Biomedical Informatics and Data Science Training at Yale

耶鲁大学生物医学信息学和数据科学培训

• 批准号: 9531731
• 负责人: CYNTHIA A. BRANDT
• 金额: $ 10万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2018-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9531731
• 关键词: Area; Bioinformatics; Biological Sciences; Clinical; Clinical Informatics; Clinical Research; Computational Biology; Computer Simulation; Data Science; Data Set; Development; Disease model; Doctor of Philosophy; Doctor' s Degree; Educational Curriculum; Enrollment; Environment; Faculty; Goals; Grant; Health Occupations; Health Sciences; Healthcare; Informatics; Interdisciplinary Study; Medical Informatics; Medical center; Mentors; Postdoctoral Fellow; Process; Research; Research Project Grants; Science; Students; Supervision; Training; Training Programs; base; biomedical informatics; career; experience; interest; post-doctoral training; pre-doctoral; programs; translational genomics

PROJECTSUMMARY/ABSTRACT The Yale Biomedical Informatics and Data Science Training Program—directed by Profs. Cynthia Brandt and Michael Krauthammer— is based in the Yale Center for Medical Informatics (YCMI) and other academic units at Yale, reflecting the diversity of Yale’s collaborative Biomedical Informatics research environment. Our training focuses on the following informatics areas: 1) health care/clinical informatics, 2) translational bioinformatics, and 3) clinical research informatics. Active research projects span a broad spectrum, from clinical decision support, to the development of new statistical and bioinformatics approaches in translational genomics, to computational modeling of disease processes. The scope of Biomedical Informatics activities is growing rapidly at Yale, with emerging opportunities in interdisciplinary projects tackling large biomedical data sets. Accordingly, the grant features mentors with expertise in Data Science, a curriculum with an elective focus on Biomedical Data Science, and provides training in interdisciplinary research. Predoctoral training is carried out primarily in Yale’s interdepartmental PhD program in Computational Biology and Bioinformatics (CBB), which was inaugurated in 2003 and recently accepted its fourteenth class of students. Postdoctoral fellows with a doctoral degree in the health professions or in an area of science other than informatics may enroll in one of two research-oriented graduate programs: studying for an MS or PhD degree in CBB or for a Master of Health Science (MHS) degree in Yale's Clinical Informatics Track. For postdoctoral trainees who already have a doctoral degree in informatics or a closely related field, degree training may not be needed or appropriate. Postdoctoral training involves defining one or two research projects which can be carried out independently, under faculty supervision. Depending on their specific backgrounds and interests, postdoctoral fellows are encouraged to take part in in a variety of other activities, including participation in institutional computing activities in both the clinical and bioscience arenas. The overall goal is to provide all trainees with the necessary background and experience that will allow them to pursue productive academic and research careers in Biomedical Informatics and Data Science. We are requesting support for 9 predoctoral trainees and 6 postdoctoral trainees.

项目概要/摘要 耶鲁大学生物医学信息学和数据科学培训计划-由教授指导。辛西娅·勃兰特和 Michael Krauthammer-位于耶鲁大学医学信息学中心（YCMI）和其他学术单位， 耶鲁大学，反映了耶鲁大学的合作生物医学信息学研究环境的多样性。我们的培训 侧重于以下信息学领域：1）医疗保健/临床信息学，2）翻译生物信息学， 3)临床研究信息学 活跃的研究项目涵盖广泛，从临床决策支持，到新的 翻译基因组学中的统计学和生物信息学方法，以及疾病的计算建模 流程.生物医学信息学的活动范围正在耶鲁大学迅速增长，并出现了新的机会 跨学科项目处理大型生物医学数据集。因此，该补助金的特点导师与 数据科学专业知识，选修生物医学数据科学的课程，并提供培训 跨学科研究。博士前培训主要在耶鲁大学的跨部门博士课程中进行 计算生物学和生物信息学（CBB），成立于2003年，最近接受了 第十四届学生。在卫生专业或某一领域获得博士学位的博士后研究员 信息学以外的科学可以参加两个研究型研究生课程之一： CBB硕士或博士学位或耶鲁临床信息学专业的健康科学硕士（MHS）学位。 对于已经获得信息学或密切相关领域博士学位的博士后学员， 培训可能不需要或不适当。博士后培训包括确定一个或两个研究项目 可以在教师的监督下独立进行。根据他们的具体背景， 兴趣，鼓励博士后研究员参加各种其他活动，包括参与 临床和生物科学领域的机构计算活动。总体目标是提供所有 具有必要背景和经验的受训人员，使他们能够从事富有成效的学术和 生物医学信息学和数据科学的研究生涯。我们正在申请9名博士预科生的支持 实习生和6名博士后。