Computational detection of allergenic proteins attains a new level of accuracy with in silico variable-length peptide extraction and machine learning

Nucleic Acids Research

Volumn 34, Issue 13, 2006, Pages 3779-3793

  Soeria Atmadja, D ^a   Lundell, T ^a   Gustafsson, M G ^b,c,d   Hammerling, U ^a  

^a NATIONAL FOOD ADMINISTRATION   (Sweden)

^b UPPSALA UNIVERSITY   (Sweden)

^c UPPSALA UNIVERSITY   (Sweden)

^d UPPSALA UNIVERSITY HOSPITAL   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

ALLERGEN; PARVALBUMIN; PEPTIDE; PROFILIN; TROPOMYOSIN; PROTEIN;

ACCURACY; ALGORITHM; ALLERGENICITY; ANALYTIC METHOD; ARTICLE; BAYES THEOREM; BIOINFORMATICS; COMPUTER MODEL; CONFIDENCE INTERVAL; DATA BASE; HUMAN; INTERMETHOD COMPARISON; LEARNING; MACHINE; MATHEMATICAL COMPUTING; NONHUMAN; PEPTIDE ANALYSIS; PRIORITY JOURNAL; PROTEIN ANALYSIS; PROTEIN FAMILY; SENSITIVITY AND SPECIFICITY; SEQUENCE ANALYSIS; SEQUENCE HOMOLOGY; SWISS-PROT; ARTIFICIAL INTELLIGENCE; BIOLOGY; CHEMISTRY; EVALUATION; IMMUNOLOGY; ISOLATION AND PURIFICATION; METHODOLOGY; PROTEIN DATABASE; REPRODUCIBILITY;

ALGORITHMS; ALLERGENS; ARTIFICIAL INTELLIGENCE; COMPUTATIONAL BIOLOGY; DATABASES, PROTEIN; HUMANS; PEPTIDES; PROTEINS; REPRODUCIBILITY OF RESULTS; SEQUENCE ANALYSIS, PROTEIN; TROPOMYOSIN;

EID: 33748672467     PISSN: 03051048     EISSN: 13624962     Source Type: Journal    
DOI: 10.1093/nar/gkl467     Document Type: Article

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