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Image-derived Spatiotemporal Models of Cellular Organization and Perturbation

细胞组织和扰动的图像衍生时空模型

基本信息

批准号：
9042386
负责人：
Robert F Murphy
金额：
$ 31.39万
依托单位：
CARNEGIE-MELLON UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2010
资助国家：
美国
起止时间：
2010-04-01 至 2019-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9042386
关键词：
Accounting Affect Alleles Behavior Biochemical Reaction Biochemistry Biological Assay Cell Cycle Cell Shape Cell model Cell physiology Cells Cellular Structures Complex Computer software Computing Methodologies Cytopathology Data Defect Dependence Dependency Disease Dysplasia Endoplasmic Reticulum Fluorescence Microscopy Foundations Future Genes Golgi Apparatus Grant Health Health Sciences Hematological Disease Hereditary Spastic Paraplegia Heterogeneity Image Lead Learning Length Life Maintenance Measures Methods Microscopy Modeling Molecular Molecular Biology Morphology Mutation Nuclear Organelles Organizational Change Pathway interactions Pattern Pharmaceutical Preparations Phenotype Play Population Positioning Attribute Preclinical Drug Evaluation Process Proteins RNA interference screen Research Reticular Cell Role Shapes Statistical Models Structure Subcellular structure System Testing Therapeutic Time Tissues Toxic effect Visual base computer framework computerized tools environmental change fluorescence imaging genetic variant instrumentation learning strategy microscopic imaging model development movie mutant open source response screening spatiotemporal temporal measurement tool

项目摘要

DESCRIPTION (provided by applicant): This research is aimed at developing and testing methods that will enable automated, information--‐rich studies of the subcellular organization of proteins and other biomolecules. We propose to develop the computational foundation for deciphering the spatiotemporal morphological pathways of different subcellular structures during important subcellular processes automatically from microscopy images. We will leverage our progress in the previous project period, in which we established the Cell Organizer system for building image-‐derived models of cell organization, to build new modeling capabilities for cisternal and reticular structures, for capturing the relationships between different cellular components, and for learning how aspects of cell organization change during processes such as the cell cycle. Given the importance of the endoplasmic reticulum in numerous cellular processes (as well as diseases including hematological disorders, cranio--‐ lenticulo--‐sutural dysplasia, chylomicro retention disease, etc.), we expect the modeling approaches we propose to provide important mechanistic clues as to the "normal" (non-- athological) morphological pathways of these structures and how they may be perturbed in disease. To provide valuable images to drive the development of modeling capabilities, and to simultaneously identify candidate lead compounds for treatment of diseases with ER defects, we will conduct extensive compound screening studies on cells expressing normal and mutant alleles of atlastin (which plays a critical role in ER structure). The computational methods we develop will be integrated into our open source CellOrganizer system (http://CellOrganizer.org). In addition to the applications mentioned above, we anticipate the computational frameworks we develop will be valuable for a wide range of imaging assays including drug screens, RNAi screens, cytology, and pathology.

描述(由申请人提供)：这项研究的目的是开发和测试方法，使自动化的，信息丰富的研究亚细胞组织蛋白质类和其他生物分子。我们建议为从显微镜图像中自动破译重要亚细胞过程中不同亚细胞结构的时空形态路径奠定计算基础。我们将利用我们在前一个项目期间的进展，在该项目中，我们建立了细胞组织者系统，用于建立细胞组织的图像派生模型，为池和网状结构建立新的建模能力，用于捕获不同细胞组件之间的关系，以及了解细胞组织的各个方面在细胞周期等过程中如何变化。鉴于内质网在许多细胞过程中的重要性(以及包括血液学疾病、颅晶状-缝合性发育不良、乳糜微滞留病等疾病)，我们期望我们提出的建模方法能够为这些结构的“正常”(非病理)形态途径以及它们如何在疾病中受到干扰提供重要的机制线索。为了提供有价值的图像来驱动建模能力的发展，并同时确定用于治疗内质网缺陷疾病的候选先导化合物，我们将对表达阿特拉斯汀(在内质网结构中起关键作用)的正常和突变等位基因的细胞进行广泛的化合物筛选研究。我们开发的计算方法将集成到我们的开源蜂窝组织器系统(http://CellOrganizer.org).除了上面提到的应用，我们预计我们开发的计算框架将对广泛的成像分析有价值，包括药物筛选、RNAi筛选、细胞学和病理学。