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Bioinformatics has become essential for modern life sciences, yet many undergraduate programs lack systematic training that bridges biological inquiry with computational analysis. We designed and implemented a project-oriented, case-based introductory bioinformatics course at Yeshiva College for biology and chemistry majors, most of whom have no prior coding experience. The course emphasizes human disease as a unifying theme and integrates foundational topics—genomic databases, sequencing technologies, sequence alignment, protein structure, statistical analysis in R, and introductory machine learning—with hands-on laboratory exercises in Python, R, PyMOL, and web-based tools. A longitudinal final project requires students to investigate a complex disease of their choice, leverage genome browsers and GWAS resources, examine SNPs and molecular mechanisms, and evaluate therapeutic implications. Over three years, student survey data ( n = 24 respondents; 68% response rate) indicated substantial self-reported gains in bioinformatics skills, high confidence in applying tools, and a strong endorsement of the course's relevance and design. Mapping the curriculum to the Network for Integrating Bioinformatics into Life Sciences Education (NIBLSE) core competencies demonstrates broad coverage across data access, analysis, modeling, and interpretation, and supports this case-based framework as an adaptable instructional model for institutions seeking to introduce bioinformatics early in the life sciences curriculum.
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Carroll et al. (2026) studied this question.
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