Jul 30 2019
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.
|Copyright© 1989-2019, Molsoft,LLC - All Rights Reserved.|
This document contains proprietary and confidential information of
The content of this document may not be disclosed to third parties, copied or duplicated in any form,
in whole or in part, without the prior written permission from Molsoft, LLC.