# RCMI - DATABIO: RCMI Data Analytics and Training for Bioinformatics, Machine Learning, and Health Disparity in Texas Southern University

> **NIH NIH U54** · TEXAS SOUTHERN UNIVERSITY · 2024 · $380,631

## Abstract

RCMI - DATABIOM: RCMI Data Analytics and Training for Bioinformatics, Machine
Learning in Health Research
Abstract
Texas Southern University (TSU), one of the largest Historically Black Colleges and Universities
in the United States, is in Houston, Texas, one of the most diverse cities in the United States. The
rapid growth of biomedical data necessitates innovative approaches to harness its potential for
precision medicine, drug discovery and development, disease diagnosis and prediction and more.
This project proposes a comprehensive framework that combines advanced data analytics
techniques with targeted training programs to develop proficiency in data science, bioinformatics,
and machine learning to enhance institutional data science competencies on TSU campus and build
institutional partnership. The overarching aim is to enhance TSU's institutional data science and
research capabilities and foster institutional partnerships. Our specific aims include; 1) Enhance
Human Capital Through Data Science Skills. Enhance TSU’s institutional data science and
computational capacity by providing a variety of training and educational initiatives aimed at
improving the data science skills of faculty, staff (including postdoctoral fellows), and students
(undergraduate and postgraduate) lacking expertise in data-related fields. These training will
include, but are not limited to: i) Integrated data analysis – employ innovative data analytics and
bioinformatics techniques to integrate diverse datasets, including genomic, pharmacological,
clinical, and health disparity information, ii) Machine learning/artificial intelligence (ML/AI) -
establish specialized training programs to empower researchers, faculty, staff, and students with
the skills required to navigate and leverage ML/AI tools effectively, iii) Public health data analysis
- Utilize existing public health datasets in program training to evaluate health disparities and allow
for hands-on training with relevant data. 2) Establish Collaborative Data Science
Partnerships. Establish strategic partnerships to advance the identity of data science and foster
fair data practices via cooperative research endeavors. Through the accomplishment of these
specific aims, this project seeks to broaden TSU data science and capacity to advance research
program and ultimately advance the field of data science. We expect that achieving these aims
will expand human capital in the field of data science, enhance TSU’s data science capabilities to
drive research programs forward, forge partnerships to promote the prominence of data science
while advocating for equitable data practices through collaborative research efforts and striving
to enhance the participation of UMCs in biomedical computing and informatics disciplines.

## Key facts

- **NIH application ID:** 11064548
- **Project number:** 3U54MD007605-31S1
- **Recipient organization:** TEXAS SOUTHERN UNIVERSITY
- **Principal Investigator:** Dong Liang
- **Activity code:** U54 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $380,631
- **Award type:** 3
- **Project period:** 1986-09-30 → 2025-09-10

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11064548

## Citation

> US National Institutes of Health, RePORTER application 11064548, RCMI - DATABIO: RCMI Data Analytics and Training for Bioinformatics, Machine Learning, and Health Disparity in Texas Southern University (3U54MD007605-31S1). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/11064548. Licensed CC0.

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