Li‐Chun Lin

NEUROeSTIMator uses deep learning to estimate neuronal activation from single-cell and spatial transcriptomic data, showing robustness across species and brain regions.

This study uses spatial transcriptomics to show that sleep deprivation causes region-specific gene expression changes in the brain, with the hippocampus showing the most significant alterations.

This study uses spatial transcriptomics to analyze gene expression in a human choroidal neovascular membrane and identifies dysregulated genes and potential upstream regulators.

The paper uses single-cell genomics to identify shared and disease-specific cell states and gene regulatory networks in three dementias, revealing distinct neuroimmune mechanisms and potential therapeutic targets.

This study uses spatial transcriptomics to identify distinct gene expression signatures in hippocampal subregions during memory consolidation and shows their functional relevance.

This study identifies the gene expression changes in the human brain following electrical stimulation, revealing non-neuronal cell involvement and a conserved gene signature.