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EpiDope: a deep neural network for linear B-cell epitope prediction

机译:ePIDOPE:用于线性B细胞表位预测的深神经网络

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摘要

Motivation: By binding to specific structures on antigenic proteins, the so-called epitopes, B-cell antibodies can neutralize pathogens. The identification of B-cell epitopes is of great value for the development of specific serodiagnostic assays and the optimization of medical therapy. However, identifying diagnostically or therapeutically relevant epitopes is a challenging task that usually involves extensive laboratory work. In this study, we show that the time, cost and labor-intensive process of epitope detection in the lab can be significantly reduced using in silico prediction.
机译:动机:通过结合抗原蛋白上的特定结构,即所谓的表位,B细胞抗体可以中和病原体。B细胞表位的鉴定对于特异性血清诊断分析的发展和药物治疗的优化具有重要价值。然而,识别诊断或治疗相关的表位是一项具有挑战性的任务,通常需要大量的实验室工作。在这项研究中,我们表明,在实验室中使用电子预测可以显著减少表位检测的时间、成本和劳动密集型过程。

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  • 来源
    《Bioinformatics》 |2021年第4期|共8页
  • 作者单位

    Friedrich Schiller Univ Jena RNA Bioinformat High Throughput Anal Fac Math &

    Comp Sci D-07743 Jena Germany;

    Friedrich Schiller Univ Jena RNA Bioinformat High Throughput Anal Fac Math &

    Comp Sci D-07743 Jena Germany;

    Friedrich Schiller Univ Jena RNA Bioinformat High Throughput Anal Fac Math &

    Comp Sci D-07743 Jena Germany;

    Friedrich Schiller Univ Jena RNA Bioinformat High Throughput Anal Fac Math &

    Comp Sci D-07743 Jena Germany;

    Friedrich Schiller Univ Jena RNA Bioinformat High Throughput Anal Fac Math &

    Comp Sci D-07743 Jena Germany;

    Friedrich Schiller Univ Jena RNA Bioinformat High Throughput Anal Fac Math &

    Comp Sci D-07743 Jena Germany;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 生物工程学(生物技术);
  • 关键词

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