IDBR: Development of CytoIQ, an Adaptive Cytometer to Measure the Noisy of Dynamics of Gne Expression in Individual Live Cells

IDBR：开发 CytoIQ，一种自适应细胞仪，用于测量单个活细胞中 Gne 表达动态的噪声

• 批准号: 0963988
• 负责人: Jean Peccoud
• 金额: $ 16万
• 依托单位: Virginia Polytechnic Institute and State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-06-15 至 2012-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0963988&HistoricalAwards=false
• 关键词: IDBR; Development; CytoIQ; Adaptive; Cytometer

The Virginia Bioinformatics Institute at Virginia Tech is awarded a grant to develop Cyto.IQ, an adaptive imaging system specifically designed to characterize the noisy dynamics of gene expression and other molecular interactions in individual live cells. Cyto.IQ analyzes microscopic images on the fly to produce statistical plots and other quantitative indicators capturing important parameters of the cell physiology. The instrument has the capability to optimize the frequency of image acquisition and the total number of images taken using machine learning algorithms. It finds an optimal tradeoff between the cost of an experiment and the information it generates using a priori knowledge of the expected gene expression dynamics and previously acquired data. The control software is able to determine what cells to observe and when to observe them to ensure a fast convergence of statistical estimators while minimizing adverse effects of light exposure, and the overall duration of the experiment. Cyto.IQ is specifically designed to meet the needs of systems biologists, bioengineers, or biophysicists who are developing quantitative models of gene networks. Due to the noise affecting gene expression mechanisms, this rapidly growing community of users needs an instrument to observe the state of many individual cells over time. Current methods used to extract this type of data out of time-series of images collected using standard imaging platforms are inherently inefficient. They represent a major obstacle to the refinement of our understanding of the dynamics of cellular processes. Cyto.IQ increases the productivity of scientists working in this field by reducing the time it takes to perform an experiment and the number of experiments needed to collect suitable data sets. The adaptive control software is open source and available from www.cytoiq.org.

弗吉尼亚理工大学的弗吉尼亚生物信息学研究所获得了开发Cyto.IQ的赠款，这是一种专门设计用于描述单个活细胞中基因表达和其他分子相互作用的噪声动态的自适应成像系统。Cyto.IQ实时分析显微图像，生成统计图和其他定量指标，捕捉细胞生理学的重要参数。该仪器具有使用机器学习算法优化图像采集频率和拍摄图像总数的能力。它利用预期的基因表达动态的先验知识和之前获得的数据，在实验成本和所产生的信息之间找到了最佳的权衡。控制软件能够确定观察哪些细胞以及何时观察它们，以确保统计估计器的快速收敛，同时将光照的不利影响降至最低，并确定实验的总持续时间。IQ是专门为满足正在开发基因网络定量模型的系统生物学家、生物工程师或生物物理学家的需求而设计的。由于噪音影响基因表达机制，这一快速增长的用户群体需要一种仪器来观察许多单个细胞随着时间的推移的状态。目前用于从使用标准成像平台收集的图像的时间序列中提取这类数据的方法固有地效率低下。它们是改善我们对细胞过程动力学理解的主要障碍。Cyto.IQ通过减少进行实验所需的时间和收集合适数据集所需的实验数量，提高了在该领域工作的科学家的生产率。自适应控制软件是开源的，可从www.cell iq.org获得。