ArticleGenome biology2026
Accurate prediction of CRISPR editing outcomes in somatic cell lines and zygotes with few-shot learning with inDecay.
Article in Genome biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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17 authors.
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Abstract
Prediction of CRISPR/Cas outcomes remains unsatisfactory in embryos due to distinct DNA repair preferences and the lack of large-scale embryo editing profiles. We introduce inDecay, a flexible system for predicting the proportion of CRISPR-induced indels from the target sequence. Owing to its parameter-efficient and cell-type-aware design, inDecay performs well in both in-sample training and out-of-sample fine-tuning. Starting with cross-cell-line predictions, we observed that inDecay maintains high accuracy in mouse zygote editing and in goat, cattle and porcine embryos. inDecay may accelerate mouse model generation, livestock embryonic editing, and gene therapy applications.
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