AUTOMATED METHODS TO IDENTIFY PATTERNS OF FEATURES BETWEEN CELL TYPES

这个子项目是利用资源的许多研究子项目之一 由NIH/NCRR资助的中心拨款提供。次级项目的主要支助 而子项目的主要调查员可能是由其他来源提供的， 包括其它NIH来源。 列出的子项目总成本可能 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。 保留字： 批量数据分析、可视化和分发协作 摘要： 使用多种模式对在96孔板中生长的细胞进行成像， 识别超过108个单独的生理细胞测量值，或者 特征，包括核密度，细胞周长， 翻译后修饰，特定的测定来计算 处于S期和有丝分裂的细胞百分比[Gasparri等人，2004. J Biomol Screen 9：232-243]，细胞质-核易位， 表征细胞毒性和受体内化。的 该项目的目标是制定方法，以确定模式， 细胞类型之间的特征（个体生理细胞测量）。

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.