Identification of the susceptibility genes for COVID-19 in lung adenocarcinoma with global data and biological computation methods.
- DOI
- 10.1016/j.csbj.2021.11.026
- Published
- 2021
- Container
- Computational and structural biotechnology journal
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1016/j.csbj.2021.11.026,
title = {Identification of the susceptibility genes for COVID-19 in lung adenocarcinoma with global data and biological computation methods.},
author = {Gao L and Li GS and Li JD and He J and Zhang Y and Zhou HF and Kong JL and Chen G},
year = {2021},
journal = {Computational and structural biotechnology journal},
doi = {10.1016/j.csbj.2021.11.026},
url = {https://doi.org/10.1016/j.csbj.2021.11.026}
}RIS
TY - JOUR TI - Identification of the susceptibility genes for COVID-19 in lung adenocarcinoma with global data and biological computation methods. AU - Gao L AU - Li GS AU - Li JD AU - He J AU - Zhang Y AU - Zhou HF AU - Kong JL AU - Chen G PY - 2021 JO - Computational and structural biotechnology journal DO - 10.1016/j.csbj.2021.11.026 UR - https://doi.org/10.1016/j.csbj.2021.11.026 ER -
APA
L, G., GS, L., JD, L., J, H., Y, Z., HF, Z., JL, K., & G, C. (2021). Identification of the susceptibility genes for COVID-19 in lung adenocarcinoma with global data and biological computation methods.. Computational and structural biotechnology journal. https://doi.org/10.1016/j.csbj.2021.11.026
Source records
- pubmed · retrieved 2026-09-26T04:42:52.257Z