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Abstract
Designing promoters with desirable properties is crucial in synthetic biology. DeepSEED, an AI-aided framework, combines expert knowledge with deep learning to efficiently design synthetic promoters by optimizing flanking sequences. It successfully improved the properties of *E. coli* constitutive and inducible, and mammalian Dox-inducible promoters. DeepSEED captures implicit features in flanking sequences like k-mer frequencies and DNA shape, crucial for promoter properties.
Publisher
Nature Communications
Published On
Oct 09, 2023
Authors
Pengcheng Zhang, Haochen Wang, Hanwen Xu, Lei Wei, Liyang Liu, Zhirui Hu, Xiaowo Wang
Tags
synthetic biology
promoter design
AI framework
deep learning
flanking sequences
E. coli
mammalian promoters

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