Evolutionary dynamic of a model of the Neurospora crassa circadian clock
The codes in matlab language for the comparison of the deterministic and stochastic simulations in the two environments (Light:Dark and Dark:Dark) and with the same parameters are divided in three files groups: The files containning the models to the deterministic and stochastic simulations are named as:
- modelo_complejo.m (Deterministic model)
- modelo_st.m (Stochactic model) The files that you can run the simulations are named as:
- Simulacion_compleja.m (Deterministic simulations; shows the graphic of the simulation)
- Simulacion_st.m (Stochatsic simulation; saves the simulations in Data_st[1-9].mat file) The files that shows the correlation functions with the simulations in both environments (LD and DD) are named as:
- Correlacion.m (Deterministic simulations; run other simulations with their correlation functions)
- Correlacion_st.m (Stochatsic simulation; use the Data_st[1-9].mat file to do their correlation functions)
The codes to do the KO like mutations and the graphics of the parameter space of my model are in two jupyter notebook files:
- With the Parameter_mutants.ipynb notebook you can generate the data of single and double mutants and many graphics of the space of parameters of the mutants and the wild type.
- With the Graphics.ipynb notebook you can explore the parameter space of my model with the mutants and wild type data generated by Parameter_mutants.ipynb notebook. Also, you can compare the mutants with the wild type parameter space to observe the more relevants parameter differences.
Finally to the evolutionary simulations you can run the EvoDynamics_Neurospora_Moran.ipynb notebook, you can modiffy the initial conditions, the composition of the initial subpopulations, the mutation rate and the selection rate, to do the different simulations that you want. The Evolutionary results are saved as three different files that contain different information of the same simulation.
Individual information This document contain the individual information of the 10% of the populations for each generation, it's organized like:
- Generation.
- Cell Tag: A flag that indicates the identity of each individual.
- Expression and repression constant: Genotype information.
- Constant of light rate: Genotype information.
- Dissociation constant: Genotype information.
- Hill exponents: Genotype information.
- Fitness.
- WCCn: The concentration of the WCC protein saved through a time span of one generation at every half hour.
- Time: The time at every half hour for a generation.
- Parent Tag: The parent individual identity.
Average Generation information This document contain the Average population information for each generation, it's organized like:
- Generation.
- Expression and repression constant.
- Constant of light rate.
- Dissociation constant.
- Hill exponents: Average genotype information.
- WCC: Mean WCC protein at each generation.
- Fitness: Mean fitness at each generation.
Lineage per cycle information This document contain the Lineage information for each two oscillation cycle (24 generations or 48 hours) of all the population, it's organized like:
- Generation.
- LTag: Flag of the identity of the first parent (Lineage).
- LMut: Flag of the cumulative lineage mutations in a cycle.
- LFit: Average fitness of the lineage.
- LOsc: Type of oscillation of the lineage (0:"perfect oscillation", 1:"delay oscillation", 2:"irregular oscillation").
- Expression and repression constant.
- Constant of light rate.
- Dissociation constant.
- Hill exponents: Average genotype information of the lineage.
And in the Data_analisys.ipynb notebook you can generate the graphics to analyze the evolutionary data.