AUTOMATED METHODS TO IDENTIFY PATTERNS OF FEATURES BETWEEN CELL TYPES

该子项目是利用 由NIH/NCRR资助的中心赠款提供的资源。子项目和 研究者（PI）可能从另一个NIH来源获得了主要资金， 因此可以在其他CRISP条目中表示。列出的机构是 研究中心，而研究中心不一定是研究者所在的机构。 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. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. 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.