ArticleBioinformatics (Oxford, England)2021
EpitopeVec: linear epitope prediction using deep protein sequence embeddings.
Article in Bioinformatics (Oxford, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed, 40 citations in OpenAlex.
- The critical role of artificial intelligence and bioinformatics in accelerating peptide-based vaccine discovery for tackling global infectious diseases.Briefings in bioinformatics · 2026Review
- Artificial intelligence advancements in monoclonal antibody development technology.Frontiers in immunology · 2026Review
- Phylogenetic Domain Adaption for Linear B-Cell Epitope Prediction.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Computational identification of B- and T-cell epitopes: a unified task taxonomy and review of databases, datasets, predictive pipelines, and gaps.Frontiers in immunology · 2026Review
- Improving B-cell Linear Epitope PredictionCurrent drug targets · 2026Article
- The impact of biologically relevant negative samples on machine learning-based B-cell epitope prediction for Influenza A.Bioinformatics advances · 2026Article
- Host-Microbe Interactions: Prospects of Machine Learning and Deep Learning Technologies in Animal Viral Disease Management.Veterinary sciences · 2025Review
- Computational Methods in Immunoinformatics: Epitope Discovery and Diagnostic Applications.ACS omega · 2025Review
- Neutralizing Antibodies vs. Viruses: Interacting Mechanisms and Escape Tactics.Microorganisms · 2025Review
- A deep learning model for predicting systemic lupus erythematosus-associated epitopes.BMC medical informatics and decision making · 2025Article
- Revolutionizing oncology: the role of Artificial Intelligence (AI) as an antibody design, and optimization tools.Biomarker research · 2025Review
- Epitope-Based Vaccines: The Next Generation of Promising Vaccines Against Bacterial Infection.Vaccines · 2025Review
- A comprehensive overview of recent advances in generative models for antibodies.Computational and structural biotechnology journal · 2024Review
- Article
- Phylogeny-aware linear B-cell epitope predictor detects targets associated with immune response to orthopoxviruses.Briefings in bioinformatics · 2024Article
- Article
- Prediction of linear B-cell epitopes based on protein sequence features and BERT embeddings.Scientific reports · 2024Article
- The rise of taxon-specific epitope predictors.Briefings in bioinformatics · 2024Article
- epitope1D: accurate taxonomy-aware B-cell linear epitope prediction.Briefings in bioinformatics · 2023Article
- Brewpitopes: a pipeline to refine B-cell epitope predictions during public health emergencies.Frontiers in immunology · 2023Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
motivationB-cell epitopes (BCEs) play a pivotal role in the development of peptide vaccines, immuno-diagnostic reagents and antibody production, and thus in infectious disease prevention and diagnostics in general. 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 51-53%.
resultsWe 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. AVAILABILITY AND IMPLEMENTATION: The software is available at https://github.com/hzi-bifo/epitope-prediction. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.