DEVELOPMENT OF ONLINE COMPUTATIONAL GENOMICS SPECIALIZATION

在线计算基因组学专业的发展

• 批准号: 10353428
• 负责人: Pavel A Pevzner
• 金额: $ 14.96万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-05-08 至 2025-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10353428
• 关键词: Address; Algorithms; Big Data; Bioinformatics; Biological; Biological Sciences; Biomedical Research; Bypass; Communities; Computational Biology; DNA sequencing; Data Analyses; Data Set; Development; E-learning; Education; Educational Curriculum; Event; Exposure to; Funding Opportunities; Genomics; Goals; Individual; Journals; Learning; Methods; Modernization; Paper; Patient Recruitments; Problem Solving; Publishing; Research Personnel; Research Project Grants; Resources; Scientist; Software Tools; Students; Textbooks; Time; Underrepresented Minority; United States National Institutes of Health; Universities; Work; biological research; cost; education research; experience; experimental study; genomic data; innovation; instructor; online resource; pedagogy; professor; response; science education; skills; symposium; tool

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.

项目摘要 在现代生物学研究中，计算已成为生物学的组成部分 大数据（BBD）分析，但是计算中的教育尚未完全纳入生活 科学教育：许多生物学家对计算基因组学进行了稀释治疗 提出了该领域中心的方法，只不过是工具包。教学 挑战计算基因组学课程的发展是需要传达的 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基因组软件工具以及在 同时，了解这些工具的工作原理，这种情况通常在现有 课程。 我们认为，高质量的在线计算基因组学教育提供了特别的 解决问题的有吸引力的解决方案，因为许多大学未能解决这个问题 挑战。它提供了承诺的教学创新，因为它没有取代任何东西，而是 而是满足重要需求。它绕过了对大规模课程改革的需求 单个大学的水平，而是适应高质量的开放在线资源 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） 将根据相同的NIH资助机会公告而开发 最大化基因组学研究教育。” 我们已经发表了流行的生物信息学和算法教科书，已发表论文 关于信誉良好的期刊计算生物学教育的各种挑战，交付了 TEDX关于在线教育的演讲，成立了一场专门从事生物信息学教育的会议 （重梳），在生物信息学方面开发了多个成功的MOOC（包括第一个） 生物信息学MOOC），并为Rosalind的开发提供了建议，Rosalind是一个开放的在线平台 通过解决问题的解决生物信息学通过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，涵盖了 现代计算基因组学中的广泛主题，（2）使用开发的MOOC进行 竞争性地将参与者招募到拟议的离线计算基因组学简短 课程并将代表性不足的少数群体带入这些事件，（3）建立 计算基因组学教育联盟，一个教育工作者社区，将有助于发展 开放，高质量的模块化在线内容，并在我们的年度课程中担任讲师。