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

• 批准号: 8050087
• 负责人: PANAGIOTIS V BENOS
• 金额: $ 35.55万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-04-01 至 2014-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8050087
• 关键词: Computational Biology; Universities; programs

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)：本提案寻求对计算生物学跨学科研究生培训计划的支持，该计划是在HHMI-NIBIB接口计划第一阶段由HHMI提供的赠款下建立的。这种支持的主要目标是认真开发和评估该方案的新课程和程序。这一目标已经完全实现，该项目已经发展到包括40多名学生。这是卡内基梅隆大学(CMU)和匹兹堡大学(PITT)之间真正的联合项目，对学生实行单点招生，两所大学在所有委员会和行政部门都有平等的代表权。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，并导致了新的合作研究努力和联合监督学生。CMU-PITT计算生物学博士项目的指导原则是，所有学生都接受计算和自然科学方面的深入培训，并在适合未来计算生物学不断增长的领域的教育和研究人员的情况下，充分了解计算生物学的原理和范例。该计划在招收优秀的美国学生方面非常成功，目前该计划的实习生已经开始为该领域做出贡献。来自两所大学不同院系的40多名培训教师组成的杰出团队为资金雄厚的研究小组提供了大量前沿论文项目的机会。该计划得到了两所大学管理部门的无条件支持，并建立在皮特大学计算生物学系和芝加哥大学莱恩计算生物学中心的重大基础设施和教师投资的基础上。已经制定了一项由专业人员管理的全面计划，对方案的所有方面进行持续的评估，第一阶段的评估工作已经确定并解决了这一阶段遇到的问题。请求为10个培训时段提供支持。虽然申请的资金将只支持在特定时间录取的培训补助金合格学生的一小部分，但它将使致力于跨学科生物学研究的优秀学生接受独特的培训，使他们跻身该领域的领导者之列。 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之间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。除了培训特定的受资助学生外，该计划还将帮助开发新的教材和实践，对计算生物学的其他培训计划有益。