课题基金 / 基金详情

CAREER: Mathematical Modeling and Computational Tools for in vivo Astrocyte Activity

CAREER: Mathematical Modeling and Computational Tools for in vivo Astrocyte Activity
职业:体内星形胶质细胞活性的数学建模和计算工具
批准号:
1750931
负责人:
Guoqiang Yu
金额:
$52.92万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-06-01 至 2023-05-31

项目摘要

项目成果

相似基金

相关文献

中文摘要
翻译
该项目旨在开发新的计算工具来解释和分析星形胶质细胞的活动。星形胶质细胞是一种胶质细胞,也是大脑中数量最多的细胞,最近发现它具有比之前认为的更活跃的功能。星形胶质细胞密切倾听并主动调节神经系统,但它们在正常和病理大脑中的确切作用仍然难以捉摸。最近的技术进步使得以前所未有的空间和时间分辨率监测星形胶质细胞活动成为可能,但考虑到星形胶质细胞活动数据的复杂性和规模性,严格的计算模型是迫切需要的。该项目将为星形胶质细胞活性的定量分析奠定坚实的基础,使活体分析成为可能,更大的重复性,并有助于了解大脑疾病。该项目中提出的具有计算挑战性的问题预计将对计算机科学的其他领域具有价值,作为建立新的统计模型和开发强大的通用机器学习理论和算法的范例。这项拟议的研究将开发一个全面的数据驱动框架来模拟星形胶质细胞的活动,具体目标是自动检测钙事件,识别功能独立的单位,并表征它们的个体和系统表现。三个研究目标包括:(1)开发检测钙事件的计算方法;(2)星形胶质细胞活性的系统建模和量化;(3)应用于小鼠和其他模型动物体内的星形胶质细胞,通过解决当前几个不同的生物学问题来展示所提出的方法的有效性。教育目标是帮助保持美国计算神经科学劳动力的竞争活力,并加深对核心计算概念的理解,将尖端计算神经科学问题纳入工程课程,通过改善女性和少数族裔学生的招生和留住,通过接触K-12学生来激发他们对这一跨学科领域的兴趣,并通过与本科生的互动提供机会并鼓励他们选择计算神经科学作为职业。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
This project aims to develop new computational tools to interpret and analyze the activity of astrocytes. Astrocytes, one type of glial cells and the most populous cells in brain, have recently been found to have much more active functionality than previously thought. Astrocytes closely listen to and proactively regulate the nervous system, yet their exact roles in normal and pathological brains remain elusive. Recent technological progress makes it possible to monitor astrocyte activity with unprecedented spatial and temporal resolution, but considering the complexity and scale of astrocyte activity data, rigorous computational modeling is critically needed. This project will establish a solid foundation for quantitative analysis of astrocyte activity, enabling in vivo analysis, greater reproducibility, and benefits for understanding brain disorders. The computationally challenging problems formulated in this project are expected to be valuable for other areas of computer science, serving as examples to build new statistical models and develop powerful generic machine-learning theory and algorithms. The proposed research will develop a comprehensive data-driven framework to model astrocyte activity, with the specific goals of automatically detecting calcium events, identifying functional independent units and characterizing their individual and systems manifestation. Three research objectives include: (1) developing computational approaches to detect calcium events (2) systems modeling and quantification of astrocyte activity, and (3) application to in vivo astrocytes of mouse and other model animals to showcase the usefulness of the proposed methodology by addressing several different current biological questions. The educational objective is to help maintain the competitive vitality of the U.S. computational neuroscience workforce, and to deepen the understanding of core computational concepts, by incorporating cutting-edge computational neuroscience problems into the engineering curriculum, by improving the recruitment and retention of women and minority students, by reaching out to K-12 students to inspire their interest in this interdisciplinary field, and by interacting with undergraduate students to offer opportunities and encourage them to choose computational neuroscience as a career.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(5)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1016/j.celrep.2018.06.033
发表时间: 2018-07-10
期刊: Cell reports
影响因子: 8.8
作者: [Mizuno GO, Wang Y, Shi G, Wang Y, Sun J, Papadopoulos S, Broussard GJ, Unger EK, Deng W, Weick J, Bhattacharyya A, Chen CY, Yu G, Looger LL, Tian L]
通讯作者: Tian L
DOI: 10.1109/isbi52829.2022.9761491
发表时间: 2022-03
期刊: 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)
影响因子: --
作者: [Mengfan Wang;Kathleen Whiting;F. Lischka;Z. Galdzicki;Guoqiang Yu]
通讯作者: Mengfan Wang;Kathleen Whiting;F. Lischka;Z. Galdzicki;Guoqiang Yu
SynQuant: an automatic tool to quantify synapses from microscopy images
SynQuant:一种从显微镜图像中量化突触的自动工具
DOI: 10.1093/bioinformatics/btz760
发表时间: 2019
期刊: Bioinformatics
影响因子: 5.8
作者: [Wang, Yizhi, Wang, Congchao, Ranefall, Petter, Broussard, Gerard Joey, Wang, Yinxue, Shi, Guilai, Lyu, Boyu, Wu, Chiung-Ting, Wang, Yue, Tian, Lin]
通讯作者: Tian, Lin
海外基金