• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

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

相似文献

1
Is the average shortest path length of gene set a reflection of their biological relatedness?基因集的平均最短路径长度是否反映了它们的生物学相关性?
J Bioinform Comput Biol. 2016 Dec;14(6):1660002. doi: 10.1142/S0219720016600027.
2
Network Properties of Cancer Prognostic Gene Signatures in the Human Protein Interactome.人类蛋白质互作网络中癌症预后基因特征的网络特性。
Genes (Basel). 2020 Feb 26;11(3):247. doi: 10.3390/genes11030247.
3
Predicting node characteristics from molecular networks.从分子网络预测节点特征。
Methods Mol Biol. 2011;781:399-414. doi: 10.1007/978-1-61779-276-2_20.
4
Shortest path counting in probabilistic biological networks.概率生物网络中的最短路径计数。
BMC Bioinformatics. 2018 Dec 4;19(1):465. doi: 10.1186/s12859-018-2480-z.
5
Investigation of the roles of trace elements during hepatitis C virus infection using protein-protein interactions and a shortest path algorithm.利用蛋白质-蛋白质相互作用和最短路径算法研究微量元素在丙型肝炎病毒感染中的作用。
Biochim Biophys Acta. 2016 Nov;1860(11 Pt B):2756-68. doi: 10.1016/j.bbagen.2016.05.018. Epub 2016 May 19.
6
Shortest-path network analysis is a useful approach toward identifying genetic determinants of longevity.最短路径网络分析是一种识别长寿基因决定因素的有用方法。
PLoS One. 2008;3(11):e3802. doi: 10.1371/journal.pone.0003802. Epub 2008 Nov 25.
7
Identification of molecular biomarkers for pancreatic cancer with mRMR shortest path method.使用mRMR最短路径方法鉴定胰腺癌的分子生物标志物。
Oncotarget. 2017 Jun 20;8(25):41432-41439. doi: 10.18632/oncotarget.18186.
8
MOSES: A New Approach to Integrate Interactome Topology and Functional Features for Disease Gene Prediction.MOSES:一种整合互作网络拓扑结构和功能特征进行疾病基因预测的新方法。
Genes (Basel). 2021 Oct 27;12(11):1713. doi: 10.3390/genes12111713.
9
Graph-based information diffusion method for prioritizing functionally related genes in protein-protein interaction networks.基于图的信息扩散方法,用于对蛋白质-蛋白质相互作用网络中的功能相关基因进行优先级排序。
Pac Symp Biocomput. 2020;25:439-450.
10
Identification of human disease genes from interactome network using graphlet interaction.利用图元相互作用从相互作用组网络中鉴定人类疾病基因。
PLoS One. 2014 Jan 22;9(1):e86142. doi: 10.1371/journal.pone.0086142. eCollection 2014.

引用本文的文献

1
Construction and characterization of rectal cancer-related lncRNA-mRNA ceRNA network reveals prognostic biomarkers in rectal cancer.构建和分析直肠癌相关 lncRNA-mRNA ceRNA 网络揭示直肠癌的预后生物标志物。
IET Syst Biol. 2021 Aug;15(6):192-204. doi: 10.1049/syb2.12035. Epub 2021 Oct 6.
2
Discovering Cerebral Ischemic Stroke Associated Genes Based on Network Representation Learning.基于网络表示学习发现脑缺血性中风相关基因
Front Genet. 2021 Sep 1;12:728333. doi: 10.3389/fgene.2021.728333. eCollection 2021.
3
Identification of the key target profiles underlying the drugs of narrow therapeutic index for treating cancer and cardiovascular disease.确定治疗癌症和心血管疾病的窄治疗指数药物的关键靶点特征。
Comput Struct Biotechnol J. 2021 Apr 21;19:2318-2328. doi: 10.1016/j.csbj.2021.04.035. eCollection 2021.
4
The Large Scale Structure of Human Metabolism Reveals Resilience via Extensive Signaling Crosstalk.人类新陈代谢的大规模结构通过广泛的信号串扰揭示了其弹性。
Front Physiol. 2020 Dec 16;11:588012. doi: 10.3389/fphys.2020.588012. eCollection 2020.
5
FOBI: an ontology to represent food intake data and associate it with metabolomic data.FOBI:一个用于表示食物摄入数据并将其与代谢组学数据相关联的本体。
Database (Oxford). 2020 Jan 1;2020. doi: 10.1093/databa/baaa033.
6
Reconstruction and Analysis of Cattle Metabolic Networks in Normal and Acidosis Rumen Tissue.正常和酸中毒瘤胃组织中牛代谢网络的重建与分析
Animals (Basel). 2020 Mar 11;10(3):469. doi: 10.3390/ani10030469.
7
Bioinformatic prediction of critical genes and pathways involved in longevity in Drosophila melanogaster.生物信息学预测参与黑腹果蝇长寿的关键基因和途径。
Mol Genet Genomics. 2019 Dec;294(6):1463-1475. doi: 10.1007/s00438-019-01589-1. Epub 2019 Jul 20.

