PuSH - Publikationsserver des Helmholtz Zentrums München

Weller, B. ; Lin, C.-W. ; Pogoutse, O.* ; Sauer, M. ; Marin De La Rosa, N.A. ; Strobel, A. ; Young, V. ; Knapp, J.J.* ; Rayhan, A.* ; Falter, C. ; Kim, D.K.* ; Roth, F.P.* ; Falter-Braun, P.

A resource of human coronavirus protein-coding sequences in a flexible, multipurpose Gateway Entry clone collection.

Genes Genomes Genetics G3 13:6 (2023)
Verlagsversion DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
The COVID-19 pandemic has catalyzed unprecedented scientific data and reagent sharing and collaboration, which enabled understanding the virology of the SARS-CoV-2 virus and vaccine development at record speed. The pandemic, however, has also raised awareness of the danger posed by the family of coronaviruses, of which 7 are known to infect humans and dozens have been identified in reservoir species, such as bats, rodents, or livestock. To facilitate understanding the commonalities and specifics of coronavirus infections and aspects of viral biology that determine their level of lethality to the human host, we have generated a collection of freely available clones encoding nearly all human coronavirus proteins known to date. We hope that this flexible, Gateway-compatible vector collection will encourage further research into the interactions of coronaviruses with their human host, to increase preparedness for future zoonotic viral outbreaks.
Altmetric
Weitere Metriken?
[➜Einloggen]
Zusatzinfos bearbeiten [➜Einloggen]
Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter 229e ; Gateway Entry Clone ; Hcov ; Hku1 ; Mers ; Nl63 ; Oc43 ; Sars-cov-2 ; Coding Sequence ; Coronavirus; Sars
ISSN (print) / ISBN 2160-1836
e-ISSN 2160-1836
Zeitschrift Genes Genomes Genetics G3
Quellenangaben Band: 13, Heft: 7, Seiten: , Artikelnummer: 6 Supplement: ,
Verlag Genetics Society of America
Verlagsort Pittsburgh, PA
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Network Biology (INET)
Förderungen Free State of Bavaria's AI for Therapy (AI4T) Initiative through the Institute of AI for Drug Discovery (AID)
European Union