MTtbox documentation: Difference between revisions

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The aim is to model the growth of microtubules (and other dynamic organelles such as actin). Organelles grow through chemical reactions and growing organelles can collide with other organelles and membranes. <br><br>
The aim is to model the growth of microtubules (and other dynamic organelles such as actin). Organelles grow through chemical reactions and growing organelles can collide with other organelles and membranes. <br><br>
=How?=
=How?=
To address these two features we adopted a data structure that stores microtubules as a list of vertices each of which is associated with a volume. Volumes are represented by a three dimensional array (lattice) of voxels. Regions within this volume are designated by numerical labels, e.g. 0 for cytoplasm, -4 for plasma-membrane. The size of the entire volume determines the resolution of the chemical reaction/diffusion system. Resolution increases with the number of voxels. Increasing the number of voxels decreases the speed of computation and increases the demand for memory (>=16 Gbytes memory is highly desirable). Dynamic organelles, such as microtubules, are represented as geometrical objects: tubes with hemispheric ends.
To address these two features we adopted a data structure that stores microtubules as a list of vertices each of which is associated with a geometrically specified volume. Cell volumes are represented by a three dimensional array (lattice) of voxels. Regions within this volume are designated by numerical labels, e.g. 0 for cytoplasm, -4 for plasma-membrane. The size of the entire volume determines the resolution of the chemical reaction/diffusion system. Resolution increases with the number of voxels. Increasing the number of voxels decreases the speed of computation and increases the demand for memory (>=16 Gbytes memory is highly desirable). Dynamic organelles, such as microtubules, are represented as geometrical objects: tubes with hemispheric ends. These can collide with other microtubules, organelles and membranes. The most CPU time consuming step is collision detection.
==Current Status==
==Current Status==
MTtbox is currently under test and further development<br>
MTtbox is currently under test and further development<br>

Revision as of 20:13, 26 November 2012

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Why?

The aim is to model the growth of microtubules (and other dynamic organelles such as actin). Organelles grow through chemical reactions and growing organelles can collide with other organelles and membranes.

How?

To address these two features we adopted a data structure that stores microtubules as a list of vertices each of which is associated with a geometrically specified volume. Cell volumes are represented by a three dimensional array (lattice) of voxels. Regions within this volume are designated by numerical labels, e.g. 0 for cytoplasm, -4 for plasma-membrane. The size of the entire volume determines the resolution of the chemical reaction/diffusion system. Resolution increases with the number of voxels. Increasing the number of voxels decreases the speed of computation and increases the demand for memory (>=16 Gbytes memory is highly desirable). Dynamic organelles, such as microtubules, are represented as geometrical objects: tubes with hemispheric ends. These can collide with other microtubules, organelles and membranes. The most CPU time consuming step is collision detection.

Current Status

MTtbox is currently under test and further development