• 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
Identifying dysfunctional miRNA-mRNA regulatory modules by inverse activation, cofunction, and high interconnection of target genes: a case study of glioblastoma.通过反向激活、共功能和靶基因的高互联性鉴定功能失调的 miRNA-mRNA 调控模块:以胶质母细胞瘤为例。
Neuro Oncol. 2013 Jul;15(7):818-28. doi: 10.1093/neuonc/not018. Epub 2013 Mar 20.
2
Identify signature regulatory network for glioblastoma prognosis by integrative mRNA and miRNA co-expression analysis.通过整合mRNA和miRNA共表达分析鉴定胶质母细胞瘤预后的特征性调控网络。
IET Syst Biol. 2016 Dec;10(6):244-251. doi: 10.1049/iet-syb.2016.0004.
3
Identifying Cancer Subtypes from miRNA-TF-mRNA Regulatory Networks and Expression Data.从miRNA-TF-mRNA调控网络和表达数据中识别癌症亚型
PLoS One. 2016 Apr 1;11(4):e0152792. doi: 10.1371/journal.pone.0152792. eCollection 2016.
4
Uncovering MicroRNA and Transcription Factor Mediated Regulatory Networks in Glioblastoma.揭示胶质母细胞瘤中 microRNA 和转录因子介导的调控网络。
PLoS Comput Biol. 2012;8(7):e1002488. doi: 10.1371/journal.pcbi.1002488. Epub 2012 Jul 19.
5
Computational analysis and verification of molecular genetic targets for glioblastoma.脑胶质母细胞瘤分子遗传学靶点的计算分析与验证。
Biosci Rep. 2020 Jun 26;40(6). doi: 10.1042/BSR20201401.
6
Identification of prognostic biomarkers in glioblastoma using a long non-coding RNA-mediated, competitive endogenous RNA network.利用长链非编码RNA介导的竞争性内源性RNA网络鉴定胶质母细胞瘤的预后生物标志物。
Oncotarget. 2016 Jul 5;7(27):41737-41747. doi: 10.18632/oncotarget.9569.
7
The analysis of miRNA expression profiling datasets reveals inverse microRNA patterns in glioblastoma and Alzheimer's disease.miRNA 表达谱数据集的分析揭示了胶质母细胞瘤和阿尔茨海默病中 miRNA 模式的反转。
Oncol Rep. 2019 Sep;42(3):911-922. doi: 10.3892/or.2019.7215. Epub 2019 Jun 28.
8
Integration of MicroRNA, mRNA, and Protein Expression Data for the Identification of Cancer-Related MicroRNAs.整合MicroRNA、mRNA和蛋白质表达数据以鉴定癌症相关的MicroRNA
PLoS One. 2017 Jan 5;12(1):e0168412. doi: 10.1371/journal.pone.0168412. eCollection 2017.
9
Identification of prognostic gene signatures of glioblastoma: a study based on TCGA data analysis.胶质母细胞瘤预后基因标志物的鉴定:基于 TCGA 数据分析的研究。
Neuro Oncol. 2013 Jul;15(7):829-39. doi: 10.1093/neuonc/not024. Epub 2013 Mar 15.
10
Estimating survival time of patients with glioblastoma multiforme and characterization of the identified microRNA signatures.多形性胶质母细胞瘤患者生存时间的估计及所鉴定的微小RNA特征的表征。
BMC Genomics. 2016 Dec 22;17(Suppl 13):1022. doi: 10.1186/s12864-016-3321-y.

