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calculation of eSALI #3
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Hi Albert, thanks a lot for your interest in our work and for reaching out to us. The calculate_counters function gives the main ingredients to then calculate the extended similarity (Se(M)), which then can be used in the eSALI formula. In this file https://github.com/ramirandaq/MultipleComparisons/blob/master/condensed_version/MultComp.py |
Hi, no problem! We don't have the extended Euclidean in this module. It'll be tricky to do this with Euclidean, but relatively easy to do with the square of the Euclidean distance. Basically, instead of using the "RMSD" using the "MSD", without the square root. |
Hi,
I read the paper - "Exploring activity landscapes with extended similarity: is Tanimoto enough?"[https://onlinelibrary.wiley.com/doi/epdf/10.1002/minf.202300056]
I am trying to relate the code this repo and the equations mentioned in the paper, specifically this
is the
calculate_counters()
function in the condensed_version/MultComp.py responsible for getting the S e(M) value?Sorry if I missed anything in the paper or in the docstrings but I cannot see a formula of how S e(M) is calculated or which code is responsible for this?
My task is simple, I am just trying to calculate the eSALI for my dataset, I have the numerical descriptors and the properties of the compounds.
Albert
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