Planning
Time |
Event |
(+)
|
09:45 - 10:00
|
Introduction |
|
10:00 - 11:00
|
Keynote: Harnessing AI in phylogenomics - Tal Pupko |
|
11:00 - 11:30
|
Realistic data simulation - Franz Baumdicker |
(+)
|
11:00 - 11:30 |
› Assessing usefulness of artificial genomes via local ancestry inference - Antoine Szatkownik, Laboratoire Interdisciplinaire des Sciences du Numérique |
|
11:30 - 12:00
|
Coffee break |
|
12:00 - 13:00
|
Realistic data simulation - Franz Baumdicker |
(+)
|
12:00 - 12:30 |
› 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 |
|
12:30 - 13:00 |
› 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 |
|
13:00 - 14:30
|
Lunch |
|
14:30 - 15:30
|
Keynote: Deep learning for the phylogenetic inference of species diversification - Hélène Morlon |
|
15:30 - 16:30
|
Phylogenetics - Alexandros Stamatakis |
(+)
|
15:30 - 16:00 |
› Phyloformer: Towards fast and accurate phylogeny reconstruction with self-attention networks - Luca Nesterenko, Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 |
|
16:00 - 16:30 |
› Learning from an Artificial Neural Network in Phylogenetics - Alina Leuchtenberger, Max Perutz Labs, Medical University of Vienna |
|
16:30 - 17:00
|
Coffee break |
|
17:00 - 18:00
|
Phylogenetics - Alexandros Stamatakis |
(+)
|
17:00 - 17:30 |
› Neural networks can predict ghost species diversity from gene transfers - Enzo Marsot, Max-Planck-Institut für Biochemie = Max Planck Institute of Biochemistry |
|
17:30 - 18:00 |
› Predicting Phylogenetic Bootstrap Values via Machine Learning - Julius Wiegert, Heidelberg Institute for Theoretical Studies |
|
18:00 - 19:00
|
Poster session |
|
Time |
Event |
(+)
|
09:00 - 10:00
|
Keynote: Generative adversarial networks, transfer learning, and interpretability for evolutionary inference - Sara Mathieson |
|
10:00 - 11:00
|
Predictions on a single sequence - Laurent Jacob |
(+)
|
10:00 - 10:30 |
› 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 |
|
10:30 - 11:00 |
› Deciphering Deep Phylogeny and Evolution of Protein Families through Protein Language Models - Ivan Koludarov, Institut für Informatik |
|
11:00 - 11:30
|
Coffee break |
|
11:30 - 13:30
|
Predictions on a single sequence - Laurent Jacob |
(+)
|
11:30 - 12:00 |
› Classification of the evolutionary origin of orphan genes using machine learning approaches - Nikolaos Vakirlis, Biomedical Sciences Research Centre Alexander Fleming [Vari, Greece] |
|
12:00 - 12:30 |
› Unsupervised learning as a tool to retrieve genomes from undersampled taxa: Fast and slow evolution in myxozoans - Claudia Weber, Wellcome Sanger Institute |
|
12:30 - 13:00 |
› 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] |
|
13:00 - 13:30 |
› Interpreting artificial neural networks for detecting genome-wide association signals for complex traits - Burak Yelmen, Institute of Genomics [Tartu, Estonia], LISN |
|
13:30 - 14:30
|
Lunch |
|
14:30 - 17:30
|
Hike at Sroumpoulas - Hike at Sroumpoulas |
|
Time |
Event |
(+)
|
09:00 - 10:00
|
Keynote: Inference of Coalescence Times and Variant Ages Using Convolutional Neural Networks - Pier Palamara |
|
10:00 - 11:00
|
Population genetics - Nikolaos Alachiotis |
(+)
|
10:00 - 10:30 |
› Using supervised machine learning methods to infer demographic history from genomic data - Arnaud Quelin, Éco-Anthropologie, Laboratoire Interdisciplinaire des Sciences du Numérique |
|
10:30 - 11:00 |
› Unifying Ideas from the Sequentially Markovian Coalescence with Deep Learning for Population Genomic Inference - Kevin Korfmann, Technische Universität München = Technical University of Munich |
|
11:00 - 11:30
|
Coffee break |
|
11:30 - 13:00
|
Detecting positive selection - Flora Jay |
(+)
|
11:30 - 12:00 |
› Scalable CNN-based classification of selective sweeps using derived allele frequencies - Sjoerd Van den Belt, University of Twente |
|
11:30 - 12:00 |
› Detecting selective sweeps using FPGA-accelerated spiking convolutional neural networks - Hanqing Zhao, University of Twente |
|
12:30 - 13:00 |
› Detecting Positive Selection using Convolutional Neural Networks - Charlotte West, European Bioinformatics Institute [Hinxton] |
|
13:00 - 14:30
|
Lunch |
|
14:30 - 16:00
|
Phylodynamics - Flora Jay |
(+)
|
14:30 - 15:00 |
› 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 |
|
15:00 - 15:30 |
› 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 |
|
15:30 - 16:00 |
› Assessing the power of artificial intelligence approaches for birth-death model classification - Pablo Gutiérrez de la Peña, Real Jardín Botánico - CSIC |
|
16:00 - 16:15
|
Closing comments |
|
16:15 - 18:00
|
After conference chill out (posters can still hang until 18h) |
|
20:00 - 22:00
|
Conference dinner downtown Heraklion |
|
|