2011 ebi industry workshop
TRANSCRIPT
![Page 1: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/1.jpg)
1 2011-EBI-Industry-SW::Dumontier
Predicting Druglikeness and Toxicity from Integrated Data and Services on
the Life Science Semantic Web
Michel Dumontier, Ph.D.
Associate Professor of Bioinformatics, Department of Biology, School of Computer Science, Institute of Biochemistry, Carleton University
Professeur Associé, Département d’informatique et de génielogiciel, Université Laval
Ottawa Institute of Systems BiologyOttawa-Carleton Institute of Biomedical Engineering
![Page 2: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/2.jpg)
2 2011-EBI-Industry-SW::Dumontier
Is caffeine a drug-like molecule?
Is acetaminophen toxic?
![Page 3: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/3.jpg)
3 2011-EBI-Industry-SW::Dumontier
Finding the right information to answer a question is hardand sometimes requires a sophisticated workflow
![Page 4: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/4.jpg)
4 2011-EBI-Industry-SW::Dumontier
![Page 5: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/5.jpg)
5 2011-EBI-Industry-SW::Dumontier
What if we could answer a question by automatically building a knowledge base
using both data and services?
![Page 6: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/6.jpg)
6 2011-EBI-Industry-SW::Dumontier
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
![Page 7: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/7.jpg)
7 2011-EBI-Industry-SW::Dumontier
To answer this question we need to know:
• what ‘drug like molecule’ really means• caffeine’s molecular structure• the ability to compute the relevant attributes• determine whether caffeine satisfies the requirements of being ‘drug like’
Is caffeine a drug-like molecule?
![Page 8: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/8.jpg)
8 2011-EBI-Industry-SW::Dumontier
Lipinski Rule of Five
• Rule of thumb for druglikeness (orally active in humans)(4 rules with multiples of 5)– mass of less than 500 Daltons– fewer than 5 hydrogen bond donors– fewer than 10 hydrogen bond acceptors– A partition coefficient value between -5 and 5
We need a more formal (machine understandable) description of a ‘drug-like molecule’ which specifies values for chemical descriptors
![Page 9: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/9.jpg)
9 2011-EBI-Industry-SW::Dumontier
ontology as a strategy to
formally represent knowledge
![Page 10: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/10.jpg)
10 2011-EBI-Industry-SW::Dumontier
The Web Ontology Language (OWL) Has Explicit Semantics
Can therefore be used to capture knowledge in a machine understandable way
![Page 11: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/11.jpg)
11 2011-EBI-Industry-SW::Dumontier
Semanticscience Integrated Ontology (SIO)
• OWL2 ontology• 900+ classes covering basic types (physical, processual, abstract,
informational) with an emphasis on biological entities• 169 basic relations (mereological, participatory, attribute/quality,
spatial, temporal and representational)• axioms can be used by reasoners to generate inferences for
consistency checking, classification and answering questions about life science knowledge
• embodies emerging ontology design patterns – specifies the representation of knowledge
• dereferenceable URIs• searchable in the NCBO bioportal• Available at http://semanticscience.org/ontology/sio.owl
![Page 12: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/12.jpg)
12 2011-EBI-Industry-SW::Dumontier
![Page 13: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/13.jpg)
2011-EBI-Industry-SW::Dumontier
The Chemical Information Ontology (CHEMINF)
• 100+ chemical descriptors• 50+ chemical qualities• Relates descriptors to their
specifications, the software that generated them (along with the running parameters, and the algorithms that they implement)
• Contributors: Nico Adams, Leonid Chepelev, Michel Dumontier, Janna Hastings, Egon Willighagen, Peter Murray-Rust, Cristoph Steinbeck
13
http://semanticchemistry.googlecode.com
![Page 14: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/14.jpg)
2011-EBI-Industry-SW::Dumontier
Molecular structure can be represented using a SMILES string, which is a common representation
of the chemical graph
14
ball & stick model for caffeine
SMILES string for caffeine
Cn1cnc2n(C)c(=O)n(C)c(=O)c12
![Page 15: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/15.jpg)
15 2011-EBI-Industry-SW::Dumontier
Lipinski Rule of Five• Empirically derived ruleset for druglikeness
(4 rules with multiples of 5)– mass of less than 500 Daltons– fewer than 5 hydrogen bond donors– fewer than 10 hydrogen bond acceptors– A partition coefficient value between -5 and 5
• A formal description using OWL:
![Page 16: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/16.jpg)
2011-EBI-Industry-SW::Dumontier
What we then need are services that will consume SMILES strings and annotate the molecule with the required chemical
descriptors
16
then we can reason about whether it satisfies the drug-likeness definition
![Page 17: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/17.jpg)
