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cplex linear programming solver for cobra  (Tomlab Optimization)

 
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    Structured Review

    Tomlab Optimization cplex linear programming solver for cobra
    The running time for both the <t>PSAMM</t> overall function (blue) and the PSAMM problem-solving steps (red) were calculated, and the running time for COBRA only included the problem-solving step (green). Each value represents a median of seven simulation runs using the same specifications, and the error bars indicate the 25th and the 75th percentiles.
    Cplex Linear Programming Solver For Cobra, supplied by Tomlab Optimization, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/cplex linear programming solver for cobra/product/Tomlab Optimization
    Average 90 stars, based on 1 article reviews
    cplex linear programming solver for cobra - by Bioz Stars, 2026-05
    90/100 stars

    Images

    1) Product Images from "PSAMM: A Portable System for the Analysis of Metabolic Models"

    Article Title: PSAMM: A Portable System for the Analysis of Metabolic Models

    Journal: PLoS Computational Biology

    doi: 10.1371/journal.pcbi.1004732

    The running time for both the PSAMM overall function (blue) and the PSAMM problem-solving steps (red) were calculated, and the running time for COBRA only included the problem-solving step (green). Each value represents a median of seven simulation runs using the same specifications, and the error bars indicate the 25th and the 75th percentiles.
    Figure Legend Snippet: The running time for both the PSAMM overall function (blue) and the PSAMM problem-solving steps (red) were calculated, and the running time for COBRA only included the problem-solving step (green). Each value represents a median of seven simulation runs using the same specifications, and the error bars indicate the 25th and the 75th percentiles.

    Techniques Used: Combined Bisulfite Restriction Analysis Assay

    The five main components include: (1) user interface, (2) model input/output, (3) model representation, (4) linear programming utilities, and (5) model checking/simulation. Connections among these components form the internal workflow of PSAMM.
    Figure Legend Snippet: The five main components include: (1) user interface, (2) model input/output, (3) model representation, (4) linear programming utilities, and (5) model checking/simulation. Connections among these components form the internal workflow of PSAMM.

    Techniques Used:

    List of commands supported in the psamm-model program. Additional parameters can be specified for the commands, for example to select a specific implementation among multiple algorithms, enable/disable thermodynamic constraints, or select linear programming solvers, etc . Details about these parameters are available through the -h or -- help options for each command.
    Figure Legend Snippet: List of commands supported in the psamm-model program. Additional parameters can be specified for the commands, for example to select a specific implementation among multiple algorithms, enable/disable thermodynamic constraints, or select linear programming solvers, etc . Details about these parameters are available through the -h or -- help options for each command.

    Techniques Used:

    (a) This diagram shows an example of the YAML model format, which includes a central model definition (model.yaml) and multiple annotation files. Each box indicates a file with a possible filename indicated above the box, and the text within is a snapshot of the file content. (b) An example showing how changes can be tracked in a PSAMM YAML file (biomass.yaml) using the Git version control system in command line. The text highlighted in red indicates the stoichiometry of the compound arg-L in an old version of the biomass function, while the text highlighted in green indicates the updated value in a new version of the model. Additional examples of applying Git version control on the YAML format are provided in the supplemental materials ( – Texts).
    Figure Legend Snippet: (a) This diagram shows an example of the YAML model format, which includes a central model definition (model.yaml) and multiple annotation files. Each box indicates a file with a possible filename indicated above the box, and the text within is a snapshot of the file content. (b) An example showing how changes can be tracked in a PSAMM YAML file (biomass.yaml) using the Git version control system in command line. The text highlighted in red indicates the stoichiometry of the compound arg-L in an old version of the biomass function, while the text highlighted in green indicates the updated value in a new version of the model. Additional examples of applying Git version control on the YAML format are provided in the supplemental materials ( – Texts).

    Techniques Used: Control



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    cplex linear programming solver for cobra  (Tomlab Optimization)
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    Tomlab Optimization cplex linear programming solver for cobra
    The running time for both the <t>PSAMM</t> overall function (blue) and the PSAMM problem-solving steps (red) were calculated, and the running time for COBRA only included the problem-solving step (green). Each value represents a median of seven simulation runs using the same specifications, and the error bars indicate the 25th and the 75th percentiles.
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    The running time for both the <t>PSAMM</t> overall function (blue) and the PSAMM problem-solving steps (red) were calculated, and the running time for COBRA only included the problem-solving step (green). Each value represents a median of seven simulation runs using the same specifications, and the error bars indicate the 25th and the 75th percentiles.
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    The running time for both the <t>PSAMM</t> overall function (blue) and the PSAMM problem-solving steps (red) were calculated, and the running time for COBRA only included the problem-solving step (green). Each value represents a median of seven simulation runs using the same specifications, and the error bars indicate the 25th and the 75th percentiles.
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    Image Search Results


    The running time for both the PSAMM overall function (blue) and the PSAMM problem-solving steps (red) were calculated, and the running time for COBRA only included the problem-solving step (green). Each value represents a median of seven simulation runs using the same specifications, and the error bars indicate the 25th and the 75th percentiles.

