Machine learning guided aptamer refinement and discovery

Machine learning guided aptamer refinement and discovery

Current aptamer discovery approaches are unable to probe the complete space of possible sequences. Here, the authors use machine learning to facilitate the development of DNA aptamers with improved binding affinities, and truncate them without significantly compromising binding affinity.

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Detalles Bibliográficos
Autores principales: Ali Bashir, Qin Yang, Jinpeng Wang, Stephan Hoyer, Wenchuan Chou, Cory McLean, Geoff Davis, Qiang Gong, Zan Armstrong, Junghoon Jang, Hui Kang, Annalisa Pawlosky, Alexander Scott, George E. Dahl, Marc Berndl, Michelle Dimon, B. Scott Ferguson
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
Materias:
Science
Q
Acceso en línea:https://doaj.org/article/9508da0079cf405d9f6f644c1119f62f
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Descripción
Sumario:Current aptamer discovery approaches are unable to probe the complete space of possible sequences. Here, the authors use machine learning to facilitate the development of DNA aptamers with improved binding affinities, and truncate them without significantly compromising binding affinity.

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