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Data Integration in the Life Sciences

7th International Conference, DILS 2010, Gothenburg, Sweden, August 25-27, 2010. Proceedings

  • Conference proceedings
  • © 2010

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 6254)

Part of the book sub series: Lecture Notes in Bioinformatics (LNBI)

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Conference proceedings info: DILS 2010.

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Table of contents (16 papers)

  1. Invited Talks

  2. Ontology Engineering

  3. Web Services

  4. Data Mining and Text Mining

  5. Information Management

Other volumes

  1. Data Integration in the Life Sciences

Keywords

About this book

The development and increasingly widespread deployment of high-throughput experimental methods in the life sciences is giving rise to numerous large, c- plex and valuable data resources. This foundation of experimental data und- pins the systematic study of organismsand diseases, which increasinglydepends on the development of models of biological systems. The development of these models often requires integration of diverse experimental data resources; once constructed, the models themselves become data and present new integration challenges for tasks such as interpretation, validation and comparison. The Data Integration in the Life Sciences (DILS) Conference series brings together data and knowledge management researchers from the computer s- ence research community with bioinformaticians and computational biologists, to improve the understanding of how emerging data integration techniques can address requirements identi?ed in the life sciences. DILS 2010 was the seventh event in the series and was held in Goth- burg, Sweden during August 25–27, 2010. The associated proceedings contain 14 peer-reviewed papers and 2 invited papers. The sessions addressed ontology engineering, and in particular, evolution, matching and debugging of ontologies, akeycomponentforsemanticintegration;Web servicesasanimportanttechn- ogy for data integration in the life sciences; data and text mining techniques for discovering and recognizing biomedical entities and relationships between these entities; and information management, introducing data integration solutions for di?erent types of applications related to cancer, systems biology and - croarray experimental data, and an approach for integrating ranked data in the life sciences.

Editors and Affiliations

  • Department of Computer and Information Science, Linköpings universitet, Linköping, Sweden

    Patrick Lambrix

  • Computer Science and Engineering, Chalmers University of Technology and University of Gothenburg, Gothenburg,, Sweden

    Graham Kemp

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