Bio2RDF : A Semantic Web Atlas of post genomic knowledge about Human and Mouse
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Transcript of Bio2RDF : A Semantic Web Atlas of post genomic knowledge about Human and Mouse
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BIO2RDF : A Semantic Web Atlas of post genomic knowledge about
Human and Mouse
François Belleau, Nicole Tourigny, Benjamin Good and Jean Morissette
● Centre de Recherche du CHUL, Université Laval● Département d'informatique et de génie logiciel, Université Laval
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Vaugondy, Louis XV geograph, view of the world in the 18th century
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Google Map view of the world in the 21th century
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Evry, June 27, 2008 CHUL research center Laval University 4
Outline
Introduction
− Problem definition− Proposed approach− The 4 rules of linked data− Related Work
Results
− Bio2RDF first knowledge map− Semantic ranking
Paget query demo with SPARQL
Future work and Conclusion
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Evry, June 27, 2008 CHUL research center Laval University 5
Problem definition
● The objective of data integration is to make data distributed over a number of distinct, heterogeneous databases accessible via a single interface [Davidson 1995].
● We already use global text search engine on the web (Google, Yahoo).
● There is many specialized integrated search tools in bioinformatics (NCBI Entrez, EBI search, KEGG GenomeNet).
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Evry, June 27, 2008 CHUL research center Laval University 6
What is known about « Paget disease» ?
but first ...
What is known about the mouse and human
genomes ?
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Evry, June 27, 2008 CHUL research center Laval University 7
Popular web search engines without semantic
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Evry, June 27, 2008 CHUL research center Laval University 8
Some Bioinformatics integrated search tools
● EMBL-EBI EB-eye search● KEGG GenomeNet● NCBI Entrez
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Evry, June 27, 2008 CHUL research center Laval University 9
EMBL-EBI search
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Evry, June 27, 2008 CHUL research center Laval University 10
NCBI Entrez life science searchacross databases
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Evry, June 27, 2008 CHUL research center Laval University 11
KEGG GenomeNet search
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Evry, June 27, 2008 CHUL research center Laval University 12
Bio2RDF search
What is known about Paget disease in the mouse and
human genomes ?
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Evry, June 27, 2008 CHUL research center Laval University 13
Proposed approach
● Apply the semantic web model to data integration in bioinformatics;
● Use a PageRank [Brin 1998] variation adapted to semantic graph, a method analog to Aleman-Meza group's work: the LinkRank;
● Adopt standard (RDF, OWL) and use existing software (Sesame, Virtuoso, PiggyBank).
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Evry, June 27, 2008 CHUL research center Laval University 14
Outline
Introduction
− Problem definition− Proposed approach− The 4 rules of linked data− Related Work
Results
− Bio2RDF first knowledge map− Semantic ranking
Paget query demo with SPARQL
Future work and Conclusion
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Evry, June 27, 2008 CHUL research center Laval University 15
Linked data 4 rules
http://www.w3.org/DesignIssues/LinkedData
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Evry, June 27, 2008 CHUL research center Laval University 16
Rule #1: Use URIs as names for things.● Using normalized identifier to name
concept is already a reality in biology domain.
● Hexokinase is GO:0004396● Definition :
− Catalysis of the reaction: ATP + D-hexose = ADP + D-hexose 6-phosphate.
● Synonym of EC:2.7.1.1
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Evry, June 27, 2008 CHUL research center Laval University 17
Rule #2 : Use HTTP URIs so that people can look up those names.● Derefencable URL ● The Banff Manifesto rule for URN
− urn:bm:public_namespace:private_identifier● Normalized URL according to Banff
Manifesto: http://bio2rdf.org/public_namespace:private_identifier
● http://bio2rdf.org/go:0004396
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Evry, June 27, 2008 CHUL research center Laval University 18
Rule #3 When someone looks up a URI, provide useful information.
● http://bio2rdf.org/go:0004396 returns the RDF graph of this topic
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Rule #4 :Include links to other URIs so that they can discover more things.
