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Author

Aidan Winters

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Open access Sep 2026

Tahoe-100M: Mapping drug-induced molecular phenotypes at single-cell resolution.

Tahoe-100M, a giga-scale single-cell perturbation atlas comprising 100 million transcriptomes from 50 diverse cancer cell lines treated with 1,100 drug-dose conditions, advances the ability to model gene regulation, drug response, and network dynamics.

Jesse Zhang, Airol A. Ubas, Valentine Svensson et al. · 8 citations · ⚡2
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. · 4 citations

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