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Data Integration in the Life Sciences

Volume 5647 of the series Lecture Notes in Computer Science pp 204-219

Towards Enhanced Retrieval of Biological Models through Annotation-Based Ranking

  • Dagmar KöhnAffiliated withInstitute of Computer Science, Database and Information Systems Group, University of Rostock
  • , Carsten MausAffiliated withInstitute of Computer Science, Modelling and Simulation Group, University of Rostock
  • , Ron HenkelAffiliated withInstitute of Computer Science, Database and Information Systems Group, University of Rostock
  • , Martin KolbeAffiliated withInstitute of Computer Science, Database and Information Systems Group, University of Rostock

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Abstract

Modelling and simulation methods gain increasing importance for the understanding of biological systems. The growing number of available computational models makes support in maintenance and retrieval of those models essential to the community. This article discusses which model information are helpful for efficient retrieval and how existing similarity measures and ranking techniques can be used to enhance the retrieval process, i. e. the model reuse. With the development of new tools and modelling formalisms, there also is an increasing demand for performing search independent of the models’ encoding. Therefore, the presented approach is not restricted to certain model storage formats. Instead, the model meta-information is used for retrieval and ranking of the search result. Meta-information include general information about the model, its encoded species and reactions, but also information about the model behaviour and related simulation experiment descriptions.

Keywords

model storage model retrieval model reuse annotation ontologies similarity ranking