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

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的资助。IQ是一种自适应成像系统，专门用于表征单个活细胞中基因表达和其他分子相互作用的噪声动态。阶段。IQ分析微观图像在飞行中产生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图像总数的能力。它在实验成本和使用预期基因表达动态的先验知识和先前获得的数据产生的信息之间找到最佳权衡。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，同时最大限度地减少光照的不利影响，以及实验的总体持续时间。阶段。IQ是专门为满足系统生物学家、生物工程师或生物物理学家的需求而设计的，他们正在开发基因网络的定量模型。由于噪声影响基因表达机制，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时间的状态。目前用于从使用标准成像平台收集的时间序列图像中提取此类数据的方法本质上是低效的。它们代表了我们对细胞过程动力学的理解的一个主要障碍。阶段。IQ通过减少执行实验所需的时间和收集合适数据集所需的实验次数，提高了在这一领域工作的科学家的生产力。自适应控制软件是开源的，可以从www.cytoiq.org获得。

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.