Reproducible Python demos using synthetic data shaped like biological and chemical experiments. Each piece links to code under demos/ in the GitHub repository. Figures are checked in under each demo’s outputs/ folder.
Differential expression (toy)
Gene-level summaries across two conditions; volcano plot with Benjamini–Hochberg FDR.
Compound similarity (no RDKit)
Synthetic fingerprints and physicochemical properties; Tanimoto similarity and PCA landscape.
Dose–response / viability
Hill-style synthetic curves; fitted potency and uncertainty for prediction-style readouts.
Residue contact map
Synthetic Cα distances; binary contact map at a distance threshold.
Generative sequences (PWM + latent)
Motif sampling with strength modulated by a 2D latent vector; scores and interpolation.
Multimodal biological samples
Expression, imaging-style features, and clinical covariates; fused view with CCA.