Development of Bioimage Informatics Tools for Spatial Expression Datasets

空间表达数据集生物图像信息学工具的开发

• 批准号: 8539040
• 负责人: Erwin Frise
• 金额: $ 37.42万
• 依托单位: UNIVERSITY OF CALIF-LAWRENC BERKELEY LAB
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-15 至 2015-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8539040
• 关键词: Algorithms; Animal Model; Applications Grants; Area; Automation; Bioinformatics; Biological; Body part; Cells; Cereals; Collection; Communities; Complex; Computer Analysis; Computer software; Custom; Data; Data Analyses; Data Set; Databases; Development; Developmental Gene; Differentiation and Growth; Drosophila genus; Embryo; Exhibits; Fiji; Foundations; Future; Gene Expression; Gene Expression Profile; Gene Expression Regulation; Genes; Goals; Human; Image; Image Analysis; Imagery; Informatics; Investigation; Java; Knowledge; Link; Location; Maps; Masks; Memory; Methods; Microscope; Microscopy; Molecular Biology; Nucleic Acid Regulatory Sequences; Organism; Pattern; Process; Regulator Genes; Reporter; Research; Research Personnel; Resolution; Resources; Role; Shapes; Slide; Staging; Structure; System; Systems Biology; Time; Tissue Differentiation; Tissues; United States National Institutes of Health; Writing; base; bioimaging; body map; computer framework; data management; data mining; data modeling; gene function; genome-wide; human disease; image processing; imaging Segmentation; imaging modality; improved; novel; programs; repository; tool; virtual; web interface

DESCRIPTION (provided by applicant): One of the critical tools for probing gene function is imaging spatial expression with confocal or higher resolution microscopy, yielding a pattern of when and where a particular gene is expressed. As a result of the increased availability of such spatial expression patterns and the increased importance of high throughput imaging, there is a need for general purpose tools for managing and analyzing spatial gene expression datasets for research and systems biology. We propose to develop and make available to the general community a suite of tools for managing and analyzing large-scale spatial gene expression datasets. For our large Drosophila spatial expression dataset, we have developed an image based virtual representation that has been practical for visualization, data mining and analysis, while being compact enough to distribute and store large expression datasets. Moreover, this representation allows for analyzing image based data without specialized image processing knowledge. We propose to enhance these tools by adding an integrated data management and analysis platform to a popular scientific image processing program, ImageJ. This ImageJ workbench will be complementary to existing web-interfaces and will enable biologists to perform additional analyses and bioinformatics researchers to extend the software by writing their own custom modules. We will expand the applicability of our virtual embryo representations to complex patterns found at later stages of development and extend microscope automation software to generate virtual representations from automatically acquired images. Finally, we plan to extend the capabilities of the software to process images from other model organisms and develop methods for cross species comparisons. The proposed toolkit will provide a strong foundation for integration of gene expression data with regulatory and gene sequences to promote research for discovering networks of regulatory interactions.

描述（由申请人提供）：探测基因功能的关键工具之一是用共聚焦或高分辨率显微镜成像空间表达，产生特定基因表达的时间和地点的模式。由于这种空间表达模式的可用性增加以及高通量成像的重要性增加，需要通用工具来管理和分析研究和系统生物学的空间基因表达数据集。我们建议开发并提供一套工具，用于管理和分析大规模空间基因表达数据集。对于我们的大型果蝇空间表达数据集，我们已经开发了一种基于图像的虚拟表示，它在可视化、数据挖掘和分析方面非常实用，同时足够紧凑，可以分发和存储大型表达数据集。此外，这种表示允许在没有专门的图像处理知识的情况下分析基于图像的数据。我们建议通过在流行的科学图像处理程序ImageJ中添加集成数据管理和分析平台来增强这些工具。这个ImageJ工作台将是现有网络界面的补充，使生物学家能够进行额外的分析，生物信息学研究人员可以通过编写自己的定制模块来扩展软件。我们将扩展我们的虚拟胚胎表示的适用性，以在发展的后期阶段发现复杂的模式，并扩展显微镜自动化软件，从自动获取的图像中生成虚拟表示。最后，我们计划扩展软件的功能，以处理来自其他模式生物的图像，并开发跨物种比较的方法。所提出的工具包将为基因表达数据与调控和基因序列的整合提供坚实的基础，以促进发现调控相互作用网络的研究。