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

生物学的新发现需要细胞动力学的广泛知识。了解亚细胞颗粒/结构（如细胞器、囊泡和mRNA）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递送，以便更好地理解疾病和病毒感染至关重要。蛋白质时空迁移率的定量研究对于从实验上理解和验证蛋白质信号传导机制和蛋白质相互作用具有重要意义。该提案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，一个发散过滤器的开发，类似于物理概念，检测定向运动是生物学的重要性。然后，马尔可夫链蒙特卡罗（MCMC）采样框架的多目标跟踪，克服了指数的复杂性问题。最后，在跟踪过程中最佳地选择不同的特征。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基于Web的CellDAS接口，本科生和研究生将在基本的计算机视觉算法，生物数据可视化和形成理解特定感兴趣的生物学问题的培训。此外，PI还将促进和激励科学和工程领域的妇女，并通过女工程师协会的辅导活动和年度高中机器人编程竞赛，激励高中生在这些领域从事职业。

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.