Dissimilarity Selection (from Matrix)

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

: 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

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

Popular Predecessors

Popular Successors

Views

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

Workflows

Developers

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Installation

To use this node in KNIME, install the extension Schrödinger Extensions for KNIME from the below update site following our NodePit Product and Node Installation Guide:

v5.2

A zipped version of the software site can be downloaded here.

Plugin provider: Schrödinger

Plugin version: 24.1.135.v202402072122

On NodePit since: 2023-12-06

Last update: 2024-04-18

KNIME versions: v5.2, v5.1, v4.7, v4.6, v4.5, v4.4, v4.3, v4.2, v4.1, v4.0, v3.7, v3.6

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