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Integrating quantitative knowledge into a qualitative gene regulatory network

Bourdon, Jérémie ; Eveillard, Damien ; Siegel, Anne

PLoS computational biology, September 2011, Vol.7(9), pp.e1002157 [Tạp chí có phản biện]

E-ISSN: 1553-7358 ; PMID: 21935350 Version:1 ; DOI: 10.1371/journal.pcbi.1002157

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  • Nhan đề:
    Integrating quantitative knowledge into a qualitative gene regulatory network
  • Tác giả: Bourdon, Jérémie ; Eveillard, Damien ; Siegel, Anne
  • Chủ đề: Algorithms ; Gene Regulatory Networks ; Escherichia Coli -- Genetics
  • Là 1 phần của: PLoS computational biology, September 2011, Vol.7(9), pp.e1002157
  • Mô tả: Despite recent improvements in molecular techniques, biological knowledge remains incomplete. Any theorizing about living systems is therefore necessarily based on the use of heterogeneous and partial information. Much current research has focused successfully on the qualitative behaviors of macromolecular networks. Nonetheless, it is not capable of taking into account available quantitative information such as time-series protein concentration variations. The present work proposes a probabilistic modeling framework that integrates both kinds of information. Average case analysis methods are used in combination with Markov chains to link qualitative information about transcriptional regulations to quantitative information about protein concentrations. The approach is illustrated by modeling the carbon starvation response in Escherichia coli. It accurately predicts the quantitative time-series evolution of several protein concentrations using only knowledge of discrete gene interactions...
  • Ngôn ngữ: English
  • Số nhận dạng: E-ISSN: 1553-7358 ; PMID: 21935350 Version:1 ; DOI: 10.1371/journal.pcbi.1002157

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