Predoctoral Training Program in Bioinformatics and Computational Biology

基于统计、数学和机器学习原理的计算方法现在 渗透到生物和生物医学研究的所有领域。推动生物计算爆炸的是 基因组学、蛋白质组学、代谢组学和化学信息学的高通量新技术及其进展 在现代成像中。这些字段中的每一个都会生成复杂的数据集，这些数据集需要计算方法才能 分析和解读。推动计算在生物医学研究中使用的另一个原因是越来越多的 高性能计算，包括图形处理单元(GPU)，可进行深度学习和其他 人工智能在计算上是可行的。因此，对……的需求越来越大 生物医学研究人员，具有科学计算和数据分析方面的专业知识，并接受过统计和 数学建模。为了满足这一需求，北卡罗来纳大学教堂山分校于2007年成立 生物信息学和计算生物学(BCB)博士课程。 BCB课程的使命是培养下一代具有计算能力和 对现代生物和生物医学研究做出重要贡献所需的量化技能。至 要实现这一目标，不仅要求学生接受计算、数学和统计方面的培训 方法，但他们也变得足够精通生物学，并获得所需的技能 多学科团队科学。BCB课程还努力为学生提供专业技能 成功地过渡到生物医学劳动力的职业所必需的。BCB的具体对象 课程是：1)提供生物信息学和计算生物学方法的广泛知识，以及 它们建立在计算、统计和数学基础上，2)在 生物信息学和计算生物学的选定领域，3)培养学生参与协作和 跨学科研究，4)培养学生开发独立研究项目并发现新研究 指导，5)培养口头和书面交流技能，6)为学生提供专业培训 在学术之外的职业机会为学生提供负责任的行为培训 在研究、严谨和可重复性方面。 拟议的T32培训计划将在6名BCB学生的研究生二年级期间支持他们 训练。除了提供教学培训和科学研究机会外，BCB课程 通过赞助“午餐与学习”等活动提供专业培训机会 来自制药和生物技术部门的代表以及与国家中心的“黑客松” 生物科技资讯。北卡罗来纳大学和BCB课程致力于提供 为所有背景的学生提供支持性环境，并为他们提供必要的培训 在学术、政府和企业环境中成功过渡到生物医学研究职业。

Computational approaches based on statistical, mathematical and machine-learning principles are now permeating all areas of biological and biomedical research. Driving this explosion in biological computation are new high-throughput techniques in genomics, proteomics, metabolomics and chemoinformatics, and advances in modern imaging. Each of these fields generates complex data sets that require computational approaches to analyze and interpret. Also driving the use of computing in biomedical research is the increasing availability of high-performance computing, including graphical processing units (GPUs), that make deep learning and other artificial intelligence approaches computationally feasible. As a result, there is an increasing demand for biomedical researchers with expertise in scientific computing and data analytics and trained in statistical and mathematical modeling. To address this need, in 2007 the University of North Carolina at Chapel Hill established the Ph.D. Curriculum in Bioinformatics and Computational Biology (BCB). The mission of the BCB curriculum is to train the next generation of scientists with the computational and quantitative skills required to make important contributions to modern biological and biomedical research. To accomplish this goal, not only requires students receive training in computational, mathematical and statistical approaches, but also that they become sufficiently versed in biology and acquire skills required for multidisciplinary team science. The BCB curriculum also strives to provide students with the professional skills required to successfully transition into careers in the biomedical workforce. The specific objects of the BCB curriculum are to: 1) provide broad knowledge of bioinformatics and computational biology approaches and the computational, statistical and mathematical foundations on which they are built, 2) provide in depth training in a chosen area of bioinformatics and computational biology, 3) train students to participate in collaborative and interdisciplinary research, 4) train students to develop independent research programs and identify new research directions, 5) develop skills in oral and written communication, 6) provide students with professional training opportunities for careers outside of academics and 7) provide students with training in the Responsible Conduct of Research, and in Rigor and Reproducibility. The proposed T32 training program will support 6 BCB students during their second year of graduate training. In addition to providing didactic training and scientific research opportunities, the BCB curriculum provides professional training opportunities by sponsoring events such as “lunch and learn” sessions with representatives from the pharmaceutical and biotechnology sectors and “hackathons” with the National Center for Biotechnology Information. The University of North Carolina and BCB curriculum are committed to providing a supportive environment for students from all backgrounds and providing them with the training needed to successfully transitions to biomedical research careers in academic, governmental and corporate settings.