We develop tools for data-driven building of subcellular biochemical signaling pathway models. This includes interoperable modules for: model building, calibration (parameter estimation) and model analysis. All information needed to perform these tasks are stored in a structured, human- and machine-readable file format based on SBtab (Lubitz et al. 2016). The information contained in the SBtab files includes: models, experimental calibration data and prior assumptions on parameter distributions. The toolset enables simulations of the same model in simulators with different characteristics, e.g. STEPS, NEURON, MATLAB’s Simbiology and R via automatic code generation. The parameter estimation is done by optimization or Bayesian approaches. Model analysis includes global sensitivity analysis and functionality for analyzing thermodynamic constraints and conserved moieties.

The documentation for the SBtab format are here: https://github.com/tlubitz/SBtab

The documentation of each respective module (tool) from our group can be found in the READ ME file of that repository, i.e.:

• icpm-kth/uqsa Uncertainty Qantification and global Sensistivity Analysis (UQSA)
• icpm-kth/SBtabVFGEN Processing of SBtab files and translating them into several common formats: vf, sbml, MOD, plain text; thus making them easy to convert further into computational models (for solvers)
• icpm-kth/rgsl Solving ordianry differential equations using the solvers in the GNU Scientific Library, interfaced with R
• icpm-kth/RPN-derivative A set of command line tools to transform an ordinary differential equation (given as either vf file, or as plain text) to a language specific set of functions (currently in R, and C)

[1] Lubitz, T., Hahn, J., Bergmann, F.T., Noor, E.,. Klipp, E, Liebermeister, W. (2016). SBtab: A flexible table format for data exchange in systems biology. Bioinformatics, 15;32(16), 2559-61

This is a high level flowchart of common tasks in systems biology (and modelling in neuroscience). We require a storage format that is robust enough to survive being moved to other platforms and must be easy to parse by common tools, on various platforms and in many programming languages. The SBtab format can be read using such tools as awk and sed but is also easy to represent as a data frame in R or an array of structs (matlab and GNU Octave have structarrays). We need to easily communicate with other groups and send them models and data. Another important task is simulation and parameter estimation. Both of these tasks require the translation of the biological model into a computational model (right hand side vector field of an ordinary differential equation or propensities for a stochastic algorithm such as the Gillespie Algorithm). Calibration and Analysis includes copmmon tasks such as parameter estimation, global sensitivity analysis, prediction; we are working on methods and implementations for these tasks.