CAREER: Image-Based Computational Methods for Understanding Spatiotemporal Dynamics of Cellular Processes

职业:基于图像的计算方法来理解细胞过程的时空动力学

基本信息

  • 批准号:
    1149494
  • 负责人:
  • 金额:
    $ 80.57万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2012
  • 资助国家:
    美国
  • 起止时间:
    2012-07-01 至 2017-06-30
  • 项目状态:
    已结题

项目摘要

The inner environment of the cell is highly heterogeneous and dynamic yet exquisitely organized. Successful completion of cellular processes within this environment requires the right molecule or molecular complex to function at the right place at the right time. Understanding dynamic spatiotemporal behaviors of cellular processes is therefore essential to understanding at the systems level their molecular mechanisms. The research objective of this project is to extract mechanistic knowledge of cellular processes from images of their spatiotemporal dynamics by developing and applying required computational analysis and modeling methods. The technological development will be driven and guided by fundamental and specific biological questions regarding the spatiotemporal regulation of axonal cargo transport in neuronal cells as well as microtubule and motor translocation in mitotic spindles, which are representatives of cellular processes that are one-dimensional (1D) and two-dimensional (2D) in space, respectively. The specific research aims are: 1) To characterize spatiotemporal cell dynamics by combining single particle tracking with super-resolution imaging techniques; 2) To represent microscopic and macroscopic spatiotemporal dynamics of 1D cellular processes using hidden Markov models and spatiotemporal point process statistics, respectively, and to combine with biophysical modeling to understand patterned axonal cargo movement; and 3) To represent spatiotemporal dynamics of 2D cellular processes via non-rigid shape registration and uniform lattice space partitioning, and to combine with biophysical modeling to understand organized spindle microtubule and motor translocation.Advances in biology over the past half a century have made it possible to identify all the molecular components of a cell. How these components function and interact in space and time to drive specific cellular processes and what general principles govern these processes are fundamental questions to biology. This project will provide computational methods and software that are required to address these questions in a broad range of biological studies. The methods and software will be made freely available to the broader research community. In the meantime, the project will advance and promote teaching and training of computational analysis and understanding of biological images (also referred to as bioimage informatics) at Carnegie Mellon University (CMU), especially for students from engineering, computer science, and biology programs, and from the CMU-University of Pittsburgh joint PhD program in computational biology. Research and educational resources made possible by this project will be used for teaching and training of graduate and undergraduate students and for participating in outreach programs organized by the Department of Biomedical Engineering and the School of Computer Science at CMU.
细胞的内部环境是高度异质性和动态的,但组织得很精致。在这种环境中成功完成细胞过程需要正确的分子或分子复合物在正确的时间在正确的地点发挥作用。因此,了解细胞过程的动态时空行为对于在系统水平上理解其分子机制至关重要。本项目的研究目标是通过开发和应用所需的计算分析和建模方法,从细胞过程的时空动态图像中提取细胞过程的机制知识。技术发展将由基本和具体的生物学问题驱动和指导,这些问题涉及神经元细胞中轴突货物运输的时空调节以及有丝分裂纺锤体中的微管和马达易位,它们分别代表一维(1D)和二维(2D)的空间细胞过程。具体的研究目标是:1)将单粒子跟踪与超分辨率成像技术相结合来表征细胞的时空动力学:2)分别用隐马尔可夫模型和时空点过程统计来表征一维细胞过程的微观和宏观时空动力学,并将联合收割机与生物物理建模相结合来理解模式化的轴突货物运动;(3)通过非刚性形状配准和均匀格点空间划分来表示二维细胞过程的时空动力学,并联合收割机生物物理模型来理解有组织的纺锤体微管和运动易位。这些成分如何在空间和时间中发挥作用并相互作用以驱动特定的细胞过程,以及哪些一般原则支配这些过程是生物学的基本问题。该项目将提供在广泛的生物学研究中解决这些问题所需的计算方法和软件。这些方法和软件将免费提供给更广泛的研究界。与此同时,该项目将推进和促进卡内基梅隆大学(CMU)生物图像(也称为生物图像信息学)的计算分析和理解的教学和培训,特别是对于工程,计算机科学和生物学课程的学生,以及来自CMU-匹兹堡大学计算生物学联合博士课程的学生。该项目所提供的研究和教育资源将用于研究生和本科生的教学和培训,以及参与CMU生物医学工程系和计算机科学学院组织的推广计划。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Ge Yang其他文献

