量子和人工智能时代生命科学的复杂性

IF 16.8 2区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY Wiley Interdisciplinary Reviews: Computational Molecular Science Pub Date : 2024-01-17 DOI:10.1002/wcms.1701
Alexey Pyrkov, Alex Aliper, Dmitry Bezrukov, Dmitriy Podolskiy, Feng Ren, Alex Zhavoronkov
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引用次数: 0

摘要

在从基因、细胞、分子、组织和途径等不同层面理解生物体方面取得重大进展之后,生命科学领域目前正转向将这些组成部分整合到更大的图景中,以理解它们的集体行为。这种视角的转变需要一个总体概念框架来理解生命科学中的复杂性,而这一框架目前尚不存在,大规模的数据收集、前所未有的计算能力和新的分析工具促进了这一转变。近年来,人工智能方法给生命科学带来了革命性的变化,而量子计算被认为是下一个最重要的技术飞跃。在此,我们提供了一个理论框架,引导研究人员围绕量子计算如何融入生物体层次复杂性研究的关键概念进行研究,并讨论了生命科学量子计算的最新进展:
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Complexity of life sciences in quantum and AI era

Having made significant advancements in understanding living organisms at various levels such as genes, cells, molecules, tissues, and pathways, the field of life sciences is now shifting towards integrating these components into the bigger picture to understand their collective behavior. Such a shift of perspective requires a general conceptual framework for understanding complexity in life sciences which is currently elusive, a transition being facilitated by large-scale data collection, unprecedented computational power, and new analytical tools. In recent years, life sciences have been revolutionized with AI methods, and quantum computing is touted to be the next most significant leap in technology. Here, we provide a theoretical framework to orient researchers around key concepts of how quantum computing can be integrated into the study of the hierarchical complexity of living organisms and discuss recent advances in quantum computing for life sciences.

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来源期刊
Wiley Interdisciplinary Reviews: Computational Molecular Science
Wiley Interdisciplinary Reviews: Computational Molecular Science CHEMISTRY, MULTIDISCIPLINARY-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
28.90
自引率
1.80%
发文量
52
审稿时长
6-12 weeks
期刊介绍: Computational molecular sciences harness the power of rigorous chemical and physical theories, employing computer-based modeling, specialized hardware, software development, algorithm design, and database management to explore and illuminate every facet of molecular sciences. These interdisciplinary approaches form a bridge between chemistry, biology, and materials sciences, establishing connections with adjacent application-driven fields in both chemistry and biology. WIREs Computational Molecular Science stands as a platform to comprehensively review and spotlight research from these dynamic and interconnected fields.
期刊最新文献
Issue Information Embedded Many-Body Green's Function Methods for Electronic Excitations in Complex Molecular Systems ROBERT: Bridging the Gap Between Machine Learning and Chemistry Advanced quantum and semiclassical methods for simulating photoinduced molecular dynamics and spectroscopy Computational design of energy-related materials: From first-principles calculations to machine learning
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