Cargando…
Similarity maps and pairwise predictions for transmission dynamics of COVID-19 with neural networks
On March 11, 2020, the World Health Organization declared COVID-19 as a pandemic. Since then, many countries have experienced the rapid transmission of this respiratory disease among their populations and have exercised many strategies to mitigate the spread of this disease. The prediction of the tr...
Autor principal: | Hartono, Pitoyo |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Author. Published by Elsevier Ltd.
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7361102/ https://www.ncbi.nlm.nih.gov/pubmed/32835075 http://dx.doi.org/10.1016/j.imu.2020.100386 |
Ejemplares similares
-
Protein-protein interaction based on pairwise similarity
por: Zaki, Nazar, et al.
Publicado: (2009) -
Pairwise sequence similarity mapping with PaSiMap: Reclassification of immunoglobulin domains from titin as case study
por: Su, Kathy, et al.
Publicado: (2022) -
Innovative Deep Neural Network Fusion for Pairwise Translation Evaluation
por: Mouratidis, Despoina, et al.
Publicado: (2020) -
Inferring gene ontologies from pairwise similarity data
por: Kramer, Michael, et al.
Publicado: (2014) -
Modeling the early transmission of COVID-19 in New York and San Francisco using a pairwise network model
por: Feng, Shanshan, et al.
Publicado: (2022)