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A Web-Based Workflow for Selecting Gene- and Tissue-Specific Enhancers

A Web-Based Workflow for Selecting Gene- and Tissue-Specific Enhancers

Published on: July 18, 2025

Interactive exploration of integrated biological datasets using context-sensitive workflows.

Fabian Horn¹, Martin Rittweger¹, Jan Taubert²

¹Systems Biology/Bioinformatics, Leibniz Institute for Natural Product Research and Infection Biology - Hans Knöll Institute Jena, Germany.

Frontiers in Genetics

|March 7, 2014

Summary

This summary is machine-generated.

This study enhances network inference tools by integrating data and analysis within the Ondex framework, enabling better exploration of complex molecular interactions and hypothesis generation for fungal gene functions.

Keywords:

Aspergillus nidulans Ondex customizable workflow data integration data visualization exploratory analysis gold-standard information network

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Area of Science:

Bioinformatics
Computational Biology
Systems Biology

Background:

Network inference reconstructs molecular interaction networks from high-throughput data, but parameter optimization and validation remain challenging.
Current tools struggle with large datasets, limiting exploration due to computational and user experience issues.
Data integration and visualization are crucial for candidate prioritization but are often separated from interactive analysis.

Purpose of the Study:

To extend the Ondex software framework with enhanced data integration and analysis functionalities for interactive exploration of molecular networks.
To overcome the limitations of existing tools in handling large-scale biological data and facilitate hypothesis generation.
To bridge the gap between data integration and interactive analysis for improved biological network exploration.

Main Methods:

Extended the Ondex framework with customizable menus for context-sensitive data integration and analysis.
Implemented on-the-fly data integration using InterProScan, PubMed Central, and sequence-based homology searches.
Applied the enhanced Ondex system to integrate and analyze publicly available data for Aspergillus nidulans, including transcriptome data.

Main Results:

Demonstrated the ability to perform computationally demanding calculations on sub-networks without information loss.
Successfully integrated diverse biological data sources, including literature and sequence databases.
Generated novel hypotheses for the functional annotation of differentially expressed fungal genes in Aspergillus nidulans.

Conclusions:

The extended Ondex framework effectively integrates data and interactive analysis, overcoming previous limitations.
The enhanced system facilitates the exploration of large biological networks and supports hypothesis generation.
Direct access to online databases ensures up-to-date information, improving the utility of network inference.