Network Biology and Hub-Gene Discovery Using STRING and Cytoscape

To construct and analyse biological networks for identifying hub genes, functional modules, disease regulators, candidate biomarkers, and potential therapeutic targets.

• Collect, clean, and standardise disease-associated gene lists.
• Construct and export protein-interaction networks using STRING.
• Import networks into Cytoscape and calculate centrality measures.
• Identify hub genes and densely connected functional modules.
• Develop miRNA–gene or transcription factor–gene networks.
• Prepare publication-quality network figures and biological interpretations.

STRING Cytoscap NetworkAnalyze cytoHubba MCODE ClueGO and CluePedia GeneMANIA Enrichr miRTarBase-Compatible Resources TRRUST-Compatible Resources

• Curated disease-gene database and standardised gene list
• STRING interaction network and exported interaction tables
• Cytoscape project file and centrality-analysis table
• Hub-gene ranking and MCODE module analysis
• Integrated miRNA or transcription factor regulatory network
• Publication-quality figures, GitHub repository, and final technical report

Network Biology-Based Identification of Hub Genes in Colorectal Cancer

Protein Interaction Network Analysis of Alzheimer’s Disease

miRNA–Gene Regulatory Network in Breast Cancer

Network Analysis of Antimicrobial Resistance Genes

Hub-Gene and Pathway Analysis of Rheumatoid Arthritis

Co-Expression Network Analysis of Metabolic Disorders

• Identification of disease-associated hub genes and biomarkers
• Discovery of functional modules and pathway interactions
• Prioritisation of potential therapeutic targets
• Analysis of miRNA and transcription-factor regulation
• Investigation of drug resistance and disease progression
• Preparation of network figures for research reports and publications

• Biotechnology, bioinformatics, and computational biology students
• Genetics, molecular biology, and biomedical science learners
• Undergraduate and postgraduate students
• PhD scholars and early-career researchers
• Faculty members and research professionals
• Learners interested in network biology and disease-gene analysis

Prerequisites: Basic knowledge of molecular biology, genetics, gene expression, or bioinformatics is recommended. Previous Cytoscape or programming experience is helpful but not mandatory.

• Import and organise node, edge, and attribute tables.
• Apply suitable layouts and customise network visualisation.
• Map node size, colour, and shape to biological attributes.
• Calculate degree, betweenness, and closeness centrality.
• Identify hub genes using cytoHubba and modules using MCODE.
• Group pathways with ClueGO and export high-quality figures.