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A Python package for representingreaction networks, and computing theirstructures andbehaviors. Currently the core of it is implemented as a wrapper ofSloppyCell.

Mathematically, a reaction network can be represented as dx/dt = N v(x,p), where x, v and p are the concentration, rate and parameter vectors, respectively and N is the stoichiometry matrix.

Examples of structures:

• Stoichiometry matrix N
• Left and right null spaces of N
• Reduced stoichiometry matrix N_r (a selection of N's rows with trivial left null space) and link matrix L where N = L N_r

Examples of behaviors:

• Dynamics x(t)
• Steady states s = x(inf) and J = v(s, p)
• Parameter sensitivities of them dx(t)/dp, R^s = ds/dp and R^J = dJ/dp
  • elasticities E_p = dv/dp and E_x = dv/dx
  • control matrices C^s = -(N E_s)^-1 N and C^J = I + E_s C^s

• SloppyCell
• pandas
• numpy
• matplotlib (optional; for plotting dynamics)
• scipy (optional; for using rootfinding to get steady states)
• sage (optional; forgetting the integer-valued null spaces of a stoichiometry matrix)
• libsbml (optional; for importing and exporting SBML files)

importrxnnetnet=rxnnet.network.Network('net')net.add_compartment(id='env')net.add_compartment(id='cell')net.add_species(id='C1',compartment='env',initial_value=2,is_constant=True)net.add_species(id='C2',compartment='env',initial_value=1,is_constant=True)net.add_species(id='X',compartment='cell',initial_value=0)net.add_reaction(id='R1',eqn='C1<->X',ratelaw='k1*(C1-X)',p={'k1':1})net.add_reaction(id='R2',eqn='X<->C2',ratelaw='k2*(X-C2)',p={'k2':2})traj=net.integrate((0,10))traj.plot()