Home /Biotechnology /Workshop /AI-Assisted Protein-Protein Interaction (PPI) Network Analysis for Biomarker Discovery

AI-Assisted Protein-Protein Interaction (PPI) Network Analysis for Biomarker Discovery

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Delivery Mode
Virtual / Online
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Level
Moderate
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Duration
3 Days (60-90 minutes)
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Certificate
Mentor Based
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Language
English
Rating
5 Stars
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About Workshop

This 3-day workshop is designed to introduce participants to Protein-Protein Interaction (PPI) network analysis and its role in biomarker discovery. Participants will learn how biological interaction data can be collected, visualized, analyzed, and interpreted using bioinformatics and AI-supported approaches. The workshop will focus on understanding how proteins interact within biological systems, how these interactions form meaningful networks, and how researchers can identify important genes or proteins that may serve as potential biomarkers for disease diagnosis, prognosis, or therapeutic research. Participants will gain hands-on exposure to tools such as STRING database, Cytoscape, CytoHubba, NetworkAnalyzer, and AI-assisted interpretation workflows.
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Aim

Aim of the Workshop: To help participants learn how to use PPI network analysis and AI-supported tools to identify hub genes/proteins and discover potential biomarkers for disease-related research.
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What Participants Will Learn

  • Learn the fundamentals of PPI networks and biomarker discovery
  • Explore public biological databases for protein interaction data
  • Perform hands-on network construction using STRING database
  • Visualize and analyze interaction networks using Cytoscape
  • Identify hub genes/proteins using CytoHubba
  • Understand network parameters such as degree, centrality, clustering, and connectivity
  • Use AI-assisted methods for biological interpretation and literature-based insights
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Structure

📅 Day 1: Introduction to PPI Networks & Biomarker Discovery
  • Introduction to genes, proteins, and biological interaction networks
  • Understanding Protein-Protein Interaction (PPI) networks
  • Importance of PPI networks in disease biology and systems biology
  • Role and types of biomarkers in healthcare, diagnostics, and therapeutic research
  • Overview of public bioinformatics databases for PPI analysis
  • Introduction to STRING database, confidence scores, and interaction evidence
🛠️ Hands-on:
  • Hands-on 1: Search disease-related genes/proteins in the STRING database
  • Hands-on 2: Create and interpret a basic PPI network using selected gene/protein lists
📅 Day 2: Network Visualization & Analysis Using Cytoscape
  • Introduction to Cytoscape for biological network visualization
  • Importing STRING-generated PPI networks into Cytoscape
  • Understanding nodes, edges, attributes, layouts, and network styles
  • Basics of network topology and key parameters: degree, centrality, clustering, and density
  • Using NetworkAnalyzer for PPI network statistics
  • Understanding hub proteins and their role in biomarker discovery
🛠️ Hands-on:
  • Hands-on 1: Import and visualize STRING-generated PPI networks in Cytoscape
  • Hands-on 2: Run NetworkAnalyzer and identify highly connected proteins
📅 Day 3: Hub Gene Identification & AI-Assisted Biomarker Interpretation
  • Introduction to hub genes/proteins and candidate biomarkers
  • Using CytoHubba for hub gene/protein identification
  • Ranking methods: Degree, MCC, MNC, Closeness, and Betweenness
  • Prioritizing candidate biomarkers from PPI networks
  • AI-assisted literature interpretation of selected hub genes/proteins
  • Best practices and limitations of computational biomarker discovery
🛠️ Hands-on:
  • Hands-on 1: Rank top hub genes/proteins using CytoHubba in Cytoscape
  • Hands-on 2: Prepare a mini biomarker discovery report using AI-assisted interpretation
🧰 Tools Covered:
  • STRING Database
  • Cytoscape
  • NetworkAnalyzer
  • CytoHubba
  • AI-assisted literature interpretation tools
  • Gene/protein datasets for biomarker discovery

Important Dates

Registration Ends

3:30 IST

Workshop Dates

2026-07-01
4:30 IST
4:30 IST
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What You Will Gain

  • A basic PPI network created using the STRING database
  • A Cytoscape-based visual network map
  • Network analysis results generated through NetworkAnalyzer
  • A list of top hub genes/proteins identified using CytoHubba
  • A mini biomarker discovery interpretation report
  • Practical understanding of how AI can support biological interpretation and biomarker research
  • Certificate of participation/completion
  • Access to live and recorded sessions
  • Post-workshop query support
  • Hands-on learning experience with bioinformatics tools and AI-assisted workflows
Sample Certificate
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Outcomes

After completing this 3-day workshop, participants will be able to construct, visualize, and analyze Protein-Protein Interaction networks and identify potential biomarker candidates using STRING, Cytoscape, CytoHubba, and AI-assisted interpretation methods.
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Who Should Attend

  • Students from biotechnology, bioinformatics, life sciences, pharmacy, biomedical sciences, and computational biology
  • Ph.D. scholars working on disease biology, molecular biology, genomics, or biomarker research
  • Researchers and academicians interested in network biology and systems biology
  • Healthcare and life sciences professionals exploring bioinformatics tools
  • Beginners who want to learn practical PPI network analysis for research applications
Prerequisites No advanced programming knowledge is required. A basic understanding of genes, proteins, and molecular biology will be helpful. Participants should have access to a laptop or desktop system with a stable internet connection. Participants are also required to download and install Cytoscape on their system before the workshop so they can actively participate in the hands-on network visualization and analysis sessions.
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Deliverables

  • A basic PPI network created using the STRING database
  • A Cytoscape-based visual network map
  • Network analysis results generated through NetworkAnalyzer
  • A list of top hub genes/proteins identified using CytoHubba
  • A mini biomarker discovery interpretation report
  • Practical understanding of how AI can support biological interpretation and biomarker research
  • Certificate of participation/completion
  • Access to live and recorded sessions
  • Post-workshop query support
  • Hands-on learning experience with bioinformatics tools and AI-assisted workflows

Dr. Abhimanyu

Department of Biotechnology

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