Hands-on PPI Network Analysis for Biomarker Identification using Cytoscape & STRING
Hands-on PPI Network Analysis for Biomarker Identification using Cytoscape & STRING is a Advanced-level, 3 Days (1.5 Hours Per Day) online program by NSTC.
- ModeRecorded Lectures
- LevelAdvanced
- Duration3 Days (1.5 Hours Per Day)
| Attribute | Detail |
|---|---|
| Format | Recorded Lectures |
| Level | Advanced |
| Duration | 3 Days (1.5 Hours Per Day) |
| Certification | e-Certification + e-Marksheet |
| Fee | Free |
| Tools | STRING Database Cytoscape CytoHubba NetworkAnalyzer gProfiler KEGG Reactome Gen‑TF miRNA interaction databases |
About the Hands-on PPI Network Analysis for Biomarker Identification using Cytoscape & STRING Course
Hands‑on PPI Network Analysis for Biomarker Identification using Cytoscape & STRING is a 3‑day mentor‑led bioinformatics program that teaches you how to build, explore and interpret protein‑protein interaction networks to uncover hub genes and potential disease biomarkers.
You will work with industry‑standard tools – STRING, Cytoscape, CytoHubba, NetworkAnalyzer and enrichment platforms – to translate raw interaction data into actionable biological insights.
Program Highlights
• Comprehensive coverage of Hands from fundamentals to advanced applications
• Hands-on projects and real-world case studies in bioinformatics
• Expert-curated curriculum aligned with current industry standards
• Access to recorded lectures and e-LMS platform for flexible, self-paced learning
• e-Certification and e-Marksheet upon successful completion
• Dedicated mentor support and interactive doubt-clearing sessions
• Practical experience with tools: STRING Database, Cytoscape, CytoHubba, NetworkAnalyzer
• Career-oriented training for academic and professional growth in bioinformatics
Course Curriculum
Module 1: Day 1 – Introduction to PPI Networks & STRING
- Understand systems‑biology concepts and the role of PPI databases
- Search and filter protein interactions in STRING
- Import data into Cytoscape and visualise basic networks
Module 2: Day 2 – Hub Protein & Biomarker Discovery
- Analyze network topology with NetworkAnalyzer
- Identify hub genes using CytoHubba
- Prioritise potential biomarkers based on centrality metrics
Module 3: Day 3 – Functional Enrichment & Regulatory Analysis
- Perform GO enrichment with gProfiler
- Identify pathways via KEGG & Reactome
- Explore transcription‑factor and miRNA interactions using Gen‑TF and public databases
