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EGFR2_pybionetfit.conf
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# Fitting the EGF model
# Model specification
# Base Models
model = EGFR_new_no_Shp.xml : EGFR_no_Shp_.exp
model = EGFR_new.xml : EGFR_.exp
mutant = EGFR_new_no_Shp 1 Lig=0.00495 : EGFR_no_Shp_1.exp
mutant = EGFR_new_no_Shp 2 Lig=0.0165 : EGFR_no_Shp_2.exp
mutant = EGFR_new_no_Shp 3 Lig=0.0495 : EGFR_no_Shp_3.exp
mutant = EGFR_new_no_Shp 4 Lig=0.165 : EGFR_no_Shp_4.exp
mutant = EGFR_new_no_Shp 5 Lig=0.495 : EGFR_no_Shp_5.exp
mutant = EGFR_new_no_Shp 6 Lig=1.65 : EGFR_no_Shp_6.exp
mutant = EGFR_new_no_Shp 7 Lig=4.95 : EGFR_no_Shp_7.exp
mutant = EGFR_new_no_Shp 8 Lig=16.5 : EGFR_no_Shp_8.exp
mutant = EGFR_new 1 Lig=0.00495 : EGFR_1.exp
mutant = EGFR_new 2 Lig=0.0165 : EGFR_2.exp
mutant = EGFR_new 3 Lig=0.0495 : EGFR_3.exp
mutant = EGFR_new 4 Lig=0.165 : EGFR_4.exp
mutant = EGFR_new 5 Lig=0.495 : EGFR_5.exp
mutant = EGFR_new 6 Lig=1.65 : EGFR_6.exp
mutant = EGFR_new 7 Lig=4.95 : EGFR_7.exp
mutant = EGFR_new 8 Lig=16.5 : EGFR_8.exp
output_dir=/home/michael/PycharmProjects/EGFR/
# Algorithm and objective function choice
fit_type = de
# fit_type = sim
# objfunc = sos
objfunc = sod
# objfunc = norm_sos
# objfunc = ave_norm_sos
population_size = 200
max_iterations = 500
stop_tolerance = 0.000001
# Parameters
##### - Starting parameter values for fitted species - #####
# kp1 0.007
# kp5 0.06
# k2 0.4
# kp2 0.023
# k_2a 0.06
# k_3 0.5
# k5 0.78
# kp3 0.015
# k_5a 0.08
# k6 0.115
# kp4 0.07
# k_6a 0.1
# k_9 0.5
# k10 0.02
# k_10 0.5
# k_11 0.011
# k12 0.8
# k13 0.5
# k_14 0.1
# k15 0.8
# k16 0.5
# k17 0.25
# k18 0.015
# k19 0.5
# loguniform_var = kp1 0.0035 0.014
# loguniform_var = kp5 0.03 0.12
# loguniform_var = k2 0.2 0.8
# loguniform_var = kp2 0.0115 0.046
# loguniform_var = k_2a 0.03 0.12
# loguniform_var = k_3 0.25 1
# loguniform_var = k5 0.39 1.56
# loguniform_var = kp3 0.0075 0.03
# loguniform_var = k_5a 0.04 0.16
# loguniform_var = k6 0.0575 0.23
# loguniform_var = kp4 0.035 0.14
# loguniform_var = k_6a 0.05 0.2
# loguniform_var = k_9 0.25 1
# loguniform_var = k10 0.01 0.04
# loguniform_var = k_10 0.25 1
# loguniform_var = k_11 0.0055 0.022
# loguniform_var = k12 0.4 1.6
# loguniform_var = k13 0.25 1
# loguniform_var = k_14 0.05 0.2
# loguniform_var = k15 0.4 1.6
# loguniform_var = k16 0.25 1
# loguniform_var = k17 0.125 0.5
# loguniform_var = k18 0.0075 0.03
# loguniform_var = k19 0.25 1
loguniform_var = kp1 0.00175 0.028
loguniform_var = kp5 0.025 0.4
loguniform_var = k_p5 0.05 0.8
loguniform_var = k2 0.1 1.6
loguniform_var = kp2 0.00575 0.092
loguniform_var = k_2a 0.015 0.24
loguniform_var = k_3 0.125 2
loguniform_var = k5 0.195 3.12
loguniform_var = kp3 0.00375 0.06
loguniform_var = k_5a 0.02 0.32
loguniform_var = k6 0.02875 0.46
loguniform_var = kp4 0.0175 0.28
loguniform_var = k_6a 0.025 0.4
loguniform_var = k_9 0.125 2
loguniform_var = k10 0.005 0.08
loguniform_var = k_10 0.125 2
loguniform_var = k11 0.025 0.4
loguniform_var = k_11 0.00275 0.044
loguniform_var = k12 0.2 3.2
loguniform_var = k13 0.125 2
loguniform_var = k14 0.025 0.4
loguniform_var = k_14 0.025 0.4
loguniform_var = k15 0.2 3.2
loguniform_var = k16 0.125 2
loguniform_var = k17 0.0625 1
loguniform_var = k18 0.00375 0.06
loguniform_var = k19 0.125 2
verbosity=2
# Actions
time_course = model:EGFR_new_no_Shp, time:720, suffix:EGFR_no_Shp_
time_course = model:EGFR_new, time:720, suffix:EGFR_