fba_data.py

# data file for flux balance analysis in systems biology
# From Segre, Zucker et al "From annotated genomes to metabolic flux
# models and kinetic parameter fitting" OMICS 7 (3), 301-316. 
import numpy as np

# Stoichiometric matrix
S = np.array([
#	M1	M2	M3	M4	M5	M6	
	[1,	0,	0,	0,	0,	0],	#	R1:  extracellular -->  M1
	[-1,	1,	0,	0,	0,	0],	#	R2:  M1 -->  M2
	[-1,	0,	1,	0,	0,	0],	#	R3:  M1 -->  M3
	[0,	-1,	0,	2,	-1,	0],	#	R4:  M2 + M5 --> 2 M4
	[0,	0,	0,	0,	1,	0],	#	R5:  extracellular -->  M5
	[0,	-2,	1,	0,	0,	1],	#	R6:  2 M2 -->  M3 + M6
	[0,	0,	-1,	1,	0,	0],	#	R7:  M3 -->  M4
	[0,	0,	0,	0,	0,	-1],	#	R8:  M6 --> extracellular
	[0,	0,	0,	-1,	0,	0],	#	R9:  M4 --> cell biomass
	]).T

m, n = S.shape
vmax = np.array([
	10.10,	# R1:  extracellular -->  M1
	100,	# R2:  M1 -->  M2
	5.90,	# R3:  M1 -->  M3
	100,	# R4:  M2 + M5 --> 2 M4
	3.70,	# R5:  extracellular -->  M5
	100,	# R6:  2 M2 --> M3 + M6
	100,	# R7:  M3 -->  M4
	100,	# R8:  M6 -->  extracellular
	100,	# R9:  M4 -->  cell biomass
	])