This Python package provides data structures to model and simulate the organisation at (unicellular) system scale.
- Genetic regulation (
pyorganism.regulation) - Analog and digital control (cf. [1])
- Transcriptional regulatory network (TRN): directed transcription factor-gene interaction network
- Gene regulatory network (GRN): directed gene-gene interaction network (projection of the TRN)
- Gene proximity network (GPN): undirected gene-gene proximity network
- Couplons (intersection between sigma factor's and nucleoid associated proteins' targets)
- Functional clusters (GO)
- Metabolic control (cf. [2])
- Continuous control (cf. [3])
- Genetic regulation (
- Metabolism (
pyorganism.metabolism) - Metabolic systems
- Network representations
- Flux balance analysis (FBA)
- Metabolism (
- future for Python2/3 compatiblity
- Cython
- networkx
- numpy
- pandas
- reading/writing SBML files requires libsbml or the PyPi package
- KEGG interface requires SOAPpy
- (pytables for HDF5 storage can be replaced by pickling of numpy objects)
Former and current members of the Computational Systems Biology workgroup headed by Prof. Marc-Thorsten Hütt at Jacobs University Bremen. In alphabetical order:
- Beber, Moritz Emanuel
- Grigore, Alexandra Mirela
- Kölling, Nils
- Sonnenschein, Nikolaus
| [1] | Marr, C., Geertz, M., Hutt, M.-T. & Muskhelishvili, G. Dissecting the logical types of network control in gene expression profiles. BMC Systems Biology 2, 18 (2008). |
| [2] | Sonnenschein, N., Geertz, M., Muskhelishvili, G. & Hütt, M.-T. Analog regulation of metabolic demand. BMC Systems Biology 5, 40 (2011). |
| [3] | Beber, M. E., Sobetzko, P., Muskhelishvili, G. & Hütt, M.-T. Interplay of digital and analog control in time-resolved gene expression profiles. BMC Systems Biology submitted, (2015). |