Article

Modular modeling improves the predictions of genetic variant effects on splicing

2018-10-10

Abstract excerpt

Predicting the effects of genetic variants on splicing is highly relevant for human genetics. We describe the framework MMSplice (modular modeling of splicing) with which we built the winning model of the CAGI 2018 exon skipping prediction challenge. The MMSplice modules are neural networks scoring exon, intron, and splice sites, trained on distinct large-scale genomics datasets. These modules are combined to pred...

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Literature Corpus work: 04c0406d-d055-5d1d-a3b3-fdc5803e7669
DOI: 10.1101/438986

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