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