Enhancing Quantitative and Data Science Education for Graduate Students in Biomedical Science

Abstract

Substantial guidance is available on undergraduate quantitative training for biologists, including reports focused on biomedical science, but far less attention has been paid to the graduate curriculum. In this setting, we propose an innovative approach to quantitative education that goes beyond recommendations of a course or set of courses or activities. Due to the diversity of quantitative methods, it is infeasible to expect that biomedical PhD students can be exposed to more than a minority of the quantitative concepts and techniques employed in modern biology. We developed a novel prioritization approach in which we mined and analyzed quantitative concepts and skills from publications that faculty in relevant units deemed central to the scientific comprehension of their field. The analysis provides a prioritization of quantitative skills and concepts and could represent an effective method to drive curricular focus based upon program-specific faculty input for biological science programs of all types. Our results highlight the disconnect between typical undergraduate quantitative education for life science students, focused on continuous mathematics, and the concepts and skills in graphics, statistics, and discrete mathematics that arise from priorities established by biomedical science faculty. One Sentence SummaryWe developed a novel approach to prioritize quantitative concepts and methods for inclusion in a graduate biomedical science curriculum based upon approaches included in faculty-identified key publications.