CAREER: Four-Dimensional Subcellular Structure Tracking and Modeling for Cell Dynamics Study

生物学上的新发现需要对细胞动力学有广泛的了解。了解亚细胞颗粒/结构，如细胞器、小泡和mRNAs，对于了解细胞如何调节特定蛋白质从合成部位到作用部位的输送，以更好地了解疾病和病毒感染是至关重要的。定量的蛋白质时空迁移率研究对于从实验上理解和验证蛋白质的信号机制和蛋白质之间的相互作用具有重要的作用。这项提议的目标是开发一个独特的和第一个基于Web的开放访问细胞动力学分析系统(CellDAS)，用于自动化亚细胞粒子运动估计、跟踪和流动性分析。首先，开发了一个类似于物理概念的发散滤光器，用于检测具有生物重要性的定向运动。在此基础上，提出了一种用于多目标跟踪的马尔可夫链蒙特卡罗(MCMC)采样框架，克服了指数复杂度问题。最后，在跟踪过程中最优地选择不同的特征。该项目将为细胞生物学和计算机科学的培训和教育提供丰富的资源。通过访问建议的开放访问的基于网络的CellDAS界面，本科生和研究生将接受基本的计算机视觉算法、生物数据可视化以及对特定感兴趣的生物学问题的形成理解的培训。此外，PI将促进和激励女性在科学和工程领域，并通过女性工程师协会(SWE)的指导活动和一年一度的高中机器人编程大赛激励高中生在这些领域追求职业生涯。

New discoveries in biology have required an extensive knowledge of cell dynamics. Knowledge of subcellular particles/structures such as organelles, vesicles, and mRNAs is critical to understand how cells regulate delivery of specific proteins from the site of synthesis to the site of action for a better understanding of diseases and viral infections. Quantitative spatial-temporal protein mobility study plays an essential role in experimentally comprehending and validating protein signaling mechanisms and protein-protein interactions. The goal of this proposal is to develop a unique and the first web-based open access Cell Dynamics Analysis System (CellDAS) for automating subcellular particle motion estimation, tracking and mobility analysis. First, a divergence filter is developed, analogous to physics concepts, to detect the directed motion that is of biological importance. Then a Markov Chain Monte Carlo (MCMC) sampling framework is presented for multi-object tracking that overcomes the exponential complexity problem. Finally, distinctive features are optimally selected during the tracking process. This project will provide rich resources for training and education in cell biology and computer science. By accessing the proposed open-access web-based CellDAS interface, undergraduates and graduates will have training in basic computer vision algorithms, biological data visualization, and formation understanding to specific interested biology problem. Moreover, the PI will promote and motivate women in science and engineering, and inspire high school students to pursue careers in these fields through the mentoring activities of the Society of Women Engineers (SWE) and the annual high school Robot Programming Contest.