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Gene network reconstruction from transcriptional dynamics under kinetic model uncertainty: a case for the second derivative

By David R. Bickel, Zahra Montazeri, Pei-Chun Hsieh, Mary Beatty, Shai J. Lawit and Nicholas J. Bate


Motivation: Measurements of gene expression over time enable the reconstruction of transcriptional networks. However, Bayesian networks and many other current reconstruction methods rely on assumptions that conflict with the differential equations that describe transcriptional kinetics. Practical approximations of kinetic models would enable inferring causal relationships between genes from expression data of microarray, tag-based and conventional platforms, but conclusions are sensitive to the assumptions made

Topics: Original Papers
Publisher: Oxford University Press
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