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PreprintCC BY-NCChemRxiv

A substrate-first-enzymology deep-learning framework

  1. 1State Key Laboratory of Bioreactor Engineering, School of Biotechnology, China University of Science and Technology, 130 Meilong Road, Shanghai, China, 200237
  2. 2School of Information Science and Engineering, East China University of Science, 130 Meilong Road, Shanghai, China, 200237
  3. 3Biotechnology Institute, University of Minnesota, 1479 Gortner Avenue, Saint Paul, Minnesota, 55108

Abstract

29 Enzyme activity data favor familiar substrates and positive outcomes, creating 30

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BibTeX
@misc{zhao2026substratefirstenzymology,
  title = {{A substrate-first-enzymology deep-learning framework}},
  author = {You-Xue Zhao and Hao-Yue Wang and Luo-Bing Meng and Yu-Xin Jia and Xi-Ruo Li and Jia-Ming Yang and Romas J. Kazlauskas and Gui-Sheng Fan and Jian-He Xu and Haoyue Wang},
  howpublished = {ChemRxiv},
  year = {2026},
  month = sep,
  doi = {10.26434/chemrxiv.15008807/v1},
  url = {https://chemrxiv.org/doi/full/10.26434/chemrxiv.15008807/v1},
  note = {CC BY-NC},
}
RIS
TY  - UNPB
TI  - A substrate-first-enzymology deep-learning framework
AU  - You-Xue Zhao
AU  - Hao-Yue Wang
AU  - Luo-Bing Meng
AU  - Yu-Xin Jia
AU  - Xi-Ruo Li
AU  - Jia-Ming Yang
AU  - Romas J. Kazlauskas
AU  - Gui-Sheng Fan
AU  - Jian-He Xu
AU  - Haoyue Wang
PY  - 2026
DA  - 2026/09/14
PB  - ChemRxiv
DO  - 10.26434/chemrxiv.15008807/v1
UR  - https://chemrxiv.org/doi/full/10.26434/chemrxiv.15008807/v1
AB  - 29 Enzyme activity data favor familiar substrates and positive outcomes, creating 30
ER  -