Targeted Infusion Project: Advancing Computational Biology Training for Undergraduate Students at Howard University

The Historically Black Colleges and Universities Undergraduate Program (HBCU-UP) through Targeted Infusion Projects supports the development, implementation, and study of evidence-based, innovative models and approaches for improving the preparation and success of HBCU undergraduate students so that they may pursue science, technology, engineering, or mathematics (STEM) graduate programs and/or careers. The goal of this project is to enhance computational biology training for undergraduate students at Howard University (HU) by integrating computational biology into the curriculum, preparing students for real-world research scenarios, and fostering interdisciplinary skills.

The project aims to advance undergraduate education in computational biology at HU through three primary objectives. First, new advanced Computational Biology courses will be developed, focusing on high-throughput data analysis, machine learning, and genomic evolution, along with practical workshops such as “R in Bioinformatics" and "Python & Biology.” Second, the project will enhance existing biology courses by integrating big data analytics modules, providing students with tools for machine learning and artificial intelligence to solve complex biological questions.

Third, a specialized Image Data Analysis Platform will be established, offering cutting-edge bioinformatics tools and cloud resources for research in cell biology, single-cell sequencing, biomechanics, and neuroscience. This platform will support in-depth image data analysis and skill development. The project will also assess its impact on the advanced computational biology training, improved quantitative skills, enhanced scientific communication, elevated self-efficacy, and the development of a strong scientific identity of students, with the goal of establishing a model program for strengthening computational biology training for underrepresented undergraduates.

By equipping students with these advanced skills, the project will contribute to the field of computational biology and broaden participation in the STEM workforce.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.