Return to ISMB/ECCB 2025 Homepage Click here for the abridged agenda
Select Track: 3DSIG | Bio-Ontologies and Knowledge Representation | BioInfo-Core | Bioinfo4Women Meet-Up | Bioinformatics in the UK | BioVis | BOSC | CAMDA | CollaborationFest | CompMS | Computational Systems Immunology | Distinguished Keynotes | Dream Challenges | Education | Equity and Diversity | EvolCompGen | Fellows Presentation | Function | General Computational Biology | HiTSeq | iRNA | ISCB-China Workshop | JPI | MICROBIOME | MLCSB | NetBio | NIH Cyberinfrastructure and Emerging Technologies Sessions | NIH/Elixir | Publications - Navigating Journal Submissions | RegSys | Special Track | Stewardship Critical Infrastructure | Student Council Symposium | SysMod | Tech Track | Text Mining | The Innovation Pipeline: How Industry & Academia Can Work Together in Computational Biology | TransMed | Tutorials | VarI | WEB 2025 | Youth Bioinformatics Symposium | All
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| Date | Start Time | End Time | Room | Track | Title | Confrimed Presenter | Format | Authors | Abstract |
|---|---|---|---|---|---|---|---|---|---|
| 2025-07-20 | 18:30:00 | 19:30:00 | 01A | Distinguished Keynotes | John Jumper | ||||
| 2025-07-21 | 08:40:00 | 09:00:00 | 01A | Distinguished Keynotes | Morning Welcome and Keynote Introduction | ||||
| 2025-07-21 | 09:00:00 | 10:00:00 | 01A | Distinguished Keynotes | Plus ça change, plus c'est la même chose | Amos Bairoch | |||
| 2025-07-22 | 08:40:00 | 09:00:00 | 01A | Distinguished Keynotes | Morning Welcome and Keynote Introduction | ||||
| 2025-07-22 | 09:00:00 | 10:00:00 | 01A | Distinguished Keynotes | James Zou | ||||
| 2025-07-23 | 08:40:00 | 09:00:00 | 01A | Distinguished Keynotes | Morning Welcome and Keynote Introduction | ||||
| 2025-07-23 | 09:00:00 | 10:00:00 | 01A | Distinguished Keynotes | Charlotte Deane | ||||
| 2025-07-24 | 16:20:00 | 18:00:00 | 01A | Distinguished Keynotes | Decoding cellular systems: From observational atlases to generative interventions | David Baker, David Baker, Fabian Theis | Over the past decade, the field of computational cell biology has undergone a transformation — from cataloging cell types to modeling how cells behave, interact, and respond to perturbations. In this talk, I will review and explore how machine learning is enabling this shift, focusing on two converging frontiers: integrated cellular mapping and actionable generative models. I’ll begin with a brief overview of recent advances in representation learning for atlas-scale integration, highlighting work across the Human Cell Atlas and beyond. These efforts aim to unify diverse single-cell and spatial modalities into shared manifolds of cellular identity and state. As one example, I will present our recent multimodal atlas of human brain organoids, which integrates transcriptomic variation across development and lab protocols. From there, I’ll review the emerging landscape of foundation models in single-cell genomics, including our work on Nicheformer, a transformer trained on millions of spatial and dissociated cells. These models offer generalizable embeddings for a range of tasks—but more importantly, they set the stage for predictive modeling of biological responses. I’ll close by introducing perturbation models leveraging generative AI to model interventions on these systems. As example I will show Cellflow, a generative framework that learns how perturbations such as drugs, cytokines or gene edits — shift cellular phenotypes. It enables virtual experimental design, including in silico protocol screening for brain organoid differentiation. This exemplifies a move toward models that not only interpret biological systems, but help shape them. |