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Quantitative models of gene regulatory activity have the potential to improve our mechanistic understanding of transcriptional regulation. However, the few models available today have been based on simplistic assumptions about the sequences being modeled or heuristic approximations of the underlying regulatory mechanisms. In this work, we have developed a thermodynamics-based model to predict gene...
Modeling of gene regulatory networks play an important role in the post genomic era. In this work, we propose a Bayesian inference based model to quantitatively analyze the transcriptional regulatory network when the structure of regulatory network is given. In the proposed model, the dynamics of transcription factors are treated as a Markov process. Besides, the sequence features of genes are employed...
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