IEDB-AR: immune epitope database—analysis resource in 2019
By Sandeep Kumar Dhanda, Swapnil Mahajan, Sinu Paul, Zhen Yan, Haeuk Kim, Martin Closter Jespersen, Vanessa Isabell Jurtz, Massimo Andreatta, J. Greenbaum, Paolo Marcatili and 3 more. Nucleic Acids Res., 2019
357 citations recorded by the source corpus.
Abstract The Immune Epitope Database Analysis Resource (IEDB-AR, http://tools.iedb.org/) is a companion website to the IEDB that provides computational tools focused on the prediction and analysis of B and T cell epitopes. All of the tools are freely available through the public website and many are also available through a REST API and/or a downloadable command-line tool. A virtual machine image of the entire site is also freely available for non-commercial use and contains most of the tools on the public site. Here, we describe the tools and functionalities that are available in the IEDB-AR, focusing on the 10 new tools that have been added since the last report in the 2012 NAR webserver edition. In addition, many of the tools that were already hosted on the site in 2012 have received updates to newest versions, including NetMHC, NetMHCpan, BepiPred and DiscoTope. Overall, this IEDB-AR update provides a substantial set of updated and novel features for epitope prediction and analysis.
Subfields: Ecology, Molecular Biology, Radiology, Nuclear Medicine and Imaging
View Paper: https://www.semanticscholar.org/paper/3ffd747c3237aefbe29e4bff85592215d8df36c3
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Citations in the corpus
- Phenotype and kinetics of SARS-CoV-2-specific T cells in COVID-19 patients with acute respiratory distress syndrome (2020, methodology): “reference sequence (GenBank: MN908947) and IEDB analysis-resource as previously described (11, 26).”
- Targets of T Cell Responses to SARS-CoV-2 Coronavirus in Humans with COVID-19 Disease and Unexposed Individuals (2020, unknown): “These re-sults are somewhat unexpected, because data for other coro-naviruses, from 27 different studies curated in the IEDB, re-ported that spike accounted for nearly two-thirds of reported CD4 + T cell reactivity (Table S3).”
- A Sequence Homology and Bioinformatic Approach Can Predict Candidate Targets for Immune Responses to SARS-CoV-2 (2020, unknown): “We also sought to address potential SARS-CoV-2 epitopes by a completely different method, namely utilizing the epitope predictions hosted by the IEDB (Dhanda et al., 2019; Vita et al., 2019).”
- SARS-CoV-2 vaccination induces immunological T cell memory able to cross-recognize variants from Alpha to Omicron (2022, unknown): “resource(Dhanda et al., 2019; Vita et al., 2019).”