引用本文的文献

1
CCmiR: a computational approach for competitive and cooperative microRNA binding prediction.CCmiR:一种用于竞争性和合作性微小RNA结合预测的计算方法。
Bioinformatics. 2018 Jan 15;34(2):198-206. doi: 10.1093/bioinformatics/btx606.
2
Cooperative genomic alteration network reveals molecular classification across 12 major cancer types.合作基因组改变网络揭示了12种主要癌症类型的分子分类。
Nucleic Acids Res. 2017 Jan 25;45(2):567-582. doi: 10.1093/nar/gkw1087. Epub 2016 Nov 29.
3
Dysfunctional miRNA-Mediated Regulation in Chromophobe Renal Cell Carcinoma.嫌色性肾细胞癌中功能失调的微小RNA介导的调控
PLoS One. 2016 Jun 3;11(6):e0156324. doi: 10.1371/journal.pone.0156324. eCollection 2016.
4
Construction and analysis of dynamic transcription factor regulatory networks in the progression of glioma.胶质瘤进展过程中动态转录因子调控网络的构建与分析
Sci Rep. 2015 Nov 3;5:15953. doi: 10.1038/srep15953.
5
Genome-wide DNA methylome reveals the dysfunction of intronic microRNAs in major psychosis.全基因组DNA甲基化组揭示了主要精神疾病中内含子微小RNA的功能障碍。
BMC Med Genomics. 2015 Oct 14;8:62. doi: 10.1186/s12920-015-0139-4.
6
Identification of subtype specific miRNA-mRNA functional regulatory modules in matched miRNA-mRNA expression data: multiple myeloma as a case.在匹配的miRNA-mRNA表达数据中鉴定亚型特异性miRNA-mRNA功能调控模块:以多发性骨髓瘤为例
Biomed Res Int. 2015;2015:501262. doi: 10.1155/2015/501262. Epub 2015 Mar 19.
7
Integrated analyses to reconstruct microRNA-mediated regulatory networks in mouse liver using high-throughput profiling.利用高通量分析重建小鼠肝脏中微小RNA介导的调控网络的综合分析。
BMC Genomics. 2015;16 Suppl 2(Suppl 2):S12. doi: 10.1186/1471-2164-16-S2-S12. Epub 2015 Jan 21.
8
Identifying core gene modules in glioblastoma based on multilayer factor-mediated dysfunctional regulatory networks through integrating multi-dimensional genomic data.通过整合多维度基因组数据,基于多层因子介导的功能失调调控网络识别胶质母细胞瘤中的核心基因模块。
Nucleic Acids Res. 2015 Feb 27;43(4):1997-2007. doi: 10.1093/nar/gkv074. Epub 2015 Feb 4.
9
MicroRNA-27a distinguishes glioblastoma multiforme from diffuse and anaplastic astrocytomas and has prognostic value.微小RNA-27a可将多形性胶质母细胞瘤与弥漫性星形细胞瘤和间变性星形细胞瘤区分开来,并具有预后价值。
Am J Cancer Res. 2014 Dec 15;5(1):201-18. eCollection 2015.
10
MicroRNA expression signatures determine prognosis and survival in glioblastoma multiforme--a systematic overview.微小RNA表达特征决定多形性胶质母细胞瘤的预后和生存——一项系统综述
Mol Neurobiol. 2014 Dec;50(3):896-913. doi: 10.1007/s12035-014-8668-y. Epub 2014 Mar 12.

本文引用的文献

1
Intratumor heterogeneity and branched evolution revealed by multiregion sequencing.多区域测序揭示的肿瘤内异质性和分支进化。
N Engl J Med. 2012 Mar 8;366(10):883-892. doi: 10.1056/NEJMoa1113205.
2
A novel computational framework for simultaneous integration of multiple types of genomic data to identify microRNA-gene regulatory modules.一种新型的计算框架,用于同时整合多种类型的基因组数据,以识别 microRNA-基因调控模块。
Bioinformatics. 2011 Jul 1;27(13):i401-9. doi: 10.1093/bioinformatics/btr206.
3
A cooperative microRNA-tumor suppressor gene network in acute T-cell lymphoblastic leukemia (T-ALL).急性 T 细胞淋巴细胞白血病(T-ALL)中协同的 microRNA-肿瘤抑制基因网络。
Nat Genet. 2011 Jun 5;43(7):673-8. doi: 10.1038/ng.858.
4
Control of tumor and microenvironment cross-talk by miR-15a and miR-16 in prostate cancer.miR-15a 和 miR-16 对前列腺癌中肿瘤与微环境相互作用的调控。
Oncogene. 2011 Oct 13;30(41):4231-42. doi: 10.1038/onc.2011.140. Epub 2011 May 2.
5
Tumour evolution inferred by single-cell sequencing.单细胞测序推断肿瘤进化。
Nature. 2011 Apr 7;472(7341):90-4. doi: 10.1038/nature09807. Epub 2011 Mar 13.
6
Identification of microRNA-mRNA modules using microarray data.使用微阵列数据鉴定 microRNA-mRNA 模块。
BMC Genomics. 2011 Mar 6;12:138. doi: 10.1186/1471-2164-12-138.
7
MiR-30 family and EMT in human fetal pancreatic islets.miR-30 家族与人类胎儿胰岛中的 EMT
Islets. 2009 Nov-Dec;1(3):283-5. doi: 10.4161/isl.1.3.9968.
8
Identifying functional miRNA-mRNA regulatory modules with correspondence latent dirichlet allocation.利用对应潜在狄利克雷分配识别功能 miRNA-mRNA 调控模块。
Bioinformatics. 2010 Dec 15;26(24):3105-11. doi: 10.1093/bioinformatics/btq576. Epub 2010 Oct 17.
9
MiRNA-miRNA synergistic network: construction via co-regulating functional modules and disease miRNA topological features.miRNA-miRNA 协同网络:通过共调控功能模块和疾病 miRNA 拓扑特征构建。
Nucleic Acids Res. 2011 Feb;39(3):825-36. doi: 10.1093/nar/gkq832. Epub 2010 Oct 6.
10
microRNA-122 as a regulator of mitochondrial metabolic gene network in hepatocellular carcinoma.microRNA-122 作为肝细胞癌中线粒体代谢基因网络的调节剂。
Mol Syst Biol. 2010 Aug 24;6:402. doi: 10.1038/msb.2010.58.

