Profiling COVID-19 Genetic Research: A Data-Driven Study Utilizing Intelligent Bibliometrics.

Wu M, Zhang Y, Grosser M, Tipper S, Venter D, Lin H, Lu J

DOI: 10.3389/frma.2021.683212
Published: 2021
Container: Frontiers in research metrics and analytics
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3389/frma.2021.683212,
  title = {Profiling COVID-19 Genetic Research: A Data-Driven Study Utilizing Intelligent Bibliometrics.},
  author = {Wu M and Zhang Y and Grosser M and Tipper S and Venter D and Lin H and Lu J},
  year = {2021},
  journal = {Frontiers in research metrics and analytics},
  doi = {10.3389/frma.2021.683212},
  url = {https://doi.org/10.3389/frma.2021.683212}
}

RIS

TY  - JOUR
TI  - Profiling COVID-19 Genetic Research: A Data-Driven Study Utilizing Intelligent Bibliometrics.
AU  - Wu M
AU  - Zhang Y
AU  - Grosser M
AU  - Tipper S
AU  - Venter D
AU  - Lin H
AU  - Lu J
PY  - 2021
JO  - Frontiers in research metrics and analytics
DO  - 10.3389/frma.2021.683212
UR  - https://doi.org/10.3389/frma.2021.683212
ER  -

APA

M, W., Y, Z., M, G., S, T., D, V., H, L., & J, L. (2021). Profiling COVID-19 Genetic Research: A Data-Driven Study Utilizing Intelligent Bibliometrics.. Frontiers in research metrics and analytics. https://doi.org/10.3389/frma.2021.683212

Source records

pubmed · retrieved 2026-09-26T03:59:52.670Z