Author

Dave P. Burke

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Open access Aug 2026

Predicting cellular responses to perturbation across diverse contexts with State.

The performance and flexibility of State set the stage for scaling the development of AI models of cell state, a machine learning model that predicts perturbation effects while accounting for cellular heterogeneity within and across experiments.

Abhinav K. Adduri, Dhruv Gautam, Beatrice Bevilacqua et al. · Cell · 2 citations

Open access Sep 2026

scBaseCount: An AI agent-curated, standardized, auto-updated single-cell data repository.

Single-cell RNA sequencing has transformed cell biology by enabling precise transcriptomic measurements of individual cells. The Sequence Read Archive (SRA) is the largest public repository of sequencing reads, yet much of it remains underutilized due to unstandardized metadata. Here, we introduce scBaseCount, a databa...

Nicholas D. Youngblut, Christopher Carpenter, Arshia Nayebnazar et al. · Cell · 1 citation