##-------------Anticancer Activity Prediction-----------##

SMILES are alpha-numeric linear representations of chemical molecules. Exploiting these representations to unravel the patterns relevant to anticancer drug space would assist in predcition of anticancer activity of drug leads. Consequently, different algorithms were explored for anticancer activity prediction using molecular SMILES.

Jupyter-notebooks of frequent scaffold analysis of NCI-60 & ChEMBL datasets are included. Codes of Multi-layer Perceptron, SVC, Logistic Regression, Decision tree, CatBoost, AdaBoost and XGBoost classification models trained using curated anticancer drug molecules for anticancer activity prediction are included.

#Suggestions & Feedback are welcome..!#

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