7.1.1. intro_to_wc_modeling.cell_modeling package

7.1.1.2. Submodules

7.1.1.3. intro_to_wc_modeling.cell_modeling.model_composition module

Model composition tutorial

  • Glycolysis model (Teusink et al., 2000)
  • Glycerol synthesis model (Cronwright et al., 2002)
Author:Jonathan Karr <jonrkarr@gmail.com>
Author:Yin Hoon Chew <yinhoon.chew@mssm.edu>
Date:2017-08-30
Copyright:2017, Karr Lab
License:MIT
class intro_to_wc_modeling.cell_modeling.model_composition.GlycerolModel[source]

Bases: object

Glycerol synthesis model (Cronwright et al., 2002)

Based on the version from JWS Online

ADP[source]

ADP concentration (mM)

Type:float
ATP[source]

ATP concentration (mM)

Type:float
DHAP[source]

DHAP concentration (mM)

Type:float
GLY[source]

GLY concentration (mM)

Type:float
F16BP[source]

F16BP concentration (mM)

Type:float
NAD[source]

NAD concentration (mM)

Type:float
NADH[source]

NADH concentration (mM)

Type:float
Phi[source]

Pi concentration (mM)

Type:float
V2[source]

forward rate constant (mM min-1)

Type:float
Vf1[source]

reverse rate constant (mM min-1)

Type:float
K1adp[source]

ADP forward affinity constant (mM)

Type:float
K1atp[source]

ATP forward affinity constant (mM)

Type:float
K1dhap[source]

DHAP forward affinity constant (mM)

Type:float
K1f16bp[source]

F16BP forward affinity constant (mM)

Type:float
K1g3p[source]

G3P forward affinity constant (mM)

Type:float
K1nad[source]

NAD forward affinity constant (mM)

Type:float
K1nadh[source]

NADH forward affinity constant (mM)

Type:float
K2g3p[source]

G3P reverse affinity constant (mM)

Type:float
K2phi[source]

Pi reverse affinity constant (mM)

Type:float
Keq1[source]

Equilibrium constant (dimensionless)

Type:float
g3p_0[source]

initial G3P concentration (mM)

Type:numpy.array
x_0[source]

initial species concentrations (mM)

Type:numpy.array
ADP = 2.17[source]
ATP = 2.37[source]
DHAP = 0.59[source]
F16BP = 6.01[source]
GLY = 0.0[source]
K1adp = 2.0[source]
K1atp = 0.73[source]
K1dhap = 0.54[source]
K1f16bp = 4.8[source]
K1g3p = 1.2[source]
K1nad = 0.93[source]
K1nadh = 0.023[source]
K2g3p = 3.5[source]
K2phi = 1.0[source]
Keq1 = 10000.0[source]
NAD = 1.45[source]
NADH = 1.87[source]
Phi = 1.0[source]
V2 = 53.0[source]
Vf1 = 47.0[source]
dg3p_dt(x)[source]

Calculate time derivative of the G3P concentration

Parameters:x (numpy.array) – species concentrations (mM)
Returns:time derivative of the G3P concentration (mM min-1)
Return type:float
dx_dt(x)[source]

Calculate the time derivative of the species concentrations

Parameters:x (numpy.array) – species concentrations (mM)
Returns:time derivative of the species concentrations (mM min-1)
Return type:numpy.array
g3p_0 = 0[source]
plot_simulation_results(t, dhap, g3p)[source]

Plot simulation results

Parameters:
  • t (numpy.array) – time (min)
  • dhap (numpy.array) – DHAP concentration (mM)
  • g3p (numpy.array) – G3P concentration (mM)
Returns:

figure

Return type:

matplotlib.figure.Figure

simulate(t_0=0, t_end=20.0, t_step=0.2)[source]

Simulate the model

Parameters:
  • t_0 (float, optional) – start time (min)
  • t_end (float, optional) – end time (min)
  • t_step (float, optional) – time step to record predicted concentrations (min)
Returns:

  • numpy.array: time (min)
  • numpy.array: DHAP concentration (mM)
  • numpy.array: G3P concentration (mM)

Return type:

tuple

v_1(x)[source]

