Top Ten Predicted Genes for Tamoxifen from HBGCN Model

A 5.5 KB Excel file containing a list of ten genes predicted to interact with the drug Tamoxifen. The data was generated by the Heterogeneous Biological Graph Convolutional Network (HBGCN) model, authored by Haoran Zhu and last updated on May 19, 2026. The model integrates multimodal biological information to predict drug-target interactions.

Use Cases

• Validating drug-target interaction predictions for Tamoxifen based on the HBGCN model's output.
• Prioritizing candidate genes for experimental follow-up in cancer research based on computational predictions.
• Benchmarking new drug-target prediction algorithms against the HBGCN model's results for Tamoxifen.

Strengths

• The dataset is small (5.5 KB), ensuring fast download and easy inspection.
• It is associated with a published computational method (HBGCN) whose source code is available for reproducibility.
• It has a clear, permissive license (CC-BY-4.0) for reuse.

Limitations

• The dataset is extremely limited in scope, containing only ten predicted genes for a single drug.
• Row count and column-level documentation are unknown, limiting assessment of data structure.
• The description metadata focuses on the model methodology rather than the specific data file's contents.

Provenance

Source

Generated by the HBGCN model, shared on figshare by author Haoran Zhu.

Collection Method

Computational prediction via a Heterogeneous Biological Graph Convolutional Network.

Freshness

Last updated 2026-05-19 17:24:36