Data Integration in the Life Sciences

1. Front Matter

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2. Keynote Presentations

   1. Data Integration and Exchange for Scientific Collaboration

      • Zachary G. Ives

      Pages 1-4

   2. Data Integration and Semantic Enrichment of Systems Biology Models and Simulations

      • Vijayalakshmi Chelliah, Lukas Endler, Nick Juty, Camille Laibe, Chen Li, Nicolas Rodriguez et al.

      Pages 5-15

3. Graph-Based Modelling and Integration

   1. Linking Life Sciences Data Using Graph-Based Mapping

      • Jan Taubert, Matthew Hindle, Artem Lysenko, Jochen Weile, Jacob Köhler, Christopher J. Rawlings

      Pages 16-30

   2. Integration of Full-Coverage Probabilistic Functional Networks with Relevance to Specific Biological Processes

      • Katherine James, Anil Wipat, Jennifer Hallinan

      Pages 31-46

   3. OpenFlyData: The Way to Go for Biological Data Integration

      • Jun Zhao, Alistair Miles, Graham Klyne, David Shotton

      Pages 47-54

4. Annotation

   1. On the Reachability of Trustworthy Information from Integrated Exploratory Biological Queries

      • Eithon Cadag, Peter Tarczy-Hornoch, Peter J. Myler

      Pages 55-70

   2. Estimating the Quality of Ontology-Based Annotations by Considering Evolutionary Changes

      • Anika Gross, Michael Hartung, Toralf Kirsten, Erhard Rahm

      Pages 71-87

   3. Integration and Mining of Genomic Annotations: Experiences and Perspectives in GFINDer Data Warehousing

      • Marco Masseroli, Stefano Ceri, Alessandro Campi

      Pages 88-95

5. Structure Inference

   1. Site-Wide Wrapper Induction for Life Science Deep Web Databases

      • Saqib Mir, Steffen Staab, Isabel Rojas

      Pages 96-112

   2. An Adaptive Combination of Matchers: Application to the Mapping of Biological Ontologies for Genome Annotation

      • Bastien Rance, Jean-François Gibrat, Christine Froidevaux

      Pages 113-126

   3. Slicing through the Scientific Literature

      • Christopher J. O. Baker, Patrick Lambrix, Jonas Laurila Bergman, Rajaraman Kanagasabai, Wee Tiong Ang

      Pages 127-140

6. Data and Work Flows

   1. Exploiting Parallelism to Accelerate Keyword Search on Deep-Web Sources

      • Tantan Liu, Fan Wang, Gagan Agrawal

      Pages 141-156

   2. A Visual Interface for on-the-fly Biological Database Integration and Workflow Design Using VizBuilder

      • Shahriyar Hossain, Hasan Jamil

      Pages 157-172

   3. EpiC: A Resource for Integrating Information and Analyses to Enable Selection of Epitopes for Antibody Based Experiments

      • Niall Haslam, Toby Gibson

      Pages 173-181

7. Data Integration for Systems Biology

   1. Design and Architecture of Web Services for Simulation of Biochemical Systems

      • Joseph O. Dada, Pedro Mendes

      Pages 182-195

   2. An Integration and Analysis Pipeline for Systems Biology in Crop Plant Metabolism

      • Stephan Weise, Christian Colmsee, Eva Grafahrend-Belau, Björn Junker, Christian Klukas, Matthias Lange et al.

      Pages 196-203

   3. Towards Enhanced Retrieval of Biological Models through Annotation-Based Ranking

      • Dagmar Köhn, Carsten Maus, Ron Henkel, Martin Kolbe

      Pages 204-219

8. Back Matter

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Data integration in the life sciences continues to be important but challe- ing. The ongoing development of new experimental methods gives rise to an increasingly wide range of data sets, which in turn must be combined to allow more integrative views of biological systems. Indeed, the growing prominence of systems biology, where mathematical models characterize behaviors observed in experiments of di?erent types, emphasizes the importance of data integration to the life sciences. In this context, the representation of models of biological behavior as data in turn gives rise to challenges relating to provenance, data quality, annotation, etc., all of which are associated with signi?cant research activities within computer science. The Data Integration in the Life Sciences (DILS) Workshop 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.

• GFIND
• HCI
• biochemical systems
• biological ontologies
• biology
• collaboration
• data mining
• genome annotation
• genomic data
• life sciences
• models
• simulation
• visual interface
• visualization
• web services

• School of Computer Science, University of Manchester, Manchester, UK

  Norman W. Paton, Paolo Missier

• School of Computer Science, The University of Manchester, Manchester, UK

  Cornelia Hedeler

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