Cargando…
Prediction of viral-host interactions of COVID-19 by computational methods
Experimental approaches are currently used to determine viral-host interactions, but these approaches are both time-consuming and costly. For these reasons, computational-based approaches are recommended. In this study, using computational-based approaches, viral-host interactions of SARS-CoV-2 viru...
Autores principales: | Alakus, Talha Burak, Turkoglu, Ibrahim |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9301933/ https://www.ncbi.nlm.nih.gov/pubmed/35879939 http://dx.doi.org/10.1016/j.chemolab.2022.104622 |
Ejemplares similares
-
A Novel Protein Mapping Method for Predicting the Protein Interactions in COVID-19 Disease by Deep Learning
por: Alakus, Talha Burak, et al.
Publicado: (2021) -
Comparison of deep learning approaches to predict COVID-19 infection
por: Alakus, Talha Burak, et al.
Publicado: (2020) -
Convolutional capsnet: A novel artificial neural network approach to detect COVID-19 disease from X-ray images using capsule networks
por: Toraman, Suat, et al.
Publicado: (2020) -
A Novel Repetition Frequency-Based DNA Encoding Scheme to Predict Human and Mouse DNA Enhancers with Deep Learning
por: Alakuş, Talha Burak
Publicado: (2023) -
Prediction of Interactions between Viral and Host Proteins Using Supervised Machine Learning Methods
por: Barman, Ranjan Kumar, et al.
Publicado: (2014)