Read 'SBML' Models and Convert Them to Simulation Code

Reads models in the Systems Biology Markup Language ('SBML') (Hucka et al. (2003) ) through the bundled 'libSBML' library (Bornstein et al. (2008) ). Lists a model's species, parameters, compartments, reactions, rules, events and function definitions, and converts the model into ready-to-run simulation code for 'deSolve', 'mrgsolve', 'rxode2', 'MATLAB', 'Julia' or 'ubiquity'. Models are read, not modified.

r2sbml

A lightweight R interface to the libSBML library, built with Rcpp.

r2sbml reads an SBML model, lets you query its components from R — species, parameters, compartments, reactions, rules, events, function definitions — and exports the mass balances as ready-to-simulate code for several ODE solvers.

Modifying an imported model from R is not supported: r2sbml reads and exports, it does not edit.

Installation

libSBML is bundled with the package and built from source during installation, so you do not need to install it yourself and the build itself downloads nothing. What you do need is a C++ compiler, CMake, and the libxml2 and bzip2 headers.

# Ubuntu / Debian
sudo apt-get update && sudo apt-get install -y cmake libxml2-dev libbz2-dev

# macOS
brew install cmake libxml2

On Windows everything required comes with Rtools; there are no extra steps.

Then, from R:

# install.packages("remotes")
remotes::install_github("sn248/r2sbml")

The first build takes several minutes, because libSBML is compiled from source.

To install with the vignettes built:

remotes::install_github("sn248/r2sbml", build_vignettes = TRUE)

Documentation

Two vignettes cover the package in detail:

vignette("r2sbml", package = "r2sbml")      # how to use it, worked end to end
vignette("limitations", package = "r2sbml") # what it does not do, and why

The second is worth reading before trusting generated code on a model you did not write: it lists which limitations raise a warning and which are silent.

Reading a model

Most functions take a model pointer, which getModel() returns:

library(r2sbml)

sbml_file <- system.file("examples", "sbmlsimple.xml", package = "r2sbml")
model     <- getModel(sbml_file)

getSpeciesTable(model)
#>   Number Name ID InitialConcentration InitialAmount Compartment CompartmentVol
#> 1      1       E                  NaN         5e-21        comp          1e-14
#> 2      2       S                  NaN         1e-20        comp          1e-14
#> 3      3       P                  NaN         0e+00        comp          1e-14
#> 4      4      ES                  NaN         0e+00        comp          1e-14
#>   BoundaryCondition Constant
#> 1                 0    FALSE
#> ...

Functions that return data:

Functions that print to the console and return 0 invisibly — capture them with capture.output() rather than assigning them:

model <- getModel(system.file("examples", "sbmlassignmentrules.xml", package = "r2sbml"))

getParameterTable(model)
#>   Number  ID Name Value         Units
#> 1      1 Keq        2.5 dimensionless

getRuleMath(model)
#> Rule 0, formula: S1 = T / (1 + Keq)
#> Rule 1, formula: S2 = Keq * S1

Note that these query functions raise an error rather than returning empty when the component is absent — getParameterTable() on a model whose parameters are all local to its kinetic laws will stop, not return a zero-row frame.

Exporting mass balances

convertReactions() is the exception: it reads the SBML file itself and writes a code file, so it takes no model pointer.

sbml_file <- system.file("examples", "sbmlsimple.xml", package = "r2sbml")

convertReactions(sbml_file, "model.R",   format = "R")         # deSolve
convertReactions(sbml_file, "model.cpp", format = "mrgsolve")
convertReactions(sbml_file, "model.R",   format = "nlmixr2")   # or "rxode2"
convertReactions(sbml_file, "model.m",   format = "MATLAB")
convertReactions(sbml_file, "model.jl",  format = "Julia")
convertReactions(sbml_file, "system.txt", format = "ubiquity")

Before writing anything, convertReactions() applies four libSBML converters — reactions become rate rules, local parameters are promoted to global, initial assignments and function definitions are expanded — so every target receives the same explicit ODE system. For sbmlsimple.xml the deSolve output contains:

massBalances <- function(time, states, params){
   dES_dt = comp * (veq_kon * E * S - veq_koff * ES) / comp + -1 * (comp * vcat_kcat * ES / comp)
   dE_dt = -1 * (comp * (veq_kon * E * S - veq_koff * ES) / comp) + comp * vcat_kcat * ES / comp
   dS_dt = -1 * (comp * (veq_kon * E * S - veq_koff * ES) / comp)
   dP_dt = comp * vcat_kcat * ES / comp

Each target gets its own spelling of the mathematics: a^b for R, rxode2, MATLAB and Julia; pow(a, b) for mrgsolve, whose model blocks are C++; and SIMINT_POWER[a][b] for ubiquity.

Initial conditions are converted into whatever units the ODE integrates. An SBML species symbol is a concentration unless hasOnlySubstanceUnits is set, and the rate rules are divided by the compartment volume to match, so a species declared with an initialAmount starts at amount / volume. For sbmlsimple.xml that turns an initialAmount of 5e-21 in a 1e-14 compartment into 5e-07. The volume is the species' own compartment's, so a multi-compartment model rescales species individually.

Limitations

• Delays are not translated. SBML's delay csymbol passes through unchanged, so a model using it will not run in any target. inst/examples/sbmldelay.xml is the example that shows this; the ubiquity writer warns about it explicitly, the others do not.
• Algebraic rules make the model a DAE. The deSolve, MATLAB and Julia writers emit one — a daspk residual function for deSolve, a singular mass matrix for the other two — so the constraint is enforced. mrgsolve, rxode2 and ubiquity integrate ODEs only: there the rule is written out as a comment, the species it constrains is left at a zero derivative, and convertReactions() raises a warning saying so. A model whose algebraic rules do not determine exactly the undetermined variables also falls back to comments, with a warning.
• Species without a rate rule — boundary conditions, or species in no reaction — keep their place in the state vector with a zero derivative, so they still appear in the solution.
• Compartments whose volume changes are handled when the volume follows a rate rule: the volume joins the state vector and every species inside it gains the dilution term -[S] * (dV/dt) / V, so a concentration falls as its compartment grows even with no reaction. If the volume follows an assignment rule the volume itself is still correct, but the dilution term cannot be formed — that needs a symbolic time derivative of the rule — and convertReactions() warns.
• Events are not exported. They can be inspected with getEventMath() but appear in generated code only as a count in the header comment.
• Generated code is a starting point, not a finished script: check initial conditions, units and the time span before trusting a simulation.

Example models

inst/examples/ holds ten small SBML files covering simple reactions, assignment rules, algebraic rules, function definitions, delay, events, multiple compartments, boundary conditions and conversion factors. The test suite runs every format against all of them.

Licence and attribution

r2sbml is released under GPL (>= 2). It bundles libSBML, which is distributed under the LGPL 2.1, and parts of src/convertReactions.cpp and src/getMath.cpp are adapted from MIT-licensed libSBML example programs by Sarah Keating and Frank T. Bergmann. See inst/COPYRIGHTS for the full attribution.