Cargando…
Interactome-Based Machine Learning Predicts Potential Therapeutics for COVID-19
[Image: see text] COVID-19, the disease caused by SARS-CoV-2, has been disrupting our lives for more than two years now. SARS-CoV-2 interacts with human proteins to pave its way into the human body, thereby wreaking havoc. Moreover, the mutating variants of the virus that take place in the SARS-CoV-...
Autores principales: | Ghosh, Nimisha, Saha, Indrajit, Gambin, Anna |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical
Society
2023
|
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10084923/ https://www.ncbi.nlm.nih.gov/pubmed/37163139 http://dx.doi.org/10.1021/acsomega.3c00030 |
Ejemplares similares
-
Interactome of human and SARS-CoV-2 proteins to identify human hub proteins associated with comorbidities
por: Ghosh, Nimisha, et al.
Publicado: (2021) -
Online Predictor Using Machine Learning to Predict
Novel Coronavirus and Other Pathogenic Viruses
por: Sarkar, Jnanendra Prasad, et al.
Publicado: (2022) -
Unveiling the Biomarkers
of Cancer and COVID-19 and
Their Regulations in Different Organs by Integrating RNA-Seq Expression
and Protein–Protein Interactions
por: Ghosh, Nimisha, et al.
Publicado: (2022) -
Transcription Factor Driven Gene Regulation in COVID-19 Patients
por: Santoni, Daniele, et al.
Publicado: (2023) -
Strategies for COVID-19 Epidemiological Surveillance in India: Overall Policies Till June 2021
por: Ghosh, Nimisha, et al.
Publicado: (2021)