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Navigating through the Jungle of Allergens: Features and Applications of Allergen Databases.
Radauer, Christian.
Afiliação
  • Radauer C; Department of Pathophysiology and Allergy Research, Center for Pathophysiology, Infectiology and Immunology, Medical University of Vienna, Vienna, Austria.
Int Arch Allergy Immunol ; 173(1): 1-11, 2017.
Article em En | MEDLINE | ID: mdl-28456806
ABSTRACT
The increasing number of available data on allergenic proteins demanded the establishment of structured, freely accessible allergen databases. In this review article, features and applications of 6 of the most widely used allergen databases are discussed. The WHO/IUIS Allergen Nomenclature Database is the official resource of allergen designations. Allergome is the most comprehensive collection of data on allergens and allergen sources. AllergenOnline is aimed at providing a peer-reviewed database of allergen sequences for prediction of allergenicity of proteins, such as those planned to be inserted into genetically modified crops. The Structural Database of Allergenic Proteins (SDAP) provides a database of allergen sequences, structures, and epitopes linked to bioinformatics tools for sequence analysis and comparison. The Immune Epitope Database (IEDB) is the largest repository of T-cell, B-cell, and major histocompatibility complex protein epitopes including epitopes of allergens. AllFam classifies allergens into families of evolutionarily related proteins using definitions from the Pfam protein family database. These databases contain mostly overlapping data, but also show differences in terms of their targeted users, the criteria for including allergens, data shown for each allergen, and the availability of bioinformatics tools.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Alérgenos / Bases de Dados de Proteínas Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Alérgenos / Bases de Dados de Proteínas Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2017 Tipo de documento: Article