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.
A New Method for Binary Classification of Proteins with Machine Learning / Damiano Perri; Marco Simonetti; Andrea Lombardi; Noelia Faginas-Lago; Osvaldo Gervasi. - ELETTRONICO. - 12958 LNTCS:(2021), pp. 388-397. ((Intervento presentato al convegno International Conference on Computational Science and Its Applications tenutosi a Cagliari nel 13/09/2021 - 16/09/2021 [10.1007/978-3-030-87016-4_29].
A New Method for Binary Classification of Proteins with Machine Learning
Damiano Perri;Marco Simonetti
;
2021
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.File | Dimensione | Formato | |
---|---|---|---|
2111.01976.pdf
accesso aperto
Tipologia:
Versione finale referata (Postprint, Accepted manuscript)
Licenza:
Creative commons
Dimensione
558.44 kB
Formato
Adobe PDF
|
558.44 kB | Adobe PDF | Visualizza/Apri |
I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.