Three dimensional protein structures determine the function of a protein within a cell. Classification of 3D structure of proteins is therefore crucial to inferring protein functional information as well as the evolution of interactions between proteins. In this paper we propose to employ a recently presented structural representation of the proteins and exploit the learning capabilities of the graph neural network model to perform the classification task.

A Supervised Approach to 3D Structural Classification of Proteins

Sanniti di Baja G
2013

Abstract

Three dimensional protein structures determine the function of a protein within a cell. Classification of 3D structure of proteins is therefore crucial to inferring protein functional information as well as the evolution of interactions between proteins. In this paper we propose to employ a recently presented structural representation of the proteins and exploit the learning capabilities of the graph neural network model to perform the classification task.
2013
Istituto di Scienze Applicate e Sistemi Intelligenti "Eduardo Caianiello" - ISASI
978-3-642-41189-2
Concavity Tree
Graph Neural Network
Structural Classification of Proteins
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/215264
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