• 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

BAR-PLUS:博洛尼亚注释资源 PLUS,用于蛋白质序列的功能和结构注释。

BAR-PLUS: the Bologna Annotation Resource Plus for functional and structural annotation of protein sequences.

机构信息

Department of Biology, Bologna Biocomputing Group, Bologna Computational Biology Network, Bologna, Italy.

出版信息

Nucleic Acids Res. 2011 Jul;39(Web Server issue):W197-202. doi: 10.1093/nar/gkr292. Epub 2011 May 26.

DOI:10.1093/nar/gkr292
PMID:21622657
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3125743/
Abstract

We introduce BAR-PLUS (BAR(+)), a web server for functional and structural annotation of protein sequences. BAR(+) is based on a large-scale genome cross comparison and a non-hierarchical clustering procedure characterized by a metric that ensures a reliable transfer of features within clusters. In this version, the method takes advantage of a large-scale pairwise sequence comparison of 13,495,736 protein chains also including 988 complete proteomes. Available sequence annotation is derived from UniProtKB, GO, Pfam and PDB. When PDB templates are present within a cluster (with or without their SCOP classification), profile Hidden Markov Models (HMMs) are computed on the basis of sequence to structure alignment and are cluster-associated (Cluster-HMM). Therefrom, a library of 10,858 HMMs is made available for aligning even distantly related sequences for structural modelling. The server also provides pairwise query sequence-structural target alignments computed from the correspondent Cluster-HMM. BAR(+) in its present version allows three main categories of annotation: PDB [with or without SCOP ()] and GO and/or Pfam; PDB () without GO and/or Pfam; GO and/or Pfam without PDB (*) and no annotation. Each category can further comprise clusters where GO and Pfam functional annotations are or are not statistically significant. BAR(+) is available at http://bar.biocomp.unibo.it/bar2.0.

摘要

我们介绍了 BAR-PLUS(BAR(+)),这是一个用于蛋白质序列功能和结构注释的网络服务器。BAR(+) 基于大规模的基因组交叉比较和非层次聚类过程,该过程的特点是采用一种度量标准,确保在聚类内部可靠地传递特征。在这个版本中,该方法利用了对 13495736 条蛋白质链的大规模两两序列比较,其中还包括 988 个完整的蛋白质组。可用的序列注释来自 UniProtKB、GO、Pfam 和 PDB。当 PDB 模板存在于一个聚类中(无论是否具有 SCOP 分类)时,会基于序列到结构的比对计算轮廓隐马尔可夫模型(HMM),并与聚类相关联(Cluster-HMM)。由此,提供了一个包含 10858 个 HMM 的库,用于对齐甚至远缘相关的序列进行结构建模。该服务器还提供了基于对应 Cluster-HMM 的两两查询序列-结构目标比对。BAR(+) 在其当前版本中允许三种主要的注释类别:PDB [带有或不带有 SCOP() ] 和 GO 和/或 Pfam;PDB() 不带 GO 和/或 Pfam;GO 和/或 Pfam 不带 PDB(*) 且没有注释。每个类别还可以进一步包含 GO 和 Pfam 功能注释是否具有统计学意义的聚类。BAR(+) 可在 http://bar.biocomp.unibo.it/bar2.0 访问。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9700/3125743/3ceddaf6afed/gkr292f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9700/3125743/dcc6f798b93f/gkr292f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9700/3125743/5fe179c685c8/gkr292f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9700/3125743/3ceddaf6afed/gkr292f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9700/3125743/dcc6f798b93f/gkr292f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9700/3125743/5fe179c685c8/gkr292f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9700/3125743/3ceddaf6afed/gkr292f3.jpg

