A new method for binary classification of proteins with Machine Learning

Abstract

In this work we set out to find a method to classify protein structures using a Deep Learning methodology. Our Artificial Intelligence has been trained to recognize complex biomolecule structures extrapolated from the Protein Data Bank (PDB) database and reprocessed as images; for this purpose various tests have been conducted with pre-trained Convolutional Neural Networks, such as InceptionResNetV2 or InceptionV3, in order to extract significant features from these images and correctly classify the molecule. A comparative analysis of the performances of the various networks will therefore be produced.

International Conference on Computational Science and Its Applications, ICCSA 2021

References in corpus (3)

• Binary classification of proteins by a Machine Learning approach
• Skin Cancer Classification using Inception Network and Transfer Learning
• Towards a learning-based performance modeling for accelerating Deep Neural Networks

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