mlsanityData to 7 Oct 2026

ApisTox: a new benchmark dataset for the classification of small molecules toxicity on honey bees

arXiv 2404.16196 ↗First posted 24 Apr 2024q-bio.QM cs.AI cs.LGcited by 6

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Abstract (arXiv)

The global decline in bee populations poses significant risks to agriculture, biodiversity, and environmental stability. To bridge the gap in existing data, we introduce ApisTox, a comprehensive dataset focusing on the toxicity of pesticides to honey bees (Apis mellifera). This dataset combines and leverages data from existing sources such as ECOTOX and PPDB, providing an extensive, consistent, and curated collection that surpasses the previous datasets. ApisTox incorporates a wide array of data, including toxicity levels for chemicals, details such as time of their publication in literature, and identifiers linking them to external chemical databases. This dataset may serve as an important tool for environmental and agricultural research, but also can support the development of policies and practices aimed at minimizing harm to bee populations. Finally, ApisTox offers a unique resource for benchmarking molecular property prediction methods on agrochemical compounds, facilitating advancements in both environmental science and cheminformatics. This makes it a valuable tool for both academic research and practical applications in bee conservation.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 2 of its 78 references that are in the map. First posted on arXiv 24 Apr 2024.

Builds on

2 of 78 references.

References · 2

  1. 2017MoleculeNet: A Benchmark for Molecular Machine Learningcited by 1,037
  2. 2021Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Developmentcited by 258

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 3; 2026: 2.

6 papers.