NOTE: The date is preliminary and will be fixed upon all registrations for the Bio-IT, Centre for Statistical Data Analysis, and Centre for Biomolecular Network Analysis courses have been closed.
Timeframe for all courses is between June 6th and 14th.
**Module 2: Analyzing and understanding networks**
This module will propose a sample workflow of dealing with networks from a furball to comprehension.
1. Topological network analysis – how to investigate and comprehend graphs and adjacency matrices
– Network centralities as means of decomposing complex graphs into comprehensible chunks of knowledge.
– Centralities in the biological context
2. Introduction to network modularity – in search of activity and complexes in networks
– clustering to detect cliques, modules, motifs, and communities
– Using experimental data to detect condition-specific changes in pathways/processes
3. Network Enrichment Analysis
– Introduction to Ontologies and Pathways (GO, KEGG, Reactome)
– Enrichment analysis with and without quantitative data
4. How to interpret your results
5. Introduction to concepts of data integration
– Integrating biological data (RNASeq, ChipSeq, miRNA, Mass Spec, knowledge)
BYOC (bring your own computer with pre-installed Cytoscape 3.x (latest), (R and RStudio optional for parts of the workshop) or use the provided lab machines.
BYOD (bring your own data): Various exercises throughout the course can be done with your own data.
Bookings
This event is fully booked.