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Updated: Jun 12, 2025
Isolation and Identification of Waterborne Antibiotic-Resistant Bacteria and Molecular Characterization of their Antibiotic Resistance Genes
Published on: March 3, 2023
Antimicrobial resistance dataset for pattern recognition in machine learning application
Bukola O Atobatele1, Segun Adebayo2, Odunola O Olaniran3
1Microbiology/Pure and Applied Biology Programme, College of Agriculture, Engineering and Science, Bowen University, Iwo, Nigeria.
Abstract:
This study presents a dataset of bacterial isolates collected from abattoirs in Osun State, Nigeria, designed to support research on antimicrobial resistance (AMR). The environment plays a critical role in the development and spread of AMR, posing a growing threat to global health. This dataset aims to address challenges in antibiotic selection by enabling the prediction of effective drugs for specific bacterial infections.
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