Apr 28 2020
There are four learning algorithms built into ICM
All 2D molecular property predictors are calculated using fragment-based contributions and 3D models use Atomic Property Fields .
For 2D fingerprints we developed an original method for splitting a molecule into a set of linear or non-linear fragments of different length and representation levels and then each chemical pattern found is converted into a descriptor.
In order to perform 'learn and predict' in ICM information must be stored in a table, molecular table or csv file. See the tables chapter for more information on ICM tables. Both chemical compounds and numeric data can be source for building prediction models.
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