Review
Nature Reviews Molecular Cell Biology 7, 820-828 (November 2006) | doi:10.1038/nrm2041
Data-driven modelling of signal-transduction networks
Kevin A. Janes1 & Michael B. Yaffe2 About the authors
Abstract
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.
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Author affiliations
- Cell Decision Processes Center, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA, and Department of Cell Biology, Harvard Medical School, Boston, Massachusetts 02115, USA.
- Cell Decision Processes Center, Center for Cancer Research and Departments of Biology and Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.
Correspondence to: Michael B. Yaffe2 Email: myaffe@mit.edu
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