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Stochastic methods in chemistry and biophysics

Stochastic methods in chemistry and biophysics
化学和生物物理学中的随机方法
批准号:
1153096
负责人:
Frank Brown
金额:
$56.92万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-06-01 至 2016-05-31

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中文摘要
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英文摘要
Frank Brown of the University of California, Santa Barbara is supported by an award from the Chemical Theory, Models and Computational Methods program within the Division of Chemistry (MPS/CHE) and the Division of Molecular and Cellular Biology (BIO/MCB) for the development of theoretical tools to model lipid bilayers and biomembranes for use in simulating complex biochemical and biophysical phenomena. Dr. Brown's algorithms allow hydrodynamically and thermodynamically consistent modeling of inhomogeneous membrane surfaces over a range of "mesocopic" length scales (tens of nanometers to tens of microns) and time scales (tens of nanoseconds to tens of seconds and longer). The research is having a broad impact on the interpretation of experiments that enhance our understanding of biological phenomena such as the diffusion of membrane proteins in complex cellular environments and the structure and dynamics of human red blood cells. Dr. Brown communicates the excitement and importance of science to grade school children through his participation in the Physics Circus and Chemistry Outreach programs at UCSB. Dr. Brown also serves as co-director of the UCSB center for scientific computing, which oversees and maintains shared scientific computing facilities for the UCSB campus, for use in both research and classroom teaching.
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Theoretical methods in chemistry and biophysics
MRI: Acquisition of a High Performance Central Computing Facility at University of California Santa Barbara
Theoretical methods in chemistry and biophysics
MRI-R2: Acquisition of a high performance central computing facility at UCSB
国内基金
海外基金
复杂图像处理中的自由非连续问题及其水平集方法研究
  • 批准号:
    60872130
  • 项目类别:
    面上项目
  • 资助金额:
    28.0万元
  • 批准年份:
    2008
  • 负责人:
    刘国才
  • 依托单位:
Computational Methods for Analyzing Toponome Data