Rational approaches to therapy of complex diseases may be improved by predictive modelling of underlying disease mechanisms. Formulating and implementing such models requires the integration of heterogeneous information from different sources and usually entails considerable effort. We need new concepts and resources making knowledge on causal regulatory interactions of genes and physiological states in a disease context available. Dedicated ontologies and text mining methods can be of great use for guiding and supporting the process of model construction and model evaluation.
@InProceedings{schuchhardt:DagSemProc.08131.16, author = {Schuchhardt, Johannes}, title = {{Systems biology approaches for prioritizing therapeutic gene targets}}, booktitle = {Ontologies and Text Mining for Life Sciences : Current Status and Future Perspectives}, pages = {1--1}, series = {Dagstuhl Seminar Proceedings (DagSemProc)}, ISSN = {1862-4405}, year = {2008}, volume = {8131}, editor = {Michael Ashburner and Ulf Leser and Dietrich Rebholz-Schuhmann}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.08131.16}, URN = {urn:nbn:de:0030-drops-15053}, doi = {10.4230/DagSemProc.08131.16}, annote = {Keywords: Rational therapy, predictive modelling, data integration, ontologies, pathway databases} }
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