期刊
NATURE REVIEWS MOLECULAR CELL BIOLOGY
卷 7, 期 11, 页码 820-828出版社
NATURE PUBLISHING GROUP
DOI: 10.1038/nrm2041
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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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