2011-EBI-Industry-SW::Dumontier
Semantic Automated Discovery and Integration
http://sadiframework.org
Mark Wilkinson, UBCMichel Dumontier, Carleton UniversityChristopher Baker, UNB
SADI is a framework to create Semantic Web services using OWL classes as service inputs and outputs
17
![Page 18: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/18.jpg)
2011-EBI-Industry-SW::Dumontier
Create code stubs using the ontology
• Publish the ontology to a web-accessible locationhttp://semanticscience.org/sadi/ontology/lipinskiserviceontology.owl
• Make sure that the class names are resolvable(easy when using the hash notation)
http://semanticscience.org/sadi/ontology/lipinskiserviceontology.owl#smiles-moleculehttp://semanticscience.org/sadi/ontology/lipinskiserviceontology.owl#logp-moleculehttp://semanticscience.org/sadi/ontology/lipinskiserviceontology.owl#hbdc-moleculehttp://semanticscience.org/sadi/ontology/lipinskiserviceontology.owl#hdba-moleculehttp://semanticscience.org/sadi/ontology/lipinskiserviceontology.owl#lipinksi-druglike-molecule
• Download/checkout the codehttp://sadiframework.org
• Run the code generator (Java, Perl, python)– specify the URIs that correspond to input and output types
• Implement the functionality– We used the Chemistry Development Kit (CDK) to implement 4 services
18
![Page 19: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/19.jpg)
2011-EBI-Industry-SW::Dumontier
Responds to a GET operation by providing the service description in RDF
conforms to Feta (BioMoby, myGrid)
19
curl http://cbrass.biordf.net/logpdc/logpc
<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:j.0="http://www.mygrid.org.uk/mygrid-moby-service#" > <rdf:Description rdf:about=""> <j.0:hasServiceDescriptionText>no description</j.0:hasServiceDescriptionText> <j.0:hasServiceNameText rdf:datatype="http://www.w3.org/2001/XMLSchema#string">logpc</j.0:hasServiceNameText> <j.0:hasOperation rdf:resource="#operation"/> <rdf:type rdf:resource="http://www.mygrid.org.uk/mygrid-moby-service#serviceDescription"/> </rdf:Description> <rdf:Description rdf:about="#input"> <j.0:objectType rdf:resource="http://semanticscience.org/sadi/ontology/lipinskiserviceontology.owl#smilesmolecule"/> <rdf:type rdf:resource="http://www.mygrid.org.uk/mygrid-moby-service#parameter"/> </rdf:Description> <rdf:Description rdf:about="#operation"> <j.0:outputParameter rdf:resource="#output"/> <j.0:inputParameter rdf:resource="#input"/> <rdf:type rdf:resource="http://www.mygrid.org.uk/mygrid-moby-service#operation"/> </rdf:Description> <rdf:Description rdf:about="#output"> <j.0:objectType rdf:resource="http://semanticscience.org/sadi/ontology/lipinskiserviceontology.owl#alogpsmilesmolecule"/> <rdf:type rdf:resource="http://www.mygrid.org.uk/mygrid-moby-service#parameter"/> </rdf:Description></rdf:RDF>
![Page 20: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/20.jpg)
2011-EBI-Industry-SW::Dumontier
Responds to a POST containing service input with a service output in RDF
20
<rdf:Description rdf:about="http://semanticscience.org/sadi/ontology/caffeine.rdf#mdalogp"> <rdf:type rdf:resource="http://semanticscience.org/resource/CHEMINF_000251"/> <j.0:SIO_000300 rdf:datatype="http://www.w3.org/2001/XMLSchema#double">-0.4311000000000006</j.0:SIO_000300> </rdf:Description>
<rdf:RDF xmlns="http://semanticscience.org/sadi/ontology/caffeine.rdf#" xmlns:so="http://semanticscience.org/sadi/ontology/lipinskiserviceontology.owl#" xmlns:owl="http://www.w3.org/2002/07/owl#" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:sio="http://semanticscience.org/resource/" xmlns:xsd="http://www.w3.org/2001/XMLSchema#"> <so:smilesmolecule rdf:about="http://semanticscience.org/sadi/ontology/caffeine.rdf#m"> <sio:SIO_000008 rdf:resource = "http://semanticscience.org/sadi/ontology/caffeine.rdf#msmiles"/> </so:smilesmolecule> <sio:CHEMINF_000018 rdf:about = "http://semanticscience.org/sadi/ontology/caffeine.rdf#msmiles"> <sio:SIO_000300 rdf:datatype="xsd:string">Cn1cnc2n(C)c(=O)n(C)c(=O)c12</sio:SIO_000300> </sio:CHEMINF_000018></rdf:RDF>
The response is in RDF:
The query is in RDF:
![Page 21: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/21.jpg)
21 2011-EBI-Industry-SW::Dumontier
61 Chemical Semantic Web Services
• these and an increasing number of semantic web services are registered at http://sadiframework.org/registry/services/
![Page 22: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/22.jpg)
2011-EBI-Industry-SW::Dumontier
Now what?
22
![Page 23: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/23.jpg)
2011-EBI-Industry-SW::Dumontier23
Semantic Health and Research Environment
SHARE is an application that execute (SPARQL) queries as workflows over SADI Services
![Page 24: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/24.jpg)
2011-EBI-Industry-SW::Dumontier
“Reckoning”
dynamic discovery of instances of OWL classes through synthesis and invocation of a Web Service workflow capable of generating data described by the OWL class restrictions, followed by reasoning to classify the data
into that ontology
24
![Page 25: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/25.jpg)
2011-EBI-Industry-SW::Dumontier
ChEBI publishes (non-SW) data!
