Suppr超能文献

网络医学:一种基于网络的人类疾病研究方法。

Network medicine: a network-based approach to human disease.

机构信息

Center for Complex Networks Research and Department of Physics, Northeastern University, 110 Forsyth Street, 111 Dana Research Center, Boston, Massachusetts 02115, USA.

出版信息

Nat Rev Genet. 2011 Jan;12(1):56-68. doi: 10.1038/nrg2918.

Abstract

Given the functional interdependencies between the molecular components in a human cell, a disease is rarely a consequence of an abnormality in a single gene, but reflects the perturbations of the complex intracellular and intercellular network that links tissue and organ systems. The emerging tools of network medicine offer a platform to explore systematically not only the molecular complexity of a particular disease, leading to the identification of disease modules and pathways, but also the molecular relationships among apparently distinct (patho)phenotypes. Advances in this direction are essential for identifying new disease genes, for uncovering the biological significance of disease-associated mutations identified by genome-wide association studies and full-genome sequencing, and for identifying drug targets and biomarkers for complex diseases.

摘要

鉴于人类细胞中分子成分之间的功能相互依赖性,疾病很少是单个基因异常的结果,而是反映了连接组织和器官系统的复杂细胞内和细胞间网络的干扰。网络医学的新兴工具提供了一个平台,可以系统地探索不仅是特定疾病的分子复杂性,导致疾病模块和途径的识别,而且是明显不同的(病理)表型之间的分子关系。在这方面的进展对于确定新的疾病基因、揭示全基因组关联研究和全基因组测序确定的与疾病相关的突变的生物学意义以及确定复杂疾病的药物靶点和生物标志物至关重要。

相似文献

3
A paradigm shift in medicine: A comprehensive review of network-based approaches.医学范式转变:基于网络方法的综合述评。
Biochim Biophys Acta Gene Regul Mech. 2020 Jun;1863(6):194416. doi: 10.1016/j.bbagrm.2019.194416. Epub 2019 Aug 2.
4
Pathway networks generated from human disease phenome.人类疾病表型生成的通路网络。
BMC Med Genomics. 2018 Sep 14;11(Suppl 3):75. doi: 10.1186/s12920-018-0386-2.
5
Assessment of network module identification across complex diseases.评估复杂疾病中的网络模块识别。
Nat Methods. 2019 Sep;16(9):843-852. doi: 10.1038/s41592-019-0509-5. Epub 2019 Aug 30.
7
Approaches for recognizing disease genes based on network.基于网络识别疾病基因的方法。
Biomed Res Int. 2014;2014:416323. doi: 10.1155/2014/416323. Epub 2014 Feb 24.
10
Systematic analysis of genes and diseases using PheWAS-Associated networks.利用 PheWAS 关联网络进行基因和疾病的系统分析。
Comput Biol Med. 2019 Jun;109:311-321. doi: 10.1016/j.compbiomed.2019.04.037. Epub 2019 May 1.

引用本文的文献

本文引用的文献

1
Viral perturbations of host networks reflect disease etiology.病毒对宿主网络的干扰反映了疾病的病因。
PLoS Comput Biol. 2012;8(6):e1002531. doi: 10.1371/journal.pcbi.1002531. Epub 2012 Jun 28.
2
Link communities reveal multiscale complexity in networks.链接社区揭示了网络的多尺度复杂性。
Nature. 2010 Aug 5;466(7307):761-4. doi: 10.1038/nature09182. Epub 2010 Jun 20.
8
Blueprint for antimicrobial hit discovery targeting metabolic networks.针对代谢网络的抗菌药物命中发现蓝图。
Proc Natl Acad Sci U S A. 2010 Jan 19;107(3):1082-7. doi: 10.1073/pnas.0909181107. Epub 2010 Jan 5.
9
Drug discovery: Predicting promiscuity.药物发现:预测多靶点作用性。
Nature. 2009 Nov 12;462(7270):167-8. doi: 10.1038/462167a.
10
Edgetic perturbation models of human inherited disorders.人类遗传性疾病的边缘扰动模型。
Mol Syst Biol. 2009;5:321. doi: 10.1038/msb.2009.80. Epub 2009 Nov 3.

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验