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Protein Networks

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
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Related Experiment Video

Updated: Apr 26, 2026

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization

Published on: October 3, 2025

NetPathMiner: R/Bioconductor package for network path mining through gene expression.

Ahmed Mohamed¹, Timothy Hancock², Canh Hao Nguyen¹

¹Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Japan and Department of Computing and Information Systems, The University of Melbourne, Victoria, Australia.

Bioinformatics (Oxford, England)

|July 31, 2014

Summary

This summary is machine-generated.

NetPathMiner is a novel framework for identifying biologically relevant pathways from genome-scale networks. It aids interpretation through ranking, clustering, and visualization of network paths under specific experimental conditions.

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A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information

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Area of Science:

Bioinformatics
Systems Biology
Network Analysis

Background:

Genome-scale networks are complex and require specialized tools for analysis.
Identifying condition-specific pathways is crucial for understanding biological processes.

Purpose of the Study:

To introduce NetPathMiner, a generalizable framework for mining condition-specific paths from biological networks.
To provide tools for network manipulation, path ranking, and interpretation.

Main Methods:

NetPathMiner accepts various network file formats (KGML, SBML, BioPAX).
It supports metabolic, reaction, and gene network representations.
Markov model-based clustering and classification are applied to ranked paths.

Main Results:

NetPathMiner facilitates the identification of condition-specific pathways.
The framework enables manipulation and analysis of biological networks.
It offers static and interactive visualizations for enhanced manual investigation.

Conclusions:

NetPathMiner provides a comprehensive approach to pathway mining from biological networks.
The tool aids in the interpretation of complex network data for specific experimental contexts.