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: 8866399
• 负责人: PANAGIOTIS V BENOS
• 金额: $ 24.98万
• 依托单位: CARNEGIE-MELLON UNIVERSITY
• 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 2019-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8866399
• 关键词: Computational Biology; Universities; programs

DESCRIPTION (provided by applicant): The practice of biomedical research has undergone dramatic changes in recent years, largely driven by new biotechnology for high-throughput data generation. These technologies include high-throughput methods for imaging, genetic sequencing, proteomics, structure determination, and numerous other tasks that now make it possible to finely characterize numerous aspects of living systems from the molecular to the organismal levels. These advances in biotechnology and the vast amounts of data they are producing have revolutionized biomedical research. They have also, however, created a pressing need for scientists capable of working in a field that is increasingly data-driven and dependent on advanced computational methods. In particular, modern biomedical research depends on a new breed of computationally and mathematically sophisticated researchers who can understand new biotechnologies, develop innovative mathematical models and computer algorithms needed to make sense of their data, and apply this knowledge to drive biological and medical advances. To do so, these researchers require a strong command of computational science, the biomedical applications on which they work, and the biological and physical sciences that inform them. The Carnegie Mellon University/University of Pittsburgh Ph.D. Program in Computational Biology (CPCB) was created to meet this need for training experts in computational biology. The program aims to prepare the future leaders of computational biology: research scientists with deep knowledge of computational theory, biological and physical sciences, and a growing body of specialized interdisciplinary knowledge at the intersection of these areas. To accomplish this, the program leverages the shared strengths of its two hosts institutions, collectively world leaders in computer science, engineering, and medical research with long track records of innovation in computational biology research and educational. The training program includes an innovative curriculum covering fundamentals of computational biology, broadly defined, and a large body of advanced elective coursework spanning four broad domains of computational biology research: bioimage informatics, cellular and systems modeling, computational genomics, and computational structural biology. Program students perform thesis research in any of numerous laboratories at the cutting edge of computational biology research. These primary components of coursework and thesis research are supplemented by numerous mechanisms to facilitate student success, promote professional development, encourage responsible conduct of research, and aid in recruiting and retaining underrepresented groups. The proposed program seeks to renew training support for a select subset of students in the broader CPCB graduate program. It will provide the most promising students with two years of research support, providing them added resources and flexibility to pursue the most innovative research directions and to aid in their development into future leaders of computational biology and biomedical research as a whole.

描述（由申请人提供）：近年来，生物医学研究的实践发生了巨大的变化，这主要是由用于高通量数据生成的新生物技术推动的。这些技术包括用于成像、基因测序、蛋白质组学、结构测定和许多其他任务的高通量方法，这些技术现在使得可以精细地表征从分子到有机体水平的生命系统的许多方面。生物技术的这些进步及其产生的大量数据彻底改变了生物医学研究。然而，它们也迫切需要能够在数据驱动和依赖先进计算方法的领域工作的科学家。特别是，现代生物医学研究依赖于新一代计算和数学复杂的研究人员，他们能够理解新的生物技术，开发理解其数据所需的创新数学模型和计算机算法，并应用这些知识来推动生物和医学进步。为此，这些研究人员需要对计算科学、他们所从事的生物医学应用以及为他们提供信息的生物和物理科学有很强的掌握。 卡内基梅隆大学/匹兹堡大学博士计算生物学项目（CPCB）的创建是为了满足培养计算生物学专家的需求。该项目旨在培养计算生物学的未来领导者：具有计算理论、生物和物理科学深厚知识的研究科学家，以及在这些领域交叉领域不断增长的专业跨学科知识。为了实现这一目标，该项目利用了两个主办机构的共同优势，这两个机构都是计算机科学、工程和医学研究领域的世界领导者，在计算生物学研究和教育方面拥有长期的创新记录。该培训计划包括涵盖广泛定义的计算生物学基础知识的创新课程，以及涵盖计算生物学研究四大领域的大量高级选修课程：生物图像信息学、细胞和系统建模、计算基因组学和计算结构生物学。项目学生在计算生物学研究前沿的众多实验室中的任何一个进行论文研究。课程作业和论文研究的这些主要组成部分得到了许多机制的补充，以促进学生的成功，促进专业发展，鼓励负责任的研究行为，并帮助招募和留住代表性不足的群体。 拟议的计划旨在为更广泛的 CPCB 研究生计划中的部分学生提供新的培训支持。它将为最有前途的学生提供两年的研究支持，为他们提供更多的资源和灵活性，以追求最具创新性的研究方向，并帮助他们发展成为计算生物学和生物医学研究的未来领导者。