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Data-driven modelling of signal-transduction networks
Kevin A Janes1, Michael B Yaffe
1Cell Decision Processes Center, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.
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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