AI Article Synopsis
- Genome-scale reconstructed metabolic networks help us understand cellular processes and their connections to phenotype, leading to an increase in the number of organisms studied.
- New online systems like DORMAN have been developed to store these reconstructions and provide tools for analyzing their topologies.
- DORMAN features interactive visualization, hierarchical navigation for easy access, a query interface for topological analysis, and a model comparison tool for different nomenclatures, making it a comprehensive resource for researchers.
Article Abstract
Genome-scale reconstructed metabolic networks have provided an organism specific understanding of cellular processes and their relations to phenotype. As they are deemed essential to study metabolism, the number of organisms with reconstructed metabolic networks continues to increase. This everlasting research interest lead to the development of online systems/repositories that store existing reconstructions and enable new model generation, integration, and constraint-based analyses. While features that support model reconstruction are widely available, current systems lack the means to help users who are interested in analyzing the topology of the reconstructed networks. Here, we present the Database of Reconstructed Metabolic Networks - DORMAN. DORMAN is a centralized online database that stores SBML-based reconstructed metabolic networks published in the literature, and provides web-based computational tools for visualizing and analyzing the model topology. Novel features of DORMAN are (i) interactive visualization interface that allows rendering of the complete network as well as editing and exporting the model, (ii) hierarchical navigation that provides efficient access to connected entities in the model, (iii) built-in query interface that allow posing topological queries, and finally, and (iv) model comparison tool that enables comparing models with different nomenclatures, using approximate string matching. DORMAN is online and freely accessible at http://ciceklab.cs.bilkent.edu.tr/dorman.
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| http://dx.doi.org/10.1109/TCBB.2019.2944905 | DOI Listing |
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