Towards Increasing the Clinical Relevance of In Silico Methods to Predict Pathogenic Missense Variants

PLoS Computational Biology

Volumn 12, Issue 5, 2016, Pages

  Masica, David L ^a   Karchin, Rachel ^a,b  

^a Johns Hopkins University   (United States)

^b JOHNS HOPKINS UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIOINFORMATICS;

IN-SILICO; PATHOGENICS;

BIOLOGY;

CYSTIC FIBROSIS TRANSMEMBRANE CONDUCTANCE REGULATOR; LOW DENSITY LIPOPROTEIN RECEPTOR; CFTR PROTEIN, HUMAN; LDLR PROTEIN, HUMAN;

ARTICLE; BIOINFORMATICS; CADD; CLASSIFIER; COMPUTER MODEL; CONDEL; CONTROLLED STUDY; CYSTIC FIBROSIS; ENDOPHENOTYPE; FAMILIAL HYPERCHOLESTEROLEMIA; FATHMM; GENETIC VARIATION; GENOTYPE PHENOTYPE CORRELATION; MISSENSE MUTATION; MUTATION ASSESSOR; MUTATIONTASTER; MUTPRED; NSSNAPANALYZER; PANTHER; PHD SNP; PHENOTYPE; POLYPHEN 2; PREDICTION; SIFT; SNAP; SNAPS AND GO; AMINO ACID SUBSTITUTION; BIOLOGICAL MODEL; BIOLOGY; COMPUTER SIMULATION; GENETIC ASSOCIATION STUDY; GENETIC PREDISPOSITION; GENETICS; HUMAN;

AMINO ACID SUBSTITUTION; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; CYSTIC FIBROSIS; CYSTIC FIBROSIS TRANSMEMBRANE CONDUCTANCE REGULATOR; ENDOPHENOTYPES; GENETIC ASSOCIATION STUDIES; GENETIC PREDISPOSITION TO DISEASE; GENETIC VARIATION; HUMANS; MODELS, GENETIC; MUTATION, MISSENSE; RECEPTORS, LDL;

EID: 84975880719     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1004725     Document Type: Article

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