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Dissimilarity Selection (from Matrix)

Schrödinger extension for KNIME Workbench version 20.3.139.202008121324 by Schrödinger

Dissimilarity Based Compound Selection

Backend implementation

utilities/canvasDBCS
canvasDBCS is used to implement this node.

Options

Number of Subsets
Number of subsets requested. Required for selection methods maxsum and maxmin. Allowed for methods sphere and dise where it is applied as a secondary filtering step.
Distance Threshold
Threshold for selection methods "sphere" and "dise".
Selection Method Type
Choice of selection method:

  • sphere (default)
  • dise
  • maxsum
  • maxmin

Metric Type
Valid types:
  • buser
  • cosine
  • dice
  • dixon
  • euclidean
  • hamann
  • hamming
  • kulczynski
  • matching
  • mcConnaughey
  • minmax
  • modifiedTanimoto
  • patternDifference
  • pearson
  • petke
  • rogersTanimoto
  • shape
  • simpson
  • size
  • soergel(default)
  • tanimoto
  • variance
  • yule
Ignore any scaled Finger Print values
Ignore any scaled fp values in input
Initialization Method
Valid methods:
  • random (default)
  • first
  • representative
  • dissimilar
Seed for random Number generation
Seed for random number generation (defaults to clock)

Input Ports

Icon
Pairwise matrix or Molecular fingerprints (both in binary format). The matrix contains only intra-distances between one set of compounds (i.e. symmetric matrix)

Output Ports

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Dissimilarity Selection as a molecule name list (1 String column)

Views

Std output/error of Dissimilarity Selection
Std output/error of Dissimilarity Selection

Best Friends (Incoming)

Best Friends (Outgoing)

Workflows

Installation

To use this node in KNIME, install Schrödinger Extensions for KNIME from the following update site:

KNIME 4.2
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Developers

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