Calculate the rate of Glycerol 3-phosphate dehydrogenase (DHAP <=> G3P)

Parameters:x (numpy.array) – species concentrations (mM)
Returns:rate of Glycerol 3-phosphate dehydrogenase (mM min-1)
Return type:float
v_2(x)[source]

Calculate the rate of Glycerol 3-phosphatase (G3P <=> Gly)

Parameters:x (numpy.array) – species concentrations (mM)
Returns:rate of Glycerol 3-phosphatase (mM min-1)
Return type:float
x_0[source]
class intro_to_wc_modeling.cell_modeling.model_composition.GlycolysisModel[source]

Bases: object

Glycolysis model (Teusink et al., 2000)

Based on the version from JWS Online

CPFKAMP (obj

float):

CPFKATP (obj

float):

CPFKF16BP (obj

float):

CPFKF26BP (obj

float):

CPFKF6P (obj

float):

CiPFKATP (obj

float):

F26BP (obj

float):

KATPASE (obj

float):

KGLYCOGEN (obj

float):

KPFKAMP (obj

float):

KPFKF16BP (obj

float):

KPFKF26BP (obj

float):

KSUCC (obj

float):

KTREHALOSE (obj

float):

KeqADH (obj

float):

KeqAK (obj

float):

KeqALD (obj

float):

KeqENO (obj

float):

KeqG3PDH (obj

float):

KeqGLK (obj

float):

KeqGLT (obj

float):

KeqPGI (obj

float):

KeqPGK (obj

float):

KeqPGM (obj

float):

KeqPYK (obj

float):

KeqTPI (obj

float): ratio of GAP to DHAP at equilibrium

KiADHACE (obj

float):

KiADHETOH (obj

float):

KiADHNAD (obj

float):

KiADHNADH (obj

float):

KiPFKATP (obj

float):

KmADHACE (obj

float):

KmADHETOH (obj

float):

KmADHNAD (obj

float):

KmADHNADH (obj

float):

KmALDDHAP (obj

float):

KmALDF16P (obj

float):

KmALDGAP (obj

float):

KmALDGAPi (obj

float):

KmENOP2G (obj

float):

KmENOPEP (obj

float):

KmG3PDHDHAP (obj

float):

KmG3PDHGLY (obj

float):

KmG3PDHNAD (obj

float):

KmG3PDHNADH (obj

float):

KmGAPDHBPG (obj

float):

KmGAPDHGAP (obj

float):

KmGAPDHNAD (obj

float):

KmGAPDHNADH (obj

float):

KmGLKADP (obj

float):

KmGLKATP (obj

float):

KmGLKG6P (obj

float):

KmGLKGLCi (obj

float):

KmGLTGLCi (obj

float):

KmGLTGLCo (obj

float):

KmPDCPYR (obj

float):

KmPFKATP (obj

float):

KmPFKF6P (obj

float):

KmPGIF6P (obj

float):

KmPGIG6P (obj

float):

KmPGKADP (obj

float):

KmPGKATP (obj

float):

KmPGKBPG (obj

float):

KmPGKP3G (obj

float):

KmPGMP2G (obj

float):

KmPGMP3G (obj

float):

KmPYKADP (obj

float):

KmPYKATP (obj

float):

KmPYKPEP (obj

float):

KmPYKPYR (obj

float):

L0 (obj

float):

SUMAXP (obj

float):

VmADH (obj

float):

VmALD (obj

float):

VmENO (obj

float):

VmG3PDH (obj

float):

VmGAPDHf (obj

float):

VmGAPDHr (obj

float):

VmGLK (obj

float):

VmGLT (obj

float):

VmPDC (obj

float):

VmPFK (obj

float):

VmPGI (obj

float):

VmPGK (obj

float):

VmPGM (obj

float):

VmPYK (obj

float):

gR (obj

float):

nPDC (obj

float):

CO2 (obj

float):

ETOH (obj

float):

GLCo (obj

float):

GLY (obj

float):

SUCC (obj

float):

Trh (obj

float):

ACE_0[source]

initial ACE concentration (mM)

Type:float
BPG_0[source]

initial BPG concentration (mM)

Type:float
F16BP_0[source]

initial F16BP concentration (mM)

