• 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

使用 HPO 测量和可视化表型相似性的在线工具。

An online tool for measuring and visualizing phenotype similarities using HPO.

机构信息

School of Computer Science, Northwestern Polytechnical University, Xi'an, 710072, China.

Department of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, 518055, China.

出版信息

BMC Genomics. 2018 Aug 13;19(Suppl 6):571. doi: 10.1186/s12864-018-4927-z.

DOI:10.1186/s12864-018-4927-z
PMID:30367579
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6101067/
Abstract

BACKGROUND

The Human Phenotype Ontology (HPO) is one of the most popular bioinformatics resources. Recently, HPO-based phenotype semantic similarity has been effectively applied to model patient phenotype data. However, the existing tools are revised based on the Gene Ontology (GO)-based term similarity. The design of the models are not optimized for the unique features of HPO. In addition, existing tools only allow HPO terms as input and only provide pure text-based outputs.

RESULTS

We present PhenoSimWeb, a web application that allows researchers to measure HPO-based phenotype semantic similarities using four approaches borrowed from GO-based similarity measurements. Besides, we provide a approach considering the unique properties of HPO. And, PhenoSimWeb allows text that describes phenotypes as input, since clinical phenotype data is always in text. PhenoSimWeb also provides a graphic visualization interface to visualize the resulting phenotype network.

CONCLUSIONS

PhenoSimWeb is an easy-to-use and functional online application. Researchers can use it to calculate phenotype similarity conveniently, predict phenotype associated genes or diseases, and visualize the network of phenotype interactions. PhenoSimWeb is available at http://120.77.47.2:8080.

摘要

背景

人类表型本体(HPO)是最受欢迎的生物信息学资源之一。最近,基于 HPO 的表型语义相似性已被有效地应用于模拟患者表型数据。然而,现有的工具是基于基于基因本体(GO)的术语相似性进行修订的。这些模型的设计没有针对 HPO 的独特特征进行优化。此外,现有的工具仅允许 HPO 术语作为输入,并且仅提供纯基于文本的输出。

结果

我们提出了 PhenoSimWeb,这是一个 Web 应用程序,允许研究人员使用从基于 GO 的相似性度量中借鉴的四种方法来衡量基于 HPO 的表型语义相似性。此外,我们还提供了一种考虑 HPO 独特属性的方法。并且,PhenoSimWeb 允许输入描述表型的文本,因为临床表型数据始终以文本形式存在。PhenoSimWeb 还提供了一个图形可视化界面,用于可视化生成的表型网络。

结论

PhenoSimWeb 是一个易于使用且功能齐全的在线应用程序。研究人员可以方便地使用它来计算表型相似性,预测与表型相关的基因或疾病,并可视化表型相互作用的网络。PhenoSimWeb 可在 http://120.77.47.2:8080 访问。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c311/6101067/44533c1dcab6/12864_2018_4927_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c311/6101067/c326d3c3e897/12864_2018_4927_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c311/6101067/eb5051cb03b5/12864_2018_4927_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c311/6101067/98030e050bf5/12864_2018_4927_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c311/6101067/3973d1fc3a4d/12864_2018_4927_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c311/6101067/e442020e44a0/12864_2018_4927_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c311/6101067/4188738d4617/12864_2018_4927_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c311/6101067/f61f87eec6d4/12864_2018_4927_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c311/6101067/44533c1dcab6/12864_2018_4927_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c311/6101067/c326d3c3e897/12864_2018_4927_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c311/6101067/eb5051cb03b5/12864_2018_4927_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c311/6101067/98030e050bf5/12864_2018_4927_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c311/6101067/3973d1fc3a4d/12864_2018_4927_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c311/6101067/e442020e44a0/12864_2018_4927_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c311/6101067/4188738d4617/12864_2018_4927_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c311/6101067/f61f87eec6d4/12864_2018_4927_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c311/6101067/44533c1dcab6/12864_2018_4927_Fig8_HTML.jpg

