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By means of a system of ordinary differential equations these models show the change in time (dynamical system) of the protein inside a single typical cell; this type of model is called a deterministic process (whereas a model describing a statistical distribution of protein concentrations in a population of cells is called a stochastic process).
A cellular automaton consists of a regular grid of cells, each in one of a finite number of states, such as on and off (in contrast to a coupled map lattice). The grid can be in any finite number of dimensions. For each cell, a set of cells called its neighborhood is defined relative to the specified cell.
The images under this map are notated with an upper index and two lower indices , so that the typical element of the image is written as . and satisfying the following conditions: The image of C {\displaystyle C} is a R {\displaystyle R} - basis of A {\displaystyle A} .
The solution of the equations, by either analytical or numerical means, describes how the biological system behaves either over time or at equilibrium. There are many different types of equations and the type of behavior that can occur is dependent on both the model and the equations used. The model often makes assumptions about the system.
To save memory, the storage can be reduced to one array plus two line buffers. One line buffer is used to calculate the successor state for a line, then the second line buffer is used to calculate the successor state for the next line. The first buffer is then written to its line and freed to hold the successor state for the third line.
The cell is the basic structural and functional unit of all forms of life. Every cell consists of cytoplasm enclosed within a membrane; many cells contain organelles, each with a specific function. The term comes from the Latin word cellula meaning 'small room'. Most cells are only visible under a microscope.
Specifically, if X and Y are CW complexes, then one can form a CW complex X × Y in which each cell is a product of a cell in X and a cell in Y, endowed with the weak topology. The underlying set of X × Y is then the Cartesian product of X and Y , as expected.
where the last equation deals with parents and daughters at branches, and =. We can iterate these equations through the tree until we get the point where the dendrites connect to the cell body (soma), where the conductance ratio is B in,stem. Then our total neuron conductance for static input is given by