Author

B. Eraslan

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Open access Oct 2026

PIE: Generalizing perturbation effects across unseen perturbations, contexts and datasets

Predicting cellular response to perturbations is key to understanding biological mechanisms and selecting therapeutic targets. However, generalizing across cellular contexts, perturbations, and experimental datasets remains challenging due to incomplete representations of the system being perturbed and the difficulty o...

Rishi Verma, Abhinav K. Adduri, Beatrice Bevilacqua et al. · bioRxiv · 3 citations · ⚡1

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 · 4 citations