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Experimental methods used to determine BCEs are costly and time-consuming. Therefore, it is essential to develop computational methods for the rapid identification of BCEs. Although several computational methods have been developed for this task, generalizability is still a major concern, where cross-testing of the classifiers trained and tested on different datasets has revealed accuracies of 51\u201353%.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We describe a new method called EpitopeVec, which uses a combination of residue properties, modified antigenicity scales, and protein language model-based representations (protein vectors) as features of peptides for linear BCE predictions. Extensive benchmarking of EpitopeVec and other state-of-the-art methods for linear BCE prediction on several large and small datasets, as well as cross-testing, demonstrated an improvement in the performance of EpitopeVec over other methods in terms of accuracy and area under the curve. As the predictive performance depended on the species origin of the respective antigens (viral, bacterial and eukaryotic), we also trained our method on a large viral dataset to create a dedicated linear viral BCE predictor with improved cross-testing performance.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>The software is available at https:\/\/github.com\/hzi-bifo\/epitope-prediction.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Supplementary information<\/jats:title>\n                    <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btab467","type":"journal-article","created":{"date-parts":[[2021,6,25]],"date-time":"2021-06-25T07:10:38Z","timestamp":1624605038000},"page":"4517-4525","source":"Crossref","is-referenced-by-count":36,"title":["EpitopeVec: linear epitope prediction using deep protein sequence embeddings"],"prefix":"10.1093","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4059-5195","authenticated-orcid":false,"given":"Akash","family":"Bahai","sequence":"first","affiliation":[{"name":"Computational Biology of Infection Research, Helmholtz Center for Infection Research , Braunschweig 38124, Germany"},{"name":"Braunschweig Integrated Center of Systems Biology (BRICS), Technische Universit\u00e4t Braunschweig , Braunschweig 38106, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6518-7238","authenticated-orcid":false,"given":"Ehsaneddin","family":"Asgari","sequence":"additional","affiliation":[{"name":"Computational Biology of Infection Research, Helmholtz Center for Infection Research , Braunschweig 38124, Germany"},{"name":"Molecular Cell Biomechanics Laboratory, Department of Bioengineering and Mechanical Engineering, University of California , Berkeley, CA 94720, USA"}]},{"given":"Mohammad R K","family":"Mofrad","sequence":"additional","affiliation":[{"name":"Molecular Cell Biomechanics Laboratory, Department of Bioengineering and Mechanical Engineering, University of California , Berkeley, CA 94720, USA"},{"name":"Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Lab , Berkeley, CA 94720, USA"}]},{"given":"Andreas","family":"Kloetgen","sequence":"additional","affiliation":[{"name":"Computational Biology of Infection Research, Helmholtz Center for Infection Research , Braunschweig 38124, Germany"}]},{"given":"Alice C","family":"McHardy","sequence":"additional","affiliation":[{"name":"Computational Biology of Infection Research, Helmholtz Center for Infection Research , Braunschweig 38124, Germany"},{"name":"Braunschweig Integrated Center of Systems Biology (BRICS), Technische Universit\u00e4t Braunschweig , Braunschweig 38106, Germany"}]}],"member":"286","published-online":{"date-parts":[[2021,6,28]]},"reference":[{"key":"2023061310483509700_btab467-B1","doi-asserted-by":"crossref","first-page":"831","DOI":"10.1038\/nbt.3300","article-title":"Predicting the sequence specificities of DNA-and RNA-binding proteins by deep learning","volume":"33","author":"Alipanahi","year":"2015","journal-title":"Nat. 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