Esha Madan

Identifying Context-Specific Cell-Cell Interaction Genes Without Ligand-Receptor Databases from Spatial Transcriptomics

CellNeighborEX v2 identifies context-specific cell-cell interaction genes from spatial transcriptomics data without relying on ligand-receptor databases.

SC2Spa: a deep learning based approach to map transcriptome to spatial origins at cellular resolution

SC2Spa maps single-cell RNA-seq data to spatial coordinates using deep learning, improving resolution for low-resolution spatial transcriptomics data and identifying spatially variable genes.

CellNeighborEX: Deciphering Neighbor-Dependent Gene Expression from Spatial Transcriptomics Data

CellNeighborEX identifies gene expression influenced by neighboring cells in spatial transcriptomics data, revealing new insights into cell-cell interactions in mouse embryos, brain, and liver cancer.

Neighbor-specific gene expression revealed from physically interacting cells during mouse embryonic development

The paper introduces PIC-seq to study cell-cell contact-specific gene expression during mouse embryonic development and identifies novel gene expression signatures dependent on neighboring cell types.