AI-driven Protein Engineering for DNA Sequence Modification

Authors

  • Luqi Lin Software Engineering, SunYat-sen University,Shanghai,China
  • Zhengrong Cui Software Engineering, Northeastern University, Shanghai, China
  • Sihao Wang Mathematics, Southern Methodist University, Dallas, TX,USA
  • Yizhi Chen Information Studies, Trine University, Allen Park, MI, USA
  • Yanqi Zong Information Studies, Trine University, PhoenixAZ, USA

DOI:

https://doi.org/10.53469/jtpes.2024.04(03).17

Keywords:

Gene editing, Artificial intelligence, CRISPR-Cas9, Precision medicine

Abstract

The integration of artificial intelligence (AI) with gene editing technologies like CRISPR-Cas9 holds immense promise for advancing biomedical research and personalized medicine. This article highlights the crucial role of AI in predicting and minimizing off-target effects, thereby enhancing the precision and efficiency of gene editing. Researchers have developed algorithms like BE-DICT to accurately predict base editing outcomes, showcasing the potential of AI-driven strategies in optimizing gene editing processes. By combining AI with bioengineering, this interdisciplinary approach aims to automate and refine DNA modifications, paving the way for innovative applications in personalized gene therapy and biofabrication. Ultimately, this research endeavors to revolutionize the life sciences field, leading to significant breakthroughs in healthcare and biotechnology.

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Published

2024-03-25

How to Cite

Lin, L., Cui, Z., Wang, S., Chen, Y., & Zong, Y. (2024). AI-driven Protein Engineering for DNA Sequence Modification. Journal of Theory and Practice of Engineering Science, 4(03), 183–190. https://doi.org/10.53469/jtpes.2024.04(03).17

Issue

Vol. 4 No. 03 (2024): JTPES-2023-4-3

Section

Articles

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Copyright (c) 2024 Luqi Lin, Zhengrong Cui, Sihao Wang, Yizhi Chen, Yanqi Zong

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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.