By Topic

A graph analysis method to detect metabolic sub-networks based on phylogenetic profile

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Miyake, S. ; Dept. of Bioinformatic Eng., Osaka Univ., Japan ; Takenaka, Y. ; Matsuda, H.

To elucidate fundamental constituting principle of functional modules or building blocks of metabolic networks, computational methods to analyze the network structure of metabolism are getting much attention. We propose a graph search method to extract highly conserved sub-networks of metabolic networks based on phylogenetic profile. We formulated reaction-conservation score for the measure of the phylogenetic conservation of reactions. We also formulated compound-conservation score to eliminate biologically-meaningless compounds and reduce the size of the networks. By applying our approach to the metabolic networks of 19 representative organisms selected from bacteria, archaea, and eukaryotes in the KEGG database, we detected some highly conserved sub-networks among the organisms. Comparing them to the metabolic maps in KEGG, we found they were mainly included in energy metabolism, sugar metabolism, and amino acid metabolism.

Published in:

Computational Systems Bioinformatics Conference, 2004. CSB 2004. Proceedings. 2004 IEEE

Date of Conference:

16-19 Aug. 2004