Biomedical Informatics and Data Science Training at Yale

项目总结/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 Mark Gerstein-拥有来自12个部门和5所学校的33名核心教师，总部设在耶鲁大学中心， 医学信息学（YCMI）和计算生物学和生物信息学（CBB）计划在耶鲁大学。的 课程和教师反映了耶鲁大学合作生物医学信息学研究的多样性和深度 环境我们继续将培训重点放在以下信息学和数据科学领域：1）健康 护理/临床信息学，2）转化生物信息学，和3）临床研究信息学。 这次更新的特点是对我们的培训计划进行了关键的改进，包括（1）更新的课程， 学员和教师的评价和反馈，许多新的数据科学，计算机科学， 信息学课程;（2）教师的领导和与大学科学举措，如新的整合 数据科学研究所与相关的生物医学数据科学中心（CBDS）和一个新的硕士 健康信息学科学，所有这些都导致雇用了许多额外的教师，并提供 研究合作的机会。博士前培训主要在耶鲁大学的跨部门 计算生物学和生物信息学（CBB）博士课程。该方案于2002年启动， 拥有超过56位博士学位，其中许多人现在是各自领域的领导者。博士后研究员， 卫生专业或信息学以外的科学领域的博士学位将在以下之一注册： 三个以研究为导向的研究生课程：CBB（攻读硕士或博士学位），临床信息学轨道， 耶鲁大学公共卫生学院健康科学硕士（MHS）学位和健康信息学硕士学位。 已获得信息学或密切相关领域博士学位的博士后培训人员不得 需要信息学或数据科学方面的额外培训。我们的博士后培训的重点涉及定义 一个或两个研究项目，可以独立进行（在教师的监督下），并将 导致出版物和赠款申请。我们计划的总体目标是为所有学员提供 必要的背景和经验，以追求生产性的学术和研究事业在生物医学 信息学和数据科学。每年申请我们课程的人数和质量都在增长， 我们积极努力，以增加在前和博士后学员和核心教师的多样性与不断增长的成功。我们 请求为9名博士前培训生和8名博士后培训生提供支助（包括2名艾滋病毒重点培训生）。我们有一个 教师的核心群体谁是资金充足，高技能和经验丰富的导师和教育工作者。的 耶鲁大学的生物医学信息学和数据科学活动为学员提供了许多工作机会， 跨学科的项目，使用大型生物医学数据集和解决关键的研究问题。

PROJECT SUMMARY/ABSTRACT The Yale Biomedical Informatics and Data Science Training Program—directed by Profs. Cynthia Brandt and Mark Gerstein— with 33 core faculty from 12 departments and five schools, is based in the Yale Center for Medical Informatics (YCMI) and the Computational Biology and Bioinformatics (CBB) Program at Yale. The program and faculty reflect the diversity and depth of Yale’s collaborative Biomedical Informatics research environment. We continue our training focus on the following informatics and data science areas: 1) health care/clinical informatics, 2) translational bioinformatics, and 3) clinical research informatics. This renewal features key enhancements to our training program including (1) an updated curriculum based on the evaluation and feedback of trainees and faculty, with many new data science, computer science, and informatics courses; (2) faculty leadership and integration with university science initiatives such as a new Institute of Data Science with an associated Center for Biomedical Data Science (CBDS) and a new Master of Science in Health Informatics, all of which have resulted in hiring many additional faculty and provided opportunities for research collaborations. Predoctoral training is carried out primarily in Yale’s interdepartmental PhD program in Computational Biology and Bioinformatics (CBB). This program was inaugurated in 2002 and has graduated over 56 PhDs many of whom are now leaders in their respective fields. Postdoctoral fellows with a doctoral degree in the health professions or in an area of science other than informatics will enroll in one of three research-oriented graduate programs: CBB (study for an MS or PhD), the Clinical Informatics track in the Master of Health Science (MHS) degree, and the MS in Health Informatics at the Yale School of Public Health. Postdoctoral trainees who already have a doctoral degree in informatics or a closely related field, may not require additional training in informatics or data science. The focus of our postdoctoral training involves defining one or two research projects which can be carried out independently (under faculty supervision) and that will result in publications and grant applications. The overall goal of our program is to provide all trainees with the necessary background and experience to pursue productive academic and research careers in Biomedical Informatics and Data Science. Each year the number and quality of applicants to our programs have grown and we actively work to increase diversity in Pre and Postdoc trainees and core faculty with growing success. We are requesting support for 9 predoctoral trainees and 8 postdoctoral trainees (including 2 with HIV focus). We have a core group of faculty who are well-funded, highly skilled and experienced as mentors and educators. The Biomedical Informatics and Data Science activities at Yale provide many opportunities for trainees to work on interdisciplinary projects that use large biomedical data sets and tackle key research questions.