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URPP Human Reproduction Reloaded | H2R

Talks "AI in Genomics", track at AMLD EPFL 2024 on March 25th, organised by Dr. Amina Mollaysa

In recent years, the intersection of machine learning and genomics has revolutionized our understanding of the code of life. From deciphering genetic variations associated with diseases to predicting protein structures and understanding the complexities of gene regulation to using deep learning to improve the function of gene editing tools such as CRISPR. Machine learning become such a powerful tool in genomics. In this track, we aim to explore the transformative potential of machine learning in genomics by bringing together researchers, data scientists, and professionals together. We will delve into the following key areas:

  1. Gene Editing and CRISPR-Cas9: Discuss the applications of machine learning in optimizing CRISPR-Cas9 gene editing techniques, target identification, and off-target prediction.
  2. Single-Cell Genomics: Explore how machine learning models are enhancing our understanding of single-cell RNA sequencing, lineage tracing, and cell type identification.
  3. Drug Discovery and Personalized Medicine: Examine how machine learning is advancing drug discovery by analyzing genomic data and enabling personalized medicine approaches.  

Talks

Charlotte Bunne (PostDoc at Genentech & Stanford, incoming EPFL assistant professor) on "Predicting Patient Treatment Outcomes using Diffusion Models and Optimal Transport." Nicolas Mathis and Kim Fabiano Fassetta (PhD candidates at the University of Zurich, Schwank lab) discussing "Advancing CRISPR-Cas Genome Editing with Machine Learning." Bruno Correia (Associate professor, Laboratory of Protein Design & Immunoengineering, EPFL) shares insights on "Machine Learning Models for Protein Design." Manuel Schürch (Postdoc, Krauthammer lab, University of Zurich) presenting "A Machine Learning Framework for Personalized Counterfactual Treatment Suggestions based on Multi-Omics Data."

Organizer: Amina Mollaysa Co-organizer: Ahmed Alam, Zsolt Balázs, Manuel Schürch

Event details