Onkar Mulay

STimage predicts gene expression and classifies cell types from histopathological images, improving robustness and interpretability for cancer and disease analysis.

The paper integrates 12 spatial and single-cell technologies to analyze cellular interactions and signatures in three skin cancers, identifying key therapeutic targets and genetic associations.

This study uses spatial transcriptomics to analyze a DIPG-infiltrated brainstem, identifying invasion markers and ligand-receptor pairs involved in tumour-TME crosstalk.

The paper develops MMCCI, a computational pipeline to integrate cell-cell interaction results across samples, and applies it to uncover global and condition-specific ligand-receptor interaction patterns in aging brain and melanoma datasets.

This paper develops a spatial multi-omics platform to analyze immune responses in SARS-CoV-2-infected lung tissues, revealing macrophage infiltration and spatial heterogeneity in cytokine and interferon signaling.

The paper uses spatial transcriptomics to analyze how CDK4/6 inhibition affects tumor response in SHH medulloblastoma by mapping cellular states and spatial organization.