相似文献

1
An online tool for measuring and visualizing phenotype similarities using HPO.使用 HPO 测量和可视化表型相似性的在线工具。
BMC Genomics. 2018 Aug 13;19(Suppl 6):571. doi: 10.1186/s12864-018-4927-z.
2
InteGO2: a web tool for measuring and visualizing gene semantic similarities using Gene Ontology.InteGO2:一个使用基因本体论来测量和可视化基因语义相似性的网络工具。
BMC Genomics. 2016 Aug 31;17 Suppl 5(Suppl 5):530. doi: 10.1186/s12864-016-2828-6.
3
HPO2Vec+: Leveraging heterogeneous knowledge resources to enrich node embeddings for the Human Phenotype Ontology.HPO2Vec+:利用异构知识资源丰富人类表型本体的节点嵌入。
J Biomed Inform. 2019 Aug;96:103246. doi: 10.1016/j.jbi.2019.103246. Epub 2019 Jun 27.
4
Doc2Hpo: a web application for efficient and accurate HPO concept curation.Doc2Hpo:一个用于高效准确的 HPO 概念编纂的网络应用程序。
Nucleic Acids Res. 2019 Jul 2;47(W1):W566-W570. doi: 10.1093/nar/gkz386.
5
Predicting disease-related phenotypes using an integrated phenotype similarity measurement based on HPO.基于人类表型本体(HPO),通过综合表型相似性测量来预测疾病相关表型。
BMC Syst Biol. 2019 Apr 5;13(Suppl 2):34. doi: 10.1186/s12918-019-0697-8.
6
HPOSim: an R package for phenotypic similarity measure and enrichment analysis based on the human phenotype ontology.HPOSim:一个基于人类表型本体论进行表型相似性测量和富集分析的R包。
PLoS One. 2015 Feb 9;10(2):e0115692. doi: 10.1371/journal.pone.0115692. eCollection 2015.
7
The Human Phenotype Ontology project: linking molecular biology and disease through phenotype data.人类表型本体论项目:通过表型数据将分子生物学和疾病联系起来。
Nucleic Acids Res. 2014 Jan;42(Database issue):D966-74. doi: 10.1093/nar/gkt1026. Epub 2013 Nov 11.
8
Investigations on factors influencing HPO-based semantic similarity calculation.基于健康问题本体(HPO)的语义相似度计算的影响因素研究。
J Biomed Semantics. 2017 Sep 20;8(Suppl 1):34. doi: 10.1186/s13326-017-0144-y.
9
A visual and curatorial approach to clinical variant prioritization and disease gene discovery in genome-wide diagnostics.一种用于全基因组诊断中临床变异优先级排序和疾病基因发现的可视化与策展方法。
Genome Med. 2016 Feb 2;8(1):13. doi: 10.1186/s13073-016-0261-8.
10
PhenPath: a tool for characterizing biological functions underlying different phenotypes.PhenPath:一个用于描述不同表型背后生物功能的工具。
BMC Genomics. 2019 Jul 16;20(Suppl 8):548. doi: 10.1186/s12864-019-5868-x.

引用本文的文献

1
Pheno-Ranker: a toolkit for comparison of phenotypic data stored in GA4GH standards and beyond.Pheno-Ranker:用于比较存储在GA4GH标准及其他标准中的表型数据的工具包。
BMC Bioinformatics. 2024 Dec 4;25(1):373. doi: 10.1186/s12859-024-05993-2.
2
DiSMVC: a multi-view graph collaborative learning framework for measuring disease similarity.DiSMVC:一种用于测量疾病相似性的多视图图协同学习框架。
Bioinformatics. 2024 May 2;40(5). doi: 10.1093/bioinformatics/btae306.
3
PhenoExam: gene set analyses through integration of different phenotype databases.

