I Chun Chou

Summary

Affiliation: Georgia Institute of Technology
Country: USA

Publications

  1. ncbi Recent developments in parameter estimation and structure identification of biochemical and genomic systems
    I Chun Chou
    Integrative BioSystems Institute and The Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, 313 Ferst Drive, Atlanta, GA 30332, USA
    Math Biosci 219:57-83. 2009
  2. ncbi Parameter optimization in S-system models
    Marco Vilela
    Dept Bioinformatics and Computational Biology, University of Texas M, d, Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030, USA
    BMC Syst Biol 2:35. 2008
  3. ncbi Parameter estimation in biochemical systems models with alternating regression
    I Chun Chou
    The Wallace H Coulter Department of Biomedical Engineering at Georgia Institute of Technology and Emory University, 313 Ferst Drive, Atlanta, GA 30332, USA
    Theor Biol Med Model 3:25. 2006
  4. ncbi System estimation from metabolic time-series data
    Gautam Goel
    Integrative BioSystems Institute and The Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, 313 Ferst Drive, Atlanta, GA 30332, USA
    Bioinformatics 24:2505-11. 2008
  5. ncbi Estimation of dynamic flux profiles from metabolic time series data
    I Chun Chou
    Integrative BioSystems Institute and The Wallace H, Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, 313 Ferst Drive, Atlanta, GA 30332, USA
    BMC Syst Biol 6:84. 2012

Collaborators

  • Marco Vilela
  • Gautam Goel
  • Eberhard O Voit
  • Jonas S Almeida
  • Susana Vinga
  • Ana Tereza R Vasconcelos

Detail Information

Publications5

  1. ncbi Recent developments in parameter estimation and structure identification of biochemical and genomic systems
    I Chun Chou
    Integrative BioSystems Institute and The Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, 313 Ferst Drive, Atlanta, GA 30332, USA
    Math Biosci 219:57-83. 2009
    ..The article concludes with a discussion of the present state of the art and with a description of open questions...
  2. ncbi Parameter optimization in S-system models
    Marco Vilela
    Dept Bioinformatics and Computational Biology, University of Texas M, d, Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030, USA
    BMC Syst Biol 2:35. 2008
    ..It was previously shown that parameter identification can be performed as an optimization based on the decoupling of the differential S-system equations, which results in a set of algebraic equations...
  3. ncbi Parameter estimation in biochemical systems models with alternating regression
    I Chun Chou
    The Wallace H Coulter Department of Biomedical Engineering at Georgia Institute of Technology and Emory University, 313 Ferst Drive, Atlanta, GA 30332, USA
    Theor Biol Med Model 3:25. 2006
    ..The estimation of parameter values continues to be the bottleneck of the computational analysis of biological systems. It is therefore necessary to develop improved methods that are effective, fast, and scalable...
  4. ncbi System estimation from metabolic time-series data
    Gautam Goel
    Integrative BioSystems Institute and The Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, 313 Ferst Drive, Atlanta, GA 30332, USA
    Bioinformatics 24:2505-11. 2008
    ..Its avoidance of error compensation among process descriptions promises significantly improved extrapolability toward new data or experimental conditions...
  5. ncbi Estimation of dynamic flux profiles from metabolic time series data
    I Chun Chou
    Integrative BioSystems Institute and The Wallace H, Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, 313 Ferst Drive, Atlanta, GA 30332, USA
    BMC Syst Biol 6:84. 2012
    ..However, such supplementations incur their own limitations. In particular, assumptions must be made regarding the functional forms of some processes and detailed kinetic information must be available, in addition to the time series data...