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Motivation: Estimating model parameters from experimental observations is oneof the key challenges in systems biology and can be computationally veryexpensive. While the Julia programming language was recently developed as ahigh-level and high-performance language for scientific computing, systemsbiologists have only started to realise its potential. For instance, we haverecently used Julia to cut down the optimization time of a microbial communitymodel by a factor of 140. To facilitate access of the systems biology communityto the efficient nonlinear solvers used for this optimisation, we developedSBML2Julia. SBML2Julia translates optimisation problems specified in SBML andTSV files (PEtab format) into Julia for Mathematical Programming (JuMP),executes the optimization and returns the results in tabular format.  Availability and implementation: SBML2Julia is freely available under the MITlicense. It comes with a command line interface and Python API. Internally,SBML2Julia calls the Julia LTS release v1.0.5 for optimisation. All necessarydependencies can be pulled from Docker Hub(https://hub.docker.com/repository/docker/paulflang/sbml2julia). Source codeand documentation are available at https://github.com/paulflang/SBML2Julia.

SBML2Julia: interfacing SBML with efficient nonlinear Julia modelling and solution tools for parameter optimization