本文引用的文献

1
KF-finder: identification of key factors from host-microbial networks in cervical cancer.KF-finder:从宫颈癌宿主-微生物网络中识别关键因素
BMC Syst Biol. 2018 Apr 24;12(Suppl 4):54. doi: 10.1186/s12918-018-0566-x.
2
Measuring phenotype-phenotype similarity through the interactome.通过互作组来测量表型-表型相似性。
BMC Bioinformatics. 2018 Apr 11;19(Suppl 5):114. doi: 10.1186/s12859-018-2102-9.
3
Improving the measurement of semantic similarity by combining gene ontology and co-functional network: a random walk based approach.
PhenoExam:通过整合不同表型数据库进行基因集分析。
BMC Bioinformatics. 2022 Dec 31;23(1):567. doi: 10.1186/s12859-022-05122-x.
4
Network modeling of patients' biomolecular profiles for clinical phenotype/outcome prediction.对患者生物分子谱进行网络建模以进行临床表型/结果预测。
Sci Rep. 2020 Feb 27;10(1):3612. doi: 10.1038/s41598-020-60235-8.
5
An Effective Method to Measure Disease Similarity Using Gene and Phenotype Associations.一种利用基因与表型关联来测量疾病相似性的有效方法。
Front Genet. 2019 May 21;10:466. doi: 10.3389/fgene.2019.00466. eCollection 2019.
6
Predicting disease-related phenotypes using an integrated phenotype similarity measurement based on HPO.基于人类表型本体(HPO),通过综合表型相似性测量来预测疾病相关表型。
BMC Syst Biol. 2019 Apr 5;13(Suppl 2):34. doi: 10.1186/s12918-019-0697-8.
通过结合基因本体和共功能网络改进语义相似性测量:一种基于随机游走的方法。
BMC Syst Biol. 2018 Mar 19;12(Suppl 2):18. doi: 10.1186/s12918-018-0539-0.
4
Measuring disease similarity and predicting disease-related ncRNAs by a novel method.基于新方法测量疾病相似性和预测与疾病相关的 ncRNAs。
BMC Med Genomics. 2017 Dec 28;10(Suppl 5):71. doi: 10.1186/s12920-017-0315-9.
5
Identifying term relations cross different gene ontology categories.跨不同基因本体论类别识别术语关系。
BMC Bioinformatics. 2017 Dec 28;18(Suppl 16):573. doi: 10.1186/s12859-017-1959-3.
6
Detection of Network Motif Based on a Novel Graph Canonization Algorithm from Transcriptional Regulation Networks.基于转录调控网络中新图正则化算法的网络基元检测。
Molecules. 2017 Dec 10;22(12):2194. doi: 10.3390/molecules22122194.
7
Identifying consistent disease subnetworks using DNet.使用 DNet 识别一致的疾病子网络。
Methods. 2017 Dec 1;131:104-110. doi: 10.1016/j.ymeth.2017.07.024. Epub 2017 Aug 12.
8
Genetic Variants and Multiple Sclerosis Risk Gene SLC9A9 Expression in Distinct Human Brain Regions.遗传变异与多发性硬化风险基因 SLC9A9 在不同人脑区域的表达。
Mol Neurobiol. 2017 Nov;54(9):6820-6826. doi: 10.1007/s12035-016-0208-5. Epub 2016 Oct 20.
9
InteGO2: a web tool for measuring and visualizing gene semantic similarities using Gene Ontology.InteGO2:一个使用基因本体论来测量和可视化基因语义相似性的网络工具。
BMC Genomics. 2016 Aug 31;17 Suppl 5(Suppl 5):530. doi: 10.1186/s12864-016-2828-6.
10
DisSim: an online system for exploring significant similar diseases and exhibiting potential therapeutic drugs.DisSim:一个用于探索显著相似疾病和展示潜在治疗药物的在线系统。
Sci Rep. 2016 Jul 26;6:30024. doi: 10.1038/srep30024.