Interpretable prediction for anticancer sensitivity of glycoside amides

Development Timeline: Selective Anticancer Logic of Glycoside Amides

/ Second supplemented edition /

📊 Interpretable Prediction Dataset:

Transparent Modeling of Anticancer Sensitivity to Glycoside Amides

The current dataset presents the exact results of our interpretable prediction model for anticancer sensitivity to glycoside amides. It is provided in *.xlsx format and includes:

• ✅ Analytical data

• ✅ Theoretical framework

• ✅ Authorial conclusions

• ✅ Full filtered dataset

• ✅ Complete raw data

All information is organized in a user-friendly structure, fully compatible with standard data export formats and ready for integration into clinical modeling, pharmaceutical analysis, or transcriptomic mapping.

🔍 Transparency and Scientific Integrity

This dataset is not a closed interpretation. It reflects our original research findings, derived from a specific theoretical and biochemical framework. We fully acknowledge that the data may be interpreted differently depending on the analytical model, clinical context, or pharmacological assumptions.

That is precisely why we have chosen to publish the exact numerical calculations—not just summaries or visualizations. This decision underscores our commitment to transparency, scientific reproducibility, and open dialogue with the broader research community.

🧠 A Platform for Collaboration

We invite clinicians, researchers, and data scientists to explore the dataset, challenge its assumptions, and build upon its structure. Whether used for comparative modeling, transcriptomic validation, or therapeutic design, the data is intended to serve as a foundation for further inquiry, not a final verdict.