Article

Sequence models conditioned on splicing factor expression predict splicing in unseen tissues

2026-01-21

Abstract excerpt

Predicting how RNA splicing varies across tissues is important for understanding the impact of genetic variation and identifying splicing-based disease mechanisms. Although many sequence-based deep learning models have been developed to predict splicing, most predict splice sites rather than full splicing events, are restricted to tissues seen during training, or do not account for trans-regulatory variation such...

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Literature Corpus work: aa494d4b-2213-5d67-ba5a-1bb5ab1de06a
DOI: 10.64898/2026.01.20.700496

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