Data Integration in the Life Sciences

6th International Workshop, DILS 2009, Manchester, UK, July 20-22, 2009. Proceedings

  • Norman W. Paton
  • Paolo Missier
  • Cornelia Hedeler

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5647)

Also part of the Lecture Notes in Bioinformatics book sub series (LNBI, volume 5647)

Table of contents

  1. Front Matter
  2. Keynote Presentations

    1. Vijayalakshmi Chelliah, Lukas Endler, Nick Juty, Camille Laibe, Chen Li, Nicolas Rodriguez et al.
      Pages 5-15
  3. Graph-Based Modelling and Integration

    1. Jan Taubert, Matthew Hindle, Artem Lysenko, Jochen Weile, Jacob Köhler, Christopher J. Rawlings
      Pages 16-30
    2. Jun Zhao, Alistair Miles, Graham Klyne, David Shotton
      Pages 47-54
  4. Annotation

    1. Eithon Cadag, Peter Tarczy-Hornoch, Peter J. Myler
      Pages 55-70
    2. Anika Gross, Michael Hartung, Toralf Kirsten, Erhard Rahm
      Pages 71-87
  5. Structure Inference

    1. Saqib Mir, Steffen Staab, Isabel Rojas
      Pages 96-112
    2. Bastien Rance, Jean-François Gibrat, Christine Froidevaux
      Pages 113-126
    3. Christopher J. O. Baker, Patrick Lambrix, Jonas Laurila Bergman, Rajaraman Kanagasabai, Wee Tiong Ang
      Pages 127-140
  6. Data and Work Flows

  7. Data Integration for Systems Biology

    1. Stephan Weise, Christian Colmsee, Eva Grafahrend-Belau, Björn Junker, Christian Klukas, Matthias Lange et al.
      Pages 196-203
    2. Dagmar Köhn, Carsten Maus, Ron Henkel, Martin Kolbe
      Pages 204-219
  8. Back Matter

About these proceedings

Introduction

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.

Keywords

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

Editors and affiliations

  • Norman W. Paton
    • 1
  • Paolo Missier
    • 1
  • Cornelia Hedeler
    • 2
  1. 1.School of Computer ScienceUniversity of ManchesterManchesterUK
  2. 2.School of Computer ScienceThe University of ManchesterManchesterUK

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-02879-3
  • Copyright Information Springer-Verlag Berlin Heidelberg 2009
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-642-02878-6
  • Online ISBN 978-3-642-02879-3
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • About this book