Satellite Workshop Series
We are excited to present our Satellite workshop series, developed with academic and industry partners across the Bay Area. Workshops will take place in parallel on November 19th.
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Location: Tahoe Therapeutics, 681 Gateway Blvd. South San Francisco, CA, 94080
This session will focus on how large-scale perturbation datasets are enabling new capabilities in disease biology and translational science — moving from static maps to predictive models and controllable systems. We encourage submissions on the following or related topics:
Novel drug mechanisms revealed through transcriptomic mimicry and perturbation signatures
Functional mapping of immune and cancer disease programs
Predictive modeling for drug response, resistance, and toxicity
Systems-level frameworks for therapeutic interventions
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Location: Chan Zuckerberg Initiative HQ, 1180 Main St, Redwood City, CA 94063
This workshop will provide an in-depth look at the latest progress in the CZ models and data ecosystem. We will begin with a recap of the foundational CELLxGENE Census resource and its role in model training. We will then explore the exciting addition of spatial data to the Census, and the explosion of new model development efforts it has inspired, both externally and internally at CZI-AI. Participants will be introduced to the new Virtual Cells Platform (VCP), a unified platform for models, data, workflows, and benchmarks. Finally, we will cover the importance of standardized model packaging using MLFlow and introduce the CZ Benchmarks platform for transparent and reproducible model evaluation.
We also invite scientists, professionals, and developers working in the fields of computational biology to submit proposals for Tutorials and workshops at the scverse conference 2025. The purpose of the Tutorials and Workshops program is to build knowledge and provide hands-on training sessions on relevant packages within the scverse community. Workshops can be of any form, ranging from presentations to brief talks or panel discussions, but should also include hands-on exercises.
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Location: Arc Institute, 3181 Porter Dr, Palo Alto, CA 94304
This workshop will focus on practical strategies for handling data from Perturb-seq experiments, including preprocessing pipelines, performing differential expression analysis, and selecting optimal target genes for genome-scale screening. Participants will also learn how to construct scalable data loaders and train machine learning models to predict perturbation effects. The session will include hands-on guidance for working with perturbation data through packages and tutorials put together by the Arc team.
