An essential part of the OCHEM platform is the modeling framework. Its main purpose is to provide facilities for the development of predictive computational models for physicochemical and biological properties of compounds. The framework is integrated with the database of experimental data and includes all the necessary steps required to build a computational model: data preparation, calculation and filtering of molecular descriptors, application of machine learning methods and analysis of a models’ performance. This section gives an overview of these features and of the steps required to build a computational model in the OCHEM.
OCHEM modeling framework allows to perform the full cycle of QSAR model development, which includes:
- Management of datasets with experimental data.
Users can create and manage reusable datasets referred to as baskets. - Calculation of molecular descriptors.
OCHEM supports more that 20 types of state-of-the-art molecular descriptors from different 3rd party vendors. - Running a machine learning method
- Proper validation protocol of the model
- Calculation of model statistics
- Application of the model to new compounds
- Recalculation of the model based on new experimental evidence
Concisely, the main features of the modeling framework within the OCHEM include:
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