●Openess Ratio > 0 (to be defined)
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Evry, June 27, 2008 CHUL research center Laval University 20
Outline
Introduction
− Problem definition− Proposed approach− The 4 rules of linked data− Related Work
Results
− Bio2RDF first knowledge map− Semantic ranking
Paget query demo with SPARQL
Future work and Conclusion
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Evry, June 27, 2008 CHUL research center Laval University 21
Related work
● DBPedia● YeastHub● UniProt● HCLS linked data● Bio2RDF architecture
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Evry, June 27, 2008 CHUL research center Laval University 22
Related work – Linked data map
http://wiki.dbpedia.org/Interlinking
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Evry, June 27, 2008 CHUL research center Laval University 23
Related work – Linked data map
● If we were to draw a map of the existing relations between linked data from bioinformatics database providers, what would it look like?
● Could we measure the amount of post genomic knowledge available related to a mouse or human genome sequence?
● Could it help answer the what is known question?
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Related work – YeastHub
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Related work – UniProt beta
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Related work – HCLS demo
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Evry, June 27, 2008 CHUL research center Laval University 27
Bio2RDF architecture
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Evry, June 27, 2008 CHUL research center Laval University 28
Bio2RDF actual datasources loaded in the Atlas graph
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Evry, June 27, 2008 CHUL research center Laval University 29
Outline
Introduction
− Problem definition− Proposed approach− The 4 rules of linked data− Related Work
Results
− Bio2RDF first knowledge map− Semantic ranking
Paget query demo with SPARQL
Future work and Conclusion
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What is known about human and mouse genome in 2008?
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Evry, June 27, 2008 CHUL research center Laval University 31
What is Bioinformatics linked data ?
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Evry, June 27, 2008 CHUL research center Laval University 32
http://bio2rdf.org/map
Bio2RDF linked data map is a first answer attempt
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Evry, June 27, 2008 CHUL research center Laval University 33
Outline
Introduction
− Problem definition− Proposed approach− The 4 rules of linked data− Related Work
Results
− Bio2RDF first knowledge map− Semantic ranking
Paget query demo with SPARQL
Future work and Conclusion
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Evry, June 27, 2008 CHUL research center Laval University 34
Semantic Web Ranking
● Openess Ratio● Averange Link Rank● Semantic weight
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Openess Ratio
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Average Link Rank
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Semantic Weight
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Evry, June 27, 2008 CHUL research center Laval University 38
The semantic mashup effect
OR = 0ALR = 2MeSH
OR = 1ALR = 1GeneID
OR = 0,5ALR = 1,5PubMed
mean OR = 0,5mean ALR = 1,5
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Evry, June 27, 2008 CHUL research center Laval University 39
The semantic mashup effect
OR = 0ALR = 2,3
MeSH
OR = 1ALR = 1GeneID
OR = 0,5ALR = 1,5PubMed
mean OR = 0,4mean ALR = 1,6
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Bio2RDF statistics by datasource
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Bio2RDF actual 30 datasources
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MeSH : OR = 0
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Pubmed: OR = 0,5
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GeneID : OR = 1
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Bio2RDF : OR = 0,630 datasources, 225 namespaces
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Evry, June 27, 2008 CHUL research center Laval University 46
Knowledge gain of 0,19
From 0,77 to 0,58
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Evry, June 27, 2008 CHUL research center Laval University 47
Bio2RDF Semantic Web Atlas in numbers
● 30 different datasources, 30 different namespaces
− go, geneid, uniprot, pubmed, pdb, reactome, omim, etc.
● 195 namespaces referencing non-rdfized datasource
− cog, genethon, tigr, cath, goa, etc.
● 8 millions topics● 65 millions triples● 973 Mo, size of N3 format compressed data
− http://bio2rdf.org/download/bio2rdf-atlas-080414.n3.gz
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Evry, June 27, 2008 CHUL research center Laval University 48
Bio2RDF Semantic Web Atlas in statistics
● Openess Ratio (OR) of 0.58● Averange Link Rank (ALR) of 4.7● 8 millions topics are connected by 19 millions
relations within the graph● 58 % of URIs are referencing the open world
outside the graph● 19 % of knowledge gain because of the mashup
effect
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Evry, June 27, 2008 CHUL research center Laval University 49
Outline
Introduction
− Problem definition− Proposed approach− The 4 rules of linked data− Related Work
Results
− Bio2RDF first knowledge map− Semantic ranking
Paget query demo with SPARQL
Future work and Conclusion
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Evry, June 27, 2008 CHUL research center Laval University 50
Bio2RDF search demo with SPARQL
What is known about Paget disease in the mouse and
human genomes ?
