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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...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2017
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| 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 |