清脆的
遗传增强
基因传递
计算生物学
病毒载体
计算机科学
基因组编辑
生物
基因
深度学习
人工智能
生物信息学
遗传学
重组DNA
作者
Akbar Hasanzadeh,Michael R. Hamblin,Jafar Kiani,Hamid Noori,Joseph Hardie,Mahdi Karimi,Hadi Shafiee
出处
期刊:Nano Today
[Elsevier]
日期:2022-12-01
卷期号:47: 101665-101665
被引量:9
标识
DOI:10.1016/j.nantod.2022.101665
摘要
Gene therapy enables the introduction of nucleic acids like DNA and RNA into host cells, and is expected to revolutionize the treatment of a wide range of diseases. This growth has been further accelerated by the discovery of CRISPR/Cas technology, which allows accurate genomic editing in a broad range of cells and organisms in vitro and in vivo. Despite many advances in gene delivery and the development of various viral and non-viral gene delivery vectors, the lack of highly efficient non-viral systems with low cellular toxicity remains a challenge. The application of cutting-edge technologies such as artificial intelligence (AI) has great potential to find new paradigms to solve this issue. Herein, we review AI and its major subfields including machine learning (ML), neural networks (NNs), expert systems, deep learning (DL), computer vision and robotics. We discuss the potential of AI-based models and algorithms in the design of targeted gene delivery vehicles capable of crossing extracellular and intracellular barriers by viral mimicry strategies. We finally discuss the role of AI in improving the function of CRISPR/Cas systems, developing novel nanobots, and mRNA vaccine carriers.
科研通智能强力驱动
Strongly Powered by AbleSci AI