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

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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Bibliographic Details
Main Authors: Andrew D. Marques, Michael Kummer, Oleksandr Kondratov, Arunava Banerjee, Oleksandr Moskalenko, Sergei Zolotukhin
Format: Article
Language:English
Published: Elsevier 2021-03-01
Series:Molecular Therapy: Methods & Clinical Development
Subjects:
Machine Learning
AAV
Capsid Libraries
Assembly
Packaging
ANN
Online Access:http://www.sciencedirect.com/science/article/pii/S2329050120302448

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http://www.sciencedirect.com/science/article/pii/S2329050120302448

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