大数据平台,实现高质量临床数据与下一代测序数据的整合

Joel Haspel
{"title":"大数据平台,实现高质量临床数据与下一代测序数据的整合","authors":"Joel Haspel","doi":"10.1016/j.nhtm.2014.11.011","DOIUrl":null,"url":null,"abstract":"<div><p><span><span><span>Today, personalized medicine is closer to reality than ever before through targeted treatment, however, the substantial increase in data correspondingly requires scalable systems to continue to effectively manage the data and to remain current with advancing technology. As organizations move to advance </span>translational research to achieve personalized medicine, researchers and clinicians must manage informatics, however, there is a shortage of fully integrated informatics solutions that integrate, store, and analyze clinical and </span>omics data from diverse sources – generated in-house as well as public consortiums. Many researchers and clinicians must rely on </span>bioinformaticians<span> to perform mundane data management tasks in order to validate a simple hypothesis. Oracle Health Sciences Translational Research Center provides a complete and scalable informatics solution, with centralized data storage and analysis across genetic information areas (genomics, transcriptomics, and proteomics), vendor platforms, biological data types, and clinical data sources. Organizations such as Cancer Research UK, Erasmus MC, MD Anderson Cancer Center and UPMC have adopted this solution and are evaluating treatment responses for similar patients in a self-sufficient manner, ultimately shortening the biomarker development cycle and accelerating the adoption of personalized medicine.</span></p></div>","PeriodicalId":90660,"journal":{"name":"New horizons in translational medicine","volume":"2 2","pages":"Pages 57-58"},"PeriodicalIF":0.0000,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.nhtm.2014.11.011","citationCount":"2","resultStr":"{\"title\":\"A big data platform to enable integration of high quality clinical data and next generation sequencing data\",\"authors\":\"Joel Haspel\",\"doi\":\"10.1016/j.nhtm.2014.11.011\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p><span><span><span>Today, personalized medicine is closer to reality than ever before through targeted treatment, however, the substantial increase in data correspondingly requires scalable systems to continue to effectively manage the data and to remain current with advancing technology. As organizations move to advance </span>translational research to achieve personalized medicine, researchers and clinicians must manage informatics, however, there is a shortage of fully integrated informatics solutions that integrate, store, and analyze clinical and </span>omics data from diverse sources – generated in-house as well as public consortiums. Many researchers and clinicians must rely on </span>bioinformaticians<span> to perform mundane data management tasks in order to validate a simple hypothesis. Oracle Health Sciences Translational Research Center provides a complete and scalable informatics solution, with centralized data storage and analysis across genetic information areas (genomics, transcriptomics, and proteomics), vendor platforms, biological data types, and clinical data sources. Organizations such as Cancer Research UK, Erasmus MC, MD Anderson Cancer Center and UPMC have adopted this solution and are evaluating treatment responses for similar patients in a self-sufficient manner, ultimately shortening the biomarker development cycle and accelerating the adoption of personalized medicine.</span></p></div>\",\"PeriodicalId\":90660,\"journal\":{\"name\":\"New horizons in translational medicine\",\"volume\":\"2 2\",\"pages\":\"Pages 57-58\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.nhtm.2014.11.011\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"New horizons in translational medicine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2307502314000289\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"New horizons in translational medicine","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2307502314000289","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

如今,通过有针对性的治疗,个性化医疗比以往任何时候都更接近现实,然而,数据的大幅增加相应地需要可扩展的系统来继续有效地管理数据,并与先进的技术保持同步。随着组织推进转化研究以实现个性化医疗,研究人员和临床医生必须管理信息学,然而,缺乏完全集成的信息学解决方案来集成、存储和分析来自不同来源的临床和组学数据-内部生成以及公共联盟。为了验证一个简单的假设,许多研究人员和临床医生必须依靠生物信息学家来执行日常的数据管理任务。Oracle健康科学转化研究中心提供了一个完整的、可扩展的信息学解决方案,具有跨遗传信息领域(基因组学、转录组学和蛋白质组学)、供应商平台、生物数据类型和临床数据源的集中数据存储和分析。英国癌症研究中心(Cancer Research UK)、伊拉斯谟癌症中心(Erasmus MC)、MD Anderson癌症中心(MD Anderson Cancer Center)和UPMC等组织已经采用了这种解决方案,并以自给自足的方式评估类似患者的治疗反应,最终缩短了生物标志物的开发周期,加速了个性化医疗的采用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
A big data platform to enable integration of high quality clinical data and next generation sequencing data

Today, personalized medicine is closer to reality than ever before through targeted treatment, however, the substantial increase in data correspondingly requires scalable systems to continue to effectively manage the data and to remain current with advancing technology. As organizations move to advance translational research to achieve personalized medicine, researchers and clinicians must manage informatics, however, there is a shortage of fully integrated informatics solutions that integrate, store, and analyze clinical and omics data from diverse sources – generated in-house as well as public consortiums. Many researchers and clinicians must rely on bioinformaticians to perform mundane data management tasks in order to validate a simple hypothesis. Oracle Health Sciences Translational Research Center provides a complete and scalable informatics solution, with centralized data storage and analysis across genetic information areas (genomics, transcriptomics, and proteomics), vendor platforms, biological data types, and clinical data sources. Organizations such as Cancer Research UK, Erasmus MC, MD Anderson Cancer Center and UPMC have adopted this solution and are evaluating treatment responses for similar patients in a self-sufficient manner, ultimately shortening the biomarker development cycle and accelerating the adoption of personalized medicine.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Contents Editorial Board Improving disease diagnosis by a new hybrid model Pros, cons and future of antibiotics Abstracts: 5th Annual Congress of the European Society for Translational Medicine (EUSTM-2017), 20-22 October 2017, Berlin, Germany
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1