QSAR Aquatic Toxicity: 546 Chemicals with 8 Molecular Descriptors

546 chemicals with values for 8 molecular descriptors used to predict acute aquatic toxicity towards Daphnia Magna. The dataset was developed by Davide Ballabio, Matteo Cassotti, Viviana Consonni, and Roberto Todeschini for quantitative regression QSAR modeling. It contains no missing values and is licensed under CC-BY-4.0.

Use Cases

• Predicting LC50 values for Daphnia Magna based on the eight provided molecular descriptors.
• Developing regression models for acute aquatic toxicity using topological and constitutional indices.
• Comparing the performance of different machine learning algorithms on a curated QSAR dataset.
• Studying the relationship between molecular properties like TPSA(Tot) or MLOGP and biological toxicity.

Strengths

• Contains 546 chemical records, providing a substantial sample for model development.
• Includes 8 specific molecular descriptors (e.g., TPSA(Tot), MLOGP, GATS1p) as defined in the cited research.
• Explicitly noted to have no missing values, which simplifies preprocessing.
• Has a clear, cited scientific reference (Cassotti et al., 2014) documenting its creation and methodology.

Limitations

• Row count is unknown, which may limit suitability assessment for large-scale training.
• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

OpenML, originally from research by Ballabio, Davide; Cassotti, Matteo; Consonni, Viviana; and Todeschini, Roberto.

Collection Method

Data compiled for developing quantitative regression QSAR models to predict acute aquatic toxicity.

Time Range

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Freshness

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Geography

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