MMSplice: modular modeling improves the predictions of genetic variant effects on splicing

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 CAGI5 exon skipping prediction challenge. The MMSplice modules are neural networks scoring exon...

Descripción completa

Detalles Bibliográficos
Autores principales: Cheng, Jun, Nguyen, Thi Yen Duong, Cygan, Kamil J., Çelik, Muhammed Hasan, Fairbrother, William G., Avsec, žiga, Gagneur, Julien
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Method
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6396468/
https://www.ncbi.nlm.nih.gov/pubmed/30823901
http://dx.doi.org/10.1186/s13059-019-1653-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6396468/
https://www.ncbi.nlm.nih.gov/pubmed/30823901
http://dx.doi.org/10.1186/s13059-019-1653-z

Ejemplares similares