A new fluorescence turn-on assay for trypsin inhibitor screening based on graphene oxide
基于氧化石墨烯的胰蛋白酶抑制剂筛选的新型荧光开启分析
Characterizing Robustness and Sensitivity of Convolutional Neural Networks in Segmentation of Fluorescence Microscopy Images
表征卷积神经网络在荧光显微镜图像分割中的鲁棒性和灵敏度
Insight into the enhancing mechanism of silica nanoparticles on denitrification: Effect on electron transfer and microbial metabolism
深入探讨二氧化硅纳米颗粒的反硝化增强机制:对电子传递和微生物代谢的影响
  • DOI:
    10.1016/j.chemosphere.2022.134510
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    8.8
  • 作者:
    Ying Zhang;Ge Yang;Caicai Lu;Hong Xu;Jiaqi Wu;Ziyuan Zhou;Yuanyuan Song;Jianbo Guo
  • 通讯作者:
    Jianbo Guo
Separation and Recovery of Iron and Nickel from Low-Grade Laterite Nickel Ore Using Reduction Roasting at Rotary Kiln Followed by Magnetic Separation Technique
回转窑还原焙烧磁选技术从低品位红土镍矿中分离回收铁和镍
  • DOI:
    10.1007/s42461-018-0012-z
  • 发表时间:
    2018-10
  • 期刊:
  • 影响因子:
    1.9
  • 作者:
    Gao Lihua;Liu Zhenggen;Pan Yuzhu;Ge Yang;Feng Cong;Chu Mansheng;Tang Jue
  • 通讯作者:
    Tang Jue
The Application of Sheet Technology in Cartilage Tissue Engineering
片材技术在软骨组织工程中的应用
  • DOI:
    10.1089/ten.teb.2015.0189
  • 发表时间:
    2016
  • 期刊:
  • 影响因子:
    6.4
  • 作者:
    Ge Yang;Gong Yi Yi;Xu Zhiwei;Lu Yanan;Fu Wei
  • 通讯作者:
    Fu Wei

Ge Yang的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Ge Yang', 18)}}的其他基金

Collaborative Research: Biological Shape Spaces, Transforming Shape into Knowledge
合作研究:生物形状空间,将形状转化为知识
  • 批准号:
    1052925
  • 财政年份:
    2010
  • 资助金额:
    $ 80.57万
  • 项目类别:
    Standard Grant
Collaborative Research: QSTORM: Switchable Quantum Dots and Adaptive Optics for Super-Resolution Imaging
合作研究:QSTORM:用于超分辨率成像的可切换量子点和自适应光学器件
  • 批准号:
    1052660
  • 财政年份:
    2010
  • 资助金额:
    $ 80.57万
  • 项目类别:
    Standard Grant

相似国自然基金

基于CE-3及IMAGE卫星地球等离子体层EUV探测数据的反演研究
  • 批准号:
    41904148
  • 批准年份:
    2019
  • 资助金额:
    27.0 万元
  • 项目类别:
    青年科学基金项目
Raw-Image微小物体高精度位姿测量法
  • 批准号:
    61105029
  • 批准年份:
    2011
  • 资助金额:
    22.0 万元
  • 项目类别:
    青年科学基金项目

相似海外基金

CAREER: Similarity-based Representation of Large-scale Image Collections
职业:大规模图像集合的基于相似性的表示
  • 批准号:
    1228082
  • 财政年份:
    2012
  • 资助金额:
    $ 80.57万
  • 项目类别:
    Continuing Grant
CAREER: Content-Based Image and Video Coding Using Higher-Level Models of Human Vision
职业:使用人类视觉的高级模型进行基于内容的图像和视频编码
  • 批准号:
    1054612
  • 财政年份:
    2011
  • 资助金额:
    $ 80.57万
  • 项目类别:
    Continuing Grant
CAREER: Learning Models for Scalable Content-Based Image Retrieval
职业:可扩展的基于内容的图像检索的学习模型
  • 批准号:
    0952943
  • 财政年份:
    2010
  • 资助金额:
    $ 80.57万
  • 项目类别:
    Continuing Grant
CAREER: Similarity-based Representation of Large-scale Image Collections
职业:大规模图像集合的基于相似性的表示
  • 批准号:
    0845629
  • 财政年份:
    2009
  • 资助金额:
    $ 80.57万
  • 项目类别:
    Continuing Grant
CAREER: Partial Differential Equation-based Image Processing with Applications to Radiation Oncology
职业:基于偏微分方程的图像处理及其在放射肿瘤学中的应用
  • 批准号:
    0820817
  • 财政年份:
    2007
  • 资助金额:
    $ 80.57万
  • 项目类别:
    Standard Grant
CAREER: Foundations for Ubiquitous Image-Based Appearance Capture
职业:无处不在的基于图像的外观捕捉的基础
  • 批准号:
    0546408
  • 财政年份:
    2006
  • 资助金额:
    $ 80.57万
  • 项目类别:
    Continuing Grant
CAREER: Machine Learning Based Intelligent Image Annotation and Retrieval
职业:基于机器学习的智能图像注释和检索
  • 批准号:
    0347148
  • 财政年份:
    2004
  • 资助金额:
    $ 80.57万
  • 项目类别:
    Continuing Grant
CAREER: A New Approach to Clustering Based on Synchronization of Coupled Oscillators with Application to Content Based Image Retrieval
职业:基于耦合振荡器同步的聚类新方法及其在基于内容的图像检索中的应用
  • 批准号:
    0514319
  • 财政年份:
    2004
  • 资助金额:
    $ 80.57万
  • 项目类别:
    Continuing Grant
CAREER: A New Approach to Clustering Based on Synchronization of Coupled Oscillators with Application to Content Based Image Retrieval
职业:基于耦合振荡器同步的聚类新方法及其在基于内容的图像检索中的应用
  • 批准号:
    0133415
  • 财政年份:
    2002
  • 资助金额:
    $ 80.57万
  • 项目类别:
    Continuing Grant
CAREER: Partial Differential Equation-based Image Processing with Applications to Radiation Oncology
职业:基于偏微分方程的图像处理及其在放射肿瘤学中的应用
  • 批准号:
    0133511
  • 财政年份:
    2002
  • 资助金额:
    $ 80.57万
  • 项目类别:
    Standard Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了