# Computational and Systems Biology Core

> **NIH NIH U19** · DUKE UNIVERSITY · 2022 · $406,030

## Abstract

ABSTRACT – Computational and Systems Biology Core
The Computational and Systems Biology Core will provide access to advanced data analysis algorithms and
pipelines for the entire project. High-quality preprocessed data will be seamlessly integrated from the Omics
and Technology Core. Our analysis pipelines will perform all major steps of data analysis, including outlier
detection, differential analysis, pathway analysis, and advanced network methods. We will develop methods
specifically tailored for multi-compartment omics data in this project, e.g. from blood, gut, and brain. Such novel
methods for integrated multi-omics, multi-compartment data will provide a unique readout of AD pathology and
allow us to unlock the full potential behind these heterogeneous datasets. Moreover, we will work on
computational models for human-microbe co-metabolism, which will allow in silico simulations of external
influences, such as diet, at physiological scale. The research questions addressed by the core will mainly be
driven by the three projects. To this end, we will focus on the blood-gut-brain axis in human omics datasets
(project 1), in animal model datasets (project 3), and the effects of environment and diet on molecular
phenotypes (project 2). A second, major focus of the core will be on the development and application of a
microbiome-centric bioinformatic knowledge base (an “atlas”). To this end, will construct a Neoj4-based
network database integrating various heterogenous information, including results from metabolomics GWAS,
eQTL studies, Alzheimer-phenotype related association studies (e.g. metabolomics biomarkers of AD
endophenotypes), microbiome-metabolome associations etc. The atlas will allow us to answer complex
research questions, such as finding the connections between a given set of metabolites, genes, metabolic
pathways, GWAS hits, and AD endophenotypes in one single query. In the final part of this project, we will
develop advanced network data mining algorithms on the atlas, to extract novel information beyond that of
simple associations. This will lead to integrated molecular modules associated with AD, providing a multi-omics
view on AD pathobiology. The core will be led by an experienced, international group of PIs with over a decade
of experience in the field. The team has a track record in major fields of metabolic research, including diabetes,
cancer, Alzheimer’s disease, microbiome analysis, and metabolic GWAS. In summary, the Computational and
Systems Biology Core will be central element for computational approaches within the consortium, providing
both data analysis and advanced data integration and data mining techniques.

## Key facts

- **NIH application ID:** 10475892
- **Project number:** 5U19AG063744-04
- **Recipient organization:** DUKE UNIVERSITY
- **Principal Investigator:** Rima F Kaddurah-Daouk
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $406,030
- **Award type:** 5
- **Project period:** 2019-09-15 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10475892

## Citation

> US National Institutes of Health, RePORTER application 10475892, Computational and Systems Biology Core (5U19AG063744-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10475892. Licensed CC0.

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