Download Genetic Component

Demetris Kennes
Contents
 Aims
 Method(The Model)
 Genetic Component
 Cellular Component
 Evolution
 Test and results
 Conclusion
 Questions?
Aims
There are two important aims:
 To show that critical periods actually occur as complex
dynamical systems that are mostly used in simulations
of natural development
 To give an extension on the positive output
Method(The Model)
 Models the early stages of embryonic development
 Models the development of cellular structures and cell
differentiation
The Model is divided in two important components:
 The genetic component
 The cellular component
 The genetic component
- Simulates genetic expression and regulation by
use of a Genetic Regulatory Network
- Artificial record factors and proteins are
synthesized, that excite and inhibit genes in the
network.
 The cellular component
- Simulates numerous cell functions that make it
feasible to grow cellular structures collected from cells
of other types
- These functions are controlled by particular proteins
formed by the Genetic Regulatory Network.
Genetic Component
 Genes are responsible for developing proteins during
genetic transcription
 Special molecules (ribosome) decode genetic set of
laws into strings of amino acids which fold into
proteins
 The essential mechanism by which genes work
together with one another
 The synthesis of a transcription factor by one gene can
affect the expression of all other genes in the genome.
Cellular Component
 Cell division
 Cell death
 Cell Spindle and Cell Orbit
 Cell signaling
 Cell division:
- When a cell is divided it makes a copy of itself and places
the copy one and a half radius lengths away from its centre
position in the way of its mitotic spindle
- The daughter cell’s genome is initialized with the value of
its mother cell.
- Inherits the mitotic spindle orientation from its mother
- This function takes 10 time steps to complete
 Cell death:
- The cell is removed from the universe freeing up a
location for another cell to divide into.
- This function takes 5 time steps to complete.
 Cell Spindle and Cell Orbit:
- The cell’s mitotic spindle points to one of twelve
positions on the cell’s surface
- The twelve positions are the corners of three
mutually orthogonal squares centred at the cell’s
centre
- Cells that perform different functions, or the same
functions at different frequencies, suitable to
dissimilar dynamics in genetic regulation are
considered to be different cell types
- In this model, various cell types are represented by
the attention of morphogens that a cell is producing
 Cell Signalling:
- Principal mechanism that cells differentiate and
organize themselves into sub populations
- Cells use concentration gradients of morphogens
proteins that can spread through cell membranes and
encourage signal responses in other cells
- Provides spatial information to cell populations
- In this model cells can produce three morphogens
- Morphogen diffusion is simulated by using a 3D
Gaussian function centred at the position of the cell
Evolution
 Several populations are developed via the identical fitness
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function, every population with a different number of
genes
The fittest individuals from these populations were
detached after 500 generations and used in experiments
Every individual in the population was run for 300 timesteps before its fitness was measured
Simple 3D shapes are placed in the virtual universe and
passing on target cell types to them, most structures could
be more precise.
The target structure was a set of 5 spheres with a gradated
target type, from blue in the centre, to strong green on the
outer layer
 The algorithm works as follows:
1. Create an initial random population of genomes.
2. Run each individual for a fixed number of time steps.
3. Compute all individual fitness based on a fitness
function.
4. Create a small sub-population (the elite population)
of the fittest individuals.
5. For each non-elite individual, select a random elite
and infect the non-elite with it.
6. Mutate the infected individual.
7. Repeat from step 2 for a fixed number of generations.
Tests and Results
 Five genomes were developed, with a genome size ranging
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from 13 to 17 genes
All created organisms with separate layers of cells
approximately match with those specified in the fitness
function
Statistically meaningful peaks do not exist in neither rate of
change nor cross correlation.
The cross-correlation reveals an important correlation
involving periods of sensitivity and the developmental
profile
None of these peaks in rate of change are significant except
a less strict threshold of one standard deviation
Explain that developmental models, do indeed exhibit
critical periods.
 It has provided facts of correlation between critical periods
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and developmental rate of change
3 of 5 organisms display critical periods around the 150th
time step
There is a period of time during which the perturbation has
an effect on the outcome of development
The presence of these critical periods is consistent with the
working hypothesis of this paper
The cross-correlation shows significant peaks, with a lag
within the window of the perturbation
Evolution has more parameters to tune for genomes, more
generations are needed to form the process
Critical periods are the product of the evolutionary process
on systems
Conclusion
 Initial step in the study of critical periods
 The model was deliberately straightforward and so
suffers from numerous limitations
 The model is completely deterministic
 The size of the perturbation window is extremely large
 The study must be broadened to other developmental
processes
 It has provided evidence of a correlation among critical
periods and developmental rate of change
 It is a first step to the goal of a general technique for
calculating critical periods in developmental systems
QUESTIONS ?