Thank you Dr. Roe for your corrections, they have clarified a lot of
doubts I had with the DBSCAN clustering.
One last issue though:
On 07/05/15 17:12, Daniel Roe wrote:
> There are two "distances" in the example. In the context of
> clustering, "distances" are just the measures of similarity of one
> data point to another. The distance (i.e. similarity) metric can be
> either coordinate-based (e.g. RMSD, DME) or based on data derived from
> coordinate frames (e.g. geometric distance, radius of gyration, etc).
>
>
I have read the Amber manual but I don't grasp the difference between
the default distance metric (rms) and dme. Out of curiosity, what
exactly is the difference between best-fit coordinate RMSD and
distance-RMSD?
>
> The pairwise distance matrix only depends on the clustering metric and
> the input frames. So as long as your input frames and distance metric
> are the same, you can re-use the pairwise distance matrix file.
>
Finally, just to be sure, the CpptrajPairDist file that is generated
does not depend on the epsilon or minpoints that are chosen, nor the
mask that is used in the command, correct? The clustering metric
strictly refers to the "rms", "srmsd" or "dme" keywords?
Since it produces a binary file I am not sure how to proceed if I want
to check myself that two of these files are identical or not.
Looking forward to hearing from you,
Juan
_______________________________________________
AMBER mailing list
AMBER.ambermd.org
http://lists.ambermd.org/mailman/listinfo/amber
Received on Fri May 08 2015 - 07:30:02 PDT
