A data integration and visualization resource for the metabolic network of Synechocystis sp. PCC 6803

Plant Physiol. 2014 Mar;164(3):1111-21. doi: 10.1104/pp.113.224394. Epub 2014 Jan 8.


Data integration is a central activity in systems biology. The integration of genomic, transcript, protein, metabolite, flux, and computational data yields unprecedented information about the system level functioning of organisms. Often, data integration is done purely computationally, leaving the user with little insight in addition to statistical information. In this article, we present a visualization tool for the metabolic network of Synechocystis sp. PCC 6803, an important model cyanobacterium for sustainable biofuel production. We illustrate how this metabolic map can be used to integrate experimental and computational data for Synechocystis sp. PCC 6803 systems biology and metabolic engineering studies. Additionally, we discuss how this map, and the software infrastructure that we supply with it, can be used in the development of other organism-specific metabolic network visualizations. In addition to the Python console package VoNDA (http://vonda.sf.net), we provide a working demonstration of the interactive metabolic map and the associated Synechocystis sp. PCC 6803 genome-scale stoichiometric model, as well as various ready-to-visualize microarray data sets, at http://f-a-m-e.org/synechocytis.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adaptation, Physiological
  • Biofuels
  • Darkness
  • Databases as Topic*
  • Genes, Bacterial
  • Metabolic Flux Analysis
  • Metabolic Networks and Pathways* / genetics
  • Models, Biological
  • Oligonucleotide Array Sequence Analysis
  • Photosynthesis
  • Synechocystis / genetics
  • Synechocystis / metabolism*


  • Biofuels