The Semantic Web is an emerging web of knowledge. It provides the basis upon which we can publish, share and link data, and perhaps more saliently, to use computers to reason about increasingly complex information using background knowledge. From the dream to using triples as a currency to pay for it, this talk will illustrate the application of Semantic Web technologies for biological knowledge discovery while touching on issues in knowledge representation, RDFizing, large scale data integration and convergence with semantic web services.

1. Triples for the People (Scientists): Liberating biological knowledge with the Semantic Web 1 Ottawa/Chicago Semantic Web Meetup : 23-11-09 Michel Dumontier, Ph.D. Associate Professor of Bioinformatics Carleton University Department of Biology School of Computer Science Institute of Biochemistry Ottawa Institute of Systems Biology Ottawa-Carleton Institute of Biomedical Engineering

2. Web-based Knowledge Discovery a very painful process Carole Goble (ISWC 2005) 2 Ottawa/Chicago Semantic Web Meetup : 23-11-09

3. With current web search engines… It takes a lot of digging to get answers 3 Ottawa/Chicago Semantic Web Meetup : 23-11-09

4. Portals provide structured information and give better results 4 Ottawa/Chicago Semantic Web Meetup : 23-11-09

5. We need to expose the deep web Surface web:167 terabytes Deep web:91,000 terabytes 545-to-one Ottawa/Chicago Semantic Web Meetup : 23-11-09 5

6. Data silos – not made for sharing 6 Ottawa/Chicago Semantic Web Meetup : 23-11-09

7. We want to simultaneously query the 1000+ biological databases 7 Ottawa/Chicago Semantic Web Meetup : 23-11-09

8. How do we integrate these resources? 8 Ottawa/Chicago Semantic Web Meetup : 23-11-09

9. The Semantic Web is a web of knowledge. 9 Ottawa/Chicago Semantic Web Meetup : 23-11-09 It is about standards for publishing, sharing and querying knowledge drawn from diverse sources It enables the answering of sophisticated questions

10. A growing web of linked data 10 Ottawa/Chicago Semantic Web Meetup : 23-11-09

11. Bio2RDF provides a framework to glue to link data networks together 11 Ottawa/Chicago Semantic Web Meetup : 23-11-09

12. Resource Description Framework (RDF) Allows one to talk about anything Uniform Resource Identifier (URI) can be used as entity names http://bio2rdf.org/uniprot:P05067 is a name for Amyloid precursor protein http://bio2rdf.org/omim:104300 is a name for Alzheimer disease uniprot:P05067 omim:104300 12 Ottawa/Chicago Semantic Web Meetup : 23-11-09

14. Predicate: resource identified by a URI

15. Object: resource or literaluniprot:P05067 is a Protein 13 Ottawa/Chicago Semantic Web Meetup : 23-11-09

16. Multi-Source Data Integration depends on consistent naming uniprot:P05067 Protein Protein is a UniProt has name + uniprot:P05067 Membrane uniprot:P05067 Membrane located in located in Gene Ontology + uniprot:P05067 interacts with uniprot:P05067 uniprot:P05067 interacts with Unified view iRefIndex 14 Ottawa/Chicago Semantic Web Meetup : 23-11-09

17. Building statements creates knowledge Amyloid precursor protein Alzheimer Disease label label is involved in uniprot:P05067 omim:104300 is a is a Protein Disease 15 Ottawa/Chicago Semantic Web Meetup : 23-11-09

18. RDF has multiple representations RDF/XML <?xml version="1.0"?> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:u="http://purl.uniprot.org/uniprot/" <rdf:Descriptionrdf:about=“&u;Q16665"> <rdf:typerdf:resource=“&u;Protein"/> </rdf:Description> </rdf:RDF> RDF/N3 PREFIX u: <http://purl.uniprot.org/uniprot/> . <u:Q16665> a <u:Protein> . 16 16 Ottawa/Chicago Semantic Web Meetup : 23-11-09

19. Bio2RDF’s RDFized data fits together Ottawa/Chicago Semantic Web Meetup : 23-11-09 17

20. Bio2RDF serves up over 4 billion triples of linked biological data 18 Ottawa/Chicago Semantic Web Meetup : 23-11-09

21. something you can lookup or search for with rich descriptions 19 Ottawa/Chicago Semantic Web Meetup : 23-11-09

22. Bio2RDF: Raw Data! Ottawa/Chicago Semantic Web Meetup : 23-11-09 20

23. 21 SPARQL is the new cool kid on the block SQLSPARQL Ottawa/Chicago Semantic Web Meetup : 23-11-09

24. Bio2RDF’s describe service uses SPARQL CONSTRUCT { ?s ?p ?o . } WHERE { ?s ?p ?o . FILTER(?s = <http://bio2rdf.org/ns:id>). } Sent to http://ns.bio2rdf.org/sparql?query=... 22 Ottawa/Chicago Semantic Web Meetup : 23-11-09 http://bio2rdf.org/ns:id

25. Bio2RDF’s search service uses SPARQLhttp://bio2rdf.org/search/hexokinase 23 Ottawa/Chicago Semantic Web Meetup : 23-11-09 bio2rdf.org kegg gene uniprot

26. Yai for data! 24 Ottawa/Chicago Semantic Web Meetup : 23-11-09 But how do we discover more than what was in the data?

