A semi-supervised deep learning approach for predicting the functional effects of genomic non-coding variations

BACKGROUND: Understanding the functional effects of non-coding variants is important as they are often associated with gene-expression alteration and disease development. Over the past few years, many computational tools have been developed to predict their functional impact. However, the intrinsic...

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Detalles Bibliográficos
Autores principales: Jia, Hao, Park, Sung-Joon, Nakai, Kenta
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8171027/
https://www.ncbi.nlm.nih.gov/pubmed/34078253
http://dx.doi.org/10.1186/s12859-021-03999-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8171027/
https://www.ncbi.nlm.nih.gov/pubmed/34078253
http://dx.doi.org/10.1186/s12859-021-03999-8

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