End-to-end information management for systems biology

  • Authors:

  • Peter Saffrey;Ofer Margoninski;James Hetherington;Marta Varela-Rey;Sachie Yamaji;Anthony Finkelstein;David Bogle;Anne Warner

  • Affiliations:

  • Centre for Mathematics and Physics in the Life and Experimental Sciences, University College London, London;Centre for Mathematics and Physics in the Life and Experimental Sciences, University College London, London;Centre for Mathematics and Physics in the Life and Experimental Sciences, University College London, London;Centre for Mathematics and Physics in the Life and Experimental Sciences, University College London, London;Centre for Mathematics and Physics in the Life and Experimental Sciences, University College London, London;Centre for Mathematics and Physics in the Life and Experimental Sciences, University College London, London;Centre for Mathematics and Physics in the Life and Experimental Sciences, University College London, London;Centre for Mathematics and Physics in the Life and Experimental Sciences, University College London, London

  • Venue:
  • Transactions on computational systems biology VIII
  • Year:
  • 2007

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Abstract

Mathematical and computational modelling are research areas with increasing importance in the study of behaviour in complex biological systems. With the increasing breadth and depth of models under consideration, a disciplined approach to managing the diverse data associated with these models is needed. Of particular importance is the issue of provenance, where a model result is linked to information about the generating model, the parameters used in that model and the papers and experiments that were used to derive those parameters. This paper presents an architecture to manage this information along with accompanying tool support and examples of the management system in use at various points in the development of a large model.