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Deep Learning for Metabolic Pathway Prediction by Anand Srinivasan is a document available to read on EtoBox.

What is Deep Learning for Metabolic Pathway Prediction about?

This paper presents a deep learning architecture for predicting metabolic pathway classes based on chemical compound structures using a hybrid approach of graph convolutional networks and random forest classifiers. The proposed method achieves a prediction accuracy of 95.16%, significantly outperforming existing methods, and also extends to multi-label classification with an accuracy of 97.61%. The framework automatically extracts relevant molecular shape features from SMILES representations, providing insi

Author

Anand Srinivasan

Language

EN