25
![Page 26: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/26.jpg)
2011-EBI-Industry-SW::Dumontier
Bio2RDF provides ChEBI in RDF
26
![Page 27: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/27.jpg)
27 2011-EBI-Industry-SW::Dumontier
Bio2RDF covers the major biological databases
![Page 28: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/28.jpg)
28
Bio2RDF’s RDFized data fits together
![Page 29: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/29.jpg)
29
Resource Description Framework (RDF)
Uniform Resource Identifier (URI) can be used as entity names
Bio2RDF specifies the naming convention
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
Allows one to talk about anything
![Page 30: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/30.jpg)
30
Life Science Dataset Registry Coordinates Naming
• Provides stable URI patterns for records and the entities they describe.
Directory Service• ~1500 datasets & dozens of resolvers.
Discovery Service• Registry links entities to records and their representations (RDF/XML,
HTML, etc) and provider (Bio2RDF, Uniprot)
Redirection Service• Automatic redirection to data provider document
Stanford : 22-04-2010
![Page 31: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/31.jpg)
31 2011-EBI-Industry-SW::Dumontier
Bio2RDF is now serving over 40 billion triples of linked biological data
![Page 32: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/32.jpg)
32
Bio2RDF is a framework to create and provision linked data networks
Francois Belleau, Laval UniversityMarc-Alexandre Nolin, Laval University
Peter Ansell, Queensland University of TechnologyMichel Dumontier, Carleton University
![Page 33: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/33.jpg)
33 2011-EBI-Industry-SW::Dumontier
Bio2RDF is part of a growing web of linked data
“Linking Open Data cloud diagram, by Richard Cyganiak and Anja Jentzsch. http://lod-cloud.net/”
![Page 34: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/34.jpg)
34 2011-EBI-Industry-SW::Dumontier
something you can lookup or search for with rich descriptions
![Page 35: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/35.jpg)
35 2011-EBI-Industry-SW::Dumontier
SPARQL is the new cool kid on the query block
SQL SPARQL
![Page 36: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/36.jpg)
2011-EBI-Industry-SW::Dumontier
Query for log p
36
![Page 37: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/37.jpg)
2011-EBI-Industry-SW::Dumontier37
![Page 38: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/38.jpg)
2011-EBI-Industry-SW::Dumontier
Query: Is caffeine a drug-like molecule?
38
![Page 39: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/39.jpg)
39 2011-EBI-Industry-SW::Dumontier
![Page 40: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/40.jpg)
2011-EBI-Industry-SW::Dumontier
Benefits
• Data remains distributed – as the internet was meant to be!
• Data is not “exposed” as a SPARQL endpoint– greater provider-control over computational resources
• Service invocation is straightforward and matchmaking by reasoning about ontology-based input/output descriptions
40
![Page 41: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/41.jpg)
41 2011-EBI-Industry-SW::Dumontier
Is acetaminophen toxic?
• Classical approaches involve decision trees or machine learning over validated data.
• Algorithms are often proprietary, even by the regulatory agencies
• Issues around which data was used, and what the informative parameters are, and how easily can new information affect the outcomes?
![Page 42: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/42.jpg)
42 2011-EBI-Industry-SW::Dumontier
OWLED2011 : Large-Scale Boolean Feature Based Trees as OWL ontologies
![Page 43: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/43.jpg)
43 2011-EBI-Industry-SW::Dumontier
DL Reasoners give Explanations
![Page 44: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/44.jpg)
44 2011-EBI-Industry-SW::Dumontier
Summary
• Semantic Web technologies offer tantalizing ability to create and share data and services for drug discovery– Bio2RDF provides linked life science data– SADI provides a framework to provide semantic web
services– SHARE allows us to simultaneously query and reason
about data and services represented using RDF/OWL– Expressive ontologies can be used to make toxicity
decisions transparent
![Page 45: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/45.jpg)
2011-EBI-Industry-SW::Dumontier45
Acknowledgements
Bio2RDF: Peter Ansell, Francois Belleau, Allison Callahan, Jacques Corbeil, Jose Cruz-Toledo, Alex De Leon, Steve Etlinger, James Hogan, Nichealla Keath, Jean Morissette, Marc-Alexandre Nolin, Nicole Tourigny, Philippe Rigault and, Paul Roe
SADI: Christopher Baker, Melanie Courtot, Jose Cruz-Toledo, Steve Etlinger, Nichealla Keath, Artjom Klein, Luke McCarthy, Silvane Paixao, Ben Vandervalk, Natalia Villanueva-Rosales, Mark Wilkinson
CHEMINF GroupLeo ChepelevJanna HastingsEgon WillighagenNico Adams
Toxicity GroupLeo ChepelevDana Klassen
![Page 46: 2011 ebi industry workshop](https://reader036.vdocuments.net/reader036/viewer/2022070315/554e8ec5b4c90573338b4c80/html5/thumbnails/46.jpg)
46 2011-EBI-Industry-SW::Dumontier
Website: http://dumontierlab.com Presentations: http://slideshare.com/micheldumontier