Welcome to PANDORA

PANDORA is a research platform developed and maintained by aTomic Lab. It is engineered to leverage advanced statistical methodologies, many specifically designed for the analysis of high-dimensional data prevalent in biomedical research. The platform supports predictive modeling, biomarker discovery, and comprehensive OMICS data analysis, thereby contributing to novel insights in systems biology.

System overview

Data exploration and visualization:

• Inspect your datasets: Quickly understand the structure and content of your data.

• Analyze correlations: Examine how different variables relate to each other.

• Perform hierarchical clustering: Group similar samples or features.

• Reduce dimensionality and find patterns: Use techniques like PCA (Principal Component Analysis), t-SNE, and UMAP to effectively visualize and identify patterns in high-dimensional data (e.g., transcriptomics, proteomics, cytometry data).

Predictive modeling and biomarker discovery:

• Build machine learning models: The integrated SIMON toolkit helps you develop and run machine learning models more easily.

• Create models for various applications: Build models for tasks such as predicting outcomes (like treatment efficacy or patient stratification) and other classification needs.

• Identify key biomarkers: Find statistically significant biomarkers that strongly influence your model's predictions.

Model evaluation and interpretation:

• Assess model performance: Use robust tools like variable importance metrics and ROC curve analysis to evaluate how well your models are working.

• Understand model predictions: Employ advanced model interpretation methods, including Explainable AI, to gain insights into why your models make certain predictions.

• Analyze complex OMICS data: PANDORA is designed for the robust analysis of OMICS datasets, helping you achieve reliable and reproducible results.