ArticleScientific reports2018
Topological assessment of metabolic networks reveals evolutionary information.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed.
- Screening of exogenous nutrients for pathogenic bacteria and development of highly active bactericides.mSystems · 2026Article
- Post-acute sequelae of SARS-CoV-2 infection symptom network centrality analysis of Taiwan population to unveil intricate symptomatology patterns.Scientific reports · 2026Article
- Metabolites of pathogenic microorganisms database (MPMdb) and its seed metabolite applications.Microbiology spectrum · 2024Article
- A community resource to mass explore the wheat grain proteome and its application to the late-maturity alpha-amylase (LMA) problem.GigaScience · 2022Article
- Article
- On the Use of Topological Features of Metabolic Networks for the Classification of Cancer Samples.Current genomics · 2021Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Evolutionary information was inferred from the topology of metabolic networks corresponding to 17 plant species belonging to major plant lineages Chlorophytes, Bryophytes, Lycophytes and Angiosperms. The plant metabolic networks were built using the substrate-product network modeling based on the metabolic reactions available on the PlantCyc database (version 9.5), from which their local topological properties such as degree, in-degree, out-degree, clustering coefficient, hub-score, authority-score, local efficiency, betweenness and eigencentrality were measured. The topological measurements corresponding to each metabolite within the networks were considered as a set of metabolic characters to compound a feature vector representing each plant. Our results revealed that some local topological characters are able to discern among plant kinships, since similar phylogenies were found when comparing dendrograms obtained by topological metrics to the one obtained by DNA sequences of chloroplast genes. Furthermore, we also found that even a smaller number of metabolic characters is able to separate among major clades with high bootstrap support (BS > 95), while for some suborders a bigger content has been required.
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