Molecular networks in Network Medicine: Development and applications.

IF 7.9 Q1 Medicine Wiley Interdisciplinary Reviews-Systems Biology and Medicine Pub Date : 2020-11-01 Epub Date: 2020-04-19 DOI:10.1002/wsbm.1489
Edwin K Silverman, Harald H H W Schmidt, Eleni Anastasiadou, Lucia Altucci, Marco Angelini, Lina Badimon, Jean-Luc Balligand, Giuditta Benincasa, Giovambattista Capasso, Federica Conte, Antonella Di Costanzo, Lorenzo Farina, Giulia Fiscon, Laurent Gatto, Michele Gentili, Joseph Loscalzo, Cinzia Marchese, Claudio Napoli, Paola Paci, Manuela Petti, John Quackenbush, Paolo Tieri, Davide Viggiano, Gemma Vilahur, Kimberly Glass, Jan Baumbach
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引用次数: 134

Abstract

Network Medicine applies network science approaches to investigate disease pathogenesis. Many different analytical methods have been used to infer relevant molecular networks, including protein-protein interaction networks, correlation-based networks, gene regulatory networks, and Bayesian networks. Network Medicine applies these integrated approaches to Omics Big Data (including genetics, epigenetics, transcriptomics, metabolomics, and proteomics) using computational biology tools and, thereby, has the potential to provide improvements in the diagnosis, prognosis, and treatment of complex diseases. We discuss briefly the types of molecular data that are used in molecular network analyses, survey the analytical methods for inferring molecular networks, and review efforts to validate and visualize molecular networks. Successful applications of molecular network analysis have been reported in pulmonary arterial hypertension, coronary heart disease, diabetes mellitus, chronic lung diseases, and drug development. Important knowledge gaps in Network Medicine include incompleteness of the molecular interactome, challenges in identifying key genes within genetic association regions, and limited applications to human diseases. This article is categorized under: Models of Systems Properties and Processes > Mechanistic Models Translational, Genomic, and Systems Medicine > Translational Medicine Analytical and Computational Methods > Analytical Methods Analytical and Computational Methods > Computational Methods.

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网络医学中的分子网络:发展与应用。
网络医学应用网络科学方法研究疾病的发病机制。许多不同的分析方法被用来推断相关的分子网络,包括蛋白质-蛋白质相互作用网络、基于相关性的网络、基因调控网络和贝叶斯网络。网络医学利用计算生物学工具,将这些综合方法应用于组学大数据(包括遗传学、表观遗传学、转录组学、代谢组学和蛋白质组学),从而有可能改善复杂疾病的诊断、预后和治疗。我们简要讨论了用于分子网络分析的分子数据类型,概述了推断分子网络的分析方法,并回顾了验证和可视化分子网络的工作。分子网络分析已成功应用于肺动脉高压、冠心病、糖尿病、慢性肺部疾病和药物开发。网络医学中重要的知识缺口包括分子相互作用组的不完整,在遗传关联区域内识别关键基因的挑战,以及对人类疾病的有限应用。本文分类如下:系统特性和过程模型>转化、基因组和系统医学的机制模型>转化医学分析和计算方法>分析方法分析和计算方法>计算方法。
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来源期刊
CiteScore
18.40
自引率
0.00%
发文量
0
审稿时长
>12 weeks
期刊介绍: Journal Name:Wiley Interdisciplinary Reviews-Systems Biology and Medicine Focus: Strong interdisciplinary focus Serves as an encyclopedic reference for systems biology research Conceptual Framework: Systems biology asserts the study of organisms as hierarchical systems or networks Individual biological components interact in complex ways within these systems Article Coverage: Discusses biology, methods, and models Spans systems from a few molecules to whole species Topical Coverage: Developmental Biology Physiology Biological Mechanisms Models of Systems, Properties, and Processes Laboratory Methods and Technologies Translational, Genomic, and Systems Medicine
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