You're trying to have your cake and it it too. This does not work.
As a general rule, for problems with features on different length scales, you need meshes that are fine in at least some parts of the mesh. This results in many cells, and this results in long computations, small time steps, and many linear iterations. All of these implications are rather ...
With conforming triangular meshes, it will be difficult to make an isotropic mesh which adapts to multiple dramatically different length scales in such a short space without introducing extraneous triangles, some of which may have very large/small angles.
I'm not very familiar with them so take this with a grain of salt, but you may have better luck using ...
So Is it neccesary to use Poisson - Boltzmann equation if I only need to build electrostatic potential from a PQR file?
No. You can use Poisson.
Since you know the positions of each point charge, you know the charge distribution $\rho$, which is a sum of delta functions.
You can thus solve numerically the Poisson's equation that links the charge ...
Your model seems to have a single stable critical point that attracts
all orbits. You're plotting $(S(t), I(t), R(t))$ as functions of time
for specific initial conditions, but actually the easier way to see
this directly is to plot the vector field $(\dot S, \dot I)$ in the
$S$-$I$ plane like so:
Immediately you can see that for this particular choice of ...
The Van der Walls radius - last column in the output - is calculated from the force field. Probably pdb2pqr and editconf uses different force fields, hence different radius. I don't use pdb2pqr, but it seems (1) AMBER99 is the default force field, though CHARMM, PARSE and TYL06 are supported. Gromacs' editconf reads force field from topology file generated ...
I'm not particularly familiar with biofilm literature. But in most computational literature, the border of the entire domain of a problem are usually referred to as the boundary. Outside of a boundary, there are no nodes, elements, or anything else under consideration.
The entire domain may also be subdivided into smaller regions. Some of these regions ...
There is something called the ODD (Overview, Design, and Details) protocol, proposed by Volker Grimm and others for describing an agent based model. It consists of a list of elements that are needed for understanding the functioning of an ABM and aims at making descriptions of such models more standardised.
The checklist of what has to be described consists ...
You might want to look at ProtoMol. It is not a library but an application but it is designed to be easily extendable. Thus it might be easier to add your custom potential than it would be with e.g. LAMPPS or Gromacs. The later two would be better options if you want to have good parallel performance.
Allow me to plug my own library, mdcore.
mdcore is an Open-Source, platform-independent library for Molecular Dynamics simulations written in C. It runs on clusters, multi-cores, and GPUs and can handle any type of inter-particle interaction potential. The code is mainly a test-bed for new algorithms, but it is extremely fast.
The library is relatively ...
Is there a reason you can't just call that function and then plot your scatter plot on the figure it creates?
Otherwise you could either open up the existing function that plots the Ramachandran regions and copy/modify the relevant parts to do what you want or you could copy the data out of the plotted objects (using the get function, see this link) and re-...
Molecular dynamics, in the computation of interactions inversely proportional to distance. Other N-body codes may share this property, but it's often an explicit goal to minimize or eliminate explicit division for exactly the reason you've given.
Resolving small features in FEM will always be costly, there is no getting away from that fact. Your problem seems to be framed in terms of computational burden. In my own case, I was looking at electric field problems in anatomical structures, so had a similar set of problems to your own. The question is usually how detailed a mesh is "good enough" for the ...
So I managed to create a spiral finally. The method I used to initiate spiral is by initializing the mesh with a set of initial values expect a small square patch which is initialized with $180°$ phase shift with others and some having $90°$ phase shift. The link to spiral video I created is here.
Pretty much any biology can be made computational. Now as it is called "computational" I hope you can do some programming, for that's what it is going to be about.
For gene stuff I think databases and algorithms are important, for they deal with big data. This is an area I know little about, but it seems what other people have been suggesting are mainly ...
You can use the set_residue_to_rotamer_number() function in Coot to do this.
m = read_pdb("test.pdb")
for irot in range(n_rotamers(m, "A", 30, "")):
set_residue_to_rotamer_number(m, "A", 30, "", "", irot)
fn = "sample-A-30-rot-" + str(irot) + ".pdb"
Estimate from the PDB the covariance matrix of the vector of atomic distances in the side chains minus the vector of template distances.
Then simulate random corrections to the template distances using the multivariate Gaussian with this covariance matrix.
Convert each vector of distances to a distance matrices.
Then convert the randomly corrected ...