本文引用的文献

1
Schizophrenia interactome with 504 novel protein-protein interactions.精神分裂症互作组与 504 个新的蛋白质-蛋白质相互作用。
NPJ Schizophr. 2016 Apr 27;2:16012. doi: 10.1038/npjschz.2016.12. eCollection 2016.
2
Drug target prioritization by perturbed gene expression and network information.基于基因表达扰动和网络信息的药物靶点优先级排序
Sci Rep. 2015 Nov 30;5:17417. doi: 10.1038/srep17417.
3
Prediction of Metabolic Gene Biomarkers for Neurodegenerative Disease by an Integrated Network-Based Approach.基于整合网络方法预测神经退行性疾病的代谢基因生物标志物
Biomed Res Int. 2015;2015:432012. doi: 10.1155/2015/432012. Epub 2015 May 3.
4
Chapter 5: Network biology approach to complex diseases.第五章:复杂疾病的网络生物学方法。
PLoS Comput Biol. 2012;8(12):e1002820. doi: 10.1371/journal.pcbi.1002820. Epub 2012 Dec 27.
5
Topological features of cancer proteins in the human NR-RTK interaction network.人类NR-RTK相互作用网络中癌症蛋白的拓扑特征
J Recept Signal Transduct Res. 2012 Oct;32(5):257-62. doi: 10.3109/10799893.2012.702116. Epub 2012 Jul 5.
6
Predicting candidate genes based on combined network topological features: a case study in coronary artery disease.基于网络拓扑特征组合预测候选基因:冠心病的案例研究。
PLoS One. 2012;7(6):e39542. doi: 10.1371/journal.pone.0039542. Epub 2012 Jun 22.
7
Walking the interactome for prioritization of candidate disease genes.遍历相互作用组以对候选疾病基因进行优先级排序。
Am J Hum Genet. 2008 Apr;82(4):949-58. doi: 10.1016/j.ajhg.2008.02.013. Epub 2008 Mar 27.
8
An integrated approach to inferring gene-disease associations in humans.一种推断人类基因与疾病关联的综合方法。
Proteins. 2008 Aug 15;72(3):1030-7. doi: 10.1002/prot.21989.
9
Reconstruction of a functional human gene network, with an application for prioritizing positional candidate genes.功能性人类基因网络的重建及其在定位候选基因优先级排序中的应用。
Am J Hum Genet. 2006 Jun;78(6):1011-25. doi: 10.1086/504300. Epub 2006 Apr 25.
10
BioGRID: a general repository for interaction datasets.生物通用互作数据集知识库(BioGRID):一个交互数据集的通用存储库。
Nucleic Acids Res. 2006 Jan 1;34(Database issue):D535-9. doi: 10.1093/nar/gkj109.

基因集的平均最短路径长度是否反映了它们的生物学相关性?

Is the average shortest path length of gene set a reflection of their biological relatedness?

作者信息

Embar Varsha, Handen Adam, Ganapathiraju Madhavi K

机构信息

* Language Technologies Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA.

† Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA 15213, USA.

出版信息

J Bioinform Comput Biol. 2016 Dec;14(6):1660002. doi: 10.1142/S0219720016600027.

DOI:10.1142/S0219720016600027
PMID:28073302
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5726383/
Abstract

When a set of genes are identified to be related to a disease, say through gene expression analysis, it is common to examine the average distance among their protein products in the human interactome as a measure of biological relatedness of these genes. The reasoning for this is that, genes associated with a disease would tend to be functionally related, and that functionally related genes would be closely connected to each other in the interactome. Typically, average shortest path length (ASPL) of disease genes (although referred to as genes in the context of disease-associations, the interactions are among protein-products of these genes) is compared to ASPL of randomly selected genes or to ASPL in a randomly permuted network. We examined whether the ASPL of a set of genes is indeed a good measure of biological relatedness or whether it is simply a characteristic of the degree distribution of those genes. We examined the ASPL of genes sets of some disease and pathway associations and compared them to ASPL of three types of randomly selected control sets: uniform selection, from entire proteome, degree-matched selection, and random permutation of the network. We found that disease associated genes and their degree-matched random genes have comparable ASPL. In other words, ASPL is a characteristic of the degree of the genes and the network topology, and not that of functional coherence.

摘要

当通过基因表达分析等方法确定一组基因与某种疾病相关时,通常会检查它们在人类相互作用组中的蛋白质产物之间的平均距离,以此作为这些基因生物学相关性的一种衡量指标。这样做的理由是,与疾病相关的基因往往在功能上相互关联,而在相互作用组中功能相关的基因会彼此紧密相连。通常,会将疾病相关基因(尽管在疾病关联的背景下被称为基因,但相互作用是在这些基因的蛋白质产物之间)的平均最短路径长度(ASPL)与随机选择的基因的ASPL或随机重排网络中的ASPL进行比较。我们研究了一组基因的ASPL是否确实是生物学相关性的良好衡量指标,或者它是否仅仅是这些基因度分布的一个特征。我们研究了一些疾病和通路关联的基因集的ASPL,并将它们与三种随机选择的对照组的ASPL进行比较:从整个蛋白质组中进行均匀选择、度匹配选择以及网络的随机重排。我们发现,与疾病相关的基因及其度匹配的随机基因具有相当的ASPL。换句话说,ASPL是基因度和网络拓扑结构的一个特征,而不是功能一致性的特征。