Phenotype-optimized sequence ensembles substantially improve prediction of disease-causing mutation in cystic fibrosis

Human Mutation

Volumn 33, Issue 8, 2012, Pages 1267-1274

  Masica, David L ^a   Sosnay, Patrick R ^b,c   Cutting, Garry R ^b   Karchin, Rachel ^a  

^a Johns Hopkins University   (United States)

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

^c PERDANA UNIVERSITY   (Malaysia)

Author keywords

CFTR; Cystic fibrosis; Phenotype optimized sequence ensembles; POSE; Prediction

Indexed keywords

TRANSMEMBRANE CONDUCTANCE REGULATOR;

ALGORITHM; ARTICLE; CYSTIC FIBROSIS; GENE MUTATION; GENE SEQUENCE; PHENOTYPE; PHENOTYPE OPTIMIZED SEQUENCE ENSEMBLE; PREDICTION; PREDICTIVE VALUE; PRIORITY JOURNAL; SENSITIVITY AND SPECIFICITY; SEQUENCE ANALYSIS;

ALGORITHMS; COMPUTATIONAL BIOLOGY; CYSTIC FIBROSIS; CYSTIC FIBROSIS TRANSMEMBRANE CONDUCTANCE REGULATOR; HUMANS; MUTATION; MUTATION, MISSENSE;

EID: 84863857768     PISSN: 10597794     EISSN: 10981004     Source Type: Journal    
DOI: 10.1002/humu.22110     Document Type: Article

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