A multi-modal data harmonisation approach for discovery of COVID-19 drug targets
Published in Briefings in Bioinformatics, 2021
Recommended citation: Tyrone Chen, Melcy Philip, Kim-Anh Lê Cao, Sonika Tyagi, "A multi-modal data harmonisation approach for discovery of COVID-19 drug targets." Briefings in Bioinformatics, May 2021, bbab185. DOI: https://doi.org/10.1093/bib/bbab185 https://doi.org/10.1093/bib/bbab185
We demonstrate with two independent case studies that our multi-modal data harmonisation pipeline easily generates a list of pertinent biological features for downstream analyses without using algorithms specifically tailored to the datasets.
Plain text citation:
Tyrone Chen, Melcy Philip, Kim-Anh Lê Cao, Sonika Tyagi, "A multi-modal data harmonisation approach for discovery of COVID-19 drug targets." Briefings in Bioinformatics, May 2021, bbab185. DOI: https://doi.org/10.1093/bib/bbab185
Bibtex citation:
@article{10.1093/bib/bbab185,
author = {Chen, Tyrone and
Philip, Melcy and
Lê Cao, Kim-Anh and
Tyagi, Sonika},
title = "{A multi-modal data harmonisation approach
for discovery of COVID-19 drug targets}",
journal = {Briefings in Bioinformatics},
year = {2021},
month = {05},
issn = {1477-4054},
doi = {10.1093/bib/bbab185},
url = {https://doi.org/10.1093/bib/bbab185},
note = {bbab185},
eprint = {https://academic.oup.com/bib/advance-article-pdf/doi/10.1093/bib/bbab185/38130519/bbab185.pdf},
}