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Coronavirus Immunotherapeutic Consortium Database.

Publication ,  Journal Article
Mahita, J; Ha, B; Gambiez, A; Schendel, SL; Li, H; Hastie, KM; Dennison, SM; Li, K; Kuzmina, N; Periasamy, S; Bukreyev, A; Munt, JE; Atyeo, C ...
Published in: Database (Oxford)
February 10, 2023

The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has seen multiple anti-SARS-CoV-2 antibodies being generated globally. It is difficult, however, to assemble a useful compendium of these biological properties if they are derived from experimental measurements performed at different sites under different experimental conditions. The Coronavirus Immunotherapeutic Consortium (COVIC) circumvents these issues by experimentally testing blinded antibodies side by side for several functional activities. To collect these data in a consistent fashion and make it publicly available, we established the COVIC database (COVIC-DB, https://covicdb.lji.org/). This database enables systematic analysis and interpretation of this large-scale dataset by providing a comprehensive view of various features such as affinity, neutralization, in vivo protection and effector functions for each antibody. Interactive graphs enable direct comparisons of antibodies based on select functional properties. We demonstrate how the COVIC-DB can be utilized to examine relationships among antibody features, thereby guiding the design of therapeutic antibody cocktails. Database URL  https://covicdb.lji.org/.

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Published In

Database (Oxford)

DOI

EISSN

1758-0463

Publication Date

February 10, 2023

Volume

2023

Location

England

Related Subject Headings

  • SARS-CoV-2
  • Immunotherapy
  • Humans
  • COVID-19
  • Antibodies, Viral
  • 4605 Data management and data science
  • 3102 Bioinformatics and computational biology
  • 0807 Library and Information Studies
  • 0804 Data Format
 

Citation

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Mahita, J., Ha, B., Gambiez, A., Schendel, S. L., Li, H., Hastie, K. M., … Peters, B. (2023). Coronavirus Immunotherapeutic Consortium Database. Database (Oxford), 2023. https://doi.org/10.1093/database/baac112
Mahita, Jarjapu, Brendan Ha, Anais Gambiez, Sharon L. Schendel, Haoyang Li, Kathryn M. Hastie, S Moses Dennison, et al. “Coronavirus Immunotherapeutic Consortium Database.Database (Oxford) 2023 (February 10, 2023). https://doi.org/10.1093/database/baac112.
Mahita J, Ha B, Gambiez A, Schendel SL, Li H, Hastie KM, et al. Coronavirus Immunotherapeutic Consortium Database. Database (Oxford). 2023 Feb 10;2023.
Mahita, Jarjapu, et al. “Coronavirus Immunotherapeutic Consortium Database.Database (Oxford), vol. 2023, Feb. 2023. Pubmed, doi:10.1093/database/baac112.
Mahita J, Ha B, Gambiez A, Schendel SL, Li H, Hastie KM, Dennison SM, Li K, Kuzmina N, Periasamy S, Bukreyev A, Munt JE, Osei-Twum M, Atyeo C, Overton JA, Vita R, Guzman-Orozco H, Mendes M, Kojima M, Halfmann PJ, Kawaoka Y, Alter G, Gagnon L, Baric RS, Tomaras GD, Germann T, Bedinger D, Greenbaum JA, Saphire EO, Peters B. Coronavirus Immunotherapeutic Consortium Database. Database (Oxford). 2023 Feb 10;2023.
Journal cover image

Published In

Database (Oxford)

DOI

EISSN

1758-0463

Publication Date

February 10, 2023

Volume

2023

Location

England

Related Subject Headings

  • SARS-CoV-2
  • Immunotherapy
  • Humans
  • COVID-19
  • Antibodies, Viral
  • 4605 Data management and data science
  • 3102 Bioinformatics and computational biology
  • 0807 Library and Information Studies
  • 0804 Data Format