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9:45 - 10:00 (15min)
Introduction
10:00 - 11:00 (1h)
Keynote: Harnessing AI in phylogenomics
Tal Pupko
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)
11:30 - 12:00 (30min)
Coffee break
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)
13:00 - 14:30 (1h30)
Lunch
14:30 - 15:30 (1h)
Keynote: Deep learning for the phylogenetic inference of species diversification
Hélène Morlon
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)
16:30 - 17:00 (30min)
Coffee break
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)
18:00 - 19:00 (1h)
Poster session
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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
Hike at Sroumpoulas
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9:00 - 10:00 (1h)
Keynote: Inference of Coalescence Times and Variant Ages Using Convolutional Neural Networks
Pier Palamara
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)
11:00 - 11:30 (30min)
Coffee break
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)
13:00 - 14:30 (1h30)
Lunch
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)
16:00 - 16:15 (15min)
Closing comments
16:15 - 18:00 (1h45)
After conference chill out (posters can still hang until 18h)
20:00 - 22:00 (2h)
Conference dinner downtown Heraklion
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