Fu Zhiyan, Lin Jing
Genome Institute of Singapore, A*STAR, Singapore, Singapore.
Bioinformatics Institute, A*STAR, Singapore, Singapore.
Methods Mol Biol. 2017;1592:223-245. doi: 10.1007/978-1-4939-6925-8_18.
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.
已鉴定过敏原数量的迅速增加对先进的信息存储、检索和分析产生了巨大需求。生物信息学和机器学习方法为过敏原研究及表位预测提供了有用工具，极大地补充了传统实验室技术。具体应用主要包括B细胞和T细胞表位的鉴定，以及过敏原性和交叉反应性的评估。为方便不熟悉生物信息学的临床和基础研究人员开展工作，我们在本章中综述了与过敏原研究相关的最重要的数据库、生物信息学工具和方法。
