RegSNPs-intron: a computational framework for predicting pathogenic impact of intronic single nucleotide variants

Single nucleotide variants (SNVs) in intronic regions have yet to be systematically investigated for their disease-causing potential. Using known pathogenic and neutral intronic SNVs (iSNVs) as training data, we develop the RegSNPs-intron algorithm based on a random forest classifier that integrates...

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Библиографические подробности
Опубликовано в: :Genome Biol
Главные авторы: Lin, Hai, Hargreaves, Katherine A., Li, Rudong, Reiter, Jill L., Wang, Yue, Mort, Matthew, Cooper, David N., Zhou, Yaoqi, Zhang, Chi, Eadon, Michael T., Dolan, M. Eileen, Ipe, Joseph, Skaar, Todd C., Liu, Yunlong
Формат: Artigo
Язык:Inglês
Опубликовано: BioMed Central 2019
Предметы:
Method
Online-ссылка:https://ncbi.nlm.nih.gov/pmc/articles/PMC6883696/
https://ncbi.nlm.nih.gov/pubmed/31779641
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s13059-019-1847-4
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