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Prediction of conformational B-cell epitopes from 3D structures by random forests with a distance-based feature

机译:具有基于距离的特征的随机森林从3D结构预测构象B细胞表位

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摘要

BackgroundAntigen-antibody interactions are key events in immune system, which provide important clues to the immune processes and responses. In Antigen-antibody interactions, the specific sites on the antigens that are directly bound by the B-cell produced antibodies are well known as B-cell epitopes. The identification of epitopes is a hot topic in bioinformatics because of their potential use in the epitope-based drug design. Although most B-cell epitopes are discontinuous (or conformational), insufficient effort has been put into the conformational epitope prediction, and the performance of existing methods is far from satisfaction.
机译:背景抗原-抗体相互作用是免疫系统中的关键事件,为免疫过程和反应提供重要线索。在抗原-抗体相互作用中,被B细胞产生的抗体直接结合的抗原上的特定位点是众所周知的B细胞表位。由于表位的潜在用途基于表位的药物设计,因此表位的鉴定是生物信息学中的热门话题。尽管大多数B细胞表位是不连续的(或构象的),但在构象表位的预测中却投入了足够的精力,而现有方法的性能远远不能令人满意。

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