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构建下一代虚拟细胞以理解细胞生物学。

Building the next generation of virtual cells to understand cellular biology.

机构信息

Allen Institute for Cell Science, Seattle, Washington.

Center for Cell Analysis and Modeling, University of Connecticut Health, Farmington, Connecticut.

出版信息

Biophys J. 2023 Sep 19;122(18):3560-3569. doi: 10.1016/j.bpj.2023.04.006. Epub 2023 Apr 11.

Abstract

Cell science has made significant progress by focusing on understanding individual cellular processes through reductionist approaches. However, the sheer volume of knowledge collected presents challenges in integrating this information across different scales of space and time to comprehend cellular behaviors, as well as making the data and methods more accessible for the community to tackle complex biological questions. This perspective proposes the creation of next-generation virtual cells, which are dynamic 3D models that integrate information from diverse sources, including simulations, biophysical models, image-based models, and evidence-based knowledge graphs. These virtual cells would provide statistically accurate and holistic views of real cells, bridging the gap between theoretical concepts and experimental data, and facilitating productive new collaborations among researchers across related fields.

摘要

细胞科学通过采用还原论方法专注于理解单个细胞过程取得了重大进展。然而,所收集的知识量庞大,这在整合不同时空尺度的信息以理解细胞行为方面带来了挑战,同时也使得数据和方法更便于社区用于解决复杂的生物学问题。本文观点提出了创建下一代虚拟细胞,这是一种动态的 3D 模型,可整合来自不同来源的信息,包括模拟、生物物理模型、基于图像的模型和基于证据的知识图谱。这些虚拟细胞将为真实细胞提供具有统计学准确性和整体性的视图,弥合理论概念和实验数据之间的差距,并促进相关领域研究人员之间富有成效的新合作。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/434d/10541477/16c8b240c7fe/gr1.jpg

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