Integrated Interdisciplinary, inter-university PhD Program Computational Biology (T32)

项目摘要 计算生物学在几十年内已经从一个专门的学科转变为最重要的学科之一。 现代生物医学研究背后的重要技术。今天的生物医学没有一个角落 不需要开发和使用先进的计算方法，以及由此产生的模型， 算法和软件已经成为生物技术新进展的重要组成部分， 生物医学的发现。高通量成像，高通量测序，代谢组学， 结构建模，网络建模，遗传关联测试，以及许多其他变革性的 今天的技术主要依赖于先进的计算技术和研究人员， 在这个领域进行设计和创新。对计算进步的需求只会加速，因为数据 洪水变得越来越严重，处理TB到PB级的数据集成为甚至 小型实验室进行常规研究。 卡内基梅隆大学-匹兹堡大学计算生物学博士课程（CPCB） 该研究所的成立是为了满足该领域对受过计算生物学培训的专家的迫切需求。该计划旨在 准备计算生物学的未来领导者：研究科学家与计算的深入了解 理论，生物和物理科学，以及越来越多的专业跨学科知识， 这些领域的交集。为了实现这一目标，该计划利用其两个主机的共同优势 机构，集体在计算机科学，工程和医学研究与长期跟踪世界领导者 计算生物学研究和教育的创新记录。培训计划包括一个 创新的课程，涵盖计算生物学的基础知识，以及大量的高级选修课程。 课程跨越计算生物学研究的许多领域。论文研究发生在任何 许多实验室处于计算和数据驱动生物学的前沿。课程和论文 研究得到了机制的补充，以促进学生的成功，促进专业发展， 鼓励负责任地开展研究，并帮助招募和留住代表性不足的群体。 我们寻求在更广泛的CPCB研究生课程的学生的选择子集更新支持。它将 为最有前途的学生提供两年的研究支持，增加资源和灵活性， 追求最创新的研究。进入第14个年头，该计划的学员有一个良好的记录 成功的毕业生已获得教师职位，在顶级研究实验室的博士后职位， 在生物医学和健康相关公司的顶级公司担任研究职位。更新建议 包括课程设计，专业发展培训和学生参与的新创新， 方案治理。 !

Project Summary Computational biology has in a few decades transformed from a specialized discipline to one of the most important enabling technologies behind modern biomedical research. There is no corner of biomedicine today that does not require the development and use of advanced computational methods, and the resulting models, algorithms, and software have become an essential component of new advances in biotechnology and the biomedical discovery they enable. High-throughput imaging, high throughput sequencing, metabolomics, structure modeling, network modeling, genetic association testing, and a host of other transformative technologies today depend critically on advanced computational technologies and on researchers able to design and innovate in this area. The need for advances in computation is only accelerating, as the data deluge becomes ever more acute and dealing with terabyte to petabyte datasets becomes the norm for even small laboratories doing routine studies. The Carnegie Mellon University – University of Pittsburgh PhD Program in Computational Biology (CPCB) was created to meet the field's pressing need for experts trained 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 host institutions, collectively world leaders in computer science, engineering, and medical research with long track records of innovation in computational biology research and education. The training program includes an innovative curriculum covering fundamentals of computational biology, and a large body of advanced elective coursework spanning many areas of computational biology research. Thesis research takes place in any of numerous laboratories at the cutting edge of computational and data-driven biology. Coursework and thesis research are supplemented by mechanisms to facilitate student success, promote professional development, encourage responsible conduct of research, and aid in recruiting and retaining underrepresented groups. We seek to renew 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, added resources, and flexibility to pursue the most innovative research. Entering its 14th year, the program’s trainees have a proven track record of success. Graduates have attained faculty positions, postdoctoral positions in top research labs, and research positions at top companies in biomedical and health-related companies. The renewal proposal includes new innovations in curriculum design, professional development training, and student participation in program governance. !