相似文献

1
BAR-PLUS: the Bologna Annotation Resource Plus for functional and structural annotation of protein sequences.BAR-PLUS:博洛尼亚注释资源 PLUS,用于蛋白质序列的功能和结构注释。
Nucleic Acids Res. 2011 Jul;39(Web Server issue):W197-202. doi: 10.1093/nar/gkr292. Epub 2011 May 26.
2
The Bologna Annotation Resource (BAR 3.0): improving protein functional annotation.博洛尼亚注释资源(BAR 3.0):改进蛋白质功能注释。
Nucleic Acids Res. 2017 Jul 3;45(W1):W285-W290. doi: 10.1093/nar/gkx330.
3
The bologna annotation resource: a non hierarchical method for the functional and structural annotation of protein sequences relying on a comparative large-scale genome analysis.博洛尼亚注释资源:一种基于大规模比较基因组分析的蛋白质序列功能和结构注释的非分层方法。
J Proteome Res. 2009 Sep;8(9):4362-71. doi: 10.1021/pr900204r.
4
How to inherit statistically validated annotation within BAR+ protein clusters.如何在 BAR+ 蛋白簇中继承经过统计学验证的注释。
BMC Bioinformatics. 2013;14 Suppl 3(Suppl 3):S4. doi: 10.1186/1471-2105-14-S3-S4. Epub 2013 Feb 28.
5
The human "magnesome": detecting magnesium binding sites on human proteins.人类“镁组学”:检测人类蛋白质上的镁结合位点。
BMC Bioinformatics. 2012;13 Suppl 14(Suppl 14):S10. doi: 10.1186/1471-2105-13-S14-S10. Epub 2012 Sep 7.
6
The HHpred interactive server for protein homology detection and structure prediction.用于蛋白质同源性检测和结构预测的HHpred交互式服务器。
Nucleic Acids Res. 2005 Jul 1;33(Web Server issue):W244-8. doi: 10.1093/nar/gki408.
7
SIFTS: updated Structure Integration with Function, Taxonomy and Sequences resource allows 40-fold increase in coverage of structure-based annotations for proteins.SIFTS:更新后的结构整合功能、分类学和序列资源允许基于结构注释的蛋白质覆盖率增加 40 倍。
Nucleic Acids Res. 2019 Jan 8;47(D1):D482-D489. doi: 10.1093/nar/gky1114.
8
SUS-BAR: a database of pig proteins with statistically validated structural and functional annotation.SUS-BAR:一个具有统计学验证的结构和功能注释的猪蛋白数据库。
Database (Oxford). 2013 Sep 23;2013:bat065. doi: 10.1093/database/bat065. Print 2013.
9
Uniclust databases of clustered and deeply annotated protein sequences and alignments.经过聚类和深度注释的蛋白质序列及比对的单簇数据库。
Nucleic Acids Res. 2017 Jan 4;45(D1):D170-D176. doi: 10.1093/nar/gkw1081. Epub 2016 Nov 28.
10
SUPERFAMILY: HMMs representing all proteins of known structure. SCOP sequence searches, alignments and genome assignments.超家族:代表所有已知结构蛋白质的隐马尔可夫模型。SCOP序列搜索、比对及基因组分配。
Nucleic Acids Res. 2002 Jan 1;30(1):268-72. doi: 10.1093/nar/30.1.268.

引用本文的文献

1
A large-scale assessment of sequence database search tools for homology-based protein function prediction.基于序列数据库搜索工具的大规模评估用于同源蛋白功能预测。
Brief Bioinform. 2024 May 23;25(4). doi: 10.1093/bib/bbae349.
2
Pseudo2GO: A Graph-Based Deep Learning Method for Pseudogene Function Prediction by Borrowing Information From Coding Genes.Pseudo2GO:一种基于图的深度学习方法,通过借鉴编码基因的信息进行假基因功能预测。
Front Genet. 2020 Aug 18;11:807. doi: 10.3389/fgene.2020.00807. eCollection 2020.
3
Graph2GO: a multi-modal attributed network embedding method for inferring protein functions.

