Abstract
Toxicity pathway modeling is an effective approach to understanding how biological systems function under chemical perturbations. Many efforts have been made to construct pathways by data-driven or literature-based approaches to elucidate the mechanisms of action of toxicity. In this chapter, we explain how to build a literature-based pathway map in a collaborative manner using in silico platforms such as CellDesigner to draw pathways and networks, Payao as the curation platform, iPathways+ as the publishing platform, and Garuda to integrate curated pathways while adopting model-descriptive standards such as Systems Biology Markup Language as a file format and Systems Biology Graphical Notation as the graphical representation.
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Acknowledgements
This work was supported, in part, by funding from the Genome Network Project of the Ministry of Education, Culture, Sports, Science and Technology, the New Energy and Industrial Technology Development Organization, the International Strategic Collaborative Research Program of the Japan Science and Technology Agency (JST), the Exploratory Research for Advanced Technology program of JST [to the Systems Biology Institute (SBI)], and a strategic cooperation partnership between the Luxembourg Centre for Systems Biomedicine and the SBI. Inspired by the sbv IMPROVER workshops.
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Matsuoka, Y., Fujita, K., Ghosh, S., Kitano, H. (2015). Weaving Knowledge into Biological Pathways in a Collaborative Manner. In: Hoeng, J., Peitsch, M. (eds) Computational Systems Toxicology. Methods in Pharmacology and Toxicology. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-2778-4_8
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DOI: https://doi.org/10.1007/978-1-4939-2778-4_8
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