Statistical and Computational Methods for Data Management and Analysis in Molecular Genetics

分子遗传学数据管理和分析的统计和计算方法

• 批准号: 9413215
• 负责人: Warren Ewens
• 金额: $ 159.26万
• 依托单位: University of Pennsylvania
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1994
• 资助国家: 美国
• 起止时间: 1994-10-01 至 2001-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9413215&HistoricalAwards=false
• 关键词: Statistical; Computational; Methods; Data; Management

9413215 Ewens This award provides support for an interdisciplinary training program in computational aspects of modern genetics. Topical areas include algorithm development, molecular evolution, sequence alignment, statistical inference, and other aspects of biological informatics. These areas are central to one of the most multidisciplinary approaches to modern biology. The faculty group includes 19 investigators from the departments of computer and information science in the school of engineering, the departments of mathematics and biology in the school of arts and sciences, and the departments of genetics and human genetics in the school of medicine. The group includes junior and senior investigators, several of international reputation. The training program will center around 8 new or existing core, additional new elective courses, a journal club and seminars. Students are expected to enter with backgrounds in computer science, mathematics or biology. Training will emphasize molecular biology, and genetics, computer science, statistics and probability, but will be tailored to the needs of individual students and an optional industrial internship program is planned. This award is also being supported by the Computational Biology Activity and by the Database Activity in the Biological Science, both in the Division of Biological Instrumentation and Resources. ***

9413215 evens该奖项为现代遗传学计算方面的跨学科培训计划提供支持。主题领域包括算法开发、分子进化、序列比对、统计推断和生物信息学的其他方面。这些领域是现代生物学最多学科方法之一的核心。教师小组包括19名研究人员，他们分别来自工程学院计算机与信息科学系、文理学院数学系和生物系，以及医学院遗传学系和人类遗传学系。该小组包括初级和高级调查员，其中几人享有国际声誉。培训计划将围绕8个新的或现有的核心课程，额外的新选修课程，期刊俱乐部和研讨会。学生应具备计算机科学、数学或生物学背景。培训将着重于分子生物学、遗传学、计算机科学、统计学和概率论，但也将根据学生个人的需要进行调整，并计划一个可选的工业实习项目。该奖项还得到了生物仪器和资源部门计算生物学活动和生物科学数据库活动的支持。＊＊＊