Volume 5 Number 2 (Feb. 2010)
Home > Archive > 2010 > Volume 5 Number 2 (Feb. 2010) >
JSW 2010 Vol.5(2): 187-194 ISSN: 1796-217X
doi: 10.4304/jsw.5.2.187-194

An Interpretation of Biological Metabolites and their Reactions Based on Relation Degree of Compound Pairs in KEGG XML Files

Myungha Jang1, 2, Jiyoung Whang1, Coleen S. Lewis2, Hyun S. Park3
1Department of Computer Science and Engineering, Ewha Womans University, Seoul, South Korea.
2Department of Natural Sciences and Mathematics, Wesleyan College, Macon, GA, United States.
3Institute of Bioinformatics, Ewha Womans University, Seoul, Korea & Institute of Bioinformatics, Macrogen Inc., Seoul, Korea.

Abstract—Biological pathways can be characterized as networks and grouped as metabolic pathways, gene regulatory networks, gene interaction networks and signal transduction pathways. It is important that edge crossings in biological pathway diagrams are kept to a minimum by strategic placement of vertices for simplification. The basic graph layout technique deals with the problem of positioning the vertices in a way to maximize understandability and usability in a graph. However, when dealing with a very large number of nodes in a global metabolic pathway, strategically positioning vertices is not enough. Understanding the properties of the metabolites and the biological reactions is crucial to pave the way for the formulation of new strategies for further development of automatic layout for global metabolic pathway. In this paper, we provide a statistical analysis of metabolic reactions based on the parsing result of publicly available XML files in KEGG. The analysis leads to a new node-abstracting scheme according to the newly defined concept, ‘relation degree of compound pairs’. The concept would suggest valuable information to software developers for graph-based visualization tools for analyzing networks in cell biology.

Index Terms—Metabolic pathway, parsing, XML, relation degree, drawing algorithm, edge crossing, statistics of metabolites.


Cite: Myungha Jang, Jiyoung Whang, Coleen S. Lewis, Hyun S. Park, "An Interpretation of Biological Metabolites and their Reactions Based on Relation Degree of Compound Pairs in KEGG XML Files," Journal of Software vol. 5, no. 2, pp. 187-194, 2010.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
  • Apr 26, 2021 News!

    Vol 14, No 4- Vol 14, No 12 has been indexed by IET-(Inspec)     [Click]

  • Jun 22, 2020 News!

    Papers published in JSW Vol 14, No 1- Vol 15 No 4 have been indexed by DBLP     [Click]

  • Sep 13, 2021 News!

    The papers published in Vol 16, No 6 have all received dois from Crossref    [Click]

  • Jan 28, 2021 News!

    [CFP] 2021 the annual meeting of JSW Editorial Board, ICCSM 2021, will be held in Rome, Italy, July 21-23, 2021   [Click]

  • Sep 13, 2021 News!

    Vol 16, No 6 has been published with online version     [Click]