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libSRES: a C library for stochastic ranking evolution strategy for parameter estimation.

Xinglai Ji1, Ying Xu

  • 1Computational Biology Institute, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA.

Bioinformatics (Oxford, England)
|November 4, 2005
PubMed
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We developed libSRES, a C library for fast computation of biochemical pathway parameters. This tool uses an evolutionary algorithm and offers a parallel version for efficient systems biology studies.

Area of Science:

  • Systems biology
  • Biochemical pathway analysis
  • Computational biology

Background:

  • Parameter estimation is crucial for understanding biological processes.
  • Non-linear biochemical pathways present computational challenges.
  • Efficient software tools are needed for systems biology research.

Purpose of the Study:

  • To implement a C library, libSRES, for rapid development of software to study non-linear biochemical pathways.
  • To provide a tool that facilitates the estimation of kinetic parameters in biochemical networks.

Main Methods:

  • Implementation of a C library named libSRES.
  • Utilizes a (mu, lambda)-ES evolutionary optimization algorithm.
  • Incorporates stochastic ranking for constraint handling.

Related Experiment Videos

  • Provides an MPI version for parallel computation and a user interface.

    • Main Results:

    • libSRES facilitates fast implementation of computer software for biochemical pathway studies.
    • The library includes a parallel MPI version for efficient computation.
    • Performance testing on various pathway parameter-estimation problems showed satisfactory results.

    Conclusions:

    • libSRES is a freely available C library for estimating kinetic parameters in biochemical pathways.
    • It offers a fast and efficient solution for systems biology studies.
    • The library can be directly integrated into C programs.