Naslov
Preparation of Simplified Molecular Input Line Entry System Notation Datasets for use in Convolutional Neural Networks

Autori
Baressi Šegota, Sandi ; Anđelić, Nikola ; Lorencin, Ivan ; Musulin, Jelena ; Štifanić, Daniel ; Car, Zlatan

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), ostalo

Izvornik
The 21st IEEE International Conference on BioInformatics and BioEngineering / Nenad Filipović - Kragujevac : Institute of Electrical and Electronics Engineers (IEEE), 2021

ISBN
978-86-81037-69-0

Skup
21st IEEE International Conference on BioInformatics and BioEngineering (BIBE 2021)

Mjesto i datum
Kragujevac, Srbija, 25.10.2021. - 27.10.2021

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
artificial intelligence, convolutional neural networks, data processing and transformation, machine learning, SMILES

Sažetak
Simplified Molecular Input Line Entry System (SMILES) is a type of chemical notation. The SMILES format allows the representation of chemical structures in a shape easily readable by computer programs. This allows many techniques, such as Artificial Neural Networks (ANNs) to be applied on the SMILES formatted data. One of the highest-performing ANN types is the Convolutional Neural Networks (CNNs), designed to work on images or matrix-shaped data. In this paper, the authors will present the preparation of the SMILES dataset for use by CNNs. The paper will start with a brief description of the SMILES format, followed by the explanation of the dataset transformation into an NPY matrix-based format, with an example of utilization via the application of popular CNN architectures on a transformed dataset. The proposed architecture achieves satisfactory results (AUC=0.92), with the transformation algorithm speed also proving satisfactory (0.08 seconds per data point)

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo

POVEZANOST RADA