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2008 11 13 Hcls Call
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2008 11 13 Hcls Call

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Social tagging to enrich biomedical data integration.

Social tagging to enrich biomedical data integration.

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2008 11 13 Hcls Call 2008 11 13 Hcls Call Presentation Transcript

  • FlyWeb: the way to go for biological data integration
      • Jun Zhao, Alistair Miles and Graham Klyne
      • Image Bioinformatics Research Group
      • Department of Zoology
      • University of Oxford
  • FlyWeb Application
    • To answer questions about "what does this gene do?”
      • Gene Expression Images
      • Sequence and ESTs (Expressed sequence tags) of the gene
      • Publications about the gene
      • ....
    • A first example of the Image Web that our group is developing
    • Investigate the feasibility of existing Semantic Web tools and technologies for real applications
  • Gene expression images
    • Reveal gene expression pattern in different development stages
    • Important for identifying genes of interests and verifying a picture of probable gene functions
  • FlyWeb demonstration
    • http://openflydata.org/flyui/build/apps/imagemashup2/
      • Run application: [ go ]
    • Two examples:
      • Single gene query (aos1)‏
      • Use gene synonyms to enhance gene matching (rbf)‏
  •  
  • More than one synonyms of gene “rbf”
  •  
  • How does it work?
    • Data from 3 independent sources:
      • www.flybase.org – model organism reference database, gene names and identifiers
      • www.fruitfly.org (BDGP) – embryo in situ images
      • www.fly-ted.org – testis in situ images
    • All data accessed via SPARQL
    • Pure Ajax user application
    • Essentially, a mashup using a SPARQL API
  • The client side
    • FlyUI:
      • a library of Javascript widgets as front ends to SPARQL data sources
      • Built on Yahoo User Interface (YUI) library
    • Widgets are composed in a browser to create the complete application
    • Each widget provides:
      • A Service that implements SPARQL queries
      • A Model encapsulating SPARQL query results
      • A Renderer
    The in situ search application GeneFinder Widget FlyTED Image Widget BDGP Image Widget
  • Gene name mapping
    • FlyTED and BDGP use different gene names
      • FlyTED data derived from spreadsheets with imperfectly controlled gene name vocabulary
      • BDGP's data are annotated using FlyBase's unique FBgn numbers
    • Use FlyBase for automatic gene mapping
    • Additional inputs from scientists for disambiguating many-many mappings
    • Mappings are stored as JSON file to assist “GeneFinder” widget (having no use for RDF/OWL reasoning at this stage)‏
  • SPARQL queries
    • Free text matchings
    • Case insensitive searching
      • Very important for our users
      • Too expensive using SPARQL Filter
      • Pre-generate lower-case gene names and load into the Flybase RDF DB
    SELECT * WHERE { ?gene fbutil:anyName &quot; userInput &quot;^^xs:string ; a chado:Feature ; chado:name ?symbol ; chado:uniquename ?flybaseID . OPTIONAL { ?gene chado:dbxref [ chado:accession ?annotationSymbol ] . } OPTIONAL { ?gene chado:synonym [ chado:name ?synonym ] . } OPTIONAL { ?gene chado:synonym [ a syntype:FullName ; chado:name ?fullName ] . } } SELECT DISTINCT * WHERE { ?fullImageURL &quot; + flyted:associatesToGene <http://openflydata.org/id/flyted/gene- geneName > ; flyted:associatesToGene ?gene ; flyted:thumbnail ?thumbnailURL; rdfs:seeAlso ?flytedURL; rdfs:label ?caption }
  • The RDF data sources
    • Flybase and BDGP: relational databases
    • FlyTED, an image repository built using Eprints
    • FlyAtlas (forthcoming), tissue-specific Drosophila gene expression levels, as a single spreadsheet
  • Creating RDF from data sources
    • D2RQ mapping
      • FlyBase and BDGP, native relational databases
      • Conservative mapping, with minimum interpretation
    • OAI2SPARQL
      • Harvesting N3 RDF metadata via the OAI-PMH protocol, built-in support by Eprints
