Abstract
Petri net is a well-established paradigm, where new algorithms with a sound biological understanding have been evolving. We have developed a new algorithm for modeling and analyzing gene expression levels. This algorithm uses fuzzy Petri net to transform Boolean network into qualitative descriptors that can be evaluated by using a set of fuzzy rules. By recognizing the fundamental links between Boolean network (two-valued) and fuzzy Petri net (multi-valued), effective structural fuzzy rules is achieved through the use of well-established methods of Petri net. For evaluation, the proposed technique has been tested using the nutritional stress response in E.Coli cells and the experimental results shows that the use of Fuzzy Reasoning Boolean Petri Nets (FRBPNs) based technique in gene expression data analysis can be quite effective and describe the dynamic behavior of genes.
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Hamed, R.I. (2011). Computational Modeling and Dynamical Analysis of Genetic Networks with FRBPN- Algorithm. In: Unnikrishnan, S., Surve, S., Bhoir, D. (eds) Advances in Computing, Communication and Control. ICAC3 2011. Communications in Computer and Information Science, vol 125. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18440-6_6
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DOI: https://doi.org/10.1007/978-3-642-18440-6_6
Publisher Name: Springer, Berlin, Heidelberg
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