Paper ID: 2111.01975

Binary classification of proteins by a Machine Learning approach

Damiano Perri, Marco Simonetti, Andrea Lombardi, Noelia Faginas-Lago, Osvaldo Gervasi

In this work we present a system based on a Deep Learning approach, by using a Convolutional Neural Network, capable of classifying protein chains of amino acids based on the protein description contained in the Protein Data Bank. Each protein is fully described in its chemical-physical-geometric properties in a file in XML format. The aim of the work is to design a prototypical Deep Learning machinery for the collection and management of a huge amount of data and to validate it through its application to the classification of a sequences of amino acids. We envisage applying the described approach to more general classification problems in biomolecules, related to structural properties and similarities.

Submitted: Nov 3, 2021