Multi-omic analysis reveals enriched pathways associated with COVID-19 and COVID-19 severity is a research paper published in PLoS ONE (2022). On theSindex it has a DataRank of 0. It has been cited 25 times.
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new frontier in research fund
Grant: NFRFE-2018-00748
natural sciences and engineering research council of canada
Grant: RGPIN-2019-04810
national institutes of health
Grant: 5KL2TR002492-04, 1R35GM142695-01
NCATS NIH HHS
Grant: KL2 TR002492
NIGMS NIH HHS
Grant: R35 GM142695
Natural Sciences and Engineering Research Council of Canada
Grant: unidentified
unidentified
National Institutes of Health
Grant: 5KL2TR002492-04
Institutional Career Development Core
National Institutes of Health
Grant: 1R35GM142695-01
Statistical and Machine Learning Methods to Address Biomedical Challenges for Integrating Multi-view Data
FWCI
2.41
Citation Percentile
0.9%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals
Additional file 1 of Integrative multi-omics approach for identifying molecular signatures and pathways and deriving and validating molecular scores for COVID-19 severity and status
Additional file 1 of Integrative multi-omics approach for identifying molecular signatures and pathways and deriving and validating molecular scores for COVID-19 severity and status