Article

X-CRISP: Domain-Adaptable and Interpretable CRISPR Repair Outcome Prediction

2025-02-08

Abstract excerpt

<h4>Motivation</h4> Controlling the outcomes of CRISPR editing is crucial for the success of gene therapy. Since donor template-based editing is often inefficient, alternative strategies have emerged that leverage mutagenic end-joining repair instead. Existing machine learning models can accurately predict end-joining repair outcomes, however: generalisability beyond the specific cell line used for training remai...

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Literature Corpus work: 8f6897ea-bd29-51e6-b121-9003e932d77f
DOI: 10.1101/2025.02.06.636858

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