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SEPIa a knowledge-driven algorithm for predicting conformational B-cell epitopes from the amino acid sequence

机译:SEPIa一种由知识驱动的算法可从氨基酸序列预测构象B细胞表位

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摘要

BackgroundThe identification of immunogenic regions on the surface of antigens, which are able to be recognized by antibodies and to trigger an immune response, is a major challenge for the design of new and effective vaccines. The prediction of such regions through computational immunology techniques is a challenging goal, which will ultimately lead to a drastic limitation of the experimental tests required to validate their efficiency. However, current methods are far from being sufficiently reliable and/or applicable on a large scale.
机译:背景技术鉴定能够被抗体识别并触发免疫反应的抗原表面上的免疫原性区域是设计新的有效疫苗的主要挑战。通过计算免疫学技术对此类区域进行预测是一个具有挑战性的目标,最终将导致对验证其效率所需的实验测试的严格限制。但是,当前的方法远未足够可靠和/或可大规模应用。

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