Applying machine learning to predict viral assembly for adeno-associated virus capsid libraries

Machine learning (ML) can aid in novel discoveries in the field of viral gene therapy. Specifically, big data gathered through next-generation sequencing (NGS) of complex capsid libraries is an especially prominent source of lost potential in data analysis and prediction. Furthermore, adeno-associat...

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Detalles Bibliográficos
Autores principales: Marques, Andrew D., Kummer, Michael, Kondratov, Oleksandr, Banerjee, Arunava, Moskalenko, Oleksandr, Zolotukhin, Sergei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society of Gene & Cell Therapy 2020
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7809249/
https://www.ncbi.nlm.nih.gov/pubmed/33511242
http://dx.doi.org/10.1016/j.omtm.2020.11.017

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7809249/
https://www.ncbi.nlm.nih.gov/pubmed/33511242
http://dx.doi.org/10.1016/j.omtm.2020.11.017

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