Anguix: Cell Signaling Modeling Improvement through Sabio-RK association to Reactome

Kinetics of biochemical reactions are widely spread in scientific papers and repositories such as Sabio-RK. This information is extremely important for the study of cell signaling pathways; however, to the best of our knowledge, there is no method available to integrate pathways reactions topology d...

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Bibliographic Details
Published in:	2022 IEEE 18th International Conference on e-Science (e-Science) pp. 425 - 426
Main Authors:	Montoni, Fabio, De Sousa, Ronaldo N., De Lima Junior, Marcelo B., Campos, Cristiano G.S., Wang, Willian, Constantino, Vivian M., Sanctos, Cassia S., Armelin, Hugo A., Reis, Marcelo S.
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01-10-2022
Subjects:	Graph Database Kinetic Data Python Reactome Sabio-RK
Online Access:	Get full text
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Summary:	Kinetics of biochemical reactions are widely spread in scientific papers and repositories such as Sabio-RK. This information is extremely important for the study of cell signaling pathways; however, to the best of our knowledge, there is no method available to integrate pathways reactions topology data with kinetic data. Therefore, we propose here an integration of kinetic data stored in Sabio-RK to the Reactome graph database. That integration, called Anguix, can be deployed using a Python program and also can be easily accessed using Neo4J. We believe the Anguix graph database might contribute to the modeling of cell signaling pathways, by combining the completeness of Reactome with kinetic and quantitative data stored in Sabio-RK.
DOI:	10.1109/eScience55777.2022.00070