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@neuLink - Knowledge Discovery in Unstructured and Structured Data Sources

Poster at the VPH Initiative Integration Day, 9.9.2009, Bruxelles
: Friedrich, C.M.; Ebeling, C.; Engelbrecht, G.; Furlong, L.I.; Fornes, O.; Bauer-Mehren, A.; Pastor, M.; Oliva, B.; Sanz, F.; Risselada, R.; Cruz-Villa, M.; Frangi, A.; Cambien, F.; Yilmaz, S.; McGregor, J.; Böker, M.; Hofmann-Apitius, M.

Volltext urn:nbn:de:0011-n-1109140 (2.4 MByte PDF)
MD5 Fingerprint: f6dd1f4a6c17cb2f0350a828c6588097
Erstellt am: 24.11.2009

2009, 1 Folie
Initiative Integration Day <2009, Bruxelles>
Poster, Elektronische Publikation
Fraunhofer SCAI ()

The @neurIST Project (Integrated Biomedical Informatics for the Management of Cerebral Aneurysms) is a European initiative, focused on intracranial aneurysms and intends to provide an integrated decision support system to assess the individual risk of aneurysm rupture in patients and to optimize their treatments. The project integrates a large amount of data from multiple scales spanning from Genomics over hemodynamic simulation results to clinical data by a Grid infrastructure. In the project 6 workflows have been developed, which fulfil various subtasks. Here we present Workflow 2, which delivers Knowledge Discovery results from Unstructured and Structured data sources with the application suite @neuLink.
@neuLink allows for rapid generation of working hypotheses and comparison of experimental data to the published state of knowledge through sophisticated information extraction machinery underlying the application suite. By using text mining methods, the current state of knowledge e.g. on simulation approaches in vascular diseases can be rapidly retrieved and represented; through mapping of named entities to database entries we can even overlay experimental data (e.g. from SNP chips or microarrays) with knowledge extracted from the literature.
The poster presents results on:
· Using SCAIView (part of @neuLink), a text mining application to search for candidate genes and Single Nucleotide Polymorphisms (SNP) in Medline and perform a genetic association study with the found SNP on integrated clinical data using the KNime workflow engine.
· Use of Data Mining methods for the individual rupture risk assessment from morphological characterizations of Aneurysms, which are obtained from a derived data store. The data is resulting from running the @neurIST complex image processing toolchain with the application suite @neuFuse (see other @neurIST workflow posters).