Predoctoral Training Program in Bioinformatics and Computational Biology

生物信息学和计算生物学博士前培训项目

• 批准号: 10436773
• 负责人: Timothy C Elston
• 金额: $ 26.02万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-01 至 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10436773
• 关键词: Bioinformatics; Computational Biology; Training Programs; pre-doctoral

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.

基于统计、数学和机器学习原理的计算方法