Abstract
Identification and characterization of B-cell epitopes in target antigens is one of the key steps in epitope-driven vaccine design, immunodiagnostic tests, and antibody production. For localizing epitopes by experimental methods is time consuming and cost expensive, researchers have been developing in silico or computational models for the prediction of B-cell epitopes, enabling immunologists and clinicians to identify the most promising epitopes for characterization in the laboratory. A sufficient number of available B-cell epitopes are indispensable for establishing the prediction models. To our knowledge, some popular databases associated with the B-cell epitopes are proposed and widely used in the immunoinformatics. In this chapter, we present an overview of the important databases and introduce how to compile datasets for the development of B-cell epitope prediction tools.
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Acknowledgments
This work was supported by the National Science Foundation of China (61272274, 61103126), Program for New Century Excellent Talents in Universities (NCET-10-0644), the Open Research Fund of State Key Laboratory of Hybrid Rice (Wuhan University) (KF201301), the Ph.D. Programs Foundation of Ministry of Education of China (20100141120049), and Natural Science Foundation of Hubei Province (No. 2011CDB454).
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Liu, J., Zhang, W. (2014). Databases for B-Cell Epitopes. In: De, R., Tomar, N. (eds) Immunoinformatics. Methods in Molecular Biology, vol 1184. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-1115-8_7
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DOI: https://doi.org/10.1007/978-1-4939-1115-8_7
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