Supervised learning techniques to predict compounds in pathway modules
based on molecular properties
# Machine learning Classifiers for prediction of Pathway module & it
We use SMILES representation of query molecules to generate relevant
fingerprints, which are then fed to the machine learning classifiers ETC
for producing binary labels corresponding pathway module & its classes.
The details of the works are described in our paper.
A dataset of 6597 downloaded from KEGG, 4612 compounds either belong or
not to Pathway module in metabolic pathway the remaining 1985 compounds
belong to module classes prediction problems
* Jupyter Notebook
We provide two folder containing Classifiers files,grid search for
optimization of hyperparameters, and datasets(module, module classes