# Core D: Bioinformatics and Modeling Core

> **NIH NIH P01** · UNIVERSITY OF TEXAS MED BR GALVESTON · 2021 · $501,580

## Abstract

CORE D: PROJECT SUMMARY/ABSTRACT
The role of the Bioinformatics and Modeling Core is to process, analyze, and model the genome and
proteome-level datasets produced in this project. This will be accomplished through two main objectives: (1) to
design and provide tools to analyze experimental data, and (2) to integrate data into network models of host
response and pathogenicity. Previously developed in-house tools, publicly available established relevant
software packages, and new bioinformatics tools developed in the Projects will be integrated, automated, and
then applied to data generated by the Projects, and made available to the larger research community through
web-based interfaces. EBOV-relevant publicly available and locally produced data will be organized into
databases that can be used by Program investigators and others to test hypotheses. The following Specific Aims
will be spearheaded by the Core in close collaboration with the project investigators.
Aim 1. Characterize the transcriptional, posttranscriptional, and posttranslational mechanisms impacted
by EBOV infection in cells and organisms. Tools aimed for revealing the host gene regulatory mechanisms
impacted by EBOV infection will be developed and applied. Differentially expressed, modified, and processed
RNAs and genomic regulatory regions between infected and uninfected cells will be identified. Differential
posttranslational protein modifications will also be identified. Specific altered regulatory mechanisms will be
predicted using transcription factor, cofactor, epigenetic regulator, RNA binding protein, and microRNA
enrichment analyses. The Core will systematically intersect the genomic locations of infection-modified loci and
processed custom databases containing more than 20,000 human publicly available genome-wide databases to
reveal molecular processes and factors affected by EBOV infection.
Aim 2. Model cell type-specific responses to EBOV in vitro and in vivo. The Core will build an integrative
model of the mechanisms controlling EBOV pathogenesis by combining data generated the Projects. To this
end, they will employ network-based data integration approaches using network propagation-based techniques.
In brief, modeling approaches will be applied to find correlates and associations between transcriptional,
posttranscriptional, and posttranslational data to define host and viral factors that (1) reflect the activation states
of the network; (2) control cell response to EBOV; and (3) can be tested for both diagnostics and therapies.
Aim 3. Facilitate internal and external collaborations through metadata standardization, and interactive
web and programmatic data interfaces. Streamlined computational pipelines will be built using best-standard
engineering processes and release the code and data through web-based interfaces.
The Bioinformatics and Modeling Core will facilitate centralized data collection, exchange and analysis, and
provide expertise by the members of the C...

## Key facts

- **NIH application ID:** 10188758
- **Project number:** 1P01AI150585-01A1
- **Recipient organization:** UNIVERSITY OF TEXAS MED BR GALVESTON
- **Principal Investigator:** Ivan Marazzi
- **Activity code:** P01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $501,580
- **Award type:** 1
- **Project period:** 2021-04-15 → 2026-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10188758

## Citation

> US National Institutes of Health, RePORTER application 10188758, Core D: Bioinformatics and Modeling Core (1P01AI150585-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10188758. Licensed CC0.

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