课题基金 / 基金详情

Statistical Methods for Flow Cytometric Data

Statistical Methods for Flow Cytometric Data
流式细胞术数据的统计方法
批准号:
DP0556518
负责人:
Prof Matt Wand
金额:
$20.83万
依托单位国家:
澳大利亚
项目类别:
Discovery Projects
财政年份:
2005
资助国家:
澳大利亚
项目状态:
已结题
起止时间:
2005-01-01 至 2008-12-31

项目摘要

项目成果

Prof Matt Wand的其他基金

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中文摘要
翻译
该项目将帮助澳大利亚各地的流式细胞仪用户。它将有助于促进生物和数学科学家之间的合作。生物学研究是澳大利亚未来的重要组成部分,并且正在变得非常量化。在该项目的过程中,两名博士生将提供面向生物应用的统计学强有力的培训。该项目与将于2004年12月在阿德莱德举行的第八届人类白细胞分化抗原研讨会保持一致,并将有助于防治血细胞癌。该项目还将有助于对浮游生物的研究,为澳大利亚的海洋扇贝产业带来潜在的商业利益。
英文摘要
The project will aid users of flow cytometry throughout Australia. It will help foster collaborations between the biological and mathematical scientists. Biological research is an important part of Australia's future and is becoming very quantitative. During the course of the project, two PhD students will be provided strong training in Statistics geared towards biological applications. The project is aligned with the 8th Human Leucocyte Differentiation Antigen workshop to culminate in Adelaide in December 2004 and will aid the fight against blood cell cancers. The project will also aid research on plankton with potential commercial benefits for Australia's marine scallop industry.
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会议论文
Technology-Driven and Scalable Regression Methodology, Computing and Theory
  • 批准号:
    DP230101179
  • 项目类别:
    Discovery Projects
  • 资助金额:
    $25.15万
  • 财政年份:
    2023
  • 负责人:
    Prof Matt Wand
  • 依托单位:
Fast approximate inference methods: new algorithms, applications and theory
  • 批准号:
    DP180100597
  • 项目类别:
    Discovery Projects
  • 资助金额:
    $26.96万
  • 财政年份:
    2018
  • 负责人:
    Prof Matt Wand
  • 依托单位:
Semiparametric Regression for Streaming Data
  • 批准号:
    DP140100441
  • 项目类别:
    Discovery Projects
  • 资助金额:
    $25.9万
  • 财政年份:
    2015
  • 负责人:
    Prof Matt Wand
  • 依托单位:
Fast approximate inference methods for flexible regression
  • 批准号:
    DP110100061
  • 项目类别:
    Discovery Projects
  • 资助金额:
    $22.93万
  • 财政年份:
    2011
  • 负责人:
    Prof Matt Wand
  • 依托单位:
国内基金
海外基金
Computational Methods for Analyzing Toponome Data