1. Overview  Introduction  Biological network data  Text mining  Gene Ontology  Expression data basics  Expression, text mining, and GO  Modules and complexes  Domains and conclusion

2. Biological Network Data (Getting external stuff)  Lecture  Cytoscape plugins  Protein interactions: types and measurement  Protein association: text mining and coexpression  Public data repositories  Hands-on  Installing Cytoscape plugins  Filters  A few external data resources

3. Cytoscape Plugins available for….  Gene Ontology analysis  Domain-level protein network analysis  Interface to the Oracle spatial network data model  Shortest-Path graph analysis algorithms

5. Interactions  Protein-protein interactions  Protein-DNA interactions  Associations (co-expression, text mining, etc).

6. Protein-protein interactions Source: http://www.biocarta.com/pathfiles/h_caspasePathway.asp

7. Measuring protein-protein interactions:  Yeast Two-Hybrid Source: http://www.bioteach.ubc.ca/

8. Measuring protein-protein interactions  Co-immunoprecipitation (Co-IP) Courtesy of Rhoded Sharan, Tel Aviv University

9. Key points on protein interactions  High false positive rate  High false negative rate  Currently, not much overlap between published interaction datasets  Most confidence given to observed interactions with other supporting evidence.

10. Protein-DNA interactions From: Molecular Biology of the Cell, Alberts et al., 2002

11. Measuring Protein-DNA Interactions  ChIP-on-chip From: http://www.chiponchip.org/

12. Key points on protein-DNA interactions  There has not been much data historically.  With new technology, that is changing rapidly.  The technology is still immature, and data interpretation should be done cautiously.

13. Text mining Courtesy of Gary Bader, Memorial Sloan Kettering Cancer Center

14. Conserved co-expression networks From: Genome Biology 2004, 5: R100

15. Genetic Interactions From: Nature Biotechnology 23, 561 - 566 (2005)

16. Key points on association data  An association does not imply an interaction.  Compared to protein interaction data  Higher false positive rate  Often better coverage, lower false negative rate

17. From: de Lichtenberg et al., Science. 2005 Feb 4;307(5710):724-7 Always remember: interactions are context-dependent!

18. Also: Metabolic pathways

19. Public data repositories  Protein-protein interaction data  BIND, DIP, MINT, MIPS, InACT, …  Protein-DNA interaction data  BIND, Transfac, …  Metabolic pathway data  BioCyc, KEGG, WIT, …  Text-mining, coexpression  Pre-BIND, Tmm, …

20. Pathway data exchange formats: 1. BioPAX (supported by Cytoscape) 2. PSI-MI (supported by Cytoscape) 3. Hundreds of other formats specific to each pathway data repository (not generally supported by Cytoscape)

21. Hands-on session  Installing Cytoscape plugins  Getting external data  Merging networks  Using filters