Multi-omics Data Analysis

By integrating multi-omics data, the pipeline supports patient classification, optimal biomarker discovery, pattern detection, and feature extraction. Transformer-based models are trained and fine-tuned to learn latent representations from multiple omics layers, enhancing disease biology insights by improving cell type annotation, inferring perturbation effects, and modeling probabilistic dependencies among genes, cells, and disease indications.