De novo protein design by deep network hallucination
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DOI: 10.1038/s41586-021-04184-w
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Cited by:
- Namrata Anand & Raphael Eguchi & Irimpan I. Mathews & Carla P. Perez & Alexander Derry & Russ B. Altman & Po-Ssu Huang, 2022. "Protein sequence design with a learned potential," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
- Evgenii Lobzaev & Giovanni Stracquadanio, 2024. "Dirichlet latent modelling enables effective learning and sampling of the functional protein design space," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
- Thomas W. Linsky & Kyle Noble & Autumn R. Tobin & Rachel Crow & Lauren Carter & Jeffrey L. Urbauer & David Baker & Eva-Maria Strauch, 2022. "Sampling of structure and sequence space of small protein folds," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
- Jan Zrimec & Xiaozhi Fu & Azam Sheikh Muhammad & Christos Skrekas & Vykintas Jauniskis & Nora K. Speicher & Christoph S. Börlin & Vilhelm Verendel & Morteza Haghir Chehreghani & Devdatt Dubhashi & Ver, 2022. "Controlling gene expression with deep generative design of regulatory DNA," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
- Tamuka M. Chidyausiku & Soraia R. Mendes & Jason C. Klima & Marta Nadal & Ulrich Eckhard & Jorge Roel-Touris & Scott Houliston & Tibisay Guevara & Hugh K. Haddox & Adam Moyer & Cheryl H. Arrowsmith & , 2022. "De novo design of immunoglobulin-like domains," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
- Md Tauhidul Islam & Zixia Zhou & Hongyi Ren & Masoud Badiei Khuzani & Daniel Kapp & James Zou & Lu Tian & Joseph C. Liao & Lei Xing, 2023. "Revealing hidden patterns in deep neural network feature space continuum via manifold learning," Nature Communications, Nature, vol. 14(1), pages 1-20, December.
- Betz, Ulrich A.K. & Arora, Loukik & Assal, Reem A. & Azevedo, Hatylas & Baldwin, Jeremy & Becker, Michael S. & Bostock, Stefan & Cheng, Vinton & Egle, Tobias & Ferrari, Nicola & Schneider-Futschik, El, 2023. "Game changers in science and technology - now and beyond," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
- Nathaniel R. Bennett & Brian Coventry & Inna Goreshnik & Buwei Huang & Aza Allen & Dionne Vafeados & Ying Po Peng & Justas Dauparas & Minkyung Baek & Lance Stewart & Frank DiMaio & Steven Munck & Savv, 2023. "Improving de novo protein binder design with deep learning," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
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