AUTOMATED METHODS TO IDENTIFY PATTERNS OF FEATURES BETWEEN CELL TYPES

识别细胞类型之间特征模式的自动化方法

• 批准号: 8364267
• 负责人: ART WETZEL
• 金额: $ 0.11万
• 依托单位: CARNEGIE-MELLON UNIVERSITY
• 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 2013-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8364267
• 关键词: Biological Assay; Biomedical Research; Cell Density; Cells; Collaborations; Cytoplasm; Data Analyses; Funding; Goals; Grant; High Performance Computing; Image; Imagery; Individual; Measurement; Methods; Mitosis; Modality; National Center for Research Resources; Nuclear; Nuclear Translocation; Pattern; Physiological; Post-Translational Protein Processing; Principal Investigator; Research; Research Infrastructure; Resources; S Phase; Source; Toxic effect; United States National Institutes of Health; abstracting; cell type; cost; receptor internalization

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Keywords: Volume data analysis, visualization and distribution collaboration Abstract: Cells, grown in a 96 well plate, are imaged using multiple modalities to identify over 108 individual physiological cellular measurements or features, including the nuclear density, cell perimeter, post-translational modifications, specific assays to calculate the percentage of cells in S-phase and mitosis [Gasparri, et al. 2004. J Biomol Screen 9:232-243], cytoplasm-nuclear translocation, characterization of cellular toxicity, and receptor internalization. The goal of this project is to develop approaches to identify patterns of features (individual physiological cellular measurements) between cell types.

该子项目是利用资源的众多研究子项目之一 由 NIH/NCRR 资助的中心拨款提供。子项目的主要支持 并且子项目的主要研究者可能是由其他来源提供的， 包括其他 NIH 来源。 子项目可能列出的总成本 代表子项目使用的中心基础设施的估计数量， NCRR 赠款不直接向子项目或子项目工作人员提供资金。 关键词： 体量数据分析、可视化和分发协作 抽象的： 使用多种模式对生长在 96 孔板中的细胞进行成像 识别超过 108 个单独的生理细胞测量值或 特征，包括核密度、细胞周长、 翻译后修饰，计算具体分析 处于 S 期和有丝分裂的细胞百分比 [Gasparri, et al. 2004.J Biomol Screen 9:232-243]，细胞质-核易位， 细胞毒性和受体内化的表征。这 该项目的目标是开发方法来识别模式 细胞类型之间的特征（个体生理细胞测量）。