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baker-carp-vis02 - GeneVis Visualization Tools for Genetic...

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GeneVis: Visualization Tools for Genetic Regulatory Network Dynamics C.A.H Baker 1 , M.S.T Carpendale 1 , P. Prusinkiewicz 1 and M.G. Surette 2 1 Department of Computer Science, University of Calgary 2 Department of Microbiology and Infectious Diseases, University of Calgary 1 bakerch,sheelagh,[email protected], 2 [email protected] A BSTRACT GeneVis provides a visual environment for exploring the dynam- ics of genetic regulatory networks. At present time, genetic regu- lation is the focus of intensive research worldwide, and computa- tional aids are being called for to help in the research of factors that are difficult to observe directly. GeneVis provides a particle-based simulation of genetic networks and visualizes the process of this simulation as it occurs. Two dynamic visualization techniques are provided, a visualization of the movement of the regulatory proteins and a visualization of the relative concentrations of these proteins. Several interactive tools relate the dynamic visualizations to the un- derlying genetic network structure. CR Categories: J.3 [Life and Medical Sciences]—Biology and genetics; I.6.7 [Computing Methodologies]: Computer Graphics— Simulation and Modeling, Simulation Support Systems, Environ- ments; I.3.6 [Computing Methodologies]: Information Systems— Information Interfaces and Presentation, User Interfaces, Interac- tion techniques. Keywords: biological visualization, visualization, multi- representation, genetic networks, lenses, focus and context 1 I NTRODUCTION Since the mapping of the human genome, research interests in biol- ogy have shifted towards the issue of discovering what the genetic code actually does. This includes such questions as: what proteins do genes code for? how does this affect the development and func- tioning of the organism? how do genes communicate appropriate information to each other? how do genetic networks function? and what are their dynamics? We consider genetic networks to consist of sets of genes that are regulated by sets of proteins. When genes in the network express they trigger the production of proteins, which in turn can regulate the expression of other genes, thus creating a network of depen- dence. Gene expression can exist in a relatively steady state of protein production, but the activity levels of genes can also change over time. With techniques such as DNA micro-arrays [10] it is now possible for biologists to measure, in parallel, the activity lev- els of genes as a function of time. Biologists may use these tem- poral measurements to infer which genes interact with which ones and what are the patterns of these interactions. However, this is a non-trivial exercise. The data is expensive and difficult to obtain, and can be noisy. Furthermore, even relatively small genetic net- works may have complex dynamics due to positive and negative feedback loops. To assist in the process of inference, models of the observed genetic activity are being developed. These models can be used to create simulations and visualizations, helping us form
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