SPDBS: An SBML-Based Biochemical Pathway Database System

  • Tae-Sung Jung
  • Kyoung-Ran Kim
  • Seung-Hyun Jung
  • Tae-Kyung Kim
  • Myung-Sang Ahn
  • Jong-Hak Lee
  • Wan-Sup Cho
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4115)


Biochemical pathways such as metabolic, regulatory, or signal transduction pathways can be viewed as a complicated network of interactions among molecular species in the cell. As the amount of pathway information for various organisms is increasing very rapidly, performing various analyses on the full network of pathways for even multiple organisms can be possible and therefore developing an integrated database for storing and analyzing pathway information is becoming a critical issue. However, analyzing these networks is not easy because of the nature of the existing pathway databases, which are often heterogeneous, incomplete, and/or inconsistent. To solve this problem, SBML(Systems Biology Markup Language) – a computer-readable format for representing various biochemical pathways – has been adopted by the most of the SW packages in systems biology. We developed an SBML-based Biochemical Pathway Database System (SPDBS) that supports (1) efficient integration of the heterogeneous and distributed pathway databases, (2) prediction of the metabolic pathways for a given (non-annotated) genome sequence, (3) dynamic visualization/ simulation of the pathways, (4) starting from the detailed pathway graph, build networks at different levels of representation, (5) imports/exports of SBML documents for the simulation and/or exchange of the biochemical pathways in various applications. To evaluate the system, we applied the system to the construction of pathways from its genome sequences. For the E. coli genome sequence, SPDBS estimates the same metabolic pathways as the original well-known E. coli pathway. We are applying our system to the pathway prediction of S. chungbukensis DJ77 and Vibrio vulnificus CMCP6.


Biochemical Pathway Pathway Database Pathway Information System Biology Markup Language Pathway Reconstruction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Tae-Sung Jung
    • 1
  • Kyoung-Ran Kim
    • 1
  • Seung-Hyun Jung
    • 1
  • Tae-Kyung Kim
    • 1
  • Myung-Sang Ahn
    • 2
  • Jong-Hak Lee
    • 3
  • Wan-Sup Cho
    • 2
  1. 1.Dept. of Information Industrial EngineeringChungbuk National UniversityCheongju, ChungbukKorea
  2. 2.Dept. of Management Information SystemsChungbuk National UniversityCheongju, ChungbukKorea
  3. 3.Division of Computer & Information Communications EngineeringCatholic University of DaeguGyeongsan, GyeongbukKorea

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