Omics-(based) Predictive Platform (OPP)
 

The Omics-based Predictive Platform (OPP) is a secure, standardized, and reproducible web-based environment designed to facilitate the use of machine learning (ML) and deep learning (DL) models trained on high-dimensional omics data - specifically DNA methylation profiles. OPP supports data preprocessing, quality control, and model inference through automated pipelines. 

Why OPP?

Modern molecular diagnostics increasingly rely on omics technologies, which generate vast amounts of data that surpass the limits of manual analysis. OPP bridges the gap between omics data complexity and clinical applicability by providing:

• Ready-to-use, well-calibrated predictive models.

• Standardized pipelines for data processing.

• Anomaly detection to assess prediction reliability.

• Open access to models and results within a secure, scalable environment.

Explore the Platform:

• 📚 Models Registry
  Access a catalog of available ML/DL models embedded on OPP, including metadata, documentation, and performance metrics.

• 🧠 CNS Tumor Classifier Exemplary Report
  Exemplary report generated using CNS Tumor Classifier, supporting 59 CNS tumor types based on DNA methylation signatures, trained and validated on state-of-the-art reference datasets.

• 🧬PanCancer Classifier Exemplary Report
  Exemplary report generated using PanCancer Classifier, supporting 54 tumor types based on DNA methylation signatures, tested and validated using over 5 000 methylomics profiles.

How to cite:

Bińkowski, J., Wojdacz, T.K. DNA methylation biomarkers-based pan-cancer classifier: predictive modeling for cancer classification. Genome Med 18, 66 (2026). https://doi.org/10.1186/s13073-026-01650-w