1. HyQue: Evaluating scientific Hypotheses using semantic web technologies Michel Dumontier, PhD Associate professor of bioinformatics, department of biology, institute of biochemistry and school of computer science @ carleton university Professeur Associé, Département d’informatique et de génielogiciel, Université Laval

2. HyQue is a collaborative WORK Work performed by Alison Callahan, a PhD student under my supervision @ Carleton University Partnership with Dr. Nigam Shah, Assistant Professor at Stanford University

4. Source: http://kentsimmons.uwinnipeg.ca/cm1504/introscience.htm

5. with unparalleled growth in research outputs, Uncovering all the evidence to support/refute a hypothesis is becoming increasingly difficult Citations added to Medline 1995-2009 Source:http://www.nlm.nih.gov/bsd/stats/cit_added.html

7. minimum event-based vocabulary

8. uses consistency checking to evaluate hypotheses

9. constraints to ensure valid claims

10. rules to evaluate evidence

11. compares hypotheses using neighborhood functions

12. incremental hypothesis improvement[1] Racunas S. A., Shah N. H., Albert I. and Fedoroff N. V. (2004). HyBrow: A prototype system for computer-aided hypothesis evaluation. Bioinformatics 20(S. 1): i1-i8.

14. permease – gal2p – transports galactose into cells

15. galactokinase – gal1p

16. uridylyltransferase – gal7p

17. epimerase – gal10p

18. phosphoglucomutase –gal5p

19. Regulation – whether the pathway is on or off

20. gal3p

21. gal4p

23. Hypothesis h1: e1 (Gal4p induces expression of GAL1) h2: e2 (Gal3p induces expression of GAL2 e3AND Gal4p induces expression of GAL7) h3: e4 (Gal4p induces expression of GAL7 e5AND Gal80p inhibits production of Gal4p when GAL3 is over-expressed e6 AND Gal80p induces expression of GAL7) simple event-based expression conjunctive hypothesis – must satisfy two expressions conjunctive hypothesis with conditional expression

25. hard coded Perl rules

26. challenging to apply to a new domain

28. Bio2RDF is part of a growing web of linked data “Linking Open Data clouddiagram, by Richard Cyganiak and Anja Jentzsch. http://lod-cloud.net/”

29. The Semantic Web is a web of knowledge It is about standards for publishing, sharing and querying knowledge drawn from diverse sources It enables the answering of sophisticated questions

30. ontology as a strategy to formally represent knowledge

31. The Web Ontology Language (OWL) Has Explicit Semantics Can therefore be used to capture knowledge in a machine understandable way

33. Built on Semantic Web technologies

34. Background knowledge encoded as OWL ontologies

35. Queries against SPARQL endpoints

36. Context-specific rules that consider experimental conditions

37. consumesand producesRDF

40. proposition: “a statement expressing something true or false”

41. HyQue propositions only specify eventsHyQuehypothesis ≡ ‘proposition’ that ‘specifies’ only `event’) HyQuehypothesis ≡ ‘proposition’ that `has component part’ only (`proposition’ that ‘specifies’ only `event’)

42. Hyque events 1. protein-protein binding 2. protein-nucleic acid binding 3. molecular activation 4. molecular inhibition 5. gene induction 6. gene repression 7. transport

43. HyQue events Events are composed of conditional assertions on a relation between ‘actor’ and ‘target’ induces(agent, target, context, location) For decidable logic (OWL), an n-ary object is used Event ‘has agent’ agent ‘has target’ target ‘has context’ context ‘is located in’ location

44. All data are represented using Rdf hypothesis RDF’s basic representation unit is the “triple” <subject> <predicate> <object> :h rdf:typehyque:Hypothesis . :h hyque:has-component-part :p1 . :p1 rdf:typehyque:Proposition . has component part proposition specifies event: gal4p positively regulates the expression of GAL1

45. All data are represented using Rdf :h a hyque:Hypothesis; hyque:specifies :e1 . :e1 a <http://bio2rdf.org/go:0010628> <!– positive regulation of gene expression --> hyque:is_negated"0"; hyque:agent<http://bio2rdf.org/sgd:Gal4p> ; hyque:target<http://bio2rdf.org/sgd:GAL1> ; …. hypothesis specifies event: gal4p positively regulates the expression of GAL1

