Semantic Web-Based Integration of Cancer Pathways and Allele Frequency Data
We demonstrate the use of Semantic Web technology to integrate the ALFRED allele frequency database and the Starpath pathway resource. The linking of population-specific genotype data with cancer-related pathway data is potentially useful given the growing interest in personalized medicine and the e...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2009-01-01
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| Series: | Cancer Informatics |
| Subjects: | |
| Online Access: | http://www.la-press.com/semantic-web-based-integration-of-cancer-pathways-and-allele-frequency-a1274 |
| _version_ | 1818275397017534464 |
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| author | Kenneth K. Kidd Kei-Hoi Cheung Hongyu Zhao E. Holford Haseena Rajeevan |
| author_facet | Kenneth K. Kidd Kei-Hoi Cheung Hongyu Zhao E. Holford Haseena Rajeevan |
| author_sort | Kenneth K. Kidd |
| collection | DOAJ |
| description | We demonstrate the use of Semantic Web technology to integrate the ALFRED allele frequency database and the Starpath pathway resource. The linking of population-specific genotype data with cancer-related pathway data is potentially useful given the growing interest in personalized medicine and the exploitation of pathway knowledge for cancer drug discovery. We model our data using the Web Ontology Language (OWL), drawing upon ideas from existing standard formats BioPAX for pathway data and PML for allele frequency data. We store our data within an Oracle database, using Oracle Semantic Technologies. We then query the data using Oracle’s rule-based inference engine and SPARQL-like RDF query language. The ability to perform queries across the domains of population genetics and pathways offers the potential to answer a number of cancer-related research questions. Among the possibilities is the ability to identify genetic variants which are associated with cancer pathways and whose frequency varies significantly between ethnic groups. This sort of information could be useful for designing clinical studies and for providing background data in personalized medicine. It could also assist with the interpretation of genetic analysis results such as those from genome-wide association studies. |
| first_indexed | 2024-12-12T22:29:06Z |
| format | Article |
| id | doaj.art-e973dff12b8540529374ee6ff7e02bd1 |
| institution | Directory Open Access Journal |
| issn | 1176-9351 |
| language | English |
| last_indexed | 2024-12-12T22:29:06Z |
| publishDate | 2009-01-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Cancer Informatics |
| spelling | doaj.art-e973dff12b8540529374ee6ff7e02bd12022-12-22T00:09:40ZengSAGE PublishingCancer Informatics1176-93512009-01-018Semantic Technologie1930Semantic Web-Based Integration of Cancer Pathways and Allele Frequency DataKenneth K. KiddKei-Hoi CheungHongyu ZhaoE. HolfordHaseena RajeevanWe demonstrate the use of Semantic Web technology to integrate the ALFRED allele frequency database and the Starpath pathway resource. The linking of population-specific genotype data with cancer-related pathway data is potentially useful given the growing interest in personalized medicine and the exploitation of pathway knowledge for cancer drug discovery. We model our data using the Web Ontology Language (OWL), drawing upon ideas from existing standard formats BioPAX for pathway data and PML for allele frequency data. We store our data within an Oracle database, using Oracle Semantic Technologies. We then query the data using Oracle’s rule-based inference engine and SPARQL-like RDF query language. The ability to perform queries across the domains of population genetics and pathways offers the potential to answer a number of cancer-related research questions. Among the possibilities is the ability to identify genetic variants which are associated with cancer pathways and whose frequency varies significantly between ethnic groups. This sort of information could be useful for designing clinical studies and for providing background data in personalized medicine. It could also assist with the interpretation of genetic analysis results such as those from genome-wide association studies.http://www.la-press.com/semantic-web-based-integration-of-cancer-pathways-and-allele-frequency-a1274Semantic WebCancerinformaticsdata integrationpathwayallele frequency |
| spellingShingle | Kenneth K. Kidd Kei-Hoi Cheung Hongyu Zhao E. Holford Haseena Rajeevan Semantic Web-Based Integration of Cancer Pathways and Allele Frequency Data Cancer Informatics Semantic Web Cancer informatics data integration pathway allele frequency |
| title | Semantic Web-Based Integration of Cancer Pathways and Allele Frequency Data |
| title_full | Semantic Web-Based Integration of Cancer Pathways and Allele Frequency Data |
| title_fullStr | Semantic Web-Based Integration of Cancer Pathways and Allele Frequency Data |
| title_full_unstemmed | Semantic Web-Based Integration of Cancer Pathways and Allele Frequency Data |
| title_short | Semantic Web-Based Integration of Cancer Pathways and Allele Frequency Data |
| title_sort | semantic web based integration of cancer pathways and allele frequency data |
| topic | Semantic Web Cancer informatics data integration pathway allele frequency |
| url | http://www.la-press.com/semantic-web-based-integration-of-cancer-pathways-and-allele-frequency-a1274 |
| work_keys_str_mv | AT kennethkkidd semanticwebbasedintegrationofcancerpathwaysandallelefrequencydata AT keihoicheung semanticwebbasedintegrationofcancerpathwaysandallelefrequencydata AT hongyuzhao semanticwebbasedintegrationofcancerpathwaysandallelefrequencydata AT eholford semanticwebbasedintegrationofcancerpathwaysandallelefrequencydata AT haseenarajeevan semanticwebbasedintegrationofcancerpathwaysandallelefrequencydata |