    Journal: PLoS Computational Biology

    Article Title: PSAMM: A Portable System for the Analysis of Metabolic Models

    doi: 10.1371/journal.pcbi.1004732

    Figure Lengend Snippet: The running time for both the PSAMM overall function (blue) and the PSAMM problem-solving steps (red) were calculated, and the running time for COBRA only included the problem-solving step (green). Each value represents a median of seven simulation runs using the same specifications, and the error bars indicate the 25th and the 75th percentiles.

    Article Snippet: The simulations were carried out on the model iJO1366 [ ] with the Cplex linear programming solver for PSAMM (version 0.17) and COBRA (version 12.6, IBM academic release for PSAMM and TOMLAB release for COBRA), and with the MOSEK solver for RAVEN (version 7.1.0.36).

    Techniques: Combined Bisulfite Restriction Analysis Assay

    The five main components include: (1) user interface, (2) model input/output, (3) model representation, (4) linear programming utilities, and (5) model checking/simulation. Connections among these components form the internal workflow of PSAMM.

    Journal: PLoS Computational Biology

    Article Title: PSAMM: A Portable System for the Analysis of Metabolic Models

    doi: 10.1371/journal.pcbi.1004732

    Figure Lengend Snippet: The five main components include: (1) user interface, (2) model input/output, (3) model representation, (4) linear programming utilities, and (5) model checking/simulation. Connections among these components form the internal workflow of PSAMM.

    Article Snippet: The simulations were carried out on the model iJO1366 [ ] with the Cplex linear programming solver for PSAMM (version 0.17) and COBRA (version 12.6, IBM academic release for PSAMM and TOMLAB release for COBRA), and with the MOSEK solver for RAVEN (version 7.1.0.36).

    Techniques:

    List of commands supported in the psamm-model program. Additional parameters can be specified for the commands, for example to select a specific implementation among multiple algorithms, enable/disable thermodynamic constraints, or select linear programming solvers, etc . Details about these parameters are available through the -h or -- help options for each command.

    Journal: PLoS Computational Biology

    Article Title: PSAMM: A Portable System for the Analysis of Metabolic Models

    doi: 10.1371/journal.pcbi.1004732

    Figure Lengend Snippet: List of commands supported in the psamm-model program. Additional parameters can be specified for the commands, for example to select a specific implementation among multiple algorithms, enable/disable thermodynamic constraints, or select linear programming solvers, etc . Details about these parameters are available through the -h or -- help options for each command.

    Article Snippet: The simulations were carried out on the model iJO1366 [ ] with the Cplex linear programming solver for PSAMM (version 0.17) and COBRA (version 12.6, IBM academic release for PSAMM and TOMLAB release for COBRA), and with the MOSEK solver for RAVEN (version 7.1.0.36).

    Techniques:

    (a) This diagram shows an example of the YAML model format, which includes a central model definition (model.yaml) and multiple annotation files. Each box indicates a file with a possible filename indicated above the box, and the text within is a snapshot of the file content. (b) An example showing how changes can be tracked in a PSAMM YAML file (biomass.yaml) using the Git version control system in command line. The text highlighted in red indicates the stoichiometry of the compound arg-L in an old version of the biomass function, while the text highlighted in green indicates the updated value in a new version of the model. Additional examples of applying Git version control on the YAML format are provided in the supplemental materials ( – Texts).

    Journal: PLoS Computational Biology

    Article Title: PSAMM: A Portable System for the Analysis of Metabolic Models

    doi: 10.1371/journal.pcbi.1004732

    Figure Lengend Snippet: (a) This diagram shows an example of the YAML model format, which includes a central model definition (model.yaml) and multiple annotation files. Each box indicates a file with a possible filename indicated above the box, and the text within is a snapshot of the file content. (b) An example showing how changes can be tracked in a PSAMM YAML file (biomass.yaml) using the Git version control system in command line. The text highlighted in red indicates the stoichiometry of the compound arg-L in an old version of the biomass function, while the text highlighted in green indicates the updated value in a new version of the model. Additional examples of applying Git version control on the YAML format are provided in the supplemental materials ( – Texts).

    Article Snippet: The simulations were carried out on the model iJO1366 [ ] with the Cplex linear programming solver for PSAMM (version 0.17) and COBRA (version 12.6, IBM academic release for PSAMM and TOMLAB release for COBRA), and with the MOSEK solver for RAVEN (version 7.1.0.36).

    Techniques: Control