# The Omics Molecule Extractor: A Web Application for the Selection of Potential Biomarker Panels

## TL;DR

OMEx is a user-friendly web tool for selecting biomarker panels from large omics datasets using machine learning, with high precision and reproducibility.

## Contribution

OMEx introduces a novel machine learning-based feature selection strategy with a user-friendly interface for biomarker panel selection.

## Key findings

- OMEx discovers group-separating molecules with high precision using synthetic datasets.
- The tool shows high reproducibility and overlap with existing methods on real-world omics data.
- OMEx identifies alternative molecules of interest not found by other methods.

## Abstract

Selecting molecular panels that are applicable to classify
the
health state of patients is a common task in omics data analysis.
Existing software for molecule selection lacks features to select
molecule panels from large data sets, requires programming experience,
or lacks user-friendly interfaces. We present the Omics Molecule Extractor
(OMEx), an open-source web application providing a user-friendly workflow
for selecting molecules and molecule panels for sample classification
from large data sets. OMEx’s user interface provides interactive
visualization for exploring input data and analysis results. The feature
selection strategy underlying the algorithm is based on machine learning
and has not been available in any software with a user interface.
Extensive testing using synthetic data sets with known ground truth
showed that the algorithm discovers group-separating molecules with
high precision. Additionally, OMEx was tested on five real-world omics
data sets, demonstrating high reproducibility and overlap with reported
molecules from other feature selection methods, while also reporting
alternative molecules of interest. OMEx is freely available at https://mdoa-tools.bi.denbi.de/omex/home.