Integrated, Interdisciplinary, Inter-university PHD Program Computational Biology

综合、跨学科、跨大学博士课程计算生物学

基本信息

项目摘要

DESCRIPTION (provided by applicant): This proposal seeks support for an interdisciplinary graduate training program in Computational Biology that has been built under a grant from HHMI in Phase I of the HHMI-NIBIB Interfaces Initiative. The primary goal of that support has been the careful development and evaluation of new curriculum and procedures for the program. This goal has been thoroughly met, and the program has grown to include over 40 students. It is a truly joint program between Carnegie Mellon University (CMU) and the University of Pittsburgh (Pitt), with a single point of admissions for students and equal representation of the two universities in all committees and administration. It has brought together the world-class strengths of the two universities in computer science and biomedical research, and has led to new collaborative research efforts and jointly supervised students. A guiding principle of the CMU-Pitt PhD Program in Computational Biology (CPCB) is that all students receive deep training in both computational and natural sciences, and, as appropriate for future educators and researchers in the growing field of computational biology, that they be fully versed in its principles and paradigms. The program has been highly successful at recruiting outstanding U.S. students, and current trainees in the program have already begun to make contributions to the field. An outstanding group of over 40 training faculty from diverse departments and schools at the two universities provide numerous opportunities for cutting-edge thesis projects in well-funded research groups. The program has the unqualified support of the administrations of both universities, and builds on the significant infrastructure and faculty investments that have been made in the establishment of the Department of Computational Biology at Pitt and the Lane Center for Computational Biology at CMU. A professionally-managed and thorough plan for evaluation of all aspects of the program on an ongoing basis has been created, and the evaluation efforts during Phase I have led to the identification and solution of problems encountered during that period. Support is requested for ten training slots. While the requested funds will support only a modest fraction of the training grant eligible students enrolled at a given time, it will enable outstanding students who are dedicated to interdisciplinary biological research to receive unique training that will place them among the leaders of this field. RELEVANCE: The funds will contribute to public health by meeting a pressing need throughout the biomedical research field for researchers capable of doing innovative work at the interface of computational and biological sciences. In addition to training the specific supported students, the program will aid in the development of novel teaching materials and practices of benefit to other training programs in computational biology.
描述(由申请人提供):该提案寻求支持计算生物学的跨学科研究生培训计划,该计划是在HHMI-NIBIB接口计划第一阶段的HHMI资助下建立的。这种支持的主要目标是认真制定和评估新的课程和方案程序。这一目标已经完全实现,该计划已发展到包括40多名学生。这是卡内基梅隆大学(CMU)和匹兹堡大学(皮特)之间的一个真正的联合计划,学生的单点招生和两所大学在所有委员会和行政部门的平等代表权。它汇集了两所大学在计算机科学和生物医学研究方面的世界级优势,并带来了新的合作研究努力和共同监督的学生。CMU-Pitt计算生物学博士课程(CPCB)的指导原则是所有学生都接受计算和自然科学的深入培训,并且,对于未来的教育工作者和研究人员来说,在计算生物学不断发展的领域,他们完全精通其原理和范式。该计划在招募优秀的美国学生方面非常成功,目前该计划的学员已经开始为该领域做出贡献。来自两所大学不同部门和学校的40多名培训教师组成的优秀团队为资金充足的研究小组提供了许多尖端论文项目的机会。该计划得到了两所大学行政部门的无条件支持,并建立在皮特计算生物学系和CMU计算生物学莱恩中心的建立中所做的重大基础设施和教师投资的基础上。已经制定了一个由专业人员管理的全面计划,以持续不断地对方案的各个方面进行评估,第一阶段的评估工作已导致查明和解决这一期间遇到的问题。请求为10个培训时段提供支助。虽然所要求的资金将只支持在特定时间入学的符合培训补助金条件的学生的一小部分,但它将使致力于跨学科生物研究的优秀学生能够接受独特的培训,使他们成为该领域的领导者。 相关性:这些资金将通过满足整个生物医学研究领域对能够在计算科学和生物科学的界面上进行创新工作的研究人员的迫切需求,为公共卫生做出贡献。除了培训特定的支持学生,该计划将有助于开发新的教学材料和有益于计算生物学其他培训计划的实践。

项目成果

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PANAGIOTIS V BENOS其他文献

PANAGIOTIS V BENOS的其他文献

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{{ truncateString('PANAGIOTIS V BENOS', 18)}}的其他基金

COPD SUBTYPES AND EARLY PREDICTION USING INTEGRATIVE PROBABILISTIC GRAPHICAL MODELS R01HL157879
使用集成概率图形模型进行 COPD 亚型和早期预测 R01HL157879
  • 批准号:
    10705838
  • 财政年份:
    2022
  • 资助金额:
    $ 29.57万
  • 项目类别:
COPD SUBTYPES AND EARLY PREDICTION USING INTEGRATIVE PROBABILISTIC GRAPHICAL MODELS R01HL157879
使用集成概率图形模型进行 COPD 亚型和早期预测 R01HL157879
  • 批准号:
    10689580
  • 财政年份:
    2022
  • 资助金额:
    $ 29.57万
  • 项目类别:
Interpretable graphical models for large multi-modal COPD data (R01HL159805)
大型多模态 COPD 数据的可解释图形模型 (R01HL159805)
  • 批准号:
    10689574
  • 财政年份:
    2021
  • 资助金额:
    $ 29.57万
  • 项目类别:
COPD SUBTYPES AND EARLY PREDICTION USING INTEGRATIVE PROBABILISTIC GRAPHICAL MODELS
使用综合概率图模型进行慢性阻塞性肺病亚型和早期预测
  • 批准号:
    10206417
  • 财政年份:
    2021
  • 资助金额:
    $ 29.57万
  • 项目类别:
Interpretable graphical models for large multi-modal COPD data (R01HL159805)
大型多模态 COPD 数据的可解释图形模型 (R01HL159805)
  • 批准号:
    10705824
  • 财政年份:
    2021
  • 资助金额:
    $ 29.57万
  • 项目类别:
Mapping Age-Related Changes in the Lung
绘制肺部与年龄相关的变化
  • 批准号:
    10440882
  • 财政年份:
    2019
  • 资助金额:
    $ 29.57万
  • 项目类别:
Mapping Age-Related Changes in the Lung
绘制肺部与年龄相关的变化
  • 批准号:
    10020437
  • 财政年份:
    2019
  • 资助金额:
    $ 29.57万
  • 项目类别:
Mapping Age-Related Changes in the Lung
绘制肺部与年龄相关的变化
  • 批准号:
    10473606
  • 财政年份:
    2019
  • 资助金额:
    $ 29.57万
  • 项目类别:
Systems Biology of Diffusion Impairment in HIV
HIV扩散损伤的系统生物学
  • 批准号:
    9753361
  • 财政年份:
    2018
  • 资助金额:
    $ 29.57万
  • 项目类别:
Systems Biology of Diffusion Impairment in HIV
HIV扩散损伤的系统生物学
  • 批准号:
    10188612
  • 财政年份:
    2018
  • 资助金额:
    $ 29.57万
  • 项目类别:

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