An architecture for collaboration in systems biology at the age of the Metaverse.

IF 3.5 2区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Eliott Jacopin, Yuki Sakamoto, Kozo Nishida, Kazunari Kaizu, Koichi Takahashi
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引用次数: 0

Abstract

As the current state of the Metaverse is largely driven by corporate interests, which may not align with scientific goals and values, academia should play a more active role in its development. Here, we present the challenges and solutions for building a Metaverse that supports systems biology research and collaboration. Our solution consists of two components: Kosmogora, a server ensuring biological data access, traceability, and integrity in the context of a highly collaborative environment such as a metaverse; and ECellDive, a virtual reality application to explore, interact, and build upon the data managed by Kosmogora. We illustrate the synergy between the two components by visualizing a metabolic network and its flux balance analysis. We also argue that the Metaverse of systems biology will foster closer communication and cooperation between experimentalists and modelers in the field.

Abstract Image

元宇宙时代的系统生物学协作架构。
由于目前的 Metaverse 主要受企业利益驱动,可能与科学目标和价值观不一致,因此学术界应在其发展中发挥更积极的作用。在此,我们将介绍构建支持系统生物学研究与合作的 Metaverse 所面临的挑战和解决方案。我们的解决方案由两部分组成:Kosmogora,一个确保生物数据访问、可追溯性和完整性的服务器,用于高度协作的环境(如元宇宙);ECellDive,一个虚拟现实应用程序,用于探索、交互和构建由 Kosmogora 管理的数据。我们通过可视化代谢网络及其通量平衡分析来说明这两个组件之间的协同作用。我们还认为,系统生物学的 Metaverse 将促进该领域的实验人员和建模人员之间更密切的交流与合作。
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来源期刊
NPJ Systems Biology and Applications
NPJ Systems Biology and Applications Mathematics-Applied Mathematics
CiteScore
5.80
自引率
0.00%
发文量
46
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.
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