Biology presents some of the most complex and high-impact challenges for machine learning, and single-cell transcriptomics is at the frontier of this work. In this workshop, we introduce the Virtual Cell Platform (VCP), a unified environment designed to accelerate model development and evaluation in biology. Using single-cell transcriptomics as a case study, we will demonstrate how the VCP enables researchers to train, benchmark, and interpret models in a reproducible and biologically meaningful way.

Participants will gain a primer on single-cell transcriptomics and learn how to evaluate models with cz-benchmarks, an open-source Python package providing standardized, community-driven tasks and metrics. Through the VCP CLI, attendees will pull datasets, run packaged models, and compare results programmatically. Hands-on exercises will guide participants through interactive visualizations, side-by-side model comparisons, and deep dives into model behavior using VCP’s no-code interface and BYOD (Bring Your Own Data) module.

By the end of the session, attendees will understand how to use the VCP to actively test and refine models during development, ensure biological relevance, and contribute models and benchmarks back to the community. This workshop highlights how the Virtual Cell Platform transforms ML infrastructure into a one-stop, researcher-friendly ecosystem, empowering the NeurIPS community to push the boundaries of AI in biology.