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Abstract
Over the past year, biology educators and staff at the U.S. Department of Energy Systems Biology Knowledgebase (KBase) initiated a collaborative effort to develop a curriculum for bioinformatics education. KBase is a free web-based platform where anyone can conduct sophisticated and reproducible bioinformatic analyses via a graphical user interface. Here, we demonstrate the utility of KBase as a platform for bioinformatics education, and present a set of modular, adaptable, and customizable instructional units for teaching concepts in Genomics, Metagenomics, Pangenomics, and Phylogenetics. Each module contains teaching resources, publicly available data, analysis tools, and Markdown capability, enabling instructors to modify the lesson as appropriate for their specific course. We present initial student survey data on the effectiveness of using KBase for teaching bioinformatic concepts, provide an example case study, and detail the utility of the platform from an instructor’s perspective. Even as in-person teaching returns, KBase will continue to work with instructors, supporting the development of new active learning curriculum modules. For anyone utilizing the platform, the growing KBase Educators Organization provides an educators network, accompanied by community-sourced guidelines, instructional templates, and peer support, for instructors wishing to use KBase within a classroom at any educational level–whether virtual or in-person.
Highlights
Modern biology is becoming more reliant on “big data” to answer a range of questions
Topics in bioinformatics have become a key feature of biology curriculum development in recent years (Maloney et al, 2010; Machluf et al, 2017)
When the 2020 global pandemic drastically increased the need for virtual, learn-from-home coursework, bioinformatics provided an attractive option for hands-on experience outside of a traditional wet lab
Summary
Modern biology is becoming more reliant on “big data” to answer a range of questions. The ability to generate or re-analyze large data sets is quickly becoming a mainstay in many areas, from cellular biology to ecosystem ecology. This is especially true for the field of genomics and molecular biology, where large data sets are commonplace. With the rapid growth and free online availability of biological data derived from DNA sequencing technologies, the need for skilled researchers to analyze these data is growing as well (Kodama et al, 2012; Koboldt et al, 2013). Bioinformatics and the techniques used to analyze data advance quickly, and it can be difficult to incorporate the most cutting edge resources into the classroom
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