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AutoresJorge Enrique González M.
ONTARE. REVISTA DE INVESTIGACIÓN DE LA FACULTAD DE INGENIERÍA
This paper deals with the predictive modeling of cellular processes at the molecular level. We consider the first product of gene expression, the MRNA, and explore different options for the modeling of its life-cycle, from the simplest to the most accurate and complex. For each of the modeling scenarios involved, we implement and analyze a continuous-deterministic and a discrete-stochastic version of the model of MRNA life-cycle. We aim at comparing the representation capabilities of the different models and their implementations, determining which modeling options are the most appropriate ones at the time of matching the available experimental observations. The results of our study indicate that the simple modeling options, which disregard the regulation of gene transcription and MRNA degradation processes, may be inadequate to represent various biological phenomena, in particular those related to the periodic expressions of genes involved in cyclic behaviors.