Modeling of system biology: from dna to protein by automata networks

Abstract

Tile emphasis o.fthis paper is on IIsing Fillile Automata (FA) as a lIIodeling tool to lIIodel, sililulate alld ana�vze the process o.fprofein production. There is tremendous potential for mathematical alld compulational appro(iches in leading to .limdamellla! inSights and important practical benefits in research 011 hiological systems. Mathematical and cOl1lpulalional approaches have long been appreCiated in physics and ill the last twenty years have ph�ved an ever-increasing role ill chemistry. Now more and 1//01'1.' moleclilar biologist and biochemists are interested if/llsing compuler science applications and mathematical app/'Oaches in tlIfir work. In the first section, we introdllce the basic concept o/hioinjo17natics and modeling tools in Biology. In the second mid third sections Ihe molecular eve!1ls a/prolein /)/'OdIlCtioll process is exp lained and then based on the lIIo/eell/ar events, G Finite AlIlomGla lIIodel is constructed During the latter half of the 20th century, biology was dominated by reductionism approaches thaI successfully allowed for the generation of information about individual cellular components and their functions. Over the past decade , thiS proces� has been greatly accelerated due to the emergence 01' gcnomics. We now have entire DNA sequences for a growing numbe r of organisms and are c ontinually defining their gene portfolios. Also Molecular processes are complex, dynamic and invisible. This complexity makes them difficult to explain, teach, demonstrate and understand, Further more, any laboratory experiment ofbiologicaJ process/reaction is a (ilbe consuming business. Many biological experiments require days or weeks, before the dynamic behavior of reaction, process or the expected result can be obs erved . Even then many biological experiments tail to get the desired or expeoted resull by carrying the experiment once. So the repetitions of the experiments not only make it time consuming business, but also costly business. Pharmaciutical companies are trying to lo wer 'the risk and financial burden of clinical trials, so technologies that use compllters to model and simulate biological systems are revolutionizing the drug discovery field. Though clinical trials are in no inm1ediate danger of replacement by simulation tecimologies, pharmaceutical companies are eagerly adopting new means of accelerating the drug discovery and development process. This study analy£es the emerging markets for technologies that enable researchers to model and simuhlle biological pathways, cells, tissue, and diseases. It examines upcoming products, pricing strategies, and competitive pressures. With such in depth coverage, your company will be well prepared to capitalize on a burgeoning industry. Modeling the struc1ure of Biological molecules and processes are critical for understanding how these structures and processes perform their function. Furthermore, these models can be u,ed for designing compounds to modify or enhance the functions of biological molecules for medical or industrial purpose, or ...

Deterministic boolean networks (DBN) modeling of molecular biology: DNA replication

“…A node may represent either a gene or a biological stimulus, where a stimulus is any relevant physical or chemical factor which influences the network and is itself not a gene or product. A sequence of states is called trajectory [6][7][8]. BN table is another representation of Boolean Networks model in figure 2.…”

“…Finally, suggestions for future works are given at the end of this paper. The author suggested different kinds of modeling methods to represent DNA, RNA, and protein process such as Petri-Nets (PN), Data-flow diagram, Discrete event-based modeling, and so on [6][7][8][9]. Each modeling has different perspective and usages, but we concentrate on the process based on "turing-machine" to maximize the point view of understanding first and controlling the process in the future.…”

Data-flow diagram representation of biological process: DNA, RNA, and protein

“…Finally, suggestions for future works are given at the end of this paper. The author suggested different kinds of modeling methods to represent DNA, RNA, and protein process such as Petri-Nets (PN), Boolean Network (BN), Discrete event-based modeling, and so on [6][7][8][9]. Each modeling has different perspective and usages, but we concentrate on the flow of data in the process to maximize the point view of understanding first and controlling the process in the future.…”

Modeling of carbohydrate metabolism: from dietary carbohydrate to pyruvic acid by petri-nets (PN)

“…Bioinformatics is the study of the inherent structure of biological information and biological systems [1][2], which integrates courses and research in biology (molecular biology) with computer modeling and information sciences. The author suggested different kinds of modeling methods to represent DNA, RNA, and protein process with Petri-Nets (PN), Boolean Network (BN) , Discrete event-based modeling, and so on [2][3][4][5][6][7][8][9]. Each modeling has different perspective and usages, but we concentrate on the flow of data in the process to maximize the point view of understanding first and controlling the process in the future.…”