Computational Biology

1. Computational Biology Networks and Pathways Lecture Slides Week 11

2. Data is Interconnected

3. What is a Graph

4. Complexity

5. A network is a collection of interactions Pathways are a subset of networks All pathways are networks of interactions not all networks are pathways

6. Young et. al: Transcriptional Regulatory Networks in Saccharomyces cerevisiae; Science 2002

7. A network is a collection of interactions Pathways are a subset of networks All pathways are networks of interactions, however not all networks are pathways! Pathway is a biological network that corresponds to a specific physiological process or phenotype

8. Biological pathways Biological components interacting with each other over time to bring about a single biological effect Pathways can be broken down sub-pathways Some common pathways: signal transduction metabolic pathways, gene regulatory pathways Entities in one pathway can be found in others

9. 3 types of interactions that can be mapped into pathways protein (enzyme) – metabolite (ligand) metabolic pathways protein – protein cell signaling pathways, protein complexes protein – gene genetic networks

10. Available resources KEGG http://www.genome.jp/kegg/ BioCyc http://www.biocyc.org/ Reactome http://www.reactome.org/ GenMAPP http://www.genmapp.org/ BioCarta http://www.biocarta.com/ TransPATH http://www.biobase- international.com/pages/index.php?id=transpathdatabases Pathguide – the pathway resource list http://www.pathguide.org/

11. Network Topology (PPI)

12. Network analysis and visualization tools Databases for analysis Text mining algorithms (e.g., natural language processing (NLP)) technologies Expert human curation

13. Ingenuity Pathway Analysis http://www.ingenuity.com/products/pathways_analysis.html PathwayStudio http://www.ariadnegenomics.com/products/pathway-studio/ PathwayArchitect http://www.selectscience.net Cytoscape http://www.cytoscape.org/ Biological Networks http://biologicalnetworks.net/ GeneGO http://www.genego.com/

14. Nanduri etal (unpublished)

15. GO term enrichment Nanduri etal (unpublished)

16. Nanduri etal (unpublished)

17. Nanduri etal (unpublished)

18. Nanduri etal (unpublished)

19. End Theory I • 5 min mindmapping • 10 min break

20. Practice I

21. Cytoscape • Download and install cytoscape • Add the reactome app • Initialize the reactome app • Inspect some metabolic pathways

22. End Practice I • 15 min break

23. Theory II

24. Pathways vs. networks Gene networks • Clusters of genes (or gene products) with evidence of co-expression • Connections usually represent degrees of co-expression • In-depth knowledge of process is not necessary • Networks are non-predictive Biochemical pathways • Series of chained, chemical reactions • Connections represent describable (and quantifiable) relations between molecules, proteins, lipids, etc. • Enzymatic process is elucidated • Changes via perturbation are predictable downstream

25. Pathways vs. networks

26. Pathway and network granularity Curated reaction pathways Qualitative networks Effort to curate Mathematical simulation models Probabilistic networks General interaction networks Level of detail

27. Introduction to pathways and networks • Examples of pathways and networks • Review of pathway databases and tools • Representing pathways and networks • Methods of inferring pathways and networks • Pathway and cellular simulations

28. Yeast gene interaction network Tong, et al., Science 303, 808 (2004)

29. Characteristics of the yeast gene network • Some genes (e.g. regulatory factors) act as ‘hubs’ in a network and have many interactions • Degrees of connectivity follows the power law • Hubs may make interesting anti-cancer targets • Clusters of genes with known function suggest function for hypothetical genes in same cluster • Network characteristics can be used to predict protein-protein interactions • Path between two genes tends to be short (average ~3.3 hops) Tong, et al., Science 303, 808 (2004)

30. E. coli metabolic pathway glycolysis Karp, et al., Science 293, 2040 (2001)

31. Pathways: E. coli metabolic map • Encompasses >791 chemical compounds in >744 noted biochemical reactions • Pathway was compiled via literature information extraction and extensive manual curation • System allows for users to indicate evidence of pathway annotations • Curation is done collaboratively with numerous experts outside of EcoCyc Karp, et al., Science 293, 2040 (2001)

32. Pathways in bioinformatics • Most resources for pathways focus on metabolic pathways (signaling and regulatory gaining prominence) • Pathways as a very specific subtype of networks • Like networks, can be made in computable (symbolic) form • Specificities in chemical reactions are more predictive • Pathways can chain together, forming larger pathways Karp, et al., Science 293, 2040 (2001)

33. Pathway repositories • BioCyc/MetaCyc • Kyoto Encyclopedia of Genes and Genomes (KEGG) PATHWAY DB • BioCarta • BioModels database

34. BioCyc databasehttp://www.biocyc.org • Pathway/genome database (PGDB) for organisms with completely sequenced genomes • 409 full genomes and pathways deposited • Species-specific pathways are inferred form MetaCyc • Query/navigation/pathway creation support through the Pathway Tools software suite

35. http://www.biocyc.org

36. MetaCyc database http://www.metacyc.org • Non-redundant reference database for metabolic pathways, reactions, enzymes and compounds • Curation through experimental verification and manual literature review • >1200 pathways from 1600+ species (mostly plants and microorganisms)

37. http://www.metacyc.org

38. Glycolysis pathway in MetaCyc http://www.metacyc.org

39. KEGG PATHWAY databasehttp://www.kegg.com • Consolidated set of databases that cover genomics (GENE), chemical compounds (LIGAND) and reaction networks (PATHWAY) • Broad focus on metabolics, signal transduction, disease, etc. • Species-specific views available (but networks are static across all organisms)

40. http://www.kegg.com

41. Glycolysis pathway in KEGG http://www.kegg.com

42. Global Pathway Map

43. BioCarta databasehttp://www.biocarta.com • Corporate-owned, publicly-curated pathway database • Series of interactive, “cartoon” pathway maps • Predominantly human and mouse pathways • Contains 120,000 gene entries and 355 pathways

44. http://www.biocarta.com

45. Glycolysis pathway in BioCarta http://www.biocarta.com

46. BioModels databasehttp://www.biomodels.net • Database for published, quantitative models of biochemical processes • All models/pathways curated manually, compliant with MIRIAM • Models can be output in SBML format for quantitative modeling • 86 curated models, 40 models pending curation

47. http://www.biomodels.net

48. Glycolysis pathways in BioModels http://www.biomodels.net

49. Comparison of pathway databases

50. Introduction to pathways and networks • Examples of pathways and networks • Review of pathway databases and tools • Representing pathways and networks • Methods of inferring pathways and networks • Pathway and cellular simulations