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Updated: May 17, 2026
07:28
JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
Published on: October 19, 2021
Systems biology: building a useful model from multiple markers and profiles
Paul Mayer1, Bernd Mayer, Gert Mayer
1Emergentec Biodevelopment GmbH, Vienna, Austria.
Summary
Diabetic nephropathy (DN) involves complex molecular interactions. This study proposes a biomarker panel derived from a gene/protein network to identify DN subtypes for better patient stratification and treatment.
Area of Science:
- * Molecular biology
- * Bioinformatics
- * Nephrology
Background:
- * Diabetic nephropathy (DN) pathophysiology is a complex interplay of molecular processes.
- * The balance of these processes, not single pathways, dictates clinical outcomes.
- * Current approaches lack comprehensive molecular profiling for personalized DN management.
Purpose of the Study:
- * To develop a concept for a biomarker panel representing key molecular processes in DN.
- * To create a DN-specific molecular model using a hybrid gene/protein interaction network.
- * To enable better patient stratification based on individual DN molecular profiles.
Main Methods:
- * Constructed a hybrid gene/protein interaction network incorporating data from omics studies (SNPs, miRNAs, transcriptomics, proteomics, metabolomics).
- * Integrated additional DN-associated genes from literature and text mining of patents/clinical trials.
- * Applied a segmentation algorithm to identify functional molecular units within a DN-specific subgraph.
Main Results:
- * Identified 2175 unique protein-coding genes from omics data and 287 from literature searches.
- * Text mining added approximately 1,000 features related to DN.
- * Segmentation algorithm revealed DN-specific molecular units representing functional processes.
Conclusions:
- * The developed molecular model represents a functionally relevant view of DN pathophysiology.
- * Biomarkers selected from identified units can characterize specific DN subtypes.
- * This approach facilitates improved patient stratification for risk assessment and intervention selection.
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