Integrative Pipeline for Analysis & Translational Application of TCGA Data (GDAC)

综合分析管道

• 批准号: 8123272
• 负责人: GORDON B. MILLS
• 金额: $ 143.84万
• 依托单位: UNIVERSITY OF TX MD ANDERSON CAN CTR
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-29 至 2014-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8123272
• 关键词: Address; Algorithms; Architecture; Bioinformatics; Biological; Biological Markers; Biology; Biometry; Cancer Center; Cancer Patient; Clinical; Clinical Research; Confidentiality; Country; Data; Data Analyses; Development; Ensure; Funding; Genome; Goals; Human; Imagery; Institution; Lead; Malignant Neoplasms; Molecular Profiling; Participant; Pathology; Pathway Analysis; Research Personnel; Software Engineering; Source; Specimen; System; Systems Biology; Technology; The Cancer Genome Atlas; Time; University of Texas M D Anderson Cancer Center; Work; base; biological systems; biosignature; cancer Biomedical Informatics Grid; computer based Semantic Analysis; data integration; design; follow-up; innovation; member; novel; programs; software development; tumor; user-friendly

DESCRIPTION (provided by applicant): The proposed Genome Data Analysis Center B (GDAC B) will work cooperatively with other GDACs funded by The Cancer Genome Atlas (TCGA) project to (i) develop an innovative, integrative pipeline for systems- level analysis of TCGA's molecular profiling data on many different types of human tumors and (ii) apply that pipeline and its component modules to TCGA data to address important biological and clinical questions. An overarching goal is to 'personalize' the management of patients' cancers on the basis of new tumor biomarkers and biosignatures. For the first time, it is easier to generate millions of data points on tumors than to analyze or interpret those data, hence the bioinformatic challenge is formidable. The pipeline will be constructed using the Agile software development paradigm and semantic web query architecture. It will be based on novel algorithms and modules developed by participants in the GDAC. Included will be modules for data integration, data visualization, pathway analysis, and systems biological interpretation, all designed to be user-friendly for the bench researcher and clinician. Those modules will be interfaced with additional ones developed by other GDACs, All development will adhere to standards of TCGA and the Cancer Biomedical Informatics Grid (caBIG) and will provide controlled access to ensure confidentiality of personally identifiable data. The proposed GDAC team brings to this project expertise in bioinformatics, biostatistics, software engineering, high-throughput molecular profiling technologies, systems-oriented biology, biomarker studies, pathology, and clinical research. The three co-PIs (for bioinformatics, systems biology, and clinical research) have each participated actively in TCGA since its inception, as have other members of the team, including the lead software engineer. A major strength is the University of Texas M. D. Anderson Cancer Center (MDACC) as an institution. MDACC has been, and presumably will continue to be, the largest source of tumor specimens for TCGA. As one of the country's foremost cancer centers, with by far the largest cancer clinical research program, MDACC has unparalleled expertise for follow up on medically important leads that result from the development and application of the pipeline to TCGA data

描述（由申请人提供）：拟议的基因组数据分析中心B（GDAC B）将与由癌症基因组学地图集（TCGA）项目合作，以（i）为（i）开发用于系统级别的创新，综合管道的系统水平分析TCGA关于许多不同类型的人类肿瘤的分子分析数据，（ii）将管道及其组件模块应用于TCGA数据，以解决重要的生物学和临床问题。一个总体目标是根据新的肿瘤生物标志物和生物签名“个性化”患者的管理。第一次，在肿瘤上产生数百万个数据点比分析或解释这些数据要容易得多，因此，生物信息学挑战是巨大的。该管道将​​使用敏捷软件开发范式和语义Web查询体系结构构建。它将基于GDAC参与者开发的新算法和模块。包括的模块是用于数据集成，数据可视化，途径分析和系统生物学解释的模块，所有这些模块均设计为对台式研究人员和临床医生的用户友好。这些模块将与其他GDAC开发的其他模块连接，所有开发都将遵守TCGA和癌症生物医学信息学网格（CABIG）的标准，并将提供受控的访问权限以确保个人身份数据的机密性。拟议的GDAC团队在生物信息学，生物统计学，软件工程，高通量分子分析技术，以系统为导向的生物学，生物标志物研究，病理学和临床研究方面为该项目提供了这一项目专业知识。自成立以来，这三个共同研究（用于生物信息学，系统生物学和临床研究）都积极参与了TCGA，包括首席软件工程师在内的团队中的其他成员也参加了比赛。得克萨斯大学M. D. Anderson癌症中心（MDACC）是一家机构。 MDACC曾经并且可能会继续是TCGA的最大肿瘤标本来源。作为该国最重要的癌症中心之一，迄今为止，MDACC拥有最大的癌症临床研究计划，它具有无与伦比的专业知识，可以跟进医学上重要的潜在客户，这是由于管道在TCGA数据上的开发和应用而导致的