合成生物学 ›› 2021, Vol. 2 ›› Issue (1): 1-14.DOI: 10.12211/2096-8280.2020-074
王也, 王昊晨, 晏明皓, 胡冠华, 汪小我
收稿日期:
2020-07-09
修回日期:
2020-11-15
出版日期:
2021-02-28
发布日期:
2021-03-12
通讯作者:
汪小我
作者简介:
王也(1995—),女,博士研究生,主要研究方向为模式识别与机器学习、生物信息学、合成生物学。E-mail:基金资助:
Ye WANG, Haochen WANG, Minghao YAN, Guanhua HU, Xiaowo WANG
Received:
2020-07-09
Revised:
2020-11-15
Online:
2021-02-28
Published:
2021-03-12
Contact:
Xiaowo WANG
摘要:
合成生物学研究本着师法自然、改造自然及超越自然的理念,其核心是通过人工方式将基因元件优化改造和重新组合,以得到满足需要的人工生物系统。获取性能优异的生物元件是构建和控制人工生物系统的基础。近年来,人工生物分子在代谢工程和基因治疗等领域有着广泛应用。如何在广袤的分子序列空间中高效地搜索与设计具有特定生物功能的分子序列,是合成生物学所面临的重要科学问题。伴随着人工智能技术的快速发展,智能算法在复杂生物特征的挖掘与生物分子的设计中表现出巨大潜力。本文从利用深度学习技术发掘的复杂特征规律为指导,智能化地探索新药物分子、核酸序列和蛋白质序列空间的角度出发,重点分析了深度生成式模型在不同人工生物序列设计中的应用特点。在此基础上,结合小分子化合物、核酸和蛋白质等生物分子设计的应用案例,总结分析了针对人工生物分子序列设计的定向寻优策略。为了对智能算法设计的分子进行评估,系统分析了不同领域中不同角度序列设计评估方案的特点,展望了人工生物序列智能设计的发展,需要充分考虑生物系统具有多层次间调控高度耦合的复杂特性,从系统角度对不同层次的生物序列进行优化设计,从而推动人工生物系统的智能适配与优化。
中图分类号:
王也, 王昊晨, 晏明皓, 胡冠华, 汪小我. 生物分子序列的人工智能设计[J]. 合成生物学, 2021, 2(1): 1-14.
Ye WANG, Haochen WANG, Minghao YAN, Guanhua HU, Xiaowo WANG. Design of biomolecular sequences by artificial intelligence[J]. Synthetic Biology Journal, 2021, 2(1): 1-14.
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