sbmlsense - Python toolbox for sensitivity analysis of biomolecular systems. There are plenty of tools available for sensitivity analysis of biological systems such as COPASI, AMIGO and many more. However, there are a few important features that we aim to develop in sbmlsense such as having capability to do sensitivity analysis and inform the parameter identification algorithms that follow. Apart from the identifiability analysis, we envision sbmlsense to be used as a standalone tool for sensitivity analysis for multiple types of data (and possibly also together) such as multiple time series data together, distributional data etc.
My current progress is available at my fork for the original repository
All code and these examples are available here
Ayush Pandey and Richard Murray
We present Sub-SBML, a Python based toolbox to create, edit, combine, and model interactions among multiple SBML models. Sub-SBML works with a “subsystem” architecture of modeling where a single SBML model can be contained within a subsystem. Three major functionalities are developed in Sub-SBML that take advantage of this subsystem framework of modeling – creating subsystems, combining multiple subsystems, and modeling interactions such as transport of molecules and input-output relationships among multiple subsystems. Sub-SBML provides functions to create subsystems for SBML models in order to use various utility functions to edit the model (such as renaming different lists of model components, creating multiple components at once, integrations for different simulator options, simulating variable species amount in a model etc). It is often desired in modeling of compounded biomolecular systems to combine multiple smaller models for different modules. The primary features of Sub-SBML allow for modeling of such systems by creating subsystems for different models and then combining these subsystems as desired, while also modeling the interactions among the models. A list of subsystems may be combined by specifying a list of species which would be shared in the final combined model. The toolbox also provides functions to model the cases when it is desired that all species that have the same name be a single combined species in the final model.
Sub-SBML can also be used to model compartments in SBML for modeling the transport of species between different models. A subsystem object in Sub-SBML consists of an SBML model that can have one compartment to hold all the species of that model. Multiple subsystems may be placed inside a “system”. A system object in Sub-SBML acts as a container for subsystems. Subsystems may be defined to be internal to a system, external to a system, or as membranes to a system. Hence, an SBML model of a system would consist of two compartments – internal and external. The membrane subsystem will also have these two compartments and reactions modeling the transport of species across it. A system model can be generated that would give a combined model of all subsystems that are internal, external and set as membrane to this system, hence modeling the transport across this system container. Similarly, multiple system objects can be modeled and interactions across multiple systems may be modeled as well.
We consider an example of IPTG transport across synthetic vesicles when α-hemolysin is expressed inside the vesicle, which creates pores in the membrane to allow transport of IPTG molecules from the environment to inside the vesicle. We demonstrate the use of Sub-SBML to model this system in SBML. We also consider other synthetic biological circuits to demonstrate input-output species interactions among subsystems and to obtain combined SBML models.
More details here