中心法则、字典和函数:使用编程概念模拟生物过程

CourseSource Pub Date : 2023-01-01 DOI:10.24918/cs.2023.24
Jyothi Kumar, Fabio Gomez-Cano, S. W. Hunt, Serena G Lotreck, Davis T Mathieu, McKena L. Wilson, T. Long
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摘要

下一代测序、蛋白质组学和高通量表型等技术已经改变了我们研究生物学的方式。在理解潜在的生物学概念的同时,仍然需要具有计算技能的科学家来分析生物学数据。植物与计算科学综合培训模式(impact)是一个跨学科的培训项目,旨在培养博士生运用计算和数据科学方法来解决植物生物学中的重大挑战。课程的第一门课程,计算植物科学基础,通过小组学习和同伴指导,使用真实世界的数据,重点介绍计算和植物科学的基础知识。这里描述的课程计划是由2019年的impact学员(编写组)制定的,作为后续STEM教学和学习课程的一部分。作者团队合作确定了基础课程中的差距,并将他们在基于证据的教学设计方面的学习应用于开发并随后在课程的下一次迭代(2020年)中教授课程。该课程计划的目标是培养学生运用字典和函数作为计算科学核心工具来回答生物学问题的能力。2020年完成课程的学生报告说,他们有信心能够有效地应用字典和函数,并提供有关修改的反馈,以提高课程效果。这个反馈被整合到本课的迭代版本中。本课程旨在通过使用真实世界的数据向计算机科学家和生物学家教授跨学科的概念,帮助他们弥合差距。
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Central Dogma, Dictionaries, and Functions: Using Programming Concepts to Simulate Biological Processes
Technologies like next-generation sequencing, proteomics, and high-throughput phenotyping have transformed the way we do biology. There is a continued need for scientists with computational skills to analyze biological data while understanding the underlying biological concepts. The Integrated training Model in Plant And ComputaTional Sciences (IMPACTS) is an interdisciplinary training program that trains doctoral students to employ computational and data science approaches to address grand challenges in plant biology. The first course in the curriculum, Foundations in Computational Plant Science , focuses on fundamental knowledge in computational and plant science through group learning and peer instruction while using real-world data. The lesson plan described here was developed by the 2019 cohort of IMPACTS trainees (authoring cohort) as part of a subsequent course on STEM teaching and learning. The authoring cohort collaborated to identify a gap in the Foundations curriculum and applied their learning about evidence-based instructional design to develop and subsequently teach the lesson in the next iteration of the course (2020). The lesson plan’s goal was to develop students’ abilities to apply dictionaries and functions as core tools in computational science to answer biological questions. The 2020 cohort that completed the lesson reported confidence in being able to effectively apply dictionaries and functions and provided feedback about modifications to improve lesson efficacy. This feedback was incorporated in the iterative version of this lesson. This lesson is designed to help bridge the gap between computer scientists and biologists by teaching them interdisciplinary concepts using real-world data.
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