On 25 May 2015 at 22:23, Tim Dudgeon <[email protected]> wrote:
> Maybe a clustering approach may work? Something like sphere exclusion
> clustering with counting the number of clusters at 0.9 - 0.8 similarity)?
> With 30K structures it sounds computationally tractable?
Thanks Tim for this idea. I hadn't heard of sphere exclusion. The problem
is we still need a distance / similarity function (which using ECFP with
high similarity 0.8-0.9 would result in very few compounds being thrown
out). I think the real issue here is selecting a sensible similarity
threshold which defines my idea of "similarity". But that is a tricky
number to get right - too high and you remove nothing, too low and you
start catching "different" molecules. I guess the best thing is try a few
values (0.5, 0.6, 0.7, 0.8, 0.9) and have a visual look at the remaining
compounds.
-
JP
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