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Development of a data science CURE in microbiology using publicly available microbiome datasets by Evelyn Sun; Stephan G. König; Mihai Cirstea; Steven J. Hallam; Marcia L. Graves; David C. Oliver is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.

What is Development of a data science CURE in microbiology using publicly available microbiome datasets about?

Scientific and technological advances within the life sciences have enabled the generation of very large datasets that must be processed, stored, and managed computationally. Researchers increasingly require data science skills to work with these datasets at scale in order to convert information into actionable insights, and undergraduate educators have started to adapt pedagogies to fulfill this need. Course-based undergraduate research experiences (CUREs) have emerged as a leading model for providing large numbers of students with authentic research experiences including data science. Originally designed around wet-lab research experiences, CURE models have proliferated and diversified globally to accommodate a broad range of academic disciplines. Within microbiology, diversity metrics derived from microbiome sequence information have become standard data products in research. In some cases, researchers have deposited data in publicly accessible repositories, providing opportunities for reproducibility and comparative analysis. In 2020, with the onset of the COVID-19 pandemic and concomitant shift to remote learning, the University of British Columbia set out to develop an online

Who reads Development of a data science CURE in microbiology using publicly available microbiome datasets?

Author

Evelyn Sun; Stephan G. König; Mihai Cirstea; Steven J. Hallam; Marcia L. Graves; David C. Oliver

Published

2022

Language

EN

Field

Biochemistry, Genetics and Molecular Biology (Life Sciences)