From 0d87ce8538df8fa788d073e466d30a767c923a51 Mon Sep 17 00:00:00 2001 From: "Documenter.jl" Date: Thu, 29 Feb 2024 23:06:35 +0000 Subject: [PATCH] build based on e5650f7 --- dev/.documenter-siteinfo.json | 2 +- dev/index.html | 4 ++-- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/dev/.documenter-siteinfo.json b/dev/.documenter-siteinfo.json index cea2aef..0e5e5eb 100644 --- a/dev/.documenter-siteinfo.json +++ b/dev/.documenter-siteinfo.json @@ -1 +1 @@ -{"documenter":{"julia_version":"1.10.1","generation_timestamp":"2024-02-29T22:58:04","documenter_version":"1.2.1"}} \ No newline at end of file +{"documenter":{"julia_version":"1.10.1","generation_timestamp":"2024-02-29T23:06:33","documenter_version":"1.2.1"}} \ No newline at end of file diff --git a/dev/index.html b/dev/index.html index a2cbbd9..3c84c74 100644 --- a/dev/index.html +++ b/dev/index.html @@ -1,5 +1,5 @@ -Home · DataDrivenEnzymeRateEqs.jl
GitHub

DataDrivenEnzymeRateEqs

Documentation for DataDrivenEnzymeRateEqs.

DataDrivenEnzymeRateEqs.data_driven_rate_equation_selection — Method

datadrivenrateequationselection( generalrateequation::Function, data::DataFrame, metabnames::Tuple{Symbol,Vararg{Symbol}}, paramnames::Tuple{Symbol,Vararg{Symbol}}, rangenumberparams::Tuple{Int,Int}, forwardmodelselection::Bool, )

This function is used to perform data-driven rate equation selection using a general rate equation and data. The function will select the best rate equation by iteratively removing parameters from the general rate equation and finding an equation that yield best test scores on data not used for fitting.

Arguments

  • general_rate_equation::Function: Function that takes a NamedTuple of metabolite concentrations (with metab_names keys) and parameters (with param_names keys) and returns an enzyme rate.
  • data::DataFrame: DataFrame containing the data with column Rate and columns for each metab_names where each row is one measurement. It also needs to have a column source that contains a string that identifies the source of the data. This is used to calculate the weights for each figure in the publication.
  • metab_names::Tuple: Tuple of metabolite names that correspond to the metabolites of rate_equation and column names in data.
  • param_names::Tuple: Tuple of parameter names that correspond to the parameters of rate_equation.
  • range_number_params::Tuple{Int,Int}: A tuple of integers representing the range of the number of parameters of generalrateequation to search over.
  • forward_model_selection::Bool: A boolean indicating whether to use forward model selection (true) or reverse model selection (false).

Returns nothing, but saves a csv file for each num_params with the results of the training for each combination of parameters tested and a csv file with test results for top 10% of the best results with each number of parameters tested.

source
DataDrivenEnzymeRateEqs.fit_rate_equation — Method
fit_rate_equation(
+Home · DataDrivenEnzymeRateEqs.jl
GitHub
DataDrivenEnzymeRateEqs
Documentation for DataDrivenEnzymeRateEqs.
DataDrivenEnzymeRateEqs.data_driven_rate_equation_selection — Method
datadrivenrateequationselection(     generalrateequation::Function,     data::DataFrame,     metabnames::Tuple{Symbol,Vararg{Symbol}},     paramnames::Tuple{Symbol,Vararg{Symbol}},     rangenumberparams::Tuple{Int,Int},     forwardmodelselection::Bool, )
This function is used to perform data-driven rate equation selection using a general rate equation and data. The function will select the best rate equation by iteratively removing parameters from the general rate equation and finding an equation that yield best test scores on data not used for fitting.
Arguments
  • general_rate_equation::Function: Function that takes a NamedTuple of metabolite concentrations (with metab_names keys) and parameters (with param_names keys) and returns an enzyme rate.
  • data::DataFrame: DataFrame containing the data with column Rate and columns for each metab_names where each row is one measurement. It also needs to have a column source that contains a string that identifies the source of the data. This is used to calculate the weights for each figure in the publication.
  • metab_names::Tuple: Tuple of metabolite names that correspond to the metabolites of rate_equation and column names in data.
  • param_names::Tuple: Tuple of parameter names that correspond to the parameters of rate_equation.
  • range_number_params::Tuple{Int,Int}: A tuple of integers representing the range of the number of parameters of generalrateequation to search over.
  • forward_model_selection::Bool: A boolean indicating whether to use forward model selection (true) or reverse model selection (false).
Returns nothing, but saves a csv file for each num_params with the results of the training for each combination of parameters tested and a csv file with test results for top 10% of the best results with each number of parameters tested.
source
DataDrivenEnzymeRateEqs.fit_rate_equation — Method
fit_rate_equation(
     rate_equation::Function,
     data::DataFrame,
     metab_names::Tuple,
@@ -11,4 +11,4 @@
     source = ["Figure 1", "Figure 1", "Figure 2"]
 )
 rate_equation(metabs, params) = params.Vmax * metabs.S / (1 + metabs.S / params.K_S)
-fit_rate_equation(rate_equation, data, (:A,), (:Vmax, :K_S))
source

+fit_rate_equation(rate_equation, data, (:A,), (:Vmax, :K_S))
source