Jörn Appeldorn

Hej, just for closure: In the traj2vis.py file I changed added the following line: os.environ[GROOVE_ENV_VAR] = "1" And you are right. Now it shows a nice Gaussian distribution around the r_0 of oxDNA2. Thanks for the help again!

Hej, just for closure: In the traj2vis.py file I changed added the following line: os.environ[GROOVE_ENV_VAR] = "1" And you are right. Now it shows a nice Gaussian distribution around the r_0 of oxDNA2. Thansk for the help again!

Hej, so I rewrite the configurations with traj2vis.py xyz. Then I am calculating the eucidean distance sqrt((x[0]-x[1])^2 + (y[0]-y[1])^2 + (z[0]-z[1])^2) along the chain. So for this system I have per time-step 39 bonds.

Dear all, I am using oxDNA2 for the ciruclar assembly (in the examples). I run the simulation with the same parameters for oxDNA, oxDNA2 with VMMC and MD as simulation type. To verify the results, I check the length of the backbone. In the documentary and papers it is written, that the backbone potential is a FENE-potential. Plugging in the values (e = 2, r_0 = 0.7525 (2: 0.7564), delta = 0.25) shows, that the backbone bondlengths should be Gaussian distributed around r_0 and diverging at 0.5 and...

Dear all, I am using oxDNA2 for the ciruclar assembly (in the examples). I run the simulation with the same parameters for oxDNA, oxDNA2 with VMMC and MD as simulation type. To verify the results, I check the length of the backbone. In the documentary and papers it is written, that the backbone potential is a FENE-potential. Plugging in the values (e = 2, r_0 = 0.7525 (2: 0.7564), delta = 0.25) shows, that the backbone bondlengths should be Gaussian distributed around r_0 and diverging at 0.5 and...