Abstract
The field of systems biology endeavors to map, study, and simulate cellular systems and their underlying mechanisms. The internal mechanisms of biological systems can be represented with networks comprising nodes and edges. Nodes denote the constituents of the biological system whereas edges indicate the relationships among them. Likewise, every layer of cellular organization can be represented by networks. Multilayered networks capture interactions between various network types, such as transcriptional regulatory networks, protein–protein interaction networks, and metabolic networks from the same biological system. This property makes multilayered networks representative of the system while its internal mechanisms are investigated. However, there are not many multilayered networks containing integrated data for nonmodel organisms including the bacterial pathogens Salmonella. Here, we outline the steps to create such an integrated network database, through the example of SalmoNet, the first integrated multilayered data resource for multiple strains belonging to distinct Salmonella serovars.
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Acknowledgments
The authors would like to acknowledge all the contributors of the SalmoNet resource as well as the helpful discussions from the members and visitors of the Baranyi, Korcsmaros, and Kingsley groups. This work was supported by a fellowship to T.K. in computational biology at the Earlham Institute (Norwich, UK) in partnership with the Quadram Institute (Norwich, UK), and strategically supported by the Biotechnological and Biosciences Research Council, UK grants (BB/J004529/1, BB/P016774/1, and BB/CSP17270/1). This work was also supported by the BBSRC Norwich Research Park Biosciences Doctoral Training Partnership grant number BB/M011216/1.
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Olbei, M., Kingsley, R.A., Korcsmaros, T., Sudhakar, P. (2019). Network Biology Approaches to Identify Molecular and Systems-Level Differences Between Salmonella Pathovars. In: Bridier, A. (eds) Foodborne Bacterial Pathogens. Methods in Molecular Biology, vol 1918. Humana, New York, NY. https://doi.org/10.1007/978-1-4939-9000-9_21
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DOI: https://doi.org/10.1007/978-1-4939-9000-9_21
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