Planning

Monday, May 13, 2024

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  

Tuesday, May 14, 2024

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  

Wednesday, May 15, 2024

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  
Online user: 2 Privacy
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