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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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| Опубликовано в: : | Genome Biol |
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| Главные авторы: | , , , , , , , , , , , , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
BioMed Central
2019
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| Предметы: | |
| 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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