<ul><li>Small molecules play a critical role in the biomedical, environmental, and agrochemical domains.</li><li>This work focuses on ApisTox, the most comprehensive dataset of experimentally validated chemical toxicity to the honey bee (Apis mellifera).</li><li>The evaluation of ApisTox using various machine learning approaches reveals that it represents a distinct chemical space.</li><li>The limited generalizability of current state-of-the-art algorithms trained solely on biomedical data highlights the need for targeted model development in the agrochemical domain.</li></ul>

Evaluating machine learning models for predicting pesticides toxicity to honey bees

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