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

综合分析管道

• 批准号: 8327267
• 负责人: GORDON B. MILLS
• 金额: $ 158.71万
• 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/8327267
• 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; Instruction; 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; cancer diagnosis; cancer therapy; cancer type; computer based Semantic Analysis; data integration; design; follow-up; innovation; member; novel; programs; software development; tumor; user-friendly

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.

拟议的基因组数据分析中心B （GDAC B）将与其他GDAC合作