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Select Track: 3DSIG: Structural Bioinformatics and Computational Biophysics | BioInfo-Core | Bioinfo4Women Meet-Up | Bioinformatics in the UK | BioVis: Biological Data Visualizations | BOKR: Bio-Ontologies and Knowledge Representation | BOSC: Bioinformatics Open Source Conference | CAMDA: Critical Assessment of Massive Data Analysis | CollaborationFest | CompMS: Computational Mass Spectrometry | CSI: Computational Systems Immunology | Distinguished Keynotes | DREAM Challenges | Education: Computational Biology and Bioinformatics Education and Training | ELIXIR/NIH-ODSS | Equity-Focused Research | EvolCompGen: Evolution & Comparative Genomics | Fellows Presentation | Function: Gene and Protein Function Annotation | GenCompBio: General Computational Biology | HiTSeq: High Throughput Sequencing Algorithms & Applications | Innovation at the Intersection: Industry's Role in Bioinformatics | iRNA: Integrative RNA Biology | ISCB-China Workshop | JPI: Junior Principal Investigators | MICROBIOME | MLCSB: Machine Learning in Computational and Systems Biology | NetBio: Network Biology | NIH Track on GenAI, Cyberinfrastructure, Digital Twins, and Quantum Computing | Publications - Navigating Journal Submissions | RegSys: Regulatory and Systems Genomics | SCS: Student Council Symposium | Special Track | Stewardship Critical Infrastructure | SysMod: Computational Modeling of Biological Systems | Tech Track | Text Mining: Text Mining for Healthcare and Biology | TransMed: Translational Medicine Informatics & Applications | Tutorials | VarI: Variant Interpretation | WEB: Workshop on Education for Bioinformatics | 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 | Extending AlphaFold to make predictions across the universe of biomolecular interactions | John Jumper | The high accuracy of AlphaFold 2 in predicting protein structures and protein-protein interactions raises the question of how to extend the success of AlphaFold to general biomolecular modeling, including protein-nucleic and protein-small molecule structure predictions as well as the effects of post-translational modification. In this talk, I will discuss our latest work on AlphaFold 3 to develop a single deep learning system that makes accurate predictions across these interaction types, as well as examine some of the remaining challenges in predicting the universe of biologically-relevant protein interactions. | ||
| 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 | Amos Bairoch | Amos Bairoch will reflect on 40 years of biocuration, from Swiss-Prot to Cellosaurus, highlighting how core challenges and values have endured despite the many developments in computational biology over that time. | |
| 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 | Computational biology in the age of AI agents | James Zou | James Zou | AI agents—large language models equipped with tools and reasoning capabilities-are emerging as powerful research enablers. This talk will explore how computational biology is particularly well-positioned to benefit from rapid advances in agentic AI. I’ll first introduce the Virtual Lab—a collaborative team of AI scientist agents conducting in silico research meetings to tackle open-ended research projects. As an example application, the Virtual Lab designed new nanobody binders to recent Covid variants that we experimentally validated. Then I will present CellVoyager, a data science agent that analyzes complex genomics data to derive new insights. Finally I will discuss using AI agents to discover and explain new biological concepts encoded by large protein foundation models (interPLM). I will conclude by discussing limits of agents and a roadmap for human researcher-AI collaboration. | |
| 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 | Building the future of AI-driven structure-based drug discovery | Charlotte Deane | Charlotte Deane | The development of new therapeutics typically takes many years and requires over $1bn in investment. Computational methods and in particular, machine learning, have shown great promise for increasing the speed and reducing the cost of therapeutic development. In this talk I will describe some of the novel computational tools and databases we are pioneering from accurate rapid structure prediction to the prediction of their affinity and binding, looking at both their promise and limitations. | |
| 2025-07-24 | 16:20:00 | 18:00:00 | 01A | Distinguished Keynotes | Decoding cellular systems: From observational atlases to generative interventions | Fabian Theis | 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. | |
| 2025-07-24 | 16:20:00 | 18:00:00 | Distinguished Keynotes | A Conversation with Nobel Laureate David Baker: Inspiration from a Life in Science | David Baker | This special fireside chat features Nobel Laureate David Baker in a candid and inspiring conversation with Christine Orengo. Rather than exploring the technical details of his groundbreaking research, this 20-minute session will highlight the moments, mindsets, and motivations that shaped his journey—from early curiosity to Nobel recognition. Together, they’ll reflect on the role of creativity, perseverance, and vision in scientific discovery, offering insight and encouragement for the next generation of researchers. |