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-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 8
  • Basım Tarihi: 2007
  • Doi Numarası: 10.1186/1471-2105-8-20
  • Dergi Adı: BMC BIOINFORMATICS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

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.