Design of strictly orthogonal biosensors for maximizing renewable biofuel overproduction
By demonstrating the dominant role of the BSH counts in TF-SM interactions and establishing a machine learning-guided framework for TF evolution, this work advances rational design principles for engineering TFs with precise molecular recognition, offering broad applications in synthetic biology and metabolic engineering.
Authors
- Tong Wu (ORCID: https://orcid.org/0000-0001-5164-527X)
- Shengzhu Yu (ORCID: https://orcid.org/0009-0004-1155-8234)
- Xiaoyan Ma (ORCID: https://orcid.org/0000-0002-3558-4486)
- Ran Zhang (ORCID: https://orcid.org/0000-0003-2001-9959)
- Yi‐Xin Huo (ORCID: https://orcid.org/0000-0003-4644-999X)
- Yuhan Wang (ORCID: https://orcid.org/0009-0001-9192-801X)
- Min Li (ORCID: https://orcid.org/0009-0005-7707-2314)
- Sheng Lin (ORCID: https://orcid.org/0009-0009-4701-143X)
- Dongli Yan
Institutions
- Beijing Institute of Technology (CN)
- North China University of Science and Technology (CN)
- Jingdong (China) (CN)
Publication Details
- Journal
- Journal of Advanced Research
- Published
- 2025-09-01
- DOI
- https://doi.org/10.1016/j.jare.2025.09.015
- Citations
- 3
- Primary Topic
- thermodynamics and calorimetric analyses
- Type
- article
- Field-Weighted Citation Impact
- 5.26