Author: Nolan, Sean; Vignali, Marissa; Klinger, Mark; Dines, Jennifer N.; Kaplan, Ian M.; Svejnoha, Emily; Craft, Tracy; Boland, Katie; Pesesky, Mitch; Gittelman, Rachel M.; Snyder, Thomas M.; Gooley, Christopher J.; Semprini, Simona; Cerchione, Claudio; Mazza, Massimiliano; Delmonte, Ottavia M.; Dobbs, Kerry; Carreño-Tarragona, Gonzalo; Barrio, Santiago; Sambri, Vittorio; Martinelli, Giovanni; Goldman, Jason D.; Heath, James R.; Notarangelo, Luigi D.; Carlson, Jonathan M.; Martinez-Lopez, Joaquin; Robins, Harlan S.
Title: A large-scale database of T-cell receptor beta (TCRβ) sequences and binding associations from natural and synthetic exposure to SARS-CoV-2. Cord-id: 0uwttqob Document date: 2020_8_4
ID: 0uwttqob
Snippet: We describe the establishment and current content of the ImmuneCODEâ„¢ database, which includes hundreds of millions of T-cell Receptor (TCR) sequences from over 1,400 subjects exposed to or infected with the SARS-CoV-2 virus, as well as over 135,000 high-confidence SARS-CoV-2-specific TCRs. This database is made freely available, and the data contained in it can be downloaded and analyzed online or offline to assist with the global efforts to understand the immune response to the SARS-CoV-2 vir
Document: We describe the establishment and current content of the ImmuneCODEâ„¢ database, which includes hundreds of millions of T-cell Receptor (TCR) sequences from over 1,400 subjects exposed to or infected with the SARS-CoV-2 virus, as well as over 135,000 high-confidence SARS-CoV-2-specific TCRs. This database is made freely available, and the data contained in it can be downloaded and analyzed online or offline to assist with the global efforts to understand the immune response to the SARS-CoV-2 virus and develop new interventions.
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