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atBioNet--an integrated network analysis tool for genomics and biomarker discovery
Yijun Ding1, Minjun Chen, Zhichao Liu
1ICF International at FDA's National Center for Toxicological Research, Jefferson, AR 72079, USA.
BMC Genomics
|July 24, 2012
Summary
atBioNet integrates protein-protein interaction databases for network analysis, aiding in disease mechanism discovery and biomarker identification for conditions like leukemia and cancer.
Area of Science:
- Bioinformatics
- Systems Biology
- Network Analysis
Background:
- Extensive mammalian protein-protein interaction (PPI) data is available.
- PPI networks are crucial for understanding disease mechanisms via systems biology.
- A comprehensive network analysis tool is needed to integrate PPI data and identify disease-related pathways.
Purpose of the Study:
- To develop and present atBioNet, a web-based tool for comprehensive protein-protein interaction network analysis.
- To enable the identification of key functional modules and pathways involved in disease and toxicity.
Main Methods:
- Integration of seven public PPI databases into a unified knowledge base.
- Knowledge expansion using user-provided gene/protein lists and network interactions.
- Application of the SCAN clustering algorithm to identify statistically significant functional modules.
- Visualization of functional modules within the broader network context.
- Integration of pathway information for enrichment analysis and functional assessment.
Main Results:
- atBioNet successfully integrates diverse PPI data, enabling knowledge expansion.
- The SCAN algorithm effectively identifies significant functional modules.
- Case studies on acute leukemia, systemic lupus erythematosus, and breast cancer demonstrated atBioNet's ability to identify disease-related pathways.
- The tool facilitated the hypothesis of novel biomarkers for these diseases.
Conclusions:
- atBioNet is a free, web-based tool offering systematic insights into protein-protein interactions.
- Identified functional modules aid in understanding disease mechanisms and discovering biomarkers.
- The tool supports biomarker discovery for various diseases through network analysis.
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