Cellular Automata Modeling of Biomolecular Networks

Bonchev, Danail

doi:10.5772/15727

Cited by 1 publication

(2 citation statements)

References 100 publications

(52 reference statements)

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“…Recently, CA has been widely used in the Center for the Study of Biological Complexity at VCU in Richmond, Virginia as a modeling approach for simulation biological problems [71]. …”

Section: Modeling Algorithmsmentioning

confidence: 99%

“…Application of CA in biology mainly shows itself in the subject of systems biology such as shape space simulations of the immune system [ 65 ], development of an artificial brain [ 66 ], a study of morphogenesis in simple cellular systems [ 67 ], modeling the competitive growth of two underwater species C. aspera and P. Pectinatus [ 68 ], a model of an enzymatic reaction [ 69 ], and especially in the study of excitable media [ 70 ]. Recently, CA has been widely used in the Center for the Study of Biological Complexity at VCU in Richmond, Virginia as a modeling approach for simulation biological problems [ 71 ].…”

Section: Modeling Algorithmsmentioning

confidence: 99%

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Genome Scale Modeling in Systems Biology: Algorithms and Resources

Najafi

Bidkhori

Bozorgmehr

et al. 2014

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In recent years, in silico studies and trial simulations have complemented experimental procedures. A model is a description of a system, and a system is any collection of interrelated objects; an object, moreover, is some elemental unit upon which observations can be made but whose internal structure either does not exist or is ignored. Therefore, any network analysis approach is critical for successful quantitative modeling of biological systems. This review highlights some of most popular and important modeling algorithms, tools, and emerging standards for representing, simulating and analyzing cellular networks in five sections. Also, we try to show these concepts by means of simple example and proper images and graphs. Overall, systems biology aims for a holistic description and understanding of biological processes by an integration of analytical experimental approaches along with synthetic computational models. In fact, biological networks have been developed as a platform for integrating information from high to low-throughput experiments for the analysis of biological systems. We provide an overview of all processes used in modeling and simulating biological networks in such a way that they can become easily understandable for researchers with both biological and mathematical backgrounds. Consequently, given the complexity of generated experimental data and cellular networks, it is no surprise that researchers have turned to computer simulation and the development of more theory-based approaches to augment and assist in the development of a fully quantitative understanding of cellular dynamics.

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“…Recently, CA has been widely used in the Center for the Study of Biological Complexity at VCU in Richmond, Virginia as a modeling approach for simulation biological problems [71]. …”

Section: Modeling Algorithmsmentioning

confidence: 99%