Authors: J.W. Yeol, I. Barjis, J. Barjis, S. Berri and Y. Ryu
Affilation: Polytechnic University, United States
Pages: 367 - 370
Keywords: boolean network, molecular, protein, DNA
In this paper, we introduce a new application of modeling tool; Boolean Networks (BN). In particular, it shows how, by means of a Boolean Networks (BN), the protein production process can be modeled and analyzed. In order to develop the model of protein product process by using Boolean Networks, we address the problem with a whole process first, then three different detail processes will be approached. The purpose of this paper is to develop modeling methodology for the production of proteins. This methodology helps formalization, modeling and simulation of the production of proteins. Therefore the first conclusion is that dynamic processes of molecular and biological systems in general, the protein production process in particular can be modeled as a discrete dynamic system. Two areas can benefit from such a methodology that has been presented in this paper: to stimulate research and to assist teaching. For the teaching purposes, this can assist to visualize the protein production processes model from state to state and to explain how all molecular events, reactions and operations together provide production of proteins from DNA. It can show how the precursors and substrates, which are required for each step of the protein production processes, are bound to their targets. This paper can be also useful for the training program offering molecular biology with modeling and information sciences integrated into the individual courses, to train students in the use of computational techniques in the study of molecular and biological science. For the research purposes, one can use this methodology for the protein production modeling and simulation. It is also useful for protein and DNA sequence analysis. Finally, it seems that the results of this paper are one of the first efforts to apply discrete systems modeling technique to molecular-biology processes. In its turn it is another one step towards bringing computer science and molecular biology closer and calling it bioinformatics.