A sequence-based method to predict the impact of regulatory variants using random forest

BACKGROUND: Most disease-associated variants identified by genome-wide association studies (GWAS) exist in noncoding regions. In spite of the common agreement that such variants may disrupt biological functions of their hosting regulatory elements, it remains a great challenge to characterize the ri...

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Detalles Bibliográficos
Autores principales: Liu, Qiao, Gan, Mingxin, Jiang, Rui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5374684/
https://www.ncbi.nlm.nih.gov/pubmed/28361702
http://dx.doi.org/10.1186/s12918-017-0389-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5374684/
https://www.ncbi.nlm.nih.gov/pubmed/28361702
http://dx.doi.org/10.1186/s12918-017-0389-1

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