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dc.contributor.author
Anwar, Nadia
dc.contributor.author
Hunt, Ela
dc.date.accessioned
2018-10-31T14:49:00Z
dc.date.available
2017-06-13T09:22:43Z
dc.date.available
2017-07-12T07:18:39Z
dc.date.available
2018-10-31T14:49:00Z
dc.date.issued
2009-10-01
dc.identifier.issn
1471-2105
dc.identifier.other
10.1186/1471-2105-10-S10-S3
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/151469
dc.identifier.doi
10.3929/ethz-a-005906803
dc.description.abstract
Background This paper summarises the lessons and experiences gained from a case study of the application of semantic web technologies to the integration of data from the bacterial species Francisella tularensis novicida (Fn). Fn data sources are disparate and heterogeneous, as multiple laboratories across the world, using multiple technologies, perform experiments to understand the mechanism of virulence. It is hard to integrate these data sources in a flexible manner that allows new experimental data to be added and compared when required. Results Public domain data sources were combined in RDF. Using this connected graph of database cross references, we extended the annotations of an experimental data set by superimposing onto it the annotation graph. Identifiers used in the experimental data automatically resolved and the data acquired annotations in the rest of the RDF graph. This happened without the expensive manual annotation that would normally be required to produce these links. This graph of resolved identifiers was then used to combine two experimental data sets, a proteomics experiment and a transcriptomic experiment studying the mechanism of virulence through the comparison of wildtype Fn with an avirulent mutant strain. Conclusion We produced a graph of Fn cross references which enabled the combination of two experimental datasets. Through combination of these data we are able to perform queries that compare the results of the two experiments. We found that data are easily combined in RDF and that experimental results are easily compared when the data are integrated. We conclude that semantic data integration offers a convenient, simple and flexible solution to the integration of published and unpublished experimental data.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
BioMed Central
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/2.0/
dc.subject
Data integration
en_US
dc.subject
Database federation
en_US
dc.subject
Transcriptomic experiment
en_US
dc.subject
Individual data source
en_US
dc.subject
Francisella pathogenicity island
en_US
dc.title
Francisella tularensis novicida proteomic and transcriptomic data integration and annotation based on semantic web technologies
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 2.0 Generic
ethz.journal.title
BMC Bioinformatics
ethz.journal.volume
10
en_US
ethz.journal.issue
S10
en_US
ethz.pages.start
S3
en_US
ethz.size
18 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.code.ddc
DDC - DDC::0 - Computer science, information & general works::004 - Data processing, computer science
en_US
ethz.code.ddc
DDC - DDC::5 - Science::570 - Life sciences
en_US
ethz.identifier.pubmed
19796400
ethz.identifier.nebis
005906803
ethz.publication.place
London
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
::ETH Zürich::00009 - ETH-nahe Einheiten
en_US
ethz.date.deposited
2017-06-13T09:29:08Z
ethz.source
ECOL
ethz.identifier.importid
imp59366adbd646a95149
ethz.ecolpid
eth:304
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2017-07-12T07:18:44Z
ethz.rosetta.lastUpdated
2021-02-15T02:21:28Z
ethz.rosetta.versionExported
true
ethz.COinS
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