Cargando…
Comprehensive analysis of pathways in Coronavirus 2019 (COVID-19) using an unsupervised machine learning method
The World Health Organization (WHO) introduced “Coronavirus disease 19” or “COVID-19” as a novel coronavirus in March 2020. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) requires the fast discovery of effective treatments to fight this worldwide crisis. Artificial intelligence and bio...
Autores principales: | Taheri, Golnaz, Habibi, Mahnaz |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Author(s). Published by Elsevier B.V.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9384336/ https://www.ncbi.nlm.nih.gov/pubmed/35992221 http://dx.doi.org/10.1016/j.asoc.2022.109510 |
Ejemplares similares
-
A new machine learning method for cancer mutation analysis
por: Habibi, Mahnaz, et al.
Publicado: (2022) -
Using informative features in machine learning based method for COVID-19 drug repurposing
por: Aghdam, Rosa, et al.
Publicado: (2021) -
Topological network based drug repurposing for coronavirus 2019
por: Habibi, Mahnaz, et al.
Publicado: (2021) -
Identification of essential genes associated with SARS-CoV-2 infection as potential drug target candidates with machine learning algorithms
por: Taheri, Golnaz, et al.
Publicado: (2023) -
A SARS-CoV-2 (COVID-19) biological network to find targets for drug repurposing
por: Habibi, Mahnaz, et al.
Publicado: (2021)