# Core 06: Biomedical Informatics Core

> **NIH NIH U54** · LSU PENNINGTON BIOMEDICAL RESEARCH CTR · 2022 · $276,877

## Abstract

Project Summary: Biomedical Informatics Core 
The overall goal of the Biomedical Informatics (BMI) Core of the Louisiana Clinical and Translational Science 
Center (LA CaTS) is to build on our accomplishments and continue to develop and deploy “state of the art” 
informatics services to LA CaTS investigators. During the current funding period, the BMI Core provided 
significant support to 27 LA CaTS Investigators across 14 institutions, resulting in 46 publications and 18 funded 
grant applications. The BMI Core constructed 12 “virtual cohorts”, which were used in 30 projects leading to 3 
major NCI grant awards. We created the data infrastructure for 3 “virtual biorepositories” and provided the 
informatics backbone for the participation of LA CaTS in the NIH “All of Us” research program and the National 
COVID-19 Cohort Collaboration (N3C). The BMI Core contributed to the LA CaTS response to the COVID-19 
pandemic in multiple ways: 1) Supported 2 multi-CTR N3C projects exploring the relationship of drug exposures 
and rurality with COVID-19 outcomes; 2) Provided the informatics infrastructure for 2 epidemiological studies of 
SARS-CoV-2 seroprevalence and virus testing; and 3) Supported 3 projects on SARS-CoV-2 variant sequencing 
in Louisiana. The BMI Core also supported the COBRE Center for Translational Viral Oncology and served an 
invaluable role in the close collaboration between LA CaTS and the University of Alabama at Birmingham (UAB)- 
led Center for Clinical and Translational Sciences (CCTS), as well as the UAB-led, NIMHD-funded Obesity and 
Health Disparity Research Center. Our commitment to building a diverse pipeline of translational data scientists 
led to a) the first Master of Science program in Bioinformatics in Louisiana, and b) the expansion of Core 
personnel to include 3 early-stage investigators. During the next funding period, the BMI Core will expand its 
mission to include integrative clinical and bioinformatics, machine learning/artificial intelligence, access to 
national and regional clinical databases, individualized mentorship, didactics, as well as community stakeholder 
and citizen scientist support. In cycle 3 we will pursue three important specific aims. Aim 1. Provide training and 
enhance utilization of high-resolution bioinformatics and artificial intelligence/machine learning algorithms. Aim 
2. Expand our existing support for collaboration and data sharing within LA CaTS Cores and between LA CaTS 
investigators and CTSA Centers, as well as with Centers of Biomedical Research Excellence (COBRE) and the 
Louisiana Biomedical Research Network (LBRN) by broadening the geographic scope and population coverage 
of data resources available to LA CaTS investigators. Aim 3. Expand our educational mission, in close 
cooperation with the Professional Development (PD) Core, to create a pipeline of translational data scientists 
with emphasis on diversity and to enable and support data research by citizen scientists an...

## Key facts

- **NIH application ID:** 10667109
- **Project number:** 2U54GM104940-07
- **Recipient organization:** LSU PENNINGTON BIOMEDICAL RESEARCH CTR
- **Principal Investigator:** Lucio Miele
- **Activity code:** U54 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $276,877
- **Award type:** 2
- **Project period:** 2012-08-15 → 2027-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10667109

## Citation

> US National Institutes of Health, RePORTER application 10667109, Core 06: Biomedical Informatics Core (2U54GM104940-07). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10667109. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*