如何利用人工智能构建虚拟细胞:优先事项和机遇

Charlotte Bunne, Yusuf Roohani, Yanay Rosen, Ankit Gupta, Xikun Zhang, Marcel Roed, Theo Alexandrov, Mohammed AlQuraishi, Patricia Brennan, Daniel B. Burkhardt, Andrea Califano, Jonah Cool, Abby F. Dernburg, Kirsty Ewing, Emily B. Fox, Matthias Haury, Amy E. Herr, Eric Horvitz, Patrick D. Hsu, Viren Jain, Gregory R. Johnson, Thomas Kalil, David R. Kelley, Shana O. Kelley, Anna Kreshuk, Tim Mitchison, Stephani Otte, Jay Shendure, Nicholas J. Sofroniew, Fabian Theis, Christina V. Theodoris, Srigokul Upadhyayula, Marc Valer, Bo Wang, Eric Xing, Serena Yeung-Levy, Marinka Zitnik, Theofanis Karaletsos, Aviv Regev, Emma Lundberg, Jure Leskovec, Stephen R. Quake
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引用次数: 0

摘要

细胞可以说是生命的最小单位,是理解生物学的核心。精确的细胞建模对于理解细胞以及确定疾病的根本原因非常重要。人工智能(AI)的最新进展与生成大规模实验数据的能力相结合,为细胞建模带来了新的机遇。在这里,我们提出了人工智能驱动的虚拟细胞的愿景,即从不断增长的跨测量和跨尺度生物数据中直接学习不同条件下细胞和细胞系统的稳健表征。我们讨论了人工智能虚拟细胞的理想功能,包括生成跨尺度的生物实体通用表征,以及利用虚拟仪器促进可解释的硅学实验,以预测和理解它们的行为。我们进一步探讨了实现这一愿景所面临的挑战、机遇和要求,包括数据需求、评估策略以及社区标准和参与,以确保生物准确性和广泛实用性。我们设想在未来,人工智能虚拟细胞将帮助确定新的药物靶点,预测细胞对扰动的反应,并扩大假设探索的规模。在包括学术界、慈善机构、生物制药和人工智能行业在内的生物医学生态系统中开展开放式科学合作,对细胞机制和相互作用的全面预测性理解指日可待。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
How to Build the Virtual Cell with Artificial Intelligence: Priorities and Opportunities
The cell is arguably the smallest unit of life and is central to understanding biology. Accurate modeling of cells is important for this understanding as well as for determining the root causes of disease. Recent advances in artificial intelligence (AI), combined with the ability to generate large-scale experimental data, present novel opportunities to model cells. Here we propose a vision of AI-powered Virtual Cells, where robust representations of cells and cellular systems under different conditions are directly learned from growing biological data across measurements and scales. We discuss desired capabilities of AI Virtual Cells, including generating universal representations of biological entities across scales, and facilitating interpretable in silico experiments to predict and understand their behavior using Virtual Instruments. We further address the challenges, opportunities and requirements to realize this vision including data needs, evaluation strategies, and community standards and engagement to ensure biological accuracy and broad utility. We envision a future where AI Virtual Cells help identify new drug targets, predict cellular responses to perturbations, as well as scale hypothesis exploration. With open science collaborations across the biomedical ecosystem that includes academia, philanthropy, and the biopharma and AI industries, a comprehensive predictive understanding of cell mechanisms and interactions is within reach.
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