Functional impact of missense variants in BRCA1 predicted by supervised learning

PLoS Computational Biology

Volumn 3, Issue 2, 2007, Pages 0268-0281

  Karchin, Rachel ^a,b   Monteiro, Alvaro N A ^c   Tavtigian, Sean V ^d   Carvalho, Marcelo A ^c   Sali, Andrej ^e,f  

^a Johns Hopkins University   (United States)

^b Johns Hopkins University   (United States)

^c H LEE MOFFITT CANCER CENTER AND RESEARCH INSTITUTE   (United States)

^d INTERNATIONAL AGENCY FOR RESEARCH ON CANCER   (France)

^e UNIVERSITY OF CALIFORNIA   (United States)

^f UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BINDING SITES; DISEASES; GENES; LEARNING ALGORITHMS; PROTEINS;

AMINO ACID RESIDUES; BRCA1 GENE; C-TERMINAL DOMAINS; FUNCTIONAL TEST; LABOUR-INTENSIVE; MAJORITY VOTER; PROTEIN FUNCTIONS; PUTATIVE BINDING SITES; SUPERVISED LEARNING APPROACHES; TRANS-ACTIVATION FUNCTION;

SUPERVISED LEARNING;

BRCA1 PROTEIN;

ALGORITHM; ARTICLE; BAY REGION BINDING SITE; CANCER SUSCEPTIBILITY; CARBOXY TERMINAL SEQUENCE; GENE LOCUS; GENETIC VARIABILITY; MISSENSE MUTATION; ONCOGENE; PROTEIN ANALYSIS; PROTEIN DOMAIN; TRANSACTIVATION; AMINO ACID SEQUENCE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; CHEMISTRY; GENETICS; METHODOLOGY; MOLECULAR GENETICS; PHYSIOLOGY; SEQUENCE ALIGNMENT; SEQUENCE ANALYSIS; STRUCTURE ACTIVITY RELATION;

ALGORITHMS; AMINO ACID SEQUENCE; ARTIFICIAL INTELLIGENCE; BRCA1 PROTEIN; GENETIC VARIATION; MOLECULAR SEQUENCE DATA; MUTATION, MISSENSE; PATTERN RECOGNITION, AUTOMATED; SEQUENCE ALIGNMENT; SEQUENCE ANALYSIS, PROTEIN; STRUCTURE-ACTIVITY RELATIONSHIP;

EID: 33847252874     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.0030026     Document Type: Article

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