      • Further from ESWC2008 paper
    • Custom Python program
      • FlyAtlas
      • Generating N3 from spreadsheet table
  • More about the data sources
    • Bulk download
      • http://openflydata.org/dump/flybase, ~8m triples
      • http://openflydata.org/dump/bdgp, ~1m triples
      • http://openflydata.org/dump/flyted, ~30,000 triples
    • SPARQL endpoint
      • http://openflydata.org/query/flybase
      • http://openflydata.org/query/bdgp
      • http://openflydata.org/query/flyted
    • Schema
      • http://purl.org/net/chado/schema/
      • http://purl.org/net/flybase/synonym-types/
      • http://purl.org/net/bdgp/schema/
  • SPARQL server
    • Amazon EC2 (Elastic Compute Cloud):
      • To run SPARQL endpoints
      • To host the demo you've just seen
    • Jena TDB as triple store
      • For better loading performance: ~6K tps for ~9M triples to Amazon Elastic Block Storage (EBS)‏
      • For better querying performance
    • SPARQLite
      • home-grown SPARQL protocol implementation
      • More later
    • Apache, Tomcat, mod_jk, etc.
  • SPARQLite protocol
    • http://sparqlite.googlecode.com
      • Also, a platform for exploring SPARQL service quality concerns, more later
    • Motivation
      • Enable streaming
      • Create a database connection pool
    • Designed for Jena TDB/SDB + Postgres
    • Restricted forms of query (SELECT, ASK)
    • Restricted query result format (e.g. only JSON)
  • Lessons
    • RDF provides a uniform and flexible data model
      • RDF dump is cheaper and quicker
      • Maintaining a separate SPARQL endpoint for each data source makes it easier than a data warehouse approach for handling data updates
    • RDF facilitates data re-use and re-purposing
    • SPARQL raises the point of departure for an application
    • Benefits for the future
      • Linking to other data sources
      • Querying genes using the Fly Anatomy ontology
      • Magic of inference
  • Performance
    • Loading: Our datasets ~10 million triples
      • Jena / RDB / Postgres, OK with <1 M triples
      • Jena / SDB / Postgres better, but problems with load performance with larger datasets
      • Jena / TDB gives much better load performance (~6K tps), even on 32 bit system with Amazon EBS storage (but not so good with local EC2 store)‏
      • Virtuoso performs reasonably well
    • Querying, particularly text matching and case insensitive search
      • Problems with using SPARQL regex filter, the only mechanism for case-insensitive search in SPARQL
      • Tried with OpenLink Virtuoso, still ~10 seconds for a case-insensitive search
      • Any suggestions?
  • Further lessons
    • SPARQL results streaming
      • Resolves out of memory errors for large datasets
      • Joseki / SDB / Postgres can be made to stream results, but using just a single JDBC connection, causing performance problems with concurrent requests
      • Therefore, SPARQLite
    • The openness of SPARQL:
      • SPARQL is an inherently open query language and protocol
      • Open endpoints are vulnerable to simple queries that can overload the service, exposing them to denial of service style attacks (whether intended or not)‏
      • Futures: API key mechanism? Restricted SPARQL profiles?
  • Future directions
    • Adding new data sources:
      • FlyAtlas tissue-specific Drosophila gene expression levels
      • More information from FlyBase – e.g. references
    • More applications:
      • Find out all the gene expression images of its neighbours
      • Find out all the genes related to “blood pressure”
      • ...
    • Linked data (dereferencable, follow-your nose)‏
      • We're thinking about this, but our application does not currently need it
    • How to control and predict quality of service for open SPARQL endpoints
  • Acknowledgement
    • Alistair Miles, Graham Klyne and David Shotton
    • Dr Helen White-Cooper and her research group
    • BBSRC for funding building the FlyTED database
    • BDGP and FlyBase for making the data available
    • JISC, for funding the FlyWeb project
    • The Jena team, esp. Andy Seaborne