Programme Parameters
Graduate / Intermediate
3 Days (4.5 Hrs)
Online (e-LMS)
• A basic understanding of the subject area and fundamental programming or scientific concepts.
• A laptop or desktop with a stable internet connection.
• Willingness to complete assignments and the capstone project.
About This Course
This 3‑day intensive program introduces participants to protein‑protein interaction (PPI) network analysis and its pivotal role in biomarker discovery. Every participant receives a verified e-Certificate and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
This 3‑day intensive program introduces participants to protein‑protein interaction (PPI) network analysis and its pivotal role in biomarker discovery.
📋 Course Objectives
1. Put biotechnology techniques to work on real datasets and case studies.
2. Produce a reproducible, portfolio-ready project you can cite in a thesis, paper, or job application.
👥 Who Should Enroll?
• Master's and senior undergraduate students specializing in biotechnology
• R&D engineers and working professionals applying biotechnology in industry
• Academics and educators building research or teaching capacity in biotechnology
🚀 Key Learning Outcomes
• A portfolio-grade biotechnology deliverable you can defend and extend.
• A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
💎 What You'll Gain
Live & Recorded Sessions
Lifetime access to class recordingse-Certificate on Completion
Cryptographically verified credentialPost-Programme Support
Direct access to mentors & councilHands-On Experience
Notebooks, real-world code & datasetsCurriculum Outline
Day 1 – Foundations of PPI Networks & Biomarker Discovery
Understand genes, proteins and interaction networks • Explore disease‑related biomarker concepts • Navigate public PPI databases and the STRING platform • Perform Hands‑on: Search disease‑related genes in STRING
Day 2 – Network Visualization & Topology with Cytoscape
Import STRING networks into Cytoscape • Visualize nodes, edges, attributes and apply layouts • Analyse topology: degree, centrality, clustering, density • Run NetworkAnalyzer for comprehensive statistics
Day 3 – Hub Gene Identification & AI‑Assisted Interpretation
Apply CytoHubba to rank hub genes/proteins • Compare ranking algorithms: Degree, MCC, MNC, Closeness, Betweenness • Prioritize candidate biomarkers from ranked hubs • Utilize AI tools for literature‑based biological interpretation
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | STRING Database |
| Covered Tool / Platform | Cytoscape |
| Covered Tool / Platform | NetworkAnalyzer |
| Covered Tool / Platform | CytoHubba |
| Covered Tool / Platform | AI-assisted literature interpretation tools |
Frequently Asked Questions
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