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Current approaches for the analysis of gene expression data include clustering the individual expression measurements and relating them to biological functions as well as modelling and simulation of gene regulation processes by additional computer tools.
From its inception twenty years ago, APSIM has evolved into a framework containing many of the key models required to explore changes in agricultural landscapes with capability ranging from simulation of gene expression through to multi-field farms and beyond.
MAMA optimizes parameters automatically to maximize the accuracy of simulation of gene expression.
Simulation of gene expression was performed using a support vector machine and based on the presence of predicted motifs and motif pairs.
When the number of motif pairs used in MAMA was set to N mp, motif pairs with the top N mp lowest P-value were used for the simulation of gene expression.
Many studies on dynamic simulation of gene regulation systems have been reported in the literature.
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Modeling and simulation of gene-regulatory networks (GRNs) has become an important aspect of modern computational biology investigations into gene regulation.
Hence, the modeling and simulation of gene-regulation networks (GRNs) is becoming an area of growing interest in systems biology research [ 3].
Modeling and simulation of gene-regulatory networks (GRNs) has become an important aspect of modern systems biology investigations into mechanisms underlying gene regulation.
Bash script used to perform simulations of gene family evolution.
This, in combination with computer simulations of gene knock-outs or knock-ins in the stoichiometric model, can identify attractive targets for metabolic engineering in the organism [ 20].
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