The Human Urinary Proteome Fingerprint Database UPdb.

International journal of proteomics Pub Date : 2013-01-01 Epub Date: 2013-10-09 DOI:10.1155/2013/760208
Holger Husi, Janice B Barr, Richard J E Skipworth, Nathan A Stephens, Carolyn A Greig, Henning Wackerhage, Rona Barron, Kenneth C H Fearon, James A Ross
{"title":"The Human Urinary Proteome Fingerprint Database UPdb.","authors":"Holger Husi,&nbsp;Janice B Barr,&nbsp;Richard J E Skipworth,&nbsp;Nathan A Stephens,&nbsp;Carolyn A Greig,&nbsp;Henning Wackerhage,&nbsp;Rona Barron,&nbsp;Kenneth C H Fearon,&nbsp;James A Ross","doi":"10.1155/2013/760208","DOIUrl":null,"url":null,"abstract":"<p><p>The use of human urine as a diagnostic tool has many advantages, such as ease of sample acquisition and noninvasiveness. However, the discovery of novel biomarkers, as well as biomarker patterns, in urine is hindered mainly by a lack of comparable datasets. To fill this gap, we assembled a new urinary fingerprint database. Here, we report the establishment of a human urinary proteomic fingerprint database using urine from 200 individuals analysed by SELDI-TOF (surface enhanced laser desorption ionisation-time of flight) mass spectrometry (MS) on several chip surfaces (SEND, HP50, NP20, Q10, CM10, and IMAC30). The database currently lists 2490 unique peaks/ion species from 1172 nonredundant SELDI analyses in the mass range of 1500 to 150000. All unprocessed mass spectrometric scans are available as \".xml\" data files. Additionally, 1384 peaks were included from external studies using CE (capillary electrophoresis)-MS, MALDI (matrix assisted laser desorption/ionisation), and CE-MALDI hybrids. We propose to use this platform as a global resource to share and exchange primary data derived from MS analyses in urinary research. </p>","PeriodicalId":73474,"journal":{"name":"International journal of proteomics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2013/760208","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of proteomics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1155/2013/760208","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2013/10/9 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15

Abstract

The use of human urine as a diagnostic tool has many advantages, such as ease of sample acquisition and noninvasiveness. However, the discovery of novel biomarkers, as well as biomarker patterns, in urine is hindered mainly by a lack of comparable datasets. To fill this gap, we assembled a new urinary fingerprint database. Here, we report the establishment of a human urinary proteomic fingerprint database using urine from 200 individuals analysed by SELDI-TOF (surface enhanced laser desorption ionisation-time of flight) mass spectrometry (MS) on several chip surfaces (SEND, HP50, NP20, Q10, CM10, and IMAC30). The database currently lists 2490 unique peaks/ion species from 1172 nonredundant SELDI analyses in the mass range of 1500 to 150000. All unprocessed mass spectrometric scans are available as ".xml" data files. Additionally, 1384 peaks were included from external studies using CE (capillary electrophoresis)-MS, MALDI (matrix assisted laser desorption/ionisation), and CE-MALDI hybrids. We propose to use this platform as a global resource to share and exchange primary data derived from MS analyses in urinary research.

Abstract Image

Abstract Image

人类尿蛋白质组指纹数据库。
使用人尿作为诊断工具有许多优点,如易于采集样本和无创性。然而,在尿液中发现新的生物标志物以及生物标志物模式主要受到缺乏可比数据集的阻碍。为了填补这一空白,我们建立了一个新的尿液指纹数据库。在这里,我们报告了使用SELDI-TOF(表面增强激光解吸电离飞行时间)质谱(MS)在几个芯片表面(SEND, HP50, NP20, Q10, CM10和IMAC30)分析200个人的尿液,建立了人类尿蛋白质组学指纹数据库。该数据库目前从1172个非冗余SELDI分析中列出了2490个独特的峰/离子种类,质量范围在1500到150000之间。所有未处理的质谱扫描都以“。xml”数据文件的形式提供。此外,使用CE(毛细管电泳)-MS, MALDI(基质辅助激光解吸/电离)和CE-MALDI杂交进行的外部研究包括1384个峰。我们建议使用这个平台作为全球资源来共享和交换来自泌尿研究的MS分析的原始数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信