Evaluating the impact of in silico predictors on clinical variant classification is a research paper published in Genetics in Medicine (2021). On theSindex it has a DataRank of 0. It has been cited 62 times.
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National Human Genome Research Institute
Grant: HG200359-12
National Human Genome Research Institute
Grant: U41HG006834
National Human Genome Research Institute
Grant: U41HG009649
Intramural NIH HHS
Grant: ZIA HG200328
Intramural NIH HHS
Grant: ZIA HG200359
National Institutes of Health
Grant: 3U41HG006834-03S2
A Unified Clinical Genomics Database
National Institutes of Health
Grant: 1ZIAHG200359-11
ClinSeq(c) - Molecular and Genetic Aspects
National Institutes of Health
Grant: 3U41HG009649-01S1
The Future of PharmGKB Funding Under NHGRI
National Institutes of Health
FWCI
6.87
Citation Percentile
1.0%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals
Additional file 2 of MAGPIE: accurate pathogenic prediction for multiple variant types using machine learning approach
Additional file 2 of MAGPIE: accurate pathogenic prediction for multiple variant types using machine learning approach
Additional file 1 of Explicable prioritization of genetic variants by integration of rule-based and machine learning algorithms for diagnosis of rare Mendelian disorders
Additional file 1 of Explicable prioritization of genetic variants by integration of rule-based and machine learning algorithms for diagnosis of rare Mendelian disorders
Additional file 2 of Explicable prioritization of genetic variants by integration of rule-based and machine learning algorithms for diagnosis of rare Mendelian disorders
Additional file 2 of Explicable prioritization of genetic variants by integration of rule-based and machine learning algorithms for diagnosis of rare Mendelian disorders
Additional file 3 of Explicable prioritization of genetic variants by integration of rule-based and machine learning algorithms for diagnosis of rare Mendelian disorders
Additional file 3 of Explicable prioritization of genetic variants by integration of rule-based and machine learning algorithms for diagnosis of rare Mendelian disorders
Additional file 1 of MAGPIE: accurate pathogenic prediction for multiple variant types using machine learning approach
Additional file 1 of MAGPIE: accurate pathogenic prediction for multiple variant types using machine learning approach