Type:float
F6P_0[source]

initial F6P concentration (mM)

Type:float
G6P_0[source]

initial G6P concentration (mM)

Type:float
GLCi_0[source]

initial GLCi concentration (mM)

Type:float
NAD_0[source]

initial NAD concentration (mM)

Type:float
NADH_0[source]

initial NADH concentration (mM)

Type:float
P2G_0[source]

initial P2G concentration (mM)

Type:float
P3G_0[source]

initial P3G concentration (mM)

Type:float
PEP_0[source]

initial PEP concentration (mM)

Type:float
PYR_0[source]

initial PYR concentration (mM)

Type:float
Prb_0[source]

initial high energy phosphates (2*ATP + ADP) concentration (mM)

Type:float
TRIO_0[source]

initial triose-phosphate (DHAP + GAP) concentration (mM)

Type:float
x_0[source]

initial species concentrations (mM)

Type:numpy.array
ACE_0 = 0.04[source]
BPG_0 = 0.0[source]
CO2 = 1.0[source]
CPFKAMP = 0.0845[source]
CPFKATP = 3.0[source]
CPFKF16BP = 0.397[source]
CPFKF26BP = 0.0174[source]
CPFKF6P = 0.0[source]
CiPFKATP = 100.0[source]
ETOH = 50.0[source]
F16BP_0 = 0.1[source]
F26BP = 0.02[source]
F6P_0 = 0.28[source]
G6P_0 = 1.39[source]
GLCi_0 = 0.087[source]
GLCo = 50.0[source]
GLY = 0.15[source]
KATPASE = 39.5[source]
KGLYCOGEN = 6.0[source]
KPFKAMP = 0.0995[source]
KPFKF16BP = 0.111[source]
KPFKF26BP = 0.000682[source]
KSUCC = 21.4[source]
KTREHALOSE = 2.4[source]
KeqADH = 6.9e-05[source]
KeqAK = 0.45[source]
KeqALD = 0.069[source]
KeqENO = 6.7[source]
KeqG3PDH = 4300.0[source]
KeqGLK = 3800.0[source]
KeqGLT = 1.0[source]
KeqPGI = 0.314[source]
KeqPGK = 3200.0[source]
KeqPGM = 0.19[source]
KeqPYK = 6500.0[source]
KeqTPI = 0.045[source]
KiADHACE = 1.1[source]
KiADHETOH = 90.0[source]
KiADHNAD = 0.92[source]
KiADHNADH = 0.031[source]
KiPFKATP = 0.65[source]
KmADHACE = 1.11[source]
KmADHETOH = 17.0[source]
KmADHNAD = 0.17[source]
KmADHNADH = 0.11[source]
KmALDDHAP = 2.4[source]
KmALDF16P = 0.3[source]
KmALDGAP = 2.0[source]
KmALDGAPi = 10.0[source]
KmENOP2G = 0.04[source]
KmENOPEP = 0.5[source]
KmG3PDHDHAP = 0.4[source]
KmG3PDHGLY = 1.0[source]
KmG3PDHNAD = 0.93[source]
KmG3PDHNADH = 0.023[source]
KmGAPDHBPG = 0.0098[source]
KmGAPDHGAP = 0.21[source]
KmGAPDHNAD = 0.09[source]
KmGAPDHNADH = 0.06[source]
KmGLKADP = 0.23[source]
KmGLKATP = 0.15[source]
KmGLKG6P = 30.0[source]
KmGLKGLCi = 0.08[source]
KmGLTGLCi = 1.1918[source]
KmGLTGLCo = 1.1918[source]
KmPDCPYR = 4.33[source]
KmPFKATP = 0.71[source]
KmPFKF6P = 0.1[source]
KmPGIF6P = 0.3[source]
KmPGIG6P = 1.4[source]
KmPGKADP = 0.2[source]
KmPGKATP = 0.3[source]
KmPGKBPG = 0.003[source]
KmPGKP3G = 0.53[source]
KmPGMP2G = 0.08[source]
KmPGMP3G = 1.2[source]
KmPYKADP = 0.53[source]
KmPYKATP = 1.5[source]
KmPYKPEP = 0.14[source]
KmPYKPYR = 21.0[source]
L0 = 0.66[source]
NADH_0 = 0.39[source]
NAD_0 = 1.2[source]
P2G_0 = 0.1[source]
P3G_0 = 0.1[source]
PEP_0 = 0.1[source]
PYR_0 = 3.36[source]
Prb_0 = 5.0[source]
SUCC = 0.0[source]
SUMAXP = 4.1[source]
TRIO_0 = 5.17[source]
Trh = 0.0[source]
VmADH = 810.0[source]
VmALD = 322.258[source]
VmENO = 365.806[source]
VmG3PDH = 70.15[source]
VmGAPDHf = 1184.52[source]
VmGAPDHr = 6549.68[source]
VmGLK = 226.452[source]
VmGLT = 97.264[source]
VmPDC = 174.194[source]
VmPFK = 182.903[source]
VmPGI = 339.677[source]
VmPGK = 1306.45[source]
VmPGM = 2525.81[source]
VmPYK = 1088.71[source]
dACE_dt(x)[source]
dBPG_dt(x)[source]
dF16BP_dt(x)[source]
dF6P_dt(x)[source]
dG6P_dt(x)[source]
dGLCi_dt(x)[source]
dNADH_dt(x)[source]
dNAD_dt(x)[source]
dP2G_dt(x)[source]
dP3G_dt(x)[source]
dPEP_dt(x)[source]
dPYR_dt(x)[source]
dPrb_dt(x)[source]
dTRIO_dt(x)[source]
dx_dt(x)[source]

