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Ultra high diversity factorizable libraries for efficient therapeutic discovery
View ORCID ProfileZheng Dai, View ORCID ProfileSachit D. Saksena, Geraldine Horny, Christine Banholzer, Stefan Ewert, View ORCID ProfileDavid K. Gifford
doi: https://doi.org/10.1101/2022.01.17.476670
Zheng Dai
1Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge MA 02139, USA
Sachit D. Saksena
1Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge MA 02139, USA
Geraldine Horny
2Novartis Institutes for BioMedical Research (NIBR), Basel, Switzerland
Christine Banholzer
2Novartis Institutes for BioMedical Research (NIBR), Basel, Switzerland
Stefan Ewert
2Novartis Institutes for BioMedical Research (NIBR), Basel, Switzerland
David K. Gifford
1Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge MA 02139, USA
Posted January 18, 2022.
Ultra high diversity factorizable libraries for efficient therapeutic discovery
Zheng Dai, Sachit D. Saksena, Geraldine Horny, Christine Banholzer, Stefan Ewert, David K. Gifford
bioRxiv 2022.01.17.476670; doi: https://doi.org/10.1101/2022.01.17.476670
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