Benchmarking foundation cell models for post-perturbation RNA-seq prediction.

Gerold Csendes¹, Gema Sanz¹, Kristóf Z Szalay¹, Bence Szalai²

¹Turbine Ltd., Budapest, Hungary.

²Turbine Ltd., Budapest, Hungary. bence.szalai@turbine.ai.

Abstract

Accurately predicting cellular responses to perturbations is essential for understanding cell behaviour in both healthy and diseased states. While perturbation data is ideal for building such predictive models, its availability is considerably lower than baseline (non-perturbed) cellular data. To address this limitation, several foundation cell models have been developed using large-scale single-c…

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