Reconcile heterogeneous evidence
Expression matrices, survival endpoints, biomarkers, and clinical variables arrive at different scales and with different missingness.
Computational biology / survival modeling
LUAD survival modeling.
A research workflow joining TCGA-LUAD expression and clinical data with survival models, regulatory signals, treatment rules, and explainable reports.
Interactive workflow
Two evidence streams, one research report.
Expression-derived risk and clinical biomarker rules remain distinct until the combined reporting layer.
Case study
Reducing complexity without hiding it
Keep risk and rules legible
Univariate Cox screening and Lasso-Cox produce a risk signature while clinical factors feed a separate R6 recommendation layer.
Generate inspectable outputs
The repository includes the TCGA workflow, survival analysis, treatment rules, regulatory-network context, and report generation.
Workflow detail
From cohort to explainable output
Prepare the cohort
Filter tumor samples and align molecular measurements with usable clinical outcomes.
Select survival signal
Use Cox screening followed by penalized Cox modeling to construct a risk score.
Apply clinical rules
Interpret biomarkers and patient factors through a separate recommendation system.
Compose the report
Present risk, clinical context, and recommendation rationale without collapsing their provenance.
Evidence boundary
Research and education, not clinical decision support.
Repository-reported cohort summaries and model outputs describe the codebase’s analysis. They do not establish clinical validity or authorize treatment decisions.