Tri-Institutional Training Program in Computational Biology & Medicine

计算生物学和医学三机构培训计划(CBM)利用纽约州伊萨卡的康奈尔大学、纽约市的威尔·康奈尔医学院和斯隆-凯特琳研究所(斯隆-凯特琳癌症纪念中心的研究机构)优秀的教育和研究资源，培训计算生物学家，使他们掌握解决生物学和医学所特有的复杂问题所需的跨学科方法。CBM培训环境旨在应对在这一领域培训科学家的独特挑战，其特点是：(1)定量和生物科学的课程工作；(2)研究轮换，以便能够充分了解论文主题；(3)期刊俱乐部和正在进行的系列研究，以加强计划的凝聚力，确保相关学科的流畅性；(4)在各种基础到翻译的计算和实验实验室之一进行论文研究；(5)进行定量和生物指导，以确保培训的平衡和广度；(6)鼓励开展计算/实验混合项目，以促进理论与实验之间的联系。三国联合体对CBM项目的热情支持使该项目每年招收和资助6名学生。然而，现在该项目已经建立得很好，已经进入第六个年头，很明显，它将受益于其最重要的组成部分--优秀学生的增加。为此，这项T32提案的目标是获得资金，将我们的年招生人数增加到9人。这种增长的理由包括：(I)CBM教师对学生的需求未得到满足；(Ii)CBM申请者池足够深，可以在不降低质量或降低录取的国内学生比例的情况下增加申请者；以及(Iii)国家需要培养更多计算生物学家。通过实现这种增长，T32资金将帮助CBM项目实现其使命，即培训下一代科学家使用计算和分析方法，通常与实验和临床研究相结合，以解决生物学中复杂的跨学科问题。

The Tri-lnstitutional Training Program in Computational Biology and Medicine (CBM) takes advantage of the outstanding educational and research resources of Cornell University in Ithaca, NY, the Weill Cornell Medical College in New York City, and the Sloan-Kettering Institute (the research arm of the Memorial Sloan- Kettering Cancer Center) to train computational biologists in the interdisciplinary approaches they need to solve the complex problems that characterize biology and medicine. The CBM training environment is designed to address the unique challenges of training scientists in this area and is characterized by: (i) coursework in both quantitative and biological sciences; (ii) research rotations to enable a well-informed thesis topic selection; (iii) journal clubs and research-in-progress series to enhance program cohesion and ensure fluency in relevant disciplines; (iv) thesis research in one of a diverse array of basic to translational computational and experimental laboratories; (v) both quantitative and biological mentorship in order to ensure training balance and breadth; (vi) encouragement to engage in hybrid computational/experimental projects to foster connections between theory and experiment. The enthusiastic support for the CBM program by the Tri-lnstitutional consortium has enabled the program to enroll and support 6 students annually. However, now that the program is well established and entering its sixth year, it is clear that it would benefit from an increase in its most vital component - outstanding students. To that end, the goal of this T32 proposal is to receive funding to increase our annual admission to 9 students. The justifications for such growth include: (i) an unmet demand by CBM faculty for students; (ii) the CBM applicant pool is deep enough to allow for an increase without either lowering quality or decreasing the percentage of admitted domestic students; and (iii) a national need to train more computational biologists. By enabling such growth, T32 funding would aid the CBM program in achieving its mission of training the next generation of scientist to use computational and analytical methods, often integrated with experimental and clinical studies, to solve complex interdisciplinary problems in biology.