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- W4283656420 endingPage "113350" @default.
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- W4283656420 abstract "Conventional drug discovery and development is tedious and time-taking process; because of which it has failed to keep the required pace to mitigate threats and cater demands of viral and re-occurring diseases, such as Covid-19. The main reasons of this delay in traditional drug development are: high attrition rates, extensive time requirements, and huge financial investment with significant risk. The effective solution to de novo drug discovery is drug repurposing. Previous studies have shown that the network-based approaches and analysis are versatile platform for repurposing as the network biology is used to model the interactions between variety of biological concepts. Herein, we provide a comprehensive background of machine learning and deep learning in drug repurposing while specifically focusing on the applications of network-based approach to drug repurposing in Covid-19, data sources, and tools used. Furthermore, use of network proximity, network diffusion, and AI on network-based drug repurposing for Covid-19 is well-explained. Finally, limitations of network-based approaches in general and specific to network are stated along with future recommendations for better network-based models." @default.
- W4283656420 created "2022-06-29" @default.
- W4283656420 creator A5000073091 @default.
- W4283656420 creator A5016567439 @default.
- W4283656420 creator A5030019217 @default.
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- W4283656420 creator A5069201665 @default.
- W4283656420 creator A5075098273 @default.
- W4283656420 creator A5076049561 @default.
- W4283656420 date "2022-09-01" @default.
- W4283656420 modified "2023-10-04" @default.
- W4283656420 title "A comprehensive review of artificial intelligence and network based approaches to drug repurposing in Covid-19" @default.
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