Difference between revisions of "DsDNA persistence length"

From OxDNA
(Persistence length of a double-stranded DNA)
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The program will produce a trajectory.dat file. To analyze the data, use the python script dspl.py:
 
The program will produce a trajectory.dat file. To analyze the data, use the python script dspl.py:
 
  
 
<tt> dspl.py trajectory.dat init.top 10 50 </tt>
 
<tt> dspl.py trajectory.dat init.top 10 50 </tt>
  
 
This program will produce a table of correlations between helical vectors, <math> $\langle {\bf n_k} \cdot {\bf n_0} \rangle$ </math>. Using an exponential fit to these data, one can find the persistence length.
 
This program will produce a table of correlations between helical vectors, <math> $\langle {\bf n_k} \cdot {\bf n_0} \rangle$ </math>. Using an exponential fit to these data, one can find the persistence length.

Revision as of 17:41, 16 April 2012

Persistence length of a double-stranded DNA

The example shows how to calculate a persistence length of a double stranded DNA molecule. dsDNA persistence length. The persistence length in this example is calculated using the following formula (see [1] for details):

In the EXAMPLES/PERSISTENCE_LENGTH directory, you will find a setup for calculating the persistence length of a 202 base pairs long dsDNA. Note that for calculating a persistence length of a dsDNA, one needs a large number of decorrelated states. To obtain the states (which will be saved into a trajectory file), run the simulatin program using the prepared input_persistence file:

oxDNA input_persistence .

The program will produce a trajectory.dat file. To analyze the data, use the python script dspl.py:

dspl.py trajectory.dat init.top 10 50

This program will produce a table of correlations between helical vectors, . Using an exponential fit to these data, one can find the persistence length.