# The University of Iowa IMSD: Iowa Biosciences Academy

> **NIH NIH R25** · UNIVERSITY OF IOWA · 2020 · $85,119

## Abstract

PROJECT SUMMARY
Bioinformatics and computational skills are no longer “elective” but must be part of the core competency for the
next generation of biomedical researchers. However, existing curricula on these areas have significant
deficiencies, including a lack of introductory, biology-focused courses that are suitable for undergraduate
biology majors and graduate students in the biological disciplines, and a lack of emphasis on good
computational practices that ensure robust and reproducible computational studies. This proposal supplement
describes strategies. This proposal supplement describes strategies for building on existing curricula at the
University of Iowa to quickly generate courses that will help students at every level become knowledgeable,
articulate and facile in manipulating large biomedical datasets to extract meaningful insights. Aim 1 concerns
adapting a newly deployed semester-length course called “Introduction to Scientific Computing” which includes
topics such as reproducibility in computational projects, version control, command-line interface, remote
computing, and general and statistical programming to a 4-6 week long summer workshop format. The
summer workshop format makes the course available to a broader community, which includes undergraduate
students from the UI IMSD program, nearby 4-year colleges doing research in the summer at the university,
high school students and teachers in the local area seeking to gain skills in computational research. Aim 2
concerns expansion of an existing Introductory level Bioinformatics course to incorporate hands-on
manipulation, analysis and graphic visualization of multiple genome/transcriptome sized datasets pertinent to
the biological theme of the course in any given semester. A second goal of Aim 2 is to develop a course
pipeline in which genomic and transcriptomic data is generated in-house, allowing students the opportunity to
bring biomedically relevant datasets from their raw format through the steps needed to generate value-added
conclusions. Fungal genomes have been selected for this purpose based on their relatively small genome size,
compelling biological diversity and estimated 1.5 million species, 300 of which can cause primary or
opportunistic infections in humans and only a fraction of which currently have publicly available genome
sequences. Fungi are also involved in the industrial processing of many of the most profitable products used in
human medicine. For example, some members of the Penicillium genus produce the antibiotic, penicillin. In
summary, these aims create a cadre of UI students with the qualifications and ambitions to pursue careers
involving analysis of biomedical datasets so central to the future of health and medicine in today's challenging
environment.

## Key facts

- **NIH application ID:** 10145902
- **Project number:** 3R25GM058939-19S1
- **Recipient organization:** UNIVERSITY OF IOWA
- **Principal Investigator:** LORI C ADAMS-PHILLIPS
- **Activity code:** R25 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $85,119
- **Award type:** 3
- **Project period:** 1999-04-01 → 2022-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10145902

## Citation

> US National Institutes of Health, RePORTER application 10145902, The University of Iowa IMSD: Iowa Biosciences Academy (3R25GM058939-19S1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10145902. Licensed CC0.

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