Dataset featuring essential oil's chemical composition in a form of Morgan fingerprints and a binary target column describing antimicrobial activity of those oils against Salmonella entereca serovar Typhimurium

This dataset, obtained from gas chromatography analyses available in the open-access database (https://essentialoils.org/plans) with permission from Dr. Robert S. Pappas, includes chemical data from essential oils (EOs). The chemical names were converted into SMILES strings and further processed into Morgan molecular fingerprints using the RDKit library in Python, focusing on compounds with quantitative significance (>10%). The dataset comprises 171 EO samples and 682 molecular descriptors, categorized by the binary presence or absence of antibacterial activity against S. Typhimurium. It was developed to support a machine learning study as part of Maria Lagerholm's PhD research, intended for publication in the scientific journal Botanica Serbica.