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01_​Clustering_​and_​Interactive_​Compound_​Selection

03_Clustering

This exercise shows how to perform hierarchical clustering using molecule fingerprints and create an interactive view to pick interesting clusters. Chemical structures were extracted from this publication: https://doi.org/10.1021/acs.jmedchem.9b01658​

Getting the data ready Another pattern you may see Remove duplicates Generate the hierarchical cluster tree Identify and highlight scaffold MFP2filter out values other than =Node 70calculate pKiEstimate scaffoldOnly selected rowsHighlight coreNode 116Only matching moleculesDuplicateRow Filter RDKit Fingerprint Bit VectorDistances Hierarchical Clustering(DistMatrix) RDKit Canon SMILES Molecule Type Cast Row Splitter Set clusterthreshold RDKit Salt Stripper Math Formula File Reader RDKit MCS Row Filter RDKit MoleculeHighlighting Table Rowto Variable RDKit SubstructureFilter pick compounds File Reader(Complex Format) Data Explorer Add descriptors,images, and colors Getting the data ready Another pattern you may see Remove duplicates Generate the hierarchical cluster tree Identify and highlight scaffold MFP2filter out values other than =Node 70calculate pKi Estimate scaffoldOnly selected rowsHighlight coreNode 116Only matching moleculesDuplicateRow Filter RDKit Fingerprint Bit VectorDistances Hierarchical Clustering(DistMatrix) RDKit Canon SMILES Molecule Type Cast Row Splitter Set clusterthreshold RDKit Salt Stripper Math Formula File Reader RDKit MCS Row Filter RDKit MoleculeHighlighting Table Rowto Variable RDKit SubstructureFilter pick compounds File Reader(Complex Format) Data Explorer Add descriptors,images, and colors

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To use this workflow in KNIME, download it from the below URL and open it in KNIME:

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Created by: glandrum
Created at: 2020-05-19
On NodePit since: 2021-10-21
Last update: 2024-04-25
Created with KNIME version: v4.4.1
Tags: Hierarchical ClusteringBit Vector DistancesMolecule DescriptorsInteractive SelectionChemistryLife SciencesEducation

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