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Experimente
To select experiments to be reproduced in the COMBINE archive, we initially reviewed the paper by Bachmann et al. [1]. It contains six main figures as well as >60 figures in the supplementary information. Any figures showing only experimental data such as immunoblotting (e.g., Figure 1) or model maps (e.g., Figure 2) were immediately excluded. From the remaining (sub-)figures we selected those containing model simulations (e.g., Figure 4).
The following table lists the figures which were (partially) reproduced:
Figure | Status | Comment/Problems | |
---|---|---|---|
1 | Phosphorylation profile of Epo-induced EpoR-JAK2-STAT5 signaling in the presence and absence of actinomycin D. | not selected | |
2 | Mathematical model of dual negative feedback regulation of JAK2-STAT5 signaling. | not selected | |
3 | Model calibration with experimental data of JAK2-STAT5 signaling obtained by different experimental techniques. | partially reproduced | tSTAT5 not defined in model |
4 | Experimental data of JAK2-STAT5 signaling under perturbed conditions used for model calibration. | partially reproduced | pJAK2, pEPOR, SHP1oe not defined in model |
5 | Linking the integral response of phosphorylated STAT5 in the nucleus to the survival rate of CFU-E cells. | Fig5A partially reproduced | unclear how to simulate Epo level |
6 | Dual negative feedback with divided function in JAK2-STAT5 signaling. | Fig6A not reproduced | unclear how to simulate knockout and Epo level |
S9 | Simulation of the effect of extrinsic noise on the model dynamics | reproduced |
[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
Bioinformatics & Systems biology SS 2021
- Synopsis Group 1
- Sources of Bachmann model
- Software tools for simulation
- How to build a Fully Featured COMBINE Archive?
- Communication channels
- Provision of a template for documentation
- Schedule (draft)
- Review of results
- COMBINE Archive (Testversion!)
- Synopsis Group 2
- Finding of SBML models
- Comparison of SBML models
- The chosen one
- Simulation tools
- Metadata
- Improving metadata annotations
- Synopsis Group 3
- SBGN Maps for Bachmann model
- Choice of SBGN language
- Tool to draw the SBGN Map
- SBGN-Map Drawing, Validation & Beautification
- Integration into COMBINE Archive
- Synopsis Group 4
- Selection of experiments
- Selection of SED-ML tool(s)
- Generation of SED-ML file(s)
- Integration into COMBINE Archive
- Test of SED-ML files and COMBINE Archive