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Synthetic Systems Biology and Nuclear Organization University of Amsterdam

Contact Details

SB@NL/BioSB and Swammerdam Institute of Life Sciences

Swammerdam Institute of Life Sciences, University of Amsterdam, Science Park 904 (room C2.103), NL-1098 XH Amsterdam, The Netherlands, EU

Hans V. Westerhoff or Matteo Barberis, or Jacky Snoep


Hotel Description

The facility engages in Integrative Systems Biology in a variety of areas. It carries out computer simulations and/or precise experiments on biological networks of limited size in order to discover the principles of their operation. It underpins these analyses with systems-biology theory such as Metabolic and Hierarchical Control Analysis. Modeled networks include the cell cycle in yeast and ammlalian cells, carbon and energy metabolism in baker’s yeast, Trypanosoma brucei and mammalian cells, ammonia assimilation in E coli, signal transduction in and around mammalian cells (MAP kinase, nuclear hormone receptor network), transcriptional regulation in the context also of chromatin and DNA structure and energetics (mammalian, plant cells and E. coli) and networks in microbial ecology. It works towards making genome wide metabolic maps for human individuals.
The facility is closely associated with the JWS-Online live model repository managed by Prof Jacky Snoep (Stellenbosch, Amsterdam, Manchester).
The facility is closely linked to the systems biology facilities at VUA and in Manchester.

Systems biology
  • Agri & Food
  • Biomedical & health
  • Industrial biotech
  • biochemistry (characterization of enzyme kinetic properties)
  • molecular cell biology
  • carbon, nitrogen and energy metabolism
  • signal transduction
  • microbial ecology
  • systems medicine
  • personalized medicine

Expertise and Track Record

  • Metabolic Control Analysis
  • Precise kinetic modelling of biochemical networks
  • Non equilibrium thermodynamics in biology
  • Live model repository (enabling through web simulations without modelling) (Jacky Snoep)
  • Enzyme kinetics and determination of functional properties of proteins
  • DNA energetics, structure and topology
  • yeast systems biology: an experiment based mathematical model of the main carbon and energy metabolism in yeast (www.mcisb.org)
  • Academic-industry project on drug detoxification
  • Differential network-based drug design against T brucei
  • Industrial project integrating metabolomics with systems biology

1. Integration of transcriptomics, proteomics, enzyme activities, metabolomics and fluxomics. For this we developed an approach called regulation analysis. It can quantify how much of a flux is regulated at the transcription, translation or metabolic level.
2. Much experience in integration of any experimental data set with modelling results.

  • J. Kouril, D. Esser, J. Kort, H.V. Westerhoff, B. Siebers and J.L. Snoep, Intermediate instability at high temperature leads to low pathway efficiency for an in vitro reconstituted system of gluconeogenesis in Sulfolobus solfataricus, FEBS J 280-18 (2013) 4666-4680. doi: 10.1111/febs.12438: in vitro enzyme kinetics assembled into a small network model
  • A.N. Kolodkin, N. Sahin, A. Phillips, S.R. Hood, F.J. Bruggeman, H.V. Westerhoff and N. Plant, Optimization of stress response through the nuclear receptor-mediated cortisol signalling network, Nature communications 4:1792 April 30 (2013) DOI:10.1038/ncomms2799.: Model of nuclear hormone receptor signalling extended to whole body scale and implications for mood.
  • S. Geenen, J.W.T. Yates, J.G. Kenna, F.Y. Bois, I.D. Wilson and H.V. Westerhoff, Multiscale modeling approach combining a kinetic model of glutathione metabolism with PBPK models of paracetamol and the potential glutathione-depletion biomarkers ophthalmic acie and 5-oxoproline in humans and rats, Integrative Biology 5-6 (2013) 877-888. doi: 10.1039/c3ib20245c. Model of glutathione metabolism around drug detoxification extended to whole body and usable for biomarker assessment for individualized drug toxicity
  • H. Firczuk, S. Kannambath, J. Pahle, A. Claydon, R. Beynon, J. Duncan, H.V. Westerhoff, P. Mendes and J.E.G. McCarthy, An in vivo control map for the eukaryotic mRNA translation machinery, Molecular Systems Biology 9 artnr 635 (2013) 1-13 doi:10.1038. Use of Metabolic Control Analysis; here for ribosome action
  • Albers S.V., Birkeland N.K., Driessen A.J., Gertig S., Haferkamp P., Klenk H.P., Kouril T., Manica A., Pham T.K., Ruoff P., Schleper C., Schomburg D., Sharkey K.J., Siebers B., Sierocinski P., Steuer R., van der Oost J., Westerhoff H.V., Wieloch P., Wright P.C. and Zaparty M., Biochem Soc Trans. 37 (2009) 58-64. SulfoSYS (Sulfolobus Systems Biology): towards a silicon cell model for the central carbohydrate metabolism of the archaeon Sulfolobus solfataricus under temperature variation: We provided the systems biology advice to a consortium of microbiologists
  • Moreno-Sanchez R., Saavedra E., Rodriguez-Enriquez S., Gallardo-Perez J.C., Quezada H. and Westerhoff H.V., Mitochondrion 10 (2010) 626-639. Metabolic control analysis indicates a change of strategy in the treatment of cancer. Developing Metabolic Control Analysis for multifactorial diseases such as cancers.
  • Monkhorst K., de Hoon B., Jonkers I., Achame E.M., Monkhorst W., Hoogerbrugge J., Rentmeester E., Westerhoff H.V., Grosveld F., Grootegoed A. and Gribnau, J., PloS One 4 (2009) in press. The probability to initiate X chromosome inactivation is determined by the X to autosomal ratio and x chromosome specific allelic properties. Modeling of genetic interactions.
  • F. He, V. Fromion and H.V. Westerhoff, (Im) Perfect robustness and adaptation of metabolic networks subject to metabolic and gene-expression regulation: marrying control engineering with metabolic control analysis, BMC Systems Biology 7 (2013) 131. Integrating control engineering and metabolic control analysis
  • Daran-Lapujade P., Rossell S., van Gulik W.M., Luttik M.A., de Groot M.J., Slijper M., Heck A.J., Daran J.M., de Winde J.H., Westerhoff H.V. , Pronk J.T. and Bakker B.M., The flux through glycolytic enzymes in Saccharomyces cerevisiae are predominantly regulated at posttranscirptionla levels, PNAS USA 104 (2007) 15753-15758. We developed the theoretical concepts and metholodogy to integrate the data sets and understand how much of regulation takes place where.

Infrastructure Systems Biology Europe (ISBE) (preparatory phase): partner, Wp coordinator
SB@NL (association of systems biology groups in NL (Chair))

Hotel Characteristics

  • 0.5
  • 0.25
  • 0.25


  • Standard PCs, standard molecular biology equipment, plus FACS