本文引用的文献

1
Extending CATH: increasing coverage of the protein structure universe and linking structure with function.扩展CATH:扩大蛋白质结构领域的覆盖范围并将结构与功能联系起来。
Nucleic Acids Res. 2011 Jan;39(Database issue):D420-6. doi: 10.1093/nar/gkq1001. Epub 2010 Nov 19.
2
The bologna annotation resource: a non hierarchical method for the functional and structural annotation of protein sequences relying on a comparative large-scale genome analysis.博洛尼亚注释资源:一种基于大规模比较基因组分析的蛋白质序列功能和结构注释的非分层方法。
J Proteome Res. 2009 Sep;8(9):4362-71. doi: 10.1021/pr900204r.
3
Efficient algorithms for accurate hierarchical clustering of huge datasets: tackling the entire protein space.
Graph2GO:一种用于推断蛋白质功能的多模态属性网络嵌入方法。
Gigascience. 2020 Aug 1;9(8). doi: 10.1093/gigascience/giaa081.
4
I-TASSER gateway: A protein structure and function prediction server powered by XSEDE.I-TASSER网关:一个由XSEDE提供支持的蛋白质结构与功能预测服务器。
Future Gener Comput Syst. 2019 Oct;99:73-85. doi: 10.1016/j.future.2019.04.011. Epub 2019 Apr 9.
5
INGA 2.0: improving protein function prediction for the dark proteome.INGA 2.0:改进黑暗蛋白质组中蛋白质功能的预测。
Nucleic Acids Res. 2019 Jul 2;47(W1):W373-W378. doi: 10.1093/nar/gkz375.
6
Genomic tools for durum wheat breeding: de novo assembly of Svevo transcriptome and SNP discovery in elite germplasm.用于杜伦小麦育种的基因组工具:Svevo 转录组的从头组装和优异种质中的 SNP 发现。
BMC Genomics. 2019 Apr 10;20(1):278. doi: 10.1186/s12864-019-5645-x.
7
The Bologna Annotation Resource (BAR 3.0): improving protein functional annotation.博洛尼亚注释资源(BAR 3.0):改进蛋白质功能注释。
Nucleic Acids Res. 2017 Jul 3;45(W1):W285-W290. doi: 10.1093/nar/gkx330.
8
LaGomiCs-Lagomorph Genomics Consortium: An International Collaborative Effort for Sequencing the Genomes of an Entire Mammalian Order.兔形目基因组联盟:一项对整个哺乳纲目进行基因组测序的国际合作项目。
J Hered. 2016 Jul;107(4):295-308. doi: 10.1093/jhered/esw010. Epub 2016 Feb 26.
9
Functional prediction of hypothetical proteins in human adenoviruses.人腺病毒中假定蛋白质的功能预测
Bioinformation. 2015 Oct 31;11(10):466-73. doi: 10.6026/97320630011466. eCollection 2015.
10
INGA: protein function prediction combining interaction networks, domain assignments and sequence similarity.INGA:结合相互作用网络、结构域分配和序列相似性的蛋白质功能预测
Nucleic Acids Res. 2015 Jul 1;43(W1):W134-40. doi: 10.1093/nar/gkv523. Epub 2015 May 27.
用于对海量数据集进行精确层次聚类的高效算法:攻克整个蛋白质空间
Bioinformatics. 2008 Jul 1;24(13):i41-9. doi: 10.1093/bioinformatics/btn174.
4
MUSTANG: a multiple structural alignment algorithm.MUSTANG:一种多重结构比对算法。
Proteins. 2006 Aug 15;64(3):559-74. doi: 10.1002/prot.20921.
5
JACOP: a simple and robust method for the automated classification of protein sequences with modular architecture.JACOP:一种用于具有模块化结构的蛋白质序列自动分类的简单且强大的方法。
BMC Bioinformatics. 2005 Aug 31;6:216. doi: 10.1186/1471-2105-6-216.
6
The predictive power of the CluSTr database.CluSTr数据库的预测能力。
Bioinformatics. 2005 Sep 15;21(18):3604-9. doi: 10.1093/bioinformatics/bti542. Epub 2005 Jun 16.
7
ProtoNet 4.0: a hierarchical classification of one million protein sequences.ProtoNet 4.0:一百万个蛋白质序列的层次分类
Nucleic Acids Res. 2005 Jan 1;33(Database issue):D216-8. doi: 10.1093/nar/gki007.
8
BLAST: at the core of a powerful and diverse set of sequence analysis tools.BLAST:一系列强大且多样的序列分析工具的核心。
Nucleic Acids Res. 2004 Jul 1;32(Web Server issue):W20-5. doi: 10.1093/nar/gkh435.
9
MUSCLE: multiple sequence alignment with high accuracy and high throughput.MUSCLE:具有高精度和高吞吐量的多序列比对。
Nucleic Acids Res. 2004 Mar 19;32(5):1792-7. doi: 10.1093/nar/gkh340. Print 2004.
10
An efficient algorithm for large-scale detection of protein families.一种用于大规模检测蛋白质家族的高效算法。
Nucleic Acids Res. 2002 Apr 1;30(7):1575-84. doi: 10.1093/nar/30.7.1575.