DEVELOPMENT OF ONLINE COMPUTATIONAL GENOMICS SPECIALIZATION

项目摘要 在现代生物学研究中，计算已成为生物学中不可或缺的组成部分。 大数据（BBD）分析，但计算教育尚未完全融入生活 科学教育：许多生物学家对计算基因组学进行了稀释处理， 提出的方法中心领域只不过是一个工具包。 教育学 计算基因组学课程开发面临的挑战是需要传达 重要的想法，而不假设以前接触编程。生物学家也会 从了解如何有效地应用各种现有的基因组学软件工具中获益， 同时，了解这些工具是如何工作的，这是现有技术中经常违反的条件。 课程 我们认为，高质量的在线计算基因组学教育提供了一个特别 这是一个很有吸引力的解决方案，因为许多大学都没有解决这个问题。 挑战.它提供了一个有前途的教学创新，因为它不是取代任何东西，但 而是满足一个重要的需求。它回避了在学校进行广泛的课程改革的必要性。 个别大学的水平，而是适应高质量，开放的在线资源， 降低每个学生的成本。我们相信我们提出的在线计算基因组学 专业化将有助于各种离线课程（例如，通过启用翻转课程）， 将响应同一NIH资助机会公告“倡议， 最大化基因组学的研究教育。” 我们出版了流行的生物信息学和算法教科书，发表了论文 在计算生物学教育的各种挑战，在著名的期刊，提供了一个 TEDx关于在线教育的演讲，成立了一个专门从事生物信息学教育的会议 （RECOMB-BE），开发了多个成功的生物信息学MOOC（包括第一个 生物信息学MOOC），并建议开发Rosalind，一个开放的在线平台， 通过解决问题来学习生物信息学，已被100多名教授使用。 我们的目标是（1）开发开放，模块化，可扩展和适应性的MOOC， 现代计算基因组学的广泛主题，（2）使用开发的MOOC， 竞争性地招募参与者进入拟议的离线计算基因组学短 课程，并使代表性不足的少数民族参加这些活动，以及（3）建立 计算基因组学教育联盟，一个教育工作者社区， 开放，高质量，模块化的在线内容，并在我们的年度课程担任讲师。

Project Summary In modern biological research, computing has become an integral component in Biological Big Data (BBD) analysis, yet education in computing has not been fully incorporated into life science education: many biologists are given a diluted treatment of computational genomics that presents the methods central to the field as nothing more than a toolkit. ​The pedagogical challenge facing the development of a computational genomics curriculum is the need to convey the important ideas ​without assuming previous exposure to programming. Biologists would also profit from knowing how to effectively apply various existing genomics software tools and, at the same time, ​understand how these tools work, a condition that is often violated in existing courses. We believe that high-quality online computational genomics education offers a particularly attractive solution to the problem because many universities have failed to address this challenge. It offers a promising pedagogical innovation because it is not ​replacing anything, but rather is fulfilling an important need. It bypasses the need for extensive curricular reform at the level of individual universities and instead adapt to high-quality, open online resources that lower the cost per student. We believe that our proposed online ​Computational Genomics Specialization will contribute to various offline courses (e.g., by enabling a flipped course) that will be developed in response to the same NIH Funding Opportunity Announcement “Initiative to Maximize Research Education in Genomics.” We have published popular bioinformatics and algorithms textbooks, ​have published papers on various challenges of education in computational biology in reputable journals, delivered a TEDx talk on online education, founded a conference specializing in bioinformatics education (RECOMB-BE), developed multiple successful MOOCs in bioinformatics (including the first bioinformatics MOOC), and advised the development of Rosalind, an open online platform for learning bioinformatics through problem solving that has been used by over 100 professors. Our goals are (1) to develop open, modular, extendable, and adaptable MOOCs covering a broad range of topics in modern computational genomics, (2) use the developed MOOCs to competitively recruit the participants into the proposed offline computational genomics short courses and to bring underrepresented minorities to these events, and (3) establish ​the Computational Genomics Education Alliance, a community of educators who will help develop open, high-quality, modular online content and serve as instructors at our annual courses.