about
Automating Construction of Machine Learning Models With Clinical Big Data: Proposal Rationale and Methods.Working toward precision medicine: Predicting phenotypes from exomes in the Critical Assessment of Genome Interpretation (CAGI) challenges.Missense variant pathogenicity predictors generalize well across a range of function-specific prediction challenges.Methods and tools for assessing the impact of genetic variations: The 2017 annual scientific meeting of the Human Genome Variation Society.Using Mobile Apps to Assess and Treat Depression in Hispanic and Latino Populations: Fully Remote Randomized Clinical TrialNew Long-Term Memory Genes Revealed by Assessing Computational Function Prediction MethodsThe accuracy of passive phone sensors in predicting daily moodAssessment of blind predictions of the clinical significance of BRCA1 and BRCA2 variantsAssessing computational predictions of the phenotypic effect of cystathionine-beta-synthase variantsCAGI SickKids challenges: Assessment of phenotype and variant predictions derived from clinical and genomic data of children with undiagnosed diseasesAssessment of predicted enzymatic activity of α-N-acetylglucosaminidase variants of unknown significance for CAGI 2016Predicting venous thromboembolism risk from exomes in the Critical Assessment of Genome Interpretation (CAGI) challengesPathogenicity and functional impact of non-frameshifting insertion/deletion variation in the human genomeAssessing the performance of in silico methods for predicting the pathogenicity of variants in the gene CHEK2, among Hispanic females with breast cancer
P50
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P50
description
researcher
@en
wetenschapper
@nl
name
Sean D Mooney
@en
Sean D Mooney
@nl
type
label
Sean D Mooney
@en
Sean D Mooney
@nl
prefLabel
Sean D Mooney
@en
Sean D Mooney
@nl
P31
P496
0000-0003-2654-0833