An Overview of Bioinformatics Tools and Resources in Allergy.
The rapidly increasing number of characterized allergens has created huge demands for advanced information storage, retrieval, and analysis. Bioinformatics and machine learning approaches provide useful tools for the study of allergens and epitopes prediction, which greatly complement traditional laboratory techniques. The specific applications mainly include identification of B- and T-cell epitopes, and assessment of allergenicity and cross-reactivity. In order to facilitate the work of clinical and basic researchers who are not familiar with bioinformatics, we review in this chapter the most important databases, bioinformatic tools, and methods with relevance to the study of allergens.
Genome Institute of Singapore, A*STAR, Singapore, Singapore. y_foote@yahoo.com.
Zhiyan
Z
Fu
Bioinformatics Institute, A*STAR, Singapore, Singapore.|Institute of High Performance Computing, A*STAR, Singapore, Singapore.|Pediatric Allergy & Immunology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Jing
J
Lin
D000485:Allergens / Q000276:immunology; D019295:Computational Biology / Q000379:methods; D003429:Cross Reactions / Q000276:immunology; D016208:Databases, Factual; D018985:Epitopes, B-Lymphocyte / Q000276:immunology; D018984:Epitopes, T-Lymphocyte / Q000276:immunology; D006801:Humans; D006967:Hypersensitivity / Q000276:immunology*
D000485:Allergens; D018985:Epitopes, B-Lymphocyte; D018984:Epitopes, T-Lymphocyte
Allergy; Bioinformatics; Epitope prediction; Food allergens; Machine learning