Lyudmila Shulga

The paper integrates transcriptomic, morphological, and electrophysiological data to define neuron types in mouse visual cortex and predict their projection targets.

This study shows that cell type-specific AADC expression in Parkinson's disease models reduces motor deficits and dyskinesia more effectively than broad targeting.

The paper creates a cross-species spinal cord cell type atlas integrating data from mouse, macaque, and human, identifying conserved and species-specific features.

The paper identifies enhancers for spinal motor neurons and develops AAV vectors to target these cells in rodents and macaques, enabling functional studies and potential therapeutic applications.

The paper introduces MerQuaCo, an open-source tool to automatically detect and quantify imperfections in spatial transcriptomics data, improving quality assessment.

The paper identifies cell-type-specific molecular signatures of aging in a brain-wide transcriptomic atlas of mice, revealing key changes in non-neuronal cells and specific regions like the hypothalamic third ventricle.