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Volumn 13, Issue 1, 2007, Pages 275-282
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Bayesian data mining of protein domains gives an efficient predictive algorithm and new insight
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Author keywords
Bayes' classification; Probability computation; PROMOTIF; Proteins structural domains; PSIPRED
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Indexed keywords
ACCURACY;
ALGORITHM;
ANALYTIC METHOD;
ARTICLE;
BAYES THEOREM;
COMPUTER ANALYSIS;
CONTROLLED STUDY;
CORRELATION ANALYSIS;
INTERMETHOD COMPARISON;
MATHEMATICAL COMPUTING;
MOLECULAR MODEL;
PREDICTION;
PRIORITY JOURNAL;
PROBABILITY;
PROTEIN ANALYSIS;
PROTEIN DOMAIN;
PROTEIN FOLDING;
PROTEIN FUNCTION;
PROTEIN LOCALIZATION;
PROTEIN MOTIF;
PROTEIN SECONDARY STRUCTURE;
SEQUENCE ANALYSIS;
STATISTICAL ANALYSIS;
THREE DIMENSIONAL IMAGING;
VALIDATION STUDY;
ALGORITHMS;
AMINO ACID MOTIFS;
BAYES THEOREM;
COMPUTATIONAL BIOLOGY;
DATABASES, PROTEIN;
MODELS, MOLECULAR;
MOLECULAR CONFORMATION;
PREDICTIVE VALUE OF TESTS;
PROTEIN CONFORMATION;
PROTEIN STRUCTURE, TERTIARY;
PROTEOMICS;
SOFTWARE;
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EID: 34249327161
PISSN: 16102940
EISSN: 09485023
Source Type: Journal
DOI: 10.1007/s00894-006-0141-z Document Type: Article |
Times cited : (6)
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References (20)
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