Berberine Anti-TNBC Multi-Omics Integration Data

Supplementary data from a 2026 study integrating network pharmacology, transcriptomic analysis, and experimental validation to elucidate the mechanism of berberine against triple-negative breast cancer. The dataset, authored by Ying Zhang and shared under CC-BY-4.0, includes results from target prediction, gene screening, and in vitro experiments. It is a 126.7 KB Excel file.

Use Cases

• Validate predicted drug-target interactions based on the 182 common targets of berberine and TNBC.
• Analyze hub gene expression patterns based on identified key targets like SRC, STAT3, and EGFR.
• Investigate tumor microenvironment associations based on immune infiltration analysis results.
• Correlate molecular docking affinity scores with experimental outcomes based on the reported -8.8 kcal/mol binding energy for BBR-SRC.

Strengths

• Includes results from a multi-method integrative strategy combining computational and experimental validation.
• Identifies 182 common targets and 12 hub genes, providing specific molecular candidates for follow-up.
• Data is openly shared under a permissive CC-BY-4.0 license.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is small (126.7 KB), suggesting limited scope or summary-level data.

Provenance

Source

figshare

Collection Method

Integrated analysis combining network pharmacology, GEO and TCGA data screening, WGCNA, PPI networks, single-cell sequencing, molecular docking, dynamics simulation, and in vitro cellular experiments.

Freshness

Last updated 2026-05-28 08:14:05.