Rxivist logo

EpiDope: A Deep neural network for linear B-cell epitope prediction

By Maximilian Collatz, Florian Mock, Martin Hölzer, Emanuel Barth, Konrad Sachse, Manja Marz

Posted 13 May 2020
bioRxiv DOI: 10.1101/2020.05.12.090019

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 shortened by using in silico prediction. Here we present EpiDope, a python tool which uses a deep neural network to detect B-cell epitope regions on individual protein sequences ([github.com/mcollatz/EpiDope][1]). With an area under the curve (AUC) between 0.67 ± 0.07 in the ROC curve, EpiDope exceeds all other currently used B-cell prediction tools. Moreover, for AUC10% (AUC for a false-positive rate < 0.1), EpiDope improves the prediction accuracy in comparison to other state-of-the-art methods. Our software is shown to reliably predict linear B-cell epitopes of a given protein sequence, thus contributing to a significant reduction of laboratory experiments and costs required for the conventional approach. ### Competing Interest Statement The authors have declared no competing interest. [1]: https://github.com/mcollatz/EpiDope

Download data

  • Downloaded 436 times
  • Download rankings, all-time:
    • Site-wide: 49,072 out of 116,126
    • In bioinformatics: 5,274 out of 9,552
  • Year to date:
    • Site-wide: 15,132 out of 116,126
  • Since beginning of last month:
    • Site-wide: 13,177 out of 116,126

Altmetric data

Downloads over time

Distribution of downloads per paper, site-wide


Sign up for the Rxivist weekly newsletter! (Click here for more details.)