# NOODAI: a webserver for network-oriented multi-omics data analysis and integration pipeline

**Authors:** Tiberiu Totu, Rafael Riudavets Puig, Lukas Jonathan Häuser, Mattia Tomasoni, Hella Anna Bolck, Marija Buljan

PMC · DOI: 10.1093/bioinformatics/btaf553 · 2025-10-06

## TL;DR

NOODAI is a web-based tool that integrates multiple omics data to identify key biological networks and modules relevant to diseases.

## Contribution

NOODAI introduces a network-oriented pipeline for multi-omics integration using MONET to highlight disease-relevant modules.

## Key findings

- NOODAI constructs joint interaction networks from omics data using known biological interactions.
- The platform identifies central elements and functionally connected modules relevant to studied phenotypes.
- NOODAI provides user-friendly analysis with visual summaries and reports for clinical multi-omics datasets.

## Abstract

Omics profiling has proven of great use for unbiased and comprehensive identification of key features that define biological phenotypes and underlie medical conditions. While each omics profile assists characterization of specific molecular components relevant for the studied phenotype, their joint evaluation can offer deeper insights into the overall mechanistic functioning of biological systems. Here, we introduce an approach where, starting from representative traits (e.g. differentially expressed elements) obtained for each omics profile, we construct and analyze joint interaction networks. The resulting networks rely on the existing knowledge of confident interactions among biological entities. We use these maps to identify and describe central elements, which connect multiple entities characteristic of the studied phenotypes and we leverage MONET network decomposition tool in order to highlight functionally connected network modules. In order to enable broad usage of this approach, we developed the NOODAI software platform, which enables integrative omics analysis through a user-friendly interface. The analysis outcomes are presented both as raw output tables as well as informative summary plots and written reports. Since the MONET tool enables the use of algorithms with strong performance in identifying disease-relevant modules, NOODAI software platform can be of a high value for analyzing clinical multi-omics datasets.

NOODAI is freely accessible at https://omics-oracle.com. Source code is available under GPL3 at: https://github.com/TotuTiberiu/NOODAI with the DOI: 10.5281/zenodo.17203984.

## Full-text entities

- **Genes:** F3 (coagulation factor III, tissue factor) [NCBI Gene 2152] {aka CD142, TF, TFA}
- **Diseases:** Cancer (MESH:D009369)
- **Chemicals:** metabolites (-)
- **Species:** Rattus norvegicus (brown rat, species) [taxon 10116], Mus musculus (house mouse, species) [taxon 10090], Homo sapiens (human, species) [taxon 9606]

## Figures

1 figure with captions in the complete paper: https://tomesphere.com/paper/PMC12582364/full.md

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Source: https://tomesphere.com/paper/PMC12582364