46. User interface facilitates designing the hypothesis

47. Template SPARQL queries completed based on event properties Hypothesis + SPARQL Template => SPARQL query binding :e1 a go:0010628; hyque:is_negated"0" ; hyque:agentsgd:Gal4p; hyque:targetsgd:GAL1 . construct { … } where { ?event hyque:is_negated?negated . ?event hyque:logical_operator?logical_operator . ?event hyque:agent <http://bio2rdf.org/sgd:Gal4p> . ?event hyque:target<http://bio2rdf.org/sgd:GAL1> . … }

48. SPARQL query results retrieved positive regulation of gene expression hybrow_data:f0957524deecae38945736737cc07d45 hyque:logical_operator<http://bio2rdf.org/go:0010628> ; hyque:is_negated"0" ; hyque:agent <http://bio2rdf.org/sgd:Gal4p> ; hyque:target <http://bio2rdf.org/sgd:GAL1>; hyque:agent_type <http://bio2rdf.org/chebi:36080> ; hyque:target_type <http://bio2rdf.org/so:0000236> ; hyque:location <http://bio2rdf.org/go:0005634> ; hyque:agent_function_type <http://bio2rdf.org/go:0003700> . Protein Gene Nucleus Transcription factor activity

49. Query results evaluated based on rule sets ‘induce’ rule (maximum score: 5): Is event negated? If yes, subtract 2 Is logical operator ‘induce’? If yes, add 1; if no, subtract 1 Is agent of type ‘protein’ or ‘RNA’? If yes, add 1; if of type ‘gene’, subtract 1 Is target of type ‘gene’? If yes, add 1; if no, subtract 1 Does agent have known ‘transcription factor activity’? If yes, add 1 Is event located in the ‘nucleus’? If yes, add 1; if no, subtract 1 GO:0010628 CHEBI:36080 SO:0000236 GO:0003700 GO:0005634

51. Target of type ‘gene’: yes -> +1

52. Agent has function ‘transcription factor activity’: no -> 0

53. Event location is ‘nucleus’: yes -> +1

54. Logical operator is ‘induce’: yes -> +1

55. Event negated in published literature: no -> 0Thus, the e1 event obtains 4 out of a maximum of 5 points, and receives a score of 0.8.

56. Evaluating hypotheses Events e2, e3, and e4 are also ‘induce’ events and are evaluated using the ‘induce’ rule set, each obtaining a score of 0.8. e5 is undecidable- no data to support that Gal80p inhibits Gal4p when GAL3 is over-expressed in HKB -> third entire event set is deemed undecidable. Overall hypothesis score selected from e1 (0.8), e2 + e3 (0.8+0.8=1.6) Final hypothesis score is 1.6 + events e2 + e3 have the strongest experimental support. e1 (Gal4p induces expression of GAL1) OR e2 (Gal3p induces expression of GAL2 e3AND Gal4p induces expression of GAL7) OR e4 (Gal4p induces expression of GAL7 e5AND Gal80p inhibits production of Gal4p when GAL3 is over-expressed e6 AND Gal80p induces expression of GAL7)

57. Hypothesis evaluation represented as rdf

58. Browse hypothesis and evaluation as linked data

59. The Semantic Automated Discovery and Integration (SADI) framework makes it easy to create Semantic Web services using OWL classes as service inputs and outputs http://sadiframework.org Users can post a hypothesis in RDF and receive the hypothesis evaluation RDF Mark Wilkinson, UBC Michel Dumontier, Carleton University Christopher Baker, UNB HyQue can become part of a workflow for investigations

61. Expand beyond the GAL network with network reconstructions and NLP facilitated data curation

63. Acknowledgements Alison Callahan (developing HyQue) Nigam Shah (key collaborator) Stephen Racunas and Amar Das for helpful discussions Bio2RDF: Peter Ansell, Francois Belleau, Allison Callahan, Jacques Corbeil, Jose Cruz-Toledo, Alex De Leon, Steve Etlinger, James Hogan, Nichealla Keith, Jean Morissette, Marc-Alexandre Nolin, Nicole Tourigny, Philippe Rigault and, Paul Roe SADI: Christopher Baker, Melanie Courtot, Jose Cruz-Toledo, Steve Etlinger, Nichealla Keith, Artjom Klein, Luke McCarthy, SilvanePaixao, Ben Vandervalk, Natalia Villanueva-Rosales, Mark Wilkinson

64. dumontierlab.com michel_dumontier@carleton.ca