A proposed workflow for proactive virus surveillance and prediction of variants for vaccine design

Jordan J Baker; Christopher J P Mathy; Julia Schaletzky

doi:10.1371/journal.pcbi.1009624

A proposed workflow for proactive virus surveillance and prediction of variants for vaccine design

PLoS Comput Biol. 2021 Dec 16;17(12):e1009624. doi: 10.1371/journal.pcbi.1009624. eCollection 2021 Dec.

Authors

Jordan J Baker^{1

2}, Christopher J P Mathy¹, Julia Schaletzky³

Affiliations

¹ Joint Graduate Program in Bioengineering, University of California, Berkeley and University of California, San Francisco, Berkeley, California, United States of America.
² Innovative Genomics Institute, University of California, Berkeley, Berkeley, California, United States of America.
³ Center for Emerging and Neglected Diseases, Immunotherapy and Vaccine Research Initiative, University of California, Berkeley, Berkeley, California, United States of America.

No abstract available

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms
COVID-19 / immunology
COVID-19 / prevention & control
COVID-19 / virology
COVID-19 Vaccines
Computational Biology / methods*
Humans
Public Health Surveillance / methods*
Research Design
SARS-CoV-2 / genetics
SARS-CoV-2 / immunology
SARS-CoV-2 / pathogenicity
Viral Vaccines*
Virus Diseases* / immunology
Virus Diseases* / prevention & control
Virus Diseases* / virology
Viruses* / genetics
Viruses* / immunology
Viruses* / pathogenicity
Workflow*

Substances

COVID-19 Vaccines
Viral Vaccines

Supplementary concepts

SARS-CoV-2 variants

Grants and funding

J.S. was supported financially by the generosity of Eric and Wendy Schmidt by recommendation of the Schmidt Futures program (https://schmidtfutures.com), and through Fast Grants (part of Emergent Ventures at George Mason University) (https://fastgrants.org). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.