Cargando…
Multi-omic analysis reveals enriched pathways associated with COVID-19 and COVID-19 severity
COVID-19 is a disease characterized by its seemingly unpredictable clinical outcomes. In order to better understand the molecular signature of the disease, a recent multi-omics study was done which looked at correlations between biomolecules and used a tree- based machine learning approach to predic...
Autores principales: | Lipman, Danika, Safo, Sandra E., Chekouo, Thierry |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9038205/ https://www.ncbi.nlm.nih.gov/pubmed/35468151 http://dx.doi.org/10.1371/journal.pone.0267047 |
Ejemplares similares
-
Integrative multi-omics approach for identifying molecular signatures and pathways and deriving and validating molecular scores for COVID-19 severity and status
por: Lipman, Danika, et al.
Publicado: (2023) -
Large-Scale Multi-omic Analysis of COVID-19 Severity
por: Overmyer, Katherine A., et al.
Publicado: (2021) -
Large-scale Multi-omic Analysis of COVID-19 Severity
por: Overmyer, Katherine A., et al.
Publicado: (2020) -
Multi-ancestry Mendelian randomization of omics traits revealing drug targets of COVID-19 severity
por: Zheng, Jie, et al.
Publicado: (2022) -
Deep IDA: A Deep Learning Method for Integrative Discriminant Analysis of Multi-View Data with Feature Ranking–An Application to COVID-19 severity
por: Wang, Jiuzhou, et al.
Publicado: (2021)