通过反向激活、共功能和靶基因的高互联性鉴定功能失调的 miRNA-mRNA 调控模块:以胶质母细胞瘤为例。

Identifying dysfunctional miRNA-mRNA regulatory modules by inverse activation, cofunction, and high interconnection of target genes: a case study of glioblastoma.

机构信息

College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.

出版信息

Neuro Oncol. 2013 Jul;15(7):818-28. doi: 10.1093/neuonc/not018. Epub 2013 Mar 20.

DOI:10.1093/neuonc/not018
PMID:23516263
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3688007/
Abstract

BACKGROUND

Accumulating evidence demonstrates that complex diseases may arise from cooperative effects of multiple dysfunctional miRNAs. Thus, identifying abnormal functions cooperatively regulated by multiple miRNAs is useful for understanding the pathogenesis of complex diseases.

METHODS

In this study, we proposed a multistep method to identify dysfunctional miRNA-mRNA regulatory modules (dMiMRMs) in a specific disease, in which a group of miRNAs cooperatively regulate a group of target genes involved in a specific function. We identified dysfunctional miRNAs, which were differentially expressed and inversely regulated most of their target genes, by integrating paired miRNA and mRNA expression profiles and miRNA target information. Then, we identified cooperative functional units, in each of which a pair of miRNAs cooperatively repressed function-enriched and highly interconnected target genes. Finally, the cooperative functional units were assembled into dMiMRMs.

RESULTS

We applied our method to glioblastoma (GBM) and identified GBM-associated dMiMRMs at the population, subtype, and individual levels. We identified 5 common dMiMRMs using all GBM samples, 3 of which were associated with the prognosis in patients with GBM and were better predictors of prognosis than were miRNAs or mRNAs alone. By applying our approach to GBM subtypes, we found consistent dMiMRMs across GBM subtypes, and some subtype-specific dMiMRMs were observed. Furthermore, personalized dMiMRMs were identified, suggesting significant individual differences in different patients with GBM.

CONCLUSIONS

Our method provides the capability to identify miRNA-mediated dysfunctional mechanisms underlying complex diseases.

摘要

背景

越来越多的证据表明,复杂疾病可能是多种功能失调 miRNA 共同作用的结果。因此,识别由多个 miRNA 共同调控的异常功能对于理解复杂疾病的发病机制是有用的。

方法

在这项研究中,我们提出了一种多步骤的方法,用于识别特定疾病中的功能失调 miRNA-mRNA 调节模块(dMiMRMs),其中一组 miRNA 协同调节一组涉及特定功能的靶基因。我们通过整合配对的 miRNA 和 mRNA 表达谱和 miRNA 靶信息,鉴定差异表达和反向调控其大部分靶基因的功能失调 miRNA。然后,我们鉴定了协同功能单元,其中每对 miRNA 协同抑制功能富集且高度相互关联的靶基因。最后,将协同功能单元组装成 dMiMRMs。

结果

我们将我们的方法应用于胶质母细胞瘤(GBM),并在群体、亚型和个体水平上鉴定了与 GBM 相关的 dMiMRMs。我们使用所有 GBM 样本鉴定了 5 个常见的 dMiMRMs,其中 3 个与 GBM 患者的预后相关,并且比 miRNAs 或 mRNAs 单独作为预后的预测因子更好。通过将我们的方法应用于 GBM 亚型,我们发现了跨 GBM 亚型一致的 dMiMRMs,并且观察到了一些亚型特异性的 dMiMRMs。此外,还鉴定了个性化的 dMiMRMs,表明不同 GBM 患者之间存在显著的个体差异。

结论

我们的方法提供了识别复杂疾病中 miRNA 介导的功能失调机制的能力。