Transcriptional regulatory network refinement and quantification through kinetic modeling, gene expression microarray data and information theory


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Sayyed-Ahmad A., Tuncay K. , Ortoleva P. J.

BMC BIOINFORMATICS, cilt.8, 2007 (SCI İndekslerine Giren Dergi) identifier identifier identifier

Özet

Background: Gene expression microarray and other multiplex data hold promise for addressing the challenges of cellular complexity, refined diagnoses and the discovery of well-targeted treatments. A new approach to the construction and quantification of transcriptional regulatory networks (TRNs) is presented that integrates gene expression microarray data and cell modeling through information theory. Given a partial TRN and time series data, a probability density is constructed that is a functional of the time course of transcription factor (TF) thermodynamic activities at the site of gene control, and is a function of mRNA degradation and transcription rate coefficients, and equilibrium constants for TF/gene binding.