Abstract
Thanks to the digital revolution, digital signal processing and control has been widely used in many areas of science and engineering today. It provides practical and powerful tools to model, simulate, analyze, design, measure, and control complex and dynamic systems such as robots and aircrafts. Gene networks are also complex dynamic systems which can be studied via digital signal processing and control. Unlike conventional computational methods, this approach is capable of not only modeling but also controlling gene networks since the experimental environment is mostly digital today. The overall aim of this article is to introduce digital signal processing and control as a useful tool for the study of gene networks.
Highlights
Digital signal processing and control engineering has been widely used in many areas of science and engineering today[1,2]
Modeling simple two-gene network as a difference equation becomes important since it can serve as the basic building block for constructing more complex gene networks[11]
Xgene is transcribed into xmRNA, which is translated into xprotein
Summary
Digital signal processing and control engineering has been widely used in many areas of science and engineering today[1,2]. There has been an explosive growth in digital signal processing and control theory and applications over the past decades In this article, it is proposed the digital approach can be useful for the study of gene networks. The production of each protein molecule requires a discrete amount of time In this context, it is proposed that difference equations can be used to model gene network dynamics, which approximate not continuous differential equations but real systems. It is proposed that difference equations can be used to model gene network dynamics, which approximate not continuous differential equations but real systems This approach is simpler and more accessible to students and researchers not familiar with differential equations since the mathematics is simple to understand. Every attempt was made to make the materials accessible to engineers, mathematicians, or physicists and to life scientists, introducing the basics of both digital signal processing and control and gene networks
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