogenetics 15:30 - 16:30 (1h) Phylogenetics Alexandros Stamatakis › Phyloformer: Towards fast and accurate phylogeny reconstruction with self-attention networks - Luca Nesterenko, Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 15:30-16:00 (30min) › Learning from an Artificial Neural Network in Phylogenetics - Alina Leuchtenberger, Max Perutz Labs, Medical University of Vienna 16:00-16:30 (30min) Coffee break 16:30 - 17:00 (30min) Coffee break Phylogenetics 17:00 - 18:00 (1h) Phylogenetics Alexandros Stamatakis › Neural networks can predict ghost species diversity from gene transfers - Enzo Marsot, Max-Planck-Institut für Biochemie = Max Planck Institute of Biochemistry 17:00-17:30 (30min) › Predicting Phylogenetic Bootstrap Values via Machine Learning - Julius Wiegert, Heidelberg Institute for Theoretical Studies 17:30-18:00 (30min) Poster session 18:00 - 19:00 (1h) Poster session	Keynote: Generative adversarial networks, transfer learning, and interpretability for evolutionary inference 9:00 - 10:00 (1h) Keynote: Generative adversarial networks, transfer learning, and interpretability for evolutionary inference Sara Mathieson Predictions on a single sequence 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) Coffee break 11:00 - 11:30 (30min) Coffee break Predictions on a single sequence 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) Lunch 13:30 - 14:30 (1h) Lunch Hike at Sroumpoulas 14:30 - 17:30 (3h) Hike at Sroumpoulas Hike at Sroumpoulas	Keynote: Inference of Coalescence Times and Variant Ages Using Convolutional Neural Networks 9:00 - 10:00 (1h) Keynote: Inference of Coalescence Times and Variant Ages Using Convolutional Neural Networks Pier Palamara Population genetics 10:00 - 11:00 (1h) Population genetics Nikolaos Alachiotis › Using supervised machine learning methods to infer demographic history from genomic data - Arnaud Quelin, Éco-Anthropologie, Laboratoire Interdisciplinaire des Sciences du Numérique 10:00-10:30 (30min) › Unifying Ideas from the Sequentially Markovian Coalescence with Deep Learning for Population Genomic Inference - Kevin Korfmann, Technische Universität München = Technical University of Munich 10:30-11:00 (30min) Coffee break 11:00 - 11:30 (30min) Coffee break Detecting positive selection 11:30 - 13:00 (1h30) Detecting positive selection Flora Jay › Scalable CNN-based classification of selective sweeps using derived allele frequencies - Sjoerd Van den Belt, University of Twente 11:30-12:00 (30min) › Detecting selective sweeps using FPGA-accelerated spiking convolutional neural networks - Hanqing Zhao, University of Twente 11:30-12:00 (30min) › Detecting Positive Selection using Convolutional Neural Networks - Charlotte West, European Bioinformatics Institute [Hinxton] 12:30-13:00 (30min) Lunch 13:00 - 14:30 (1h30) Lunch Phylodynamics 14:30 - 16:00 (1h30) Phylodynamics Flora Jay › Improving tree representation and neural network architecture for deep learning from phylogenies in phylodynamics and diversification studies - Manolo Perez, Muséum national d'Histoire naturelle, Imperial College London 14:30-15:00 (30min) › Transformers for EpiDemiological DYnamics: from genomic data to epidemiological parameters - Vincent GAROT, Biologie Computationnelle et Quantitative = Laboratory of Computational and Quantitative Biology, Centre interdisciplinaire de recherche en biologie 15:00-15:30 (30min) › Assessing the power of artificial intelligence approaches for birth-death model classification - Pablo Gutiérrez de la Peña, Real Jardín Botánico - CSIC 15:30-16:00 (30min) Closing comments 16:00 - 16:15 (15min) Closing comments After conference chill out (posters can still hang until 18h) 16:15 - 18:00 (1h45) After conference chill out (posters can still hang until 18h) Conference dinner downtown Heraklion 20:00 - 22:00 (2h) Conference dinner downtown Heraklion

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