F. Ramos*1, C. Hallal2, A. Nieto3, D. García4, J. Berúmen5, D. Escárcega*6
1, 4, 6 Tecnológico de Monterrey, Campus Cuernavaca. Autopista del Sol Km 104+060. Col. Real del Puente, C.P. 62790, Xochitepec, Morelos, México.*fernando.Ramos@itesm.mx; *daescarcega@gmail.com
2, 3 Universidad Autónoma del Estado de Morelos. Facultad de Farmacia, Av. Universidad 1001. Col. Chamilpa. Cuernavaca, Morelos. C. P. 62209.
5 Hospital General de México. Dr. Balmis 148, Colonia Doctores, delegación Cuauhtémoc, C.P. 06726, México, D.F.
Abstract
]]> Dynamic visualizations and expressive representations are needed in systems biology to handle multiple interactions occurring during the biological processes of biopathway representations. Dynamic visualizations allow users an ease of interaction with pathway models. At the same time, representations of biopathways should express how interactions take place. In spite of the fact that diverse databases provide users with pathways, their information and representation are frequently different from each other and show restricted interactions because of their static visualization. An adopted solution is to merge diverse representations to obtain a richer one. However, due to different formats and the multiple links involved in the pathway representations, the merge results frequently in erroneous models and in a tangle web of relations very hard to be manipulated. Instead, this work introduces a concurrent dynamic visualization (CDV) of the same pathway, which is retrieved from different sites and then transformed into Petri net representations to facilitate the understanding of their biological processes by interacting with them. We applied this approach to the analysis of the Notch signaling pathway, associated with cervical cancer; we obtained it from different sources which we compared and manipulated simultaneously by interacting with the provided CDV until the user generated a personalized pathway.Keywords: Petri nets, dynamic visualization, signaling pathways, pathway databases.
Resumen
En biología de sistemas la visualización dinámica y las representaciones expresivas son necesarias para representar interacciones múltiples que ocurren durante los procesos biológicos en bioredes. La visualización dinámica facilita a los usuarios interactuar con modelos de bioredes, mientras que las representaciones deben expresar como se llevan a cabo las interacciones dentro de éstas. A pesar de que diversas bases de datos proveen de redes a los usuarios, generalmente la información y representación contenidas en cada una son diferentes, y la interacción usuario-biored es restringida debido a la visualización estática. Una solución que se ha adoptado es hacer converger varias representaciones para obtener una más completa. Sin embargo, debido al uso de diferentes formatos incompatibles entre ellos y a las múltiples conexiones involucradas en las redes, la integración frecuentemente resulta en modelos erróneos y en una maraña de conexiones representadas en la red que son muy difíciles de analizar y manipular. En este trabajo introducimos la visualización dinámica concurrente (VDC) de una misma vía, la cual es recuperada de diferentes bases de datos y transformada a representaciones en redes de Petri para facilitar el entendimiento de los procesos biológicos y modificar las vías obtenidas interactuando con ellas. Hemos aplicado esta estrategia al análisis de la vía de señalización de Notch, asociada a cáncer cérvicouterino, obteniéndola de tres diferentes fuentes, comparándolas y manipulándolas simultáneamente interactuando con la VDC provista, hasta la generación de una vía personalizada.
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