Sign in to view source links and access this dataset
Description
182 common targets of berberine and triple-negative breast cancer were identified through integrated network pharmacology and transcriptomic analysis. The dataset includes results from molecular docking, dynamics simulations, and in vitro experiments validating berberine's effects on cell proliferation, apoptosis, and stemness. This supplementary data, authored by Ying Zhang and shared under CC-BY-4.0, was last updated on 2026-05-28.
Use Cases
Validate predicted drug-target interactions based on the 182 common targets identified.
Analyze tumor microenvironment associations based on immune infiltration analysis results.
Correlate pathway activity changes with experimental outcomes based on p-PI3K/p-AKT and p-SRC/p-STAT3 downregulation data.
Prioritize hub genes for further study based on the list of 12 genes including SRC, STAT3, and EGFR.
Strengths
Integrates results from multiple methodologies including network pharmacology, transcriptomics, molecular docking, and in vitro experiments.
Identifies 182 common targets and 12 hub genes, providing concrete starting points for analysis.
Includes molecular docking affinity scores, such as -8.8 kcal/mol for BBR-SRC binding.
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 at 70.7 KB, indicating limited scope.
Provenance
Source
figshare, authored by Ying Zhang.
Collection Method
Integrated strategy combining network pharmacology, transcriptomic analysis (GEO, TCGA), molecular docking, dynamics simulation, and in vitro validation.
Freshness
Last updated 2026-05-28 08:14:03; freshness should be verified.