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Related Experiment Video

Updated: May 14, 2026

A Web Tool for Generating High Quality Machine-readable Biological Pathways
08:01

A Web Tool for Generating High Quality Machine-readable Biological Pathways

Published on: February 8, 2017

A program code generator for multiphysics biological simulation using markup languages.

Akira Amano1, Masanari Kawabata, Yoshiharu Yamashita

  • 1Institute of Medical Engineering, University of Luebeck, 23562 Luebeck, Germany. fschuetz@imt.uni-luebeck.de

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|February 1, 2013
PubMed
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This study introduces a novel system for generating biological simulation code. It simplifies modifying complex simulation conditions and calculation methods, enhancing the flexibility of biological function simulations.

Area of Science:

  • Computational Biology
  • Systems Biology
  • Bioinformatics

Background:

  • Biological function simulation models are increasingly complex.
  • Existing simulation software presents challenges in modifying conditions, resources, and calculation methods.
  • Description model files partially address complexity but struggle with diverse calculation schemes for coupled models.

Purpose of the Study:

  • To develop a simulation software generation system that simplifies the creation and modification of complex biological simulations.
  • To enable easy integration of various coupling calculation schemes.
  • To address the limitations of current description model files in handling diverse computational aspects.

Main Methods:

  • Developed a system using a description language for coupling calculation schemes alongside cell model description files.

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Last Updated: May 14, 2026

A Web Tool for Generating High Quality Machine-readable Biological Pathways
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Published on: February 8, 2017

Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion
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  • The system generates biological simulation code based on these descriptions.
  • Demonstrated the system's efficiency using an example with three coupled elementary models.

    • Main Results:

    • The introduced system allows for easy generation of biological simulation code.
    • It effectively handles various coupling calculation schemes required for complex models.
    • The example showcases the system's capability with multi-component simulations.

    Conclusions:

    • The novel software generation system simplifies the development of complex biological simulations.
    • It enhances flexibility in managing simulation conditions and calculation methods.
    • This approach facilitates more adaptable and efficient computational biology research.