Phase II: Robust analysis of subcellular time-lapse assays

描述(申请人提供)：该项目的目标是开发和商业化下一代活细胞，时间推移显微镜图像识别软件，专门用于高通量量化亚细胞功能。该软件集成了新的和强大的亚细胞延时分析和建模方法，这是目前用于增强信号检测和噪声免疫力的信息学工具所不具备的，以显著提高分析吞吐量、准确性、效率和可靠性。这些分析工具包括三个层次：1)稳健目标检测通过使用置信度图进行像素与对象的非二进制、概率关联来增强目标检测；2)稳健特征优化通过利用整个图像或电影中的时空信息来改进置信度图或加权它们以用于模型拟合来增强定量特征测量；3)以结果为导向的模型拟合通过迭代拟合内置可靠性评估和使用时空图像信息的纠错来增强分析模型参数。该第二阶段项目的目标是将这些技术整合到SVCell(Tm)平台中，推广和表征它们在更广泛的新亚细胞分析中的表现，并为整个平台通过我们的商业合作伙伴发布产品做好准备。第二阶段的交付成果将是为基础和药物发现科学家准备好的市场软件包。我们的具体目标是：1)为广泛的生物分析应用优化和验证亚细胞分析模块；2)SVCell亚细胞分析模块的产品软件工程；3)通过现场测试和科学合作评估SVCell测试版的产品准备情况。成像分析着眼于固定细胞和活细胞中的亚细胞表型，是生命科学成像研究的前沿。它们为研究人员提供了新的工具，以高分辨率剖析细胞功能的机制。它们带来了新的见解和新的发现，可以对所有基础研究产生重大影响。使用SVCell平台，这些新的分析方法可以快速缩放并转换为成像屏幕，用于药物或生物发现和疾病诊断。总体而言，这个第二阶段项目承诺通过提高基础研究、高通量成像分析开发的速度和效率，以及部署具有微妙表型的新型高通量成像分析，对人类健康产生重大影响。显微图像识别软件有望通过提高基础研究、高通量成像分析开发的准确性、速度和效率，以及部署具有微妙表型的新型高通量成像分析，对人类健康产生重大影响。它将为研究人员提供一个新的工具，以高分辨率剖析细胞功能的机制。

DESCRIPTION (provided by applicant): The goal of this project is to develop and commercialize next generation live cell, time-lapse microscopy image recognition software specialized for high throughput quantification of subcellular functions. The software integrates novel and robust methods of subcellular time-lapse analysis and modeling not available in the current informatics tools for the enhancement of signal detection and noise immunity to significantly improve on assay throughput, accuracy, efficiency, and reliability. These include three levels of analysis tools: 1) robust object detection enhances object detection by making a non-binary, probabilistic association of pixels to objects using confidence maps; 2) robust feature optimization enhances quantitative feature measurement by utilizing the spatial temporal information within the entire image or movie to refine the confidence maps or weight them for model fitting; and 3) outcome directed model fitting enhances the assay model parameter through iterative fitting with built-in reliability assessment and error correction using spatial-temporal image information The goal of this phase II project is to incorporate these technologies into the SVCell(tm) platform, generalize and characterize their performance in a wider range of new subcellular assays, and prepare the entire platform for product release through our commercial partners. The phase II deliverables will be a market ready software package for basic and drug discovery scientists. Our specific aims are: 1) Optimize and validate the subcellular analysis module for broad bio-assay application; 2) Product software engineering of the subcellular analysis module in SVCell; and 3) Evaluate the product readiness of the SVCell beta through field tests and scientific collaborations. Imaging assays looking at subcellular phenotypes in both fixed and live cells are at the cutting edge of life science imaging research. They provide researchers with new tools to dissect the mechanisms of cellular function with great resolution. They lead to new insights and new discoveries that can have significant impact across all of basic research. These new assays can be rapidly scaled and translated into imaging screens for drug or biological discovery and disease diagnosis using the SVCell platform. Overall this phase II project promises to make a significant impact on human health by increasing the speed and efficiency of basic research, high throughput imaging assay development, and deployment of novel high throughput imaging assays with subtle phenotypes. Microscopy image recognition software promises to make a significant impact on human health by increasing the accuracy, speed and efficiency of basic research, high throughput imaging assay development, and deployment of novel high throughput imaging assays with subtle phenotypes. It will provide researchers with a new tool to dissect the mechanisms of cellular function with great resolution.