Ultra-high-diversity factorizable libraries for efficient therapeutic discovery

The successful discovery of novel biological therapeutics by selection requires highly diverse libraries of candidate sequences that contain a high proportion of desirable candidates. Here we propose the use of computationally designed factorizable libraries made of concatenated segment libraries as...

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Detalles Bibliográficos
Autores principales: Dai, Zheng, Saksena, Sachit D., Horny, Geraldine, Banholzer, Christine, Ewert, Stefan, Gifford, David K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory Press 2022
Materias:
RECOMB 2022 Special/Methods
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9528983/
https://www.ncbi.nlm.nih.gov/pubmed/35738900
http://dx.doi.org/10.1101/gr.276593.122

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9528983/
https://www.ncbi.nlm.nih.gov/pubmed/35738900
http://dx.doi.org/10.1101/gr.276593.122

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