Non-Coding RNA Therapeutics: miRNA, lncRNA & Disease Network Analysis

Aim

Workshop Objectives

Workshop Structure

📅 Day 1: ncRNA Biology, Disease Associations & Target Discovery

Focus: Understand regulatory ncRNAs and identify disease-associated miRNAs and lncRNAs.

Topics Covered

• Fundamentals of non-coding RNA biology
• miRNA, lncRNA, circRNA and other regulatory RNA classes
• miRNA biogenesis and post-transcriptional gene regulation
• lncRNA-mediated gene regulation
• ncRNA–mRNA and competing endogenous RNA concepts
• Disease-associated ncRNAs and molecular signatures
• Public ncRNA databases and disease resources
• miRNA and lncRNA expression datasets
• miRNA target-gene prediction
• Functional interpretation of candidate ncRNAs

🛠️ Hands-on

• Search disease-associated miRNAs and lncRNAs
• Explore ncRNA expression and target information
• Predict target genes for selected miRNAs
• Build a curated disease-associated ncRNA dataset

Workflow:
Disease → ncRNA Identification → Expression/Target Data → Target Prediction → Candidate Selection

🧰 Tools Covered

miRBase, miRDB, TargetScan, DIANA tools, LncBase, NCBI, Ensembl, Python/Google Colab

📅 Day 2: ncRNA Regulatory Networks & Disease Pathway Analysis

Focus: Connect ncRNAs with target genes, pathways, and protein-interaction networks to identify disease mechanisms.

Topics Covered

• miRNA–mRNA regulatory relationships
• lncRNA–miRNA–mRNA regulatory networks
• Target-gene filtering and prioritisation
• Gene Ontology and pathway enrichment
• Disease-associated biological pathways
• Protein–protein interaction networks
• Hub-gene and network-module identification
• Network topology and biological interpretation
• Cancer, inflammation, metabolic and neurological disease case studies

🛠️ Hands-on

• Construct miRNA–gene regulatory networks
• Perform functional and pathway enrichment
• Build protein–protein interaction networks
• Identify hub genes and important regulatory modules
• Visualise disease-associated ncRNA networks

Workflow:
ncRNA → Target Genes → Enrichment → PPI Network → Hub Genes → Disease Pathways

🧰 Tools Covered

Enrichr, STRING, Cytoscape, miRNet, g:Profiler, R/Python, Google Colab

📅 Day 3: ncRNA Therapeutics & Candidate Target Prioritisation

Focus: Translate ncRNA network insights into therapeutic hypotheses and prioritised candidate targets.

Topics Covered

• Therapeutic potential of miRNAs and lncRNAs
• miRNA mimics, inhibitors/antagomirs and RNA-based modulation
• lncRNA-targeting strategies
• ncRNA-based disease intervention concepts
• Target selection and therapeutic prioritisation
• Integration of ncRNA, gene, pathway, and disease evidence
• Network-based target prioritisation
• Biomarker versus therapeutic-target assessment
• Delivery challenges for RNA therapeutics
• Specificity, off-target effects, stability, and safety considerations
• Computational prediction versus experimental validation
• Translational challenges in ncRNA therapeutics

🛠️ Hands-on

• Integrate ncRNA, target-gene, pathway, and PPI information
• Rank candidate ncRNAs and therapeutic targets
• Identify hub genes and key regulatory pathways
• Develop a disease-specific ncRNA therapeutic network
• Generate a research-oriented candidate prioritisation report

Workflow:
ncRNA Candidates → Target Integration → Network Analysis → Therapeutic Prioritisation → Candidate Selection → Validation Strategy

🧰 Tools Covered

Python, R, miRNet, Cytoscape, STRING, Enrichr, TargetScan, pandas, Google Colab

Who Should Enrol?

Important Dates

Workshop Outcomes

Fee Structure