Concurrent Dynamic Visualizations With Expressive Petri Net Representations to Enrich the Understanding of Biological and Pathological Processes: an Application to Signaling Pathways

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F. Ramos
C. Hallal
A. Nieto
D. García
J. Berúmen
D. Escárcega

Abstract

Dynamic visualizations and expressive representations are needed in systems biology to handle multiple interactionsoccurring during the biological processes of biopathway representations. Dynamic visualizations allow users an easeof interaction with pathway models. At the same time, representations of biopathways should express how interactionstake place. In spite of the fact that diverse databases provide users with pathways, their information andrepresentation are frequently different from each other and show restricted interactions because of their staticvisualization. An adopted solution is to merge diverse representations to obtain a richer one. However, due to differentformats and the multiple links involved in the pathway representations, the merge results frequently in erroneousmodels and in a tangle web of relations very hard to be manipulated. Instead, this work introduces a concurrentdynamic visualization (CDV) of the same pathway, which is retrieved from different sites and then transformed intoPetri net representations to facilitate the understanding of their biological processes by interacting with them. Weapplied this approach to the analysis of the Notch signaling pathway, associated with cervical cancer; we obtained itfrom different sources which we compared and manipulated simultaneously by interacting with the provided CDV untilthe user generated a personalized pathway.

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How to Cite
Ramos, F., Hallal, C., Nieto, A., García, D., Berúmen, J., & Escárcega, D. (2012). Concurrent Dynamic Visualizations With Expressive Petri Net Representations to Enrich the Understanding of Biological and Pathological Processes: an Application to Signaling Pathways. Journal of Applied Research and Technology, 10(5). https://doi.org/10.22201/icat.16656423.2012.10.5.370
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