Data-driven modelling of signal-transduction networks

Nat Rev Mol Cell Biol. 2006 Nov;7(11):820-8. doi: 10.1038/nrm2041.


New technologies are permitting large-scale quantitative studies of signal-transduction networks. Such data are hard to understand completely by inspection and intuition. 'Data-driven models' help users to analyse large data sets by simplifying the measurements themselves. Data-driven modelling approaches such as clustering, principal components analysis and partial least squares can derive biological insights from large-scale experiments. These models are emerging as standard tools for systems-level research in signalling networks.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Cluster Analysis
  • Computer Simulation
  • Models, Biological*
  • Regression Analysis
  • Signal Transduction*
  • Systems Biology*