多学科方法对虚拟人肺建模。

IF 3.5 2区生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY

NPJ Systems Biology and Applications Pub Date : 2025-04-18 DOI:10.1038/s41540-025-00517-x

Timothy Lam, Henry T Quach, Lauren Hall, Maria Abou Chakra, Amy P Wong

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引用次数: 0

摘要

将生物数据与计算机建模相结合，为开发虚拟人体模型或“数字双胞胎”提供了变革性的潜力。这些模型对加深我们对疾病的理解和发现新的治疗策略有着巨大的希望。这种方法对缺乏可靠模型的疾病特别有价值。在这里，我们回顾了目前人类肺发育的建模工作，强调了跨学科合作的作用和数字肺双胞胎的关键进展。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

A multidisciplinary approach towards modeling of a virtual human lung.

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A multidisciplinary approach towards modeling of a virtual human lung.

Integrating biological data with in silico modeling offers the transformative potential to develop virtual human models, or "digital twins." These models hold immense promise for deepening our understanding of diseases and uncovering new therapeutic strategies. This approach is especially valuable for diseases lacking reliable models. Here we review current modelling efforts in of human lung development, highlighting the role of interdisciplinary collaboration and key advances toward a digital lung twin.

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来源期刊

NPJ Systems Biology and Applications Mathematics-Applied Mathematics

CiteScore

5.80

自引率

0.00%

发文量

审稿时长

8 weeks

期刊介绍： npj Systems Biology and Applications is an online Open Access journal dedicated to publishing the premier research that takes a systems-oriented approach. The journal aims to provide a forum for the presentation of articles that help define this nascent field, as well as those that apply the advances to wider fields. We encourage studies that integrate, or aid the integration of, data, analyses and insight from molecules to organisms and broader systems. Important areas of interest include not only fundamental biological systems and drug discovery, but also applications to health, medical practice and implementation, big data, biotechnology, food science, human behaviour, broader biological systems and industrial applications of systems biology. We encourage all approaches, including network biology, application of control theory to biological systems, computational modelling and analysis, comprehensive and/or high-content measurements, theoretical, analytical and computational studies of system-level properties of biological systems and computational/software/data platforms enabling such studies.