Systems Biology is the science that describes the behavior of a system
through mathematical and computational modeling. It is a multidisciplinary and
recent area in bioinformatics. Using a holistic approach, it seeks to understand the
biological complexity of living things. On a biological level, we can represent our
organism as a set of integrated metabolic networks that form the whole. Systems
biology studies these metabolic networks to understand the behavior of the organism
and to propose hypotheses, computational models and contribute to the study of
biological functions. In this work, the regulation network of the gene expression of
fatty acids of the model organism Escherichia coli k12 is studied. Gene expression
regulation is a mechanism of cellular control that ensures that genes in an organism
are expressed according to need, governing the individual's ability to respond to
stimuli and adapt to the environment. We can simplify this process by stating that
the regulation of gene expression controls the activation or repression of genes.
From this principle, a similarity was detected between the process of gene regulation
and a computational modeling technique called Boolean Networks. These networks
work with binary values 0 and 1. In Boolean modeling we use the basic operations
AND, OR and NOT to represent the transitions that occur in the biological model.
These grouped operations form Boolean networks. In this work we use this principle
to model the metabolic pathway of the model organism, based on information
contained in the genome available in biological databases. The results obtained
show the relationships between the genes of the fatty acid pathway according to the
KEGG database in the form of Boolean networks.
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