Aug 4 2022 Feedback.
Contents
 
Help Videos
Reference Guide
Getting Started
Protein Structure
Molecular Graphics
Slides & ActiveICM
Cheminformatics
Learn and Predict
 Learn
 Predict
 Fingerprint Methods
 3D QSAR
 Theory
MolScreen
3D Ligand Editor
Tables and Plots
Local Databases
KNIME
Tutorials
 
Index
PrevICM User's Guide
8 Learn and Predict
Next

Available in the following product(s): ICM-Chemist-Pro | ICM-VLS
In this chapter:

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.


Prev
3D QSAR
Home
Up
Next
Learn

Copyright© 1989-2020, Molsoft,LLC - All Rights Reserved.
This document contains proprietary and confidential information of Molsoft, LLC.
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.