Published October 5, 2022
| Version v1
Presentation
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Anguix: Cell Signaling Modeling Improvement Through Sabio-RK Association to Reactome
Creators
- 1. Center of Toxins, Immune-Response and Cell Signaling (CeTICS),Butantan Institute/ Cell Cycle Laboratory, Butantan Institute/ Bioinformatics Graduate Program, University of São Paulo
- 2. Center of Toxins, Immune-Response and Cell Signaling (CeTICS),Butantan Institute/ Cell Cycle Laboratory, Butantan Institute/ Bioinformatics Graduate Program
- 3. Laboratory of Artificial Intelligence and Inference in Complex Data (Recod.ai)
- 4. Center of Toxins, Immune-Response and Cell Signaling (CeTICS),Butantan Institute
- 5. Center of Toxins, Immune-Response and Cell Signaling (CeTICS)/ Cell Cycle Laboratory, Butantan Institute/ Biochemistry Department, Institute of Chemistry, University of São Paulo
- 6. Center of Toxins, Immune-Response and Cell Signaling (CeTICS),Butantan Institute/ Laboratory of Artificial Intelligence and Inference in Complex Data (Recod.ai)
Description
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.
Notes
Access to our GitHub: https://github.com/anthraxodus/Anguix-command-line
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Anguix_IEEE_2022_2min_Slide_Final.pdf
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