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- Dragisic, Zlatan, et al.
(författare)
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Completing the is-a structure of biomedical ontologies
- 2014
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Ingår i: Data Integration in the Life Sciences 10th International Conference, DILS 2014, Lisbon, Portugal, July 17-18, 2014. Proceedings. - Berlin : Springer Science+Business Media B.V.. - 9783319085890 - 9783319085906 ; , s. 66-80
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Konferensbidrag (refereegranskat)abstract
- Ontologies in the biomedical domain are becoming a key element for data integration and search. The usefulness of the applications which use ontologies is often directly influenced by the quality of ontologies, as incorrect or incomplete ontologies might lead to wrong or incomplete results for the applications. Therefore, there is an increasing need for repairing defects in ontologies. In this paper we focus on completing ontologies. We provide an algorithm for completing the is-a structure in TeX ontologies which covers many biomedical ontologies. Further, we present an implemented system based on the algorithm as well as an evaluation using three biomedical ontologies.
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| 2. |
- Spjuth, Ola, 1977-, et al.
(författare)
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Data Integration between Swedish National Clinical Health Registries and Biobanks Using an Availability System
- 2014
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Ingår i: Data Integration in the Life Sciences. - Cham : Springer International Publishing. - 9783319085890 ; , s. 32-40
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Bokkapitel (refereegranskat)abstract
- Linking biobank data, such as molecular profiles, with clinical phenotypes is of great importance in epidemiological and predictive studies. A comprehensive overview of various data sources that can be combined in order to power up a study is a key factor in the design. Clinical data stored in health registries and biobank data in research projects are commonly provisioned in different database systems and governed by separate organizations, making the integration process challenging and hampering biomedical investigations. We here describe the integration of data on prostate cancer from a clinical health registry with data from a biobank, and its provisioning in the SAIL availability system. We demonstrate the implications of using the actual raw data, data transformed to availability data, and availability data which has been subjected to anonymization techniques to reduce the risk of re-identification. Our results show that an availability system such as SAIL with integrated clinical and biobank data can be a valuable tool for planning new studies and finding interesting subsets to investigate further. We also show that an availability system can deliver useful insights even when the data has been subjected to anonymization techniques.
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