Executive Summary

the project:

This public repository is the collaborative work of the participants of the module "Bioinformatik und Systembiologie" in the Master Program BIDS. Over a six-week period we aimed to build a COMBINE archive of the Bachmann model [1], a cellular signal transduction model. The main idea of creating a COMBINE archive is to achieve reproducibility of the published data by 'combining' all necessary tools, data, fiels and metadata to run the simulation yourself without touching a 🧪. Isn´t that cool?

pave one

Divided into work packages this project was delivered within 3 weeks. A git-repository was installed as a central information and documentation hub (group 1). You will find the detailed work packages and the respective results in the wiki below.

pick one

As the modelling information usually is wrapped in the 'SBML'-format we searched for all publicly available model files of the Bachmann model and picked the most soothing one for our archive. Also a deeper understanding of the included metadata and its heredity was developed and can be found in the documentation of group 2.

pimp one

To provide a graphical representation of the Bachmann model [1] consistent with the COMBINE-standards, we chose the Systems Biology Graphical Notation (SBGN) and created a SBGN map from scratch.

Based on the authors´ diagram choice in the publications and the suggestions of Le Novère et al. and Touré et al. we chose the Process Description language for our COMBINE archive [2, 3]. Following the selection of the SBGN language, we identified several useful tools and ultimately created the PD map with Newt Editor. To confirm the validity of the developed SBGN we used the integrated LibSBGN-based validation feature of Newt Editor as well as imported the SBGN-ML into VANTED/SBGN-ED, Krayon for SBGN and SBGNViz. Finally, we visually improved the map by cleaning it up and colouring the most important features of the model.

In conclusion, we were able to develop a SBGN-conform process diagram for the model published in Bachmann et al. The process diagram was validated by the built-in validation tool of Newt Editor and by importing it into to three other tools. Our process diagram was mainly compatible with different tools, minor changes of the SBGN-ML code were necessary after exporting it from Newt. Finally, the diagram was beautified to provide a more readable graphical representation.

pack one

To reproduce the figures from the original paper, we created experiment-specific SED-ML files using various tools (SED-ML WebTools, COPASI, Tellurium), adjusting parameters of the model as required, e.g. to simulate an overexpression. These files were validated, added to the COMBINE archive together with the corresponding output files and successfully used to simulate the SBML model.

In summary, we were able to reproduce many, but not all experiments included in the paper. Several parameters required to generate parts of the figures were missing from the model and could therefore not be used for simulations. Details of these parameters are provided in the supplementary material of the paper, however not in an easily accessible format. These could be added to the SBML model directly or via modified SED-ML files in the future with the help of the authors.

perfect one

The final Bachmann COMBINE archive is available online as will be this documentation.

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References

[1] Bachmann, J. et al. Division of labor by dual feedback regulators controls JAK2/STAT5 signaling over broad ligand range. Molecular Systems Biology 7, 516 (2011). https://doi.org/10.1038/msb.2011.50

[2] Le Novère, N. Quantitative and logic modelling of molecular and gene networks. Nat Rev Genet 16, 146–158 (2015). https://doi.org/10.1038/nrg3885

[3] Touré, V., Le Novère, N., Waltemath, D. et al. Quick tips for creating effective and impactful biological pathways using the Systems Biology Graphical Notation. PLoS Comput Biol 14, e1005740 (2018). https://doi.org/10.1371/journal.pcbi.1005740