model of the human follicle growth More...
Go to the source code of this file.
Functions | |
function model = | follicle_model (params) |
model of the human follicle growth More... | |
function A = | folliclemodel>A_func (model, model_data) |
function Acomp = | folliclemodel>A_components (model, model_data) |
function Acoeff = | folliclemodel>A_coefficients (model) |
function B = | folliclemodel>B_func (model, model_data) |
function Bcomp = | folliclemodel>B_components (model, model_data) |
function Bcoeff = | folliclemodel>B_coefficients (model) |
function C = | folliclemodel>C_func_separatrix (model, model_data) |
function C = | folliclemodel>C_func_expectation_M (model, model_data) |
function C = | folliclemodel>C_func_expectation_N (model, model_data) |
function Ccomp = | folliclemodel>C_components_separatrix (model, model_data) |
function Ccomp = | folliclemodel>C_components_expectation_M (model, model_data) |
function Ccomp = | folliclemodel>C_components_expectation_N (model, model_data) |
function Ccoeff = | folliclemodel>C_coefficients (model) |
function D = | folliclemodel>D_func (model, model_data) |
function x0 = | folliclemodel>x0_func (model, model_data) |
function x0comp = | folliclemodel>x0_components (model, model_data) |
function
x0coeff = | folliclemodel>x0_coefficients (model) |
function
model_data = | folliclemodel>my_ds_gen_model_data (model) |
function
detailed_data = | folliclemodel>my_ds_gen_detailed_data (model, model_data) |
function p = | folliclemodel>plot_state_probabilities (model, model_data, sim_data, params) |
function p = | folliclemodel>my_plot_slice (model, model_data, sim_data, params) |
model of the human follicle growth
Definition in file follicle_model.m.
function model = follicle_model | ( | params | ) |
model of the human follicle growth
two chemical components are assumed to be characteristic for the growth of human follicles.
A deterministic model for the two species is given by a positive feedback loop, a bistable switch, i.e. 2-d nonlinear ODE.
An approximation to the Chemical Master Equation gives a linear dynamical system.
here, the state vector is the probability of states (pair of number of two chemical components) and the matrix A describes the change in these probabilities over time. The number of states is p = (range+1)*(range+2)/2
separatrix
: an average over a subset of states, the ones below the "separatrix", which are assumed to be still "in rest", i.e. waiting for their growth specified by model.output_range expectation_M
: the expectation of M state is computed expectation_N
: the expectation of N state is computedparams | params |
model | model |
range —
range output_range —
output range init_range —
init range reg_epsilon —
reg epsilon output_type —
output type output_plot_indices —
output plot indices estimate_bounds —
estimate boundsdata_const_in_time —
data const in time verbose —
flag indicating the verbosity level of informative output debug —
flag indicating wether debug output shall be turned on M1 —
M1 h —
h M2 —
M2 range —
range output_range —
output range init_range —
init range reg_epsilon —
reg epsilon u1 —
u1 u2 —
u2 k1fact —
k1fact V1fact —
V1fact V2fact —
V2fact mu_names —
a string array containing the symbolic names of the parameter vector \(\mu\) mu_ranges —
matrix storing the admissable ranges for parameter vector components. Each two dimensional column vector represents a range for a component specified by model.mu_names
. T —
end time for evolution problems nt —
number of time steps for evolution discretizations affinely_decomposed —
affinely decomposed A_function_ptr —
A function ptr B_function_ptr —
B function ptr C_function_ptr —
C function ptr D_function_ptr —
D function ptr x0_function_ptr —
x0 function ptr u_function_ptr —
u function ptr G_matrix_function_ptr —
G matrix function ptr gen_model_data —
gen model data gen_detailed_data —
gen detailed data plot_sim_data_state —
plot sim data state plot_slice —
plot slice axis_tight —
axis tight orthonormalize —
orthonormalize dim_x —
dim x dim_y —
dim y output_plot_indices —
output plot indices theta —
theta enable_error_estimator —
enable error estimator state_bound_constant_C1 —
state bound constant C1 output_bound_constant_C2 —
output bound constant C2 estimate_lin_ds_nmu —
estimate lin ds nmu estimate_lin_ds_nX —
estimate lin ds nX estimate_lin_ds_nt —
estimate lin ds nt inner_product_matrix_algorithm —
function pointer to a function computing a inner product matrix \(W\), such that \(u^t W v = <u, v>\). An example is fv_inner_product_matrix(). error_algorithm —
error algorithm RB_stop_timeout —
RB stop timeout RB_stop_epsilon —
RB stop epsilon RB_error_indicator —
RB error indicator RB_stop_Nmax —
RB stop Nmax RB_generation_mode —
RB generation mode RB_numintervals —
RB numintervals RB_detailed_train_savepath —
RB detailed train savepath RB_extension_algorithm —
RB extension algorithm save_detailed_simulations —
save detailed simulations Definition at line 17 of file follicle_model.m.