aspirincode / crnpy

A python library for the analysis of chemical reaction networks.

crnpy

crnpy is a python library for the manipulation and analysis of chemical reaction networks.

Install

crnpy can be installed from source. After downloading the repository, run

$ python setup.py install --user

crnpy requires libSBML, SciPy, NumPy and SymPy. To generate the network invariants, pycddlib is also required.

Some example scripts require NetworkX or PuLP.

Getting Started

We can create a network from an SBML file

>>> from crnpy.crn import CRN, from_sbml, from_react_strings, from_react_file
>>> crn = from_sbml("examples/data/sbml/enzyme.xml")

from a file containing a list of reactions in human-readable format

>>> crn = from_react_file("examples/data/reactions/biomodels/biomd0000000026")

or directly from a list of reaction strings:

>>> crn = from_react_strings(["A <-> B", "2A + C <-> D", "D -> E", "E -> 2A + C"])

Now we can explore some properties of the network. For example, we can look at the stoichiometric matrix

>>> crn.print_stoich_matrix()
    r0  r0_rev  r1  r1_rev  r2  r3
A | -1       1  -2       2   0   2 |
B |  1      -1   0       0   0   0 |
C |  0       0  -1       1   0   1 |
D |  0       0   1      -1  -1   0 |
E |  0       0   0       0   1  -1 |

at the derivatives of the species concentrations and the conservation laws:

>>> crn.stoich_matrix * crn.rates
Matrix([
[-2*A**2*C*k_r1 - A*k_r0 + B*k_r0_rev + 2*D*k_r1_rev + 2*E*k_r3],
[                                           A*k_r0 - B*k_r0_rev],
[                            -A**2*C*k_r1 + D*k_r1_rev + E*k_r3],
[                             A**2*C*k_r1 - D*k_r1_rev - D*k_r2],
[                                               D*k_r2 - E*k_r3]])
>>> crn.cons_laws
(A + B + 2*D + 2*E, C + D + E)

We can check whether the conditions of the deficiency zero theorem are satisfied:

>>> crn.is_ma
True
>>> crn.deficiency
0
>>> crn.is_weakly_rev
True

For more information, a tutorial is available as well as some example scripts.

Citation

If you use crnpy for your work, please cite

Elisa Tonello, CrnPy: a python library for the analysis of chemical reaction networks, 2016.