Submitted athttp://bio2rdf.org:8890/sparql
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Evry, June 27, 2008 CHUL research center Laval University 51
Submit the SPARQL query to Virtuoso
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Evry, June 27, 2008 CHUL research center Laval University 52
SPARQL query in a URL
http://bio2rdf.org:8890/sparql?defaultgraphuri=&query=CONSTRUCT+%7B%0D%0A%3Fs1+%3Fp1+%3Fo1+.%0D%0A%3Fs1+%3Chttp%3A%2F%2Fwww.w3.org%2F1999%2F02%2F22rdfsyntaxns%23type%3E+%3Ftype+.+%0D%0A%3Fs1+%3Chttp%3A%2F%2Fwww.w3.org%2F2000%2F01%2Frdfschema%23label%3E+%3Flabel.+%0D%0A%3Fs1+%3Chttp%3A%2F%2Fbio2rdf.org%2Fbio2rdf%23linkRank%3E+%3FlinkRank.+%0D%0A%7D%0D%0AWHERE+%7B%0D%0A%3Fs1+%3Fp1+%3Fo1+.+%0D%0A%3Fo1+bif%3Acontains+%22paget%22+.%0D%0A%3Fs1+%3Chttp%3A%2F%2Fwww.w3.org%2F1999%2F02%2F22rdfsyntaxns%23type%3E+%3Ftype+.+%0D%0A%3Fs1+%3Chttp%3A%2F%2Fwww.w3.org%2F2000%2F01%2Frdfschema%23label%3E+%3Flabel.+%0D%0A%3Fs1+%3Chttp%3A%2F%2Fbio2rdf.org%2Fbio2rdf%23linkRank%3E+%3FlinkRank.+%0D%0A%7D%0D%0A%0D%0A%0D%0A%0D%0A&format=application%2Frdf%2Bxml&debug=on
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Evry, June 27, 2008 CHUL research center Laval University 53
View results in HTML
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Evry, June 27, 2008 CHUL research center Laval University 54
View results with Sesame
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Evry, June 27, 2008 CHUL research center Laval University 55
View results with Piggy Bank
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Evry, June 27, 2008 CHUL research center Laval University 56
Outline
Introduction
− Problem definition− Proposed approach− The 4 rules of linked data− Related Work
Results
− Bio2RDF first knowledge map− Semantic ranking
Paget query demo with SPARQL
Future work and Conclusion
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Evry, June 27, 2008 CHUL research center Laval University 57
Future works
● Create new rdfizer for public data source;● Build a community of users around the
Bio2RDF project (visit the Google group);● Connect more datasources to Bio2RDF by
building collaboration between research groups;
● Offer a public SPARQL endpoint based on Virtuoso server :
− http://bio2rdf.org:8890/sparql
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Conclusion
Those devices in the hands of scientists have forged our understanding of nature.
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Evry, June 27, 2008 CHUL research center Laval University 59
Conclusion
We have started to map the knowledge space of biology, we have a first impression of what the bioinformatics nation looks like, the time has come to explore it, the time has come to build
the knowledgescope.
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Evry, June 27, 2008 CHUL research center Laval University 60
Acknowlegments
Jean MorissetteNicole TourignyBenjamin Good
Bioinformatics lab’s team at CHUL Research Center :Philippe Rigault
Marc-Alexandre Nolin
Thanks to the essential annotators and data providerand to developers of open source project :
Sesame, Virtuoso and PiggyBank.François Belleau was a recipient of a studentship from Génome Québec. This work have been financed in part by the Atlas of Genomic Profiles of SteroidAction, a Genome Canada project. BMG is funded by Pacific Century and University of British Columbia Graduate Fellowships.
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http://bio2rdf.orgQuery the graph with SPARQL http://bio2rdf.org:8890/sparql
Download our software http://sourceforge.net/projects/bio2rdf/
Download the Atlas data in N3 format http://bio2rdf.org/download
Join our group http://groups.google.ca/group/bio2rdf
Contact us at [email protected]