Data Integration in the Life Sciences (Paperback)

Patrick Lambrix

ISBN 10: 3642151191 / ISBN 13: 9783642151194

Published by Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Berlin, 2010

About this Item

Paperback. 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 2527, 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. Constitutes the refereed proceedings of the 7th International Conference on Data Integration in the Life Sciences, DILS 2010, held in Gothenburg, Sweden, on August 25-27, 2010. This book features the papers covering the following topics: ontology engineering, web services, data mining and text mining and information management. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Seller Inventory # 9783642151194

Bibliographic Details

• Title: Data Integration in the Life Sciences (Paperback)
• Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Berlin
• Publication Date: 2010
• Language: English
• ISBN 10: 3642151191
• ISBN 13: 9783642151194
• Binding: Paperback
• Condition: new

About this title

Synopsis

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.