Calculate the time derivative of the species concentrations

Parameters:x (numpy.array) – species concentrations (mM)
Returns:time derivative of the species concentrations (mM min-1)
Return type:numpy.array
gR = 1.12[source]
nPDC = 1.9[source]
plot_simulation_results(t, dhap)[source]

Plot simulation results

Parameters:
  • t (numpy.array) – time (min)
  • dhap (numpy.array) – DHAP concentration (mM)
Returns:

figure

Return type:

matplotlib.figure.Figure

simulate(t_0=0, t_end=20.0, t_step=0.2)[source]

Simulate the model

Parameters:
  • t_0 (float, optional) – start time (min)
  • t_end (float, optional) – end time (min)
  • t_step (float, optional) – time step to record predicted concentrations (min)
Returns:

  • numpy.array: time (min)
  • numpy.array: DHAP concentration (mM)

Return type:

tuple

v_1(x)[source]
v_10(x)[source]
v_11(x)[source]
v_12(x)[source]
v_13(x)[source]
v_14(x)[source]
v_15(x)[source]
v_16(x)[source]
v_17(x)[source]
v_2(x)[source]
v_3(x)[source]
v_4(x)[source]
v_5(x)[source]
v_6(x)[source]
v_7(x)[source]
v_8(x)[source]
v_9(x)[source]
x_0[source]
class intro_to_wc_modeling.cell_modeling.model_composition.MergedModel[source]

Bases: object

Merged model

glycolysis_model[source]

glycolysis model

Type:GlycolysisModel
glycerol_model[source]

glycerol model

Type:GlycerolModel
x_0[source]

initial species concentrations (mM)

Type:numpy.array
dx_dt(x)[source]

Calculate the time derivative of the species concentrations

Parameters:x (numpy.array) – species concentrations (mM)
Returns:time derivative of the species concentrations (mM min-1)
Return type:numpy.array
simulate(t_0=0, t_end=20.0, t_step=0.2)[source]

Simulate the model

Parameters:
  • t_0 (float, optional) – start time (min)
  • t_end (float, optional) – end time (min)
  • t_step (float, optional) – time step to record predicted concentrations (min)
Returns:

  • numpy.array: time (min)
  • numpy.array: DHAP concentration (mM)
  • numpy.array: G3P concentration (mM)

Return type:

tuple

v_18(x)[source]
v_19(x)[source]
x_0[source]
intro_to_wc_modeling.cell_modeling.model_composition.main(out_dir=None)[source]

Simulate individual models and combined model, plot results, and save plots

Parameters:out_dir (str, optional) – path to directory to save results

7.1.1.4. Module contents