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Eduomics: a Nextflow pipeline to simulate -omics data for education
Lorenzo Sola1, Davide Bagordo1, Simone Carpanzano1
1Department of Biology and Biotechnology "L. Spallazani", University of Pavia, Pavia, IT-27100, Italy.
Abstract:
Bridging the gap between learning algorithms and biological interpretation remains the central challenge of bioinformatics education. To move students beyond just learning code and acquire higher-order knowledge, educators face a complexity overload when attempting to design realistic learning experiences. Simulating realistic data forces educators to master different tools and dependencies. Existing simulators are built for benchmarking and lack the narrative context essential for teaching interpretation; this limitation prevents a shift from problem-solving to what we believe should be an immersive 'storyline-based learning'. Eduomics facilitates massive scaling: educators can generate hundreds of unique, validated datasets for assessments or tutoring in a matter of hours. By removing barriers to adoption and embedding raw data within a rich clinical context, eduomics offers an accessible, scalable solution to truly innovate bioinformatics education. Eduomics facilitates massive scaling: educators can generate hundreds of unique, validated datasets for assessments or tutoring in a matter of hours. By removing barriers to adoption and embedding raw data within a rich clinical context, eduomics offers an accessible, scalable solution to truly innovate bioinformatics education.
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