Cell tracking and analysis for time-lapse microscopy

产品说明： 自动延时显微镜成像提供了一种重要的和革命性的方法来研究动态细胞过程，并以动态的方式测量药物反应。荧光蛋白标记物的可用性使得有可能在长时间的成像中监测活细胞中的有丝分裂和凋亡。然而，在处理、建模、管理和分析由延时显微镜在研究动态细胞信息中产生的大量细胞图像方面存在重大的信息学挑战。现有的生物成像工具在用于活细胞成像的图像分析的范围和能力方面是极其有限的，特别是在延时和高通量数据方面。 目前，科学家们不得不依靠缓慢的手动分析来提取信息。因此，图像信息学已成为动态分子和细胞成像研究的限速因素。 该提案旨在填补这一空白，提供了一个先进的软件包，动态细胞图像定量仪（D-CELLIQ），具有更大的能力，以识别和跟踪对象，并分析和定量对象特征提取的大量图像产生的延时显微镜，提供了一个完整的图片的演变的功能和行为的细胞在时间和空间。该假设是，D-CELLIQ系统将是有用的，以测量细胞周期的进展，有丝分裂的时间和启动的细胞凋亡观察到的延时成像和表征新的抗有丝分裂化合物的作用机制。为了验证这一假设，我们的目标是定义D-CELLIQ的集成数据处理管道和架构，开发新的细胞图像分析和计算建模工具，并通过一组定义明确的生物驱动实验来评估D-CELLIQ的实用性。 目前还没有软件包可以进行这样的分析，因此，我们计划使这个包免费提供给生物医学界。

DESCRIPTION: Automated time-lapse microscopy imaging provides an important and revolutionary method to study dynamic cellular processes and to measure drug response in a dynamic fashion. The availability of fluorescent protein markers makes it possible to monitor mitosis and apoptosis in living cells over extended periods of imaging. Nevertheless, there are significant informatics challenges in processing, modeling, managing, and analyzing large volumes of cellular images generated by time-lapse microscopy in studying dynamic cellular information. The existing bioimaging tools are extremely limited in their scope and capacity for image analysis for live-cell imaging, particularly in respect of time-lapse and high throughput data. Currently, the scientists have to rely on slow, manual analysis to extract information. Thus, image informatics has become the rate-limiting factor in dynamic molecular and cellular imaging studies. This proposal seeks to fill that gap by providing an advanced software package, dynamic cellular image quantitator (D-CELLIQ), with increased capacity to identify and track objects and to analyze and quantitate object features extracted from the large amounts of images generated by time-lapse microscopy, providing a complete picture of the evolution of the features and behaviors of cells in time and space. The hypothesis is that the D-CELLIQ system will be useful to measure cell cycle progression, mitotic timing and initiation of apoptosis in cells observed by time-lapse imaging and to characterize the mechanism of action of novel antimitotic compounds. To test this hypothesis, we aim to define the integrated data processing pipeline and architecture of D-CELLIQ, develop new cellular image analysis and computational modeling tools, and evaluate the utility of the D-CELLIQ with a set of well defined, biological-driven experiments. There are currently no software packages that can perform such analyses, and we therefore plan to make this package freely available to biomedical community.