Analysis and Prediction of Nutritional Requirements Using Structural Properties of Metabolic Networks and Support Vector Machines

Takeyuki Tamura, Nils Christian, Kazuhiro Takemoto, Oliver Ebenhoeh, Tatsuya Akutsu

Research output: Contribution to journalArticle

Abstract

Properties of graph representation of genome scale metabolic networks have been extensively studied. However, the relationship between these structural properties and functional properties of the networks are still very unclear. In this paper, we focus on nutritional requirements of organisms as a functional property and study the relationship with structural properties of a graph representation of metabolic networks. In order to examine the relationship, we study to what extent the nutritional requirements can be predicted by using support vector machines from structural properties, which include degree exponent, edge density, clustering coefficient, degree centrality, closeness centrality, betweenness centrality and eigenvector centrality. Furthermore, we study which properties are influential to the nutritional requirements.
Original languageEnglish
Pages (from-to)176-190
Number of pages15
JournalGenome Informatics
Volume22
DOIs
Publication statusPublished - 2009
EventProceedings of the 9th Annual International Workshop on Bioinformatics and Systems Biology (IBSB 2009) - Boston, United States
Duration: 27 Jul 200929 Jul 2009

Keywords

  • metabolic networks
  • support vector machines
  • nutritional profile
  • centrality

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