
WebAllergen: a web-based database for protein allergenicity prediction
Abstract
Allergies are an important health problem. In the present study, a web-based allergen platform was developed with an allergen database and allergenicity prediction functions. Drawing from the literature and public databases, 2,939 allergens were identified and categorised according to their origin and known information. This platform provides a function to search allergenic proteins through formats such as keywords, FASTA, BLAST, and provides sequence-based, motif-based and epitope-based methods for allergenicity prediction. Using specific sequence or allergen predictions, the user can find summarised allergen information to link the UniProtKB and the PDB databases.
© 2018 So Youn Won, Jeong-Ho Baek, Jae-Hyeon Oh, Gang-Seob Lee, Yong-Hwan Kim, Chang-Kug Kim, published by National Science Foundation of Sri Lanka
This work is licensed under the Creative Commons License.