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Learning Objectives
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Now · 1. Network Medicine Paradigm
Learning Objectives
- Understand disease as network perturbation
- Apply network medicine concepts
- Identify disease modules
1. Network Medicine Paradigm
Diseases emerge from perturbations in interaction networks, not single gene defects.
Disease Module Hypothesis: Disease-associated proteins cluster in subnetworks (disease modules).
2. Identifying Disease Modules
Seed genes: Known disease genes (GWAS, OMIM). Network Propagation: Random Walk with Restart from seeds. Finds network neighbors. Module Detection: DIAMOnD algorithm expands seeds into disease module.
3. Drug Discovery Applications
Drug Targets: Network hubs are common targets. Drug Repurposing: If drug targets in/near disease module, drug may work. Side Effects: Off-target module interactions cause side effects. Combinatorial Therapy: Multi-target more effective.
Q1: What is the disease module hypothesis?Disease proteins cluster in network modules. Identifying modules reveals mechanisms, new disease genes, and drug targets. Q2: What is network propagation?Simulate information flow from seed nodes. Random Walk with Restart: walk from seeds, revisit seeds with probability. Nodes with high visitation are candidates. Q3: How does network proximity explain comorbidities?If two disease modules are close (overlap/adjacent) in PPI network, diseases may share mechanisms and co-occur. Q4: How to identify drug repurposing opportunities?If drug target near disease module (even for different disease), drug may work. Network distance between targets and disease genes predicts efficacy. Q5: Why avoid targeting hubs?Hubs involved in many processes. Inhibiting causes widespread side effects. Ideal targets: in disease module but not essential elsewhere. Q6: Essential vs disease genes in networks?Essential (lethal KO): hubs (central, many connections). Disease: non-hubs in peripheries, specific modules. Hubs too essential for viable disease. Join Discord PreviousMetabolic NetworksNextNetwork Evolution & Dynamics