Tools to Analyze Morphology and Spatially Mapped Molecular Data

分析形态学和空间映射分子数据的工具

• 批准号: 9127923
• 负责人: Joel H. Saltz
• 金额: $ 64.42万
• 依托单位: STATE UNIVERSITY NEW YORK STONY BROOK
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9127923
• 关键词: 3-Dimensional; Anatomy; Automobile Driving; Biomedical Research; Brain Neoplasms; Cancer Research Project; Chromosome Mapping; Clinic; Cloud Computing; Collaborations; Communities; Complex; Computer Simulation; Computer software; Data; Data Analytics; Databases; Department of Energy; Development; Diagnostic; Disease; Distant; Doctor of Philosophy; Educational process of instructing; Educational workshop; Foundations; Funding; Genetic; Genomics; Grant; Health; Heterogeneity; High Performance Computing; Image; Image Analysis; Imagery; Individual; Informatics; Institution; Laboratories; Lead; Leadership; Letters; Link; Malignant Neoplasms; Malignant neoplasm of gastrointestinal tract; Malignant neoplasm of lung; Maps; Medical Imaging; Methods; Microscopic; Microscopy; Molecular; Molecular Genetics; Morphology; National Cancer Institute; National Institute of Biomedical Imaging and Bioengineering; Neoplasm Metastasis; Ohio; Outcome; Pathology; Pattern; Performance; Play; Polyps; Positioning Attribute; Prevention; Principal Investigator; Proteomics; Radiogenomics; Radiology Specialty; Research; Research Infrastructure; Research Personnel; Resolution; Resource Sharing; Resources; Role; Running; Science; Shotguns; Site; Slice; Slide; Structure; System; The Cancer Genome Atlas; Three-Dimensional Image; Time; Tissue Sample; Tissue imaging; Tissues; Training Support; United States National Library of Medicine; Universities; Work; anticancer research; cancer Biomedical Informatics Grid; cancer cell; cancer clinical trial; cancer imaging; cohort; colon cancer family registry; design; digital; experience; image archival system; imaging modality; in vivo imaging; innovation; instrument; laser capture microdissection; melanoma; method development; microscopic imaging; middleware; next generation sequencing; novel therapeutics; open source; programs; protein expression; quantitative imaging; reconstruction; research and development; sialodacryoadenitis virus; tool; tool development; treatment response; tumor; tumor initiation

DESCRIPTION (provided by applicant): This project is to develop, deploy, and disseminate a suite of open source tools and integrated informatics platform that will facilitate multi-scale, correlative analyses of high resolution whole slide tissue image data, spatially mapped genetics and molecular data for cancer research. This platform will play an essential role in supporting studies of tumor initiation, development, heterogeneity, invasion, and metastasis. These tools will allow quantitative analyses of the interplay between morphology and spatially mapped genetics and molecular data and will be used in studies that predict outcome and response to treatment, in radiogenomic and quantitative radiology imaging studies and in studies to identify cancer targets. The software and methods will enable researchers to assemble and visualize detailed, multi-scale descriptions of tissue morphologic changes originating from a wide range of microscopy instruments and make it possible to efficiently manage, interrogate, and explore microscopy imaging data at multiple scales and to identify and analyze features across individuals and cohorts. The project will build on and extend the software and methods we have developed in microscopy imaging, integrative image analysis, high performance computing, databases, and visualization over the past fifteen years and will also leverage, integrate and adapt the Harvard Slicer platform. The design and implementation of the informatics platform will be driven by four well funded, leading edge cancer focused studies along with many additional collaborative efforts including the Cancer Imaging Archive (TCIA), the Mayo Clinic Quantitative Imaging Network site, the Colon Cancer Family Registry and the Polyp Prevention Study.

描述(申请人提供)：该项目是开发、部署和传播一套开源工具和综合信息学平台，将促进高分辨率全切片组织图像数据、空间图谱遗传学和分子数据的多尺度相关分析，用于癌症研究。该平台将在支持肿瘤发生、发展、异质性、侵袭和转移的研究中发挥重要作用。这些工具将能够对形态和空间绘制的遗传学和分子数据之间的相互作用进行量化分析，并将用于预测结果和治疗反应的研究、放射基因组和定量放射成像研究以及识别癌症靶点的研究。该软件和方法将使研究人员能够汇编和可视化源自各种显微镜仪器的组织形态变化的详细、多尺度描述，并使其能够有效地管理、询问和探索多尺度的显微成像数据，并识别和分析个人和队列中的特征。该项目将建立和扩展我们在过去15年中在显微成像、综合图像分析、高性能计算、数据库和可视化方面开发的软件和方法，并将利用、集成和适应哈佛切片平台。信息学平台的设计和实施将由四项资金充足的前沿癌症研究以及许多其他合作努力推动，包括癌症成像档案(TCIA)、梅奥诊所定量成像网络网站、结肠癌家庭登记和息肉预防研究。