Network Medicine: From Conceptual Frameworks to Applications and Future Trends

IF 2.4 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Transactions on Molecular, Biological, and Multi-Scale Communications Pub Date : 2023-08-25 DOI:10.1109/TMBMC.2023.3308689

Enes Sefa Ayar;Sina Dadmand;Nurcan Tuncbag

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引用次数: 0

Abstract

The intricate nature of biological processes is orchestrated by molecular interactions. The complexity of these interactions stems from the sheer number of components involved and their relationships. To overcome this complexity, network medicine adopts a holistic, integrative approach at multiple levels. The human interactome involves over 100,000 molecules, including proteins, RNAs, and metabolites, all interconnected by a network of connections. One challenge in understanding the human interactome is associating specific parts of this network with biological phenomena such as diseases, drug resistance, and other abnormalities. Although molecular measurements can quantitatively identify many altered molecules, making sense of these molecular changes within the broader network context is a formidable task. Notably, alterations in the human interactome often occur in closely connected regions of the network. By using prior biological knowledge and applying the context-specific molecular interplays, specific sub-networks can be extracted. These network modules can provide valuable insights into complex biological questions. Furthermore, a range of learning and graph-based methodologies are employed to deduce meaningful clinical outcomes in these modules. In this context, we present a comprehensive overview of the standard workflows utilized in network medicine, along with a discussion of its applications and future directions.

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网络医学：从概念框架到应用和未来趋势

生物过程的复杂性是由分子相互作用协调的。这些相互作用的复杂性源于所涉及的组件数量及其关系。为了克服这种复杂性，网络医学在多个层面上采用了整体、综合的方法。人类相互作用组涉及超过100000个分子，包括蛋白质、RNA和代谢物，所有这些都通过连接网络相互连接。理解人类相互作用机制的一个挑战是将这个网络的特定部分与疾病、耐药性和其他异常等生物现象联系起来。尽管分子测量可以定量识别许多改变的分子，但在更广泛的网络环境中理解这些分子变化是一项艰巨的任务。值得注意的是，人类互动机制的改变经常发生在网络的紧密连接区域。通过使用先前的生物学知识并应用上下文特定的分子相互作用，可以提取特定的子网络。这些网络模块可以为复杂的生物学问题提供有价值的见解。此外，在这些模块中，还采用了一系列基于学习和图形的方法来推断有意义的临床结果。在此背景下，我们全面概述了网络医学中使用的标准工作流程，并讨论了其应用和未来方向。

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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来源期刊

IEEE Transactions on Molecular, Biological, and Multi-Scale Communications Mathematics-Modeling and Simulation

CiteScore

3.90

自引率

13.60%

发文量

期刊介绍： As a result of recent advances in MEMS/NEMS and systems biology, as well as the emergence of synthetic bacteria and lab/process-on-a-chip techniques, it is now possible to design chemical “circuits”, custom organisms, micro/nanoscale swarms of devices, and a host of other new systems. This success opens up a new frontier for interdisciplinary communications techniques using chemistry, biology, and other principles that have not been considered in the communications literature. The IEEE Transactions on Molecular, Biological, and Multi-Scale Communications (T-MBMSC) is devoted to the principles, design, and analysis of communication systems that use physics beyond classical electromagnetism. This includes molecular, quantum, and other physical, chemical and biological techniques; as well as new communication techniques at small scales or across multiple scales (e.g., nano to micro to macro; note that strictly nanoscale systems, 1-100 nm, are outside the scope of this journal). Original research articles on one or more of the following topics are within scope: mathematical modeling, information/communication and network theoretic analysis, standardization and industrial applications, and analytical or experimental studies on communication processes or networks in biology. Contributions on related topics may also be considered for publication. Contributions from researchers outside the IEEE’s typical audience are encouraged.