Small-Molecule Phenotypic Screening Data for Ferroptosis and Necrosis

Kenichi Shimada's research dataset investigates the heterogeneous cell-death programs induced by the lethal small molecule CIL56 and its related analogs. It contains results from a phenotypic suppressor screen identifying distinct sets of compounds that selectively attenuate ferroptotic or necrotic death. The data includes ligand-based target predictions used to classify suppressor compounds and prioritize candidate proteins linked to each death modality.

Use Cases

• Analyze the distinct sets of suppressor compounds identified for selectively attenuating ferroptotic or necrotic death phenotypes.
• Apply classification models to the shared ligand-based target predictions to group suppressor compounds and prioritize candidate protein targets.
• Investigate the relationship between the chemical structures of CIL56 analogs and their induction of chemically separable death phenotypes.

Strengths

• Data originates from a published research study investigating specific cell-death mechanisms (ferroptosis and necrosis).
• Includes results from a phenotypic suppressor screen, providing a layer of mechanistic validation.
• Dataset is structured in an XLSX file format, facilitating tabular analysis.

Limitations

• The dataset is small at 2.8 MB, limiting the scale of potential machine learning applications.
• Specific details on data volume (e.g., row count, column count) are not provided, making it difficult to assess scope.
• Data is focused on a specific set of small molecules (CIL56 and analogs), limiting generalizability to other compounds.

Provenance

Source

figshare, authored by Kenichi Shimada.

Collection Method

Generated from experimental phenotypic screening and subsequent suppressor classification and target prediction analysis.

Freshness

Last updated on March 24, 2026.