1. Where we are and where we are going From biology to data and back again Chris Evelo Department of Bioinformatics - BiGCaT Maastricht University

2. Faculty of Health, Medicine and Life Sciences Existing knowledge Genomic Results Genetic Results

3. Faculty of Health, Medicine and Life Sciences Existing Knowledge Carefully Hidden in:

4. Faculty of Health, Medicine and Life Sciences Computers aren’t good at: Reading Listening

5. Faculty of Health, Medicine and Life Sciences There is a lot of knowledge to structure

6. Cardiomyopathy: Downregulated genes

7. Fatty Acid Degradation? Other pathways / processes?

8. Faculty of Health, Medicine and Life Sciences What do we really need? Well…

9. Find the pathways: Biological processes in duodenal mucosa affected by glutamine administration number of genes PathwayChangedUpDownMeasuredTotalZ Score Hs_Mitochondrial_fatty_acid_betaoxidation 66016 4.456 Hs_Electron_Transport_Chain 17 0851054.278 Hs_Fatty_Acid_Synthesis 55021222.757 Hs_Fatty_Acid_Beta-Oxidation 66031322.424 Hs_mRNA_processing_Reactome 166101181272.402 Hs_Unsaturated_Fatty_Acid_Beta_Oxidation 220662.342 Hs_HSP70_and_Apoptosis 44018 2.299 Hs_Oxidative_Stress 55027282.097 Hs_Fatty_Acid_Omega_Oxidation 33014151.915 Hs_Proteasome_Degradation 88060611.629 Hs_RNA_transcription_Reactome 55038401.25 Hs_Irinotecan_pathway_PharmGKB 21112 1.154 Hs_Synthesis_and_Degradation_of_Ketone_Bodie s_KEGG 110551.023

10. Faculty of Health, Medicine and Life Sciences Understand genomics Example WikiPathway Pathway Pathway on glycolysis. Using modern systems iology annotation. And genes and metabolites connected to major databases.

11. PathVisio Visualize data on biological pathways It can use gene expression, proteomics and metabolomics data Identify significantly changed processes www.pathvisio.org Martijn P van Iersel, Thomas Kelder, Alexander R Pico, Kristina Hanspers, Susan Coort, Bruce R Conklin, Chris Evelo (2008) Presenting and exploring biological pathways with PathVisio. BMC Bioinformatics 9: 399

12. Faculty of Health, Medicine and Life Sciences adding data = adding colour Example PathVisio result Showing proteomics and transcriptomics results on the glycolysis pathway in mice liver after starvation. [Data from Kaatje Lenaerts and Milka Sokolovic, analysis by Martijn van Iersel]

13. Faculty of Health, Medicine and Life Sciences Process the data…

14. Faculty of Health, Medicine and Life Sciences GSCF Templates Groups Protocols Subjects Samples Events Query module Structured querying Full-text querying Profile-based analysis Study comparison Pathways, GO, metabolite profiles Simple Assay module Body weight, BMI, etc. Epigenetics module Transcriptomics module Raw data Nimblegen Illumina Resulting Genome Feature data Clean CPG island data Raw data cell files Result data p-values z-values Clean data gene expression Web user interface dbNP Architecture Assays

15. custom programs custom programs custom dbs custom dbs GSCF Templates Groups Protocols Subjects Samples Events Assays NCBO Ontologies Data import xls, cvs, text Molgenis EBI repository custom dbs Output xls ISAtab API custom programs web interface Generic Study Capture Framework Data input / output

16. Epigenetics DNA Methylation Pipeline R QC, processing R QC, processing R QC, processing Sequence QC, processing Statistical analysis Raw data Nimblegen Raw sequencing data MeDIP, BIS-Seq Raw data Illumina Clean DNA methylation data (Genome Feature Format) Result data with p-values (GFF) RA 6 RA1 2

17. Now we just need the Pathways

18. WikiPathways Public resource for biological pathways Anyone can contribute and curate More up-to-date representation of biological knowledge WikiPathways: Pathway Editing for the People. Alexander R. Pico, Thomas Kelder, Martijn P. van Iersel, Kristina Hanspers, Bruce R. Conklin, Chris Evelo. PLoS Biology 2008: 6: 7. e184 Commentaries: Big data: Wikiomics. Mitch Waldrop. Nature 2008: 455, 22-25 We the curators. Allison Doerr. Nature Methods 2008: 5, 754–755 No rest for the bio-wikis. Ewen Callaway. Nature 2010: 468, 359-360

19. Search: “One carbon” www.wikipathways.org

20. Click

22. Editing Login needed Registration by e-mail address All edits logged

24. Draw the proteins and interactions

25. How to ever do data visualization?

26. Connect to Genome Databases

27. Double click to annotate the proteins

28. Click Add reference to literature

29. Download

30. PPS1 Liver All pathways Pathways with high z-score grouped together. Explains why there are relatively few significant genes, but many pathways with high z-score. Cytoscape visualization used to group

31. Faculty of Health, Medicine and Life Sciences Existing Knowledge Carefully Hidden in:

32. Faculty of Health, Medicine and Life Sciences Backpages link to databases

33. Assisted content generation Suggestions from: Compound sources (HMDB) Gene resources (UniProt, IntAct) Pathways & processes (KEGG, GO, local) Text mining Semantic web data stores

38. Faculty of Health, Medicine and Life Sciences Existing knowledge Genomic Results Genetic Results

39. Faculty of Health, Medicine and Life Sciences Existing knowledge Genomic Results Genetic Results

41. Problem: Identifier Mapping ? Affymetrix probeset 100234_at Entrez Gene 3643

42. BridgeDB: Abstraction Layer interface IDMapper class IDMapperRdb relational database class IDMapperFile tab-delimited text class IDMapperBiomart web service

43. Faculty of Health, Medicine and Life Sciences Can we show SNPs? Using dbSNP links in ENSEMBL as part of BridgeDB libs

44. Faculty of Health, Medicine and Life Sciences But it will look like this….

45. Gene/Protein Z Metabolite X Metabolite Y mi999 TF RS00001 RS00003 RS00002 RS00004 Gene/Protein Y RS00005

46. Gene/Protein Z Metabolite X Metabolite Y mi999 TF RS00001 RS00003 RS00002 RS00004 Functionalize SNPs Unkown function (attribute to gene) In miRNA binding site In TF binding site Changing protein functionality (coding) Gene/Protein Y RS00005 Changing protein interactions (coding)

47. Gene/Protein Z Gene/Protein Y RS00011 RS00013 RS00012 RS00014 RS00015 Many more SNPs in one interaction (which is one reason Hapmap based approaches don’t work well) RS00001 RS00003 RS00002 RS00004 RS00005

48. Gene/Protein Z Gene/Protein Y RS00011 RS00013 RS00012 RS00014 RS00015 Give them (predicted) direction Which helps in evaluating epidemiology studies RS00001 RS00003 RS00002 RS00004 RS00005

49. Gene/Protein Z Gene/Protein Y RS00011 RS00013 RS00012 RS00014 RS00015 Give them quantities (from Biochemistry and Epidemiology) Which makes them usable in SBML models But then also the interactions in the model need to have directions and quantities. RS00001 RS00003 RS00002 RS00004 RS00005

50. So we just have to color the jellies, ehhrm SNPs

51. Thanks!

52. Faculty of Health, Medicine and Life Sciences Where does this connect to you? What can you use? What do you need? Where can you contribute? What courses/training should be organized? And… where do you disagree? Also please fill the evaluation