27. Ontology as Strategy 25 Ottawa/Chicago Semantic Web Meetup : 23-11-09

28. Reasoning and Inference through Semantics fact uniprot:P05067 is a is a Protein is a Molecule ontology Knowledge base 26 Ottawa/Chicago Semantic Web Meetup : 23-11-09

29. Logic Based Ontologies Are Conceptual Lego 27 Ottawa/Chicago Semantic Web Meetup : 23-11-09

30. A simple ontology: Animals Living Thing Body Part eats has part Plant Arm Animal eats Grass Leg eats Herbivore Tree Person Carnivore Cow 28 Ottawa/Chicago Semantic Web Meetup : 23-11-09

31. The Web Ontology Language (OWL) Has Explicit Semantics Can therefore be used to capture knowledge in a machine understandable way 29 Ottawa/Chicago Semantic Web Meetup : 23-11-09

33. Protein is a subclass of Molecule

34. Molecule is a superclass of Protein

35. Molecule subsumes Protein30 Ottawa/Chicago Semantic Web Meetup : 23-11-09

36. Key Idea: Disjunction DNA Protein Stating that 2 classes are disjoint means = individual Something cannot be both an Protein and DNA This can help us find errors 31 Ottawa/Chicago Semantic Web Meetup : 23-11-09

37. Key Idea: Class equivalence By stating the necessary and sufficient conditions we discover new knowledge Transcription Factor “A protein that binds to DNA and regulates gene expression. Ottawa/Chicago Semantic Web Meetup : 23-11-09 32

38. Many ontologies required Barry smith Ottawa/Chicago Semantic Web Meetup : 23-11-09 33

39. Over 170 bio-ontologies Ottawa/Chicago Semantic Web Meetup : 23-11-09 34

40. We’re interested in Personalized Medicine The ability to offer The Right Drug To The Right Patient For The Right Disease At The Right Time With The Right Dosage Genetic and metabolic data will allow drugs to be tailored to patient subgroups 35 Ottawa/Chicago Semantic Web Meetup : 23-11-09

41. PHARMGKB is an emerging resource for pharmacogenomics + Role of genes, gene variants , drugs + pharmacokinetics + pharmacodynamics + clinical outcomes. + Links to publications - Natural language descriptions - Variant details in publications 36 Ottawa/Chicago Semantic Web Meetup : 23-11-09

42. Pharmacogenomics of Depression KNOWLEDGE BASE contains statements from 11/40 relevant publications involving 45 genes / gene variants, 57 drugs annotated with 19 classes of antidepressants, 45 drug treatments, 47 drug-gene interactions, 29 clinical outcomes, 10 drug-induced side-effects, and 8 gene-disease interactions. 37 Ottawa/Chicago Semantic Web Meetup : 23-11-09

43. Protégé 4, FaCT++, DL Query Tab Querying the PDKB Nortriptyline induced side effects for ABCB1 gene variants ‘side effect’ that ‘is realized by’ some (‘drug treatment’ that ‘involves’ some ‘nortriptyline’ and ‘involves’ some (‘variant of’ some ‘ABCB1’)) 38 Ottawa/Chicago Semantic Web Meetup : 23-11-09 postural hypotension is a side effect of nortriptyline treatment of depression for individuals presenting the 3435C>T genotype

44. Web-based Knowledge Discovery Some of our queries need services 39 Ottawa/Chicago Semantic Web Meetup : 23-11-09

45. The Holy Grail: Align the promoters of all serine threoninekinases involved exclusively in the regulation of cell sorting during wound healing in blood vessels. Retrieve and align 2000nt 5' from every serine/threoninekinase in Musmusculus expressed exclusively in the tunica [I | M |A] whose expression increases 5X or more within 5 hours of wounding but is not activated during the normal development of blood vessels, and is <40% homologous in the active site to kinases known to be involved in cell-cycle regulation in any other species. 40 Ottawa/Chicago Semantic Web Meetup : 23-11-09

46. 41 Ottawa/Chicago Semantic Web Meetup : 23-11-09

47. Semantic Automated Discovery and Integration http://sadiframework.org 42 Ottawa/Chicago Semantic Web Meetup : 23-11-09 Mark Wilkinson, UBC Michel Dumontier, Carleton University Christopher Baker, UNB

48. As OWL AxiomsHomologousGeneImageis owl:equivalentTo { Gene Q hasImage image P Gene Q hasSequence Sequence Q Gene R hasSequence Sequence R Sequence Q similarTo Sequence R Gene R = “my gene of interest” } 43 Ottawa/Chicago Semantic Web Meetup : 23-11-09

49. Build a knowledge base from a series of questions 44 Ottawa/Chicago Semantic Web Meetup : 23-11-09

50. You want to join the knowledge web 45 Ottawa/Chicago Semantic Web Meetup : 23-11-09

51. Share your data 46 Ottawa/Chicago Semantic Web Meetup : 23-11-09

52. Bridge your data with others in semantic communities 47 Ottawa/Chicago Semantic Web Meetup : 23-11-09

53. Time-sensitive or frequently updated data is one way to encourage more visits. 48 Ottawa/Chicago Semantic Web Meetup : 23-11-09

54. 49 Ottawa/Chicago Semantic Web Meetup : 23-11-09

55. 50 Ottawa/Chicago Semantic Web Meetup : 23-11-09

56. The Knowledge Web • Merging data & services • Reasoning & question answering • Persistent (RESTful) • Trust & Security Data consumers must be able to rely upon your data to use it as a foundation for their own applications. 51 Ottawa/Chicago Semantic Web Meetup : 23-11-09

57. Join the knowledge web. 52 Ottawa/Chicago Semantic Web Meetup : 23-11-09

58. dumontierlab.com michel_dumontier@carleton.ca 53 Ottawa/Chicago Semantic Web Meetup : 23-11-09