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A Generative Neural Network for Maximizing Fitness and Diversity of Synthetic DNA and Protein Sequences
Engineering gene and protein sequences with defined functional properties is a major goal of synthetic biology. Deep neural network models, together with gradient ascent-style optimization, show promise for sequence design. The generated sequences can however get stuck in local minima and often have...
Autores principales: | Linder, Johannes, Bogard, Nicholas, Rosenberg, Alexander B., Seelig, Georg |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8694568/ https://www.ncbi.nlm.nih.gov/pubmed/32711843 http://dx.doi.org/10.1016/j.cels.2020.05.007 |
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