Debasish Swapnesh Kumar Nayak, Saswati Mahapatra, Sweta Padma Routray, Swayamprabha Sahoo, Santanu Kumar Sahoo, Mostafa M Fouda, Narpinder Singh, Esma R Isenovic, Luca Saba, Jasjit S Suri, Tripti Swarnkar
BACKGROUND: There are several antibiotic resistance genes (ARG) for the Escherichia coli (E. coli) bacteria that cause urinary tract infections (UTI), and it is therefore important to identify these ARG. Artificial Intelligence (AI) has been used previously in the field of gene expression data, but never adopted for the detection and classification of bacterial ARG. We hypothesize, if the data is correctly conferred, right features are selected, and Deep Learning (DL) classification models are optimized, then (i) non-linear DL models would perform better than Machine Learning (ML) models, (ii) leads to higher accuracy, (iii) can identify the hub genes, and, (iv) can identify gene pathways accurately...
February 22, 2024: Frontiers in Bioscience (Landmark Edition)