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

职业：用于细胞动力学研究的四维亚细胞结构跟踪和建模

• 批准号: 0546605
• 负责人: Jean Gao
• 金额: $ 43.82万
• 依托单位: University of Texas at Arlington
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-01-01 至 2012-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0546605&HistoricalAwards=false
• 关键词: CAREER; Four; Dimensional; Subcellular; Structure

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.

生物学的新发现要求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、囊泡和mrna，对于理解细胞如何调节特定蛋白质从合成位点到作用位点的传递，从而更好地理解疾病和病毒感染至关重要。定量的蛋白质时空迁移研究在实验上理解和验证蛋白质信号机制和蛋白质-蛋白质相互作用具有重要作用。该提案的目标是开发一个独特的、第一个基于网络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、跟踪和迁移分析。首先，开发了一个发散滤波器，类似于物理概念，以检测具有生物学重要性的定向运动。然后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，在跟踪过程中选择最优的特征。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。通过访问拟议的基于web的开放访问CellDAS接口，本科生和毕业生将获得基本计算机视觉算法，生物数据可视化和对特定感兴趣的生物学问题的形成理解的培训。此外，PI将通过女性工程师协会（SWE）的指导活动和年度高中机器人编程竞赛，促进和激励科学和工程领域的女性，并激励高中生在这些领域从事职业。