Sloan Kettering Institute
Sloan Kettering Institute
Trey Ideker (UC San Diego) gave a talk on "Building a mind for cancer."
Marinka Zitnik (Harvard Medical School) gave a colloquium entitled "Foundation models for therapeutic design and treatment prediction."
Fabian Theis (Helmholtz Munich) gave a colloquium entitled "Generative AI for modeling single-cell responses."
Mikhail Belkin (UC San Diego) gave a talk entitled "The challenges of training infinitely large neural networks."
Anna Goldenberg (SickKids Research Institute and University of Toronto) gave a colloquium entitled "Time series ML for deployment in healthcare."
Jennifer Listgarten (UC Berkeley) gave a colloquium entitled "Some thoughts on machine-learning based protein engineering."
David Baker (University of Washington) gave a colloquium on "Protein design using deep learning."
Ziad Obermeyer (UC Berkeley) gave a colloquium entitled "Machine earning about sudden cardiac death from ECG waveforms."
Jure Leskovec (Stanford University) gave a colloquium entitled "Towards universal cell embeddings."
While T cells, our immune system's fighter cells, should, in theory, recognize and kill growing tumors, cancer cells send signals to T cells that cause these fighter cells to malfunction. But what if we could modify individual genes in T cells to stop this process — and transform T cells into more effective tumor destroyers? To that end, the Eric and Wendy Schmidt Center and collaborators are calling on machine learning enthusiasts to identify genetic modifications to make T cells better at killing cancer cells. Top submissions will be tested out in a lab at the Broad.
Smita Krishnaswamy (Yale University) gave a colloquium entitled "Multiscale diffusion-based flows and embeddings for molecular and cellular data."
Michael Bronstein (University of Oxford) gave a colloquium on “Geometric deep Learning and applications to proteins.”
Jay Bradner (president of the Novartis Institute for Medical Research) gave a talk on “The new science of therapeutics.”
The workshop brought together experts in biology, computation, and technology development for talks and discussions centered on tissue modelling, cell communication, and machine learning.
Co-hosted with the Klarman Cell Observatory
Yoshua Bengio (founder and scientific director of the Mila - Quebec AI institute) spoke at EWSC's February colloquium.
This workshop featured speakers from multiple disciplines that are taking on some of the toughest challenges at the interface of cellular biology, computational method development — and advances in the technology to power both.
Co-hosted with the Gene Regulation Observatory
G.V. Shivashankar (head of the Laboratory of Nanoscale Biology, Paul Scherrer Institute and Professor of Mechano-Genomics, ETH Zurich) shared insights on understanding the role that mechano-chemical signals play in regulating cell-state transitions.
Bradley Bernstein (director of the Gene Regulation Observatory at the Broad Institute and chair of the Cancer Biology at the Dana-Farber Cancer Institute) researches how changes to the protein scaffold of genes contribute to development and cancer.
Speakers from multiple disciplines shared their insights into taking on some of the toughest challenges at the interface of machine learning and biology.
Co-hosted with the Jameel Clinic
Rick Young (professor of Biology at MIT and core member of the Whitehead Institute) researches gene expression differences in healthy and diseased cells.
A discussion and plenary sessions on the biggest questions driving machine learning in clinical medicine and biology.