Chemical-Protein Interaction Annotations from BioCreative VI

Chemical-Protein interaction data identifies chemical and protein entities and classifies their likely relations, such as agonists or antagonists. The dataset was created by the bigbio team for the BioCreative VI challenge track. It was last updated on the platform in June 2025.

Use Cases

• Train named entity recognition models to identify chemical and protein entities in biomedical text.
• Develop relation classification models to predict interaction types like 'agonist' or 'antagonist' between identified entities.
• Benchmark sequence labeling and relation extraction systems against the BioCreative VI challenge standards.

Strengths

• Annotated for a specific, high-value task in biomedical NLP: chemical-protein interaction.
• Derived from the authoritative BioCreative VI challenge, ensuring a standard benchmark.

Limitations

• Specific row count, column details, and dataset size are unknown from the provided information.
• The scope is limited to the specific chemical-protein interaction task defined by the BioCreative track.

Provenance

Source

BioCreative VI Chemical-Protein interaction Track.

Collection Method

Manually annotated biomedical literature, likely for a shared task challenge.

Freshness

Last updated on the platform in June 2025, but the underlying BioCreative VI challenge data is from 2017.