I will second Peter's comment. If you are after frequent subgraph
mining/identification using brics (or recap or Murcko frameworks) would get
you what you need.
MCS's are often thought of in the context clustering, as scaffolds to
clusters. If that is what you are after the answer to your question becomes
much lengthier and probably not appropriate for this mailing list.
best,
--cn
On Tue, Dec 11, 2012 at 8:32 AM, Peter Gedeck <[email protected]>wrote:
> Hello
>
> > given a data set of let's say 2000 compounds,
> > how do I extract the most
> > common substructures rather than the
> > maximum common substructures?
> > In addition, I would like to output the
> > frequency of the found
>
> One approach would be to take a brics decomposition where you keep the
> full decomposition hierarchy of a structure. You can then just count the
> fragments in your data set to get the frequencies. As the brics decomp is
> done in python it's not particularly fast (I mean interactive speed) but
> for 2000 compounds it's ok.
>
> The nice thing about the brics fragments is that chemists will like them.
> I would terminate the decomposition at a fragment size of 3 to avoid
> getting single atoms. check the arguments of the brics decomposition
> function for ways to do this.
>
> Best,
>
> Peter
>
>
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--
Christos Nicolaou
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