Kristen R. Maynard

The paper uses spatial transcriptomics to analyze molecular differences in mood disorders and biological sex in the human prefrontal cortex, identifying sex- and disorder-specific gene expression patterns.

This study maps the spatiomolecular organization of the human habenula using multi-omic approaches, identifying molecular signatures and spatial domains linked to psychiatric disorders.

This paper develops a 3D spatial genomics framework to reconstruct the molecular and cellular organization of the human nucleus accumbens across anatomical axes.

This study creates a spatial transcriptomic atlas of the human amygdala, revealing distinct cell types and genetic risk localization across its subnuclei.

This study compares the molecular effects of prenatal nicotine exposure and maternal smoking during pregnancy on mouse brain development and adulthood, finding distinct gene expression changes in pups but not adults.

This study creates a spatiomolecular atlas of the human nucleus accumbens using spatial transcriptomics and single-nucleus RNA sequencing, revealing spatial gradients and conserved features across species.

This study identifies transcriptomic changes in rat habenula and amygdala after chronic fentanyl self-administration, linking them to human cell types and risk genes for addiction.

The paper perturbs schizophrenia risk genes in mice to identify ciliary transcriptional programs as a potential downstream mechanism of disease.

The paper integrates microglia morphology and gene expression using spatial transcriptomics and proteogenomics to identify morphology-related genes in the human brain.

The paper integrates spatial transcriptomics and single-nucleus RNA-seq data from the human dACC to define molecular profiles, spatial domains, and functional insights.

This study maps molecular and genetic signatures of schizophrenia in human prefrontal cortex across spatial scales, revealing altered BDNF-TrkB signaling and inhibitory circuit dysfunction.

The paper creates a single-cell atlas of sex-differentially expressed genes in human hypothalamus regions, revealing molecular sex differences and their links to neurodevelopmental disorders.

spaTransfer transfers cell type or spatial domain labels between single-cell and spatial transcriptomics datasets using non-negative matrix factorization and a multinomial model.

The paper provides an open-source online book for analyzing spatial transcriptomics data using Bioconductor in R, with reproducible code and datasets.

The paper investigates how APOE genotype affects gene expression in the human entorhinal cortex, identifying an oligodendrocyte subtype as a potential mediator of Alzheimer's disease risk.

The paper performs transcriptomic analysis of the human habenula and identifies molecular changes associated with schizophrenia risk and illness state.

The paper analyzes the transcriptomic landscape of the human locus coeruleus in relation to Alzheimer's disease risk factors and neuromelanin content using spatially-resolved transcriptomics.

The paper integrates single-nucleus and spatial transcriptomics data to map the molecular landscape of the human hippocampus, identifying cell types and spatial domains.

lute improves cell composition estimation in bulk RNA-seq by accounting for varying cell sizes, using simulated and real datasets to demonstrate its accuracy.

The paper benchmarks cellular deconvolution methods using a multi-assay dataset from human prefrontal cortex, finding Bisque and hspe to be the most accurate.

This study analyzes age-related changes in gene expression in the human dentate gyrus, identifying shifts in neurogenesis, maturation, and neuroinflammation across the lifespan.

This study identifies Reelin as a marker of cocaine-activated neuronal ensembles in the rat nucleus accumbens and shows its role in cocaine reward and neuronal excitability.

The paper investigates ligand-receptor interactions (LRIs) in neurological diseases and finds that 96.8% of disease-associated LRIs are interconnected, highlighting their role in disease comorbidity and potential drug targets.

The paper generates a molecular neuroanatomical map of the human prefrontal cortex using spatial transcriptomics and single nucleus RNA-sequencing, revealing novel spatial domains and cell-cell interactions linked to psychiatric disorders.

The paper introduces a data-driven method to identify Total RNA Expression Genes (TREGs) for estimating RNA abundance in heterogeneous cell types and identifies AKT3 as a top TREG in brain regions.

The paper uses spatial proteogenomics to analyze gene expression changes in Alzheimer's disease brains linked to amyloid-beta and tau pathology.

The paper identifies cell type-specific activity-regulated gene expression patterns in mouse hippocampal neurons using snRNA-seq and ECS, revealing divergent transcriptomic responses and enriched biological pathways.

The paper characterizes the molecular landscape of the human locus coeruleus using spatially-resolved transcriptomics and single-nucleus RNA-sequencing, providing a publicly accessible resource.

SUFI automates spectral unmixing of fluorescent multiplex images in mouse and postmortem human brain tissues, improving accuracy over manual methods and existing software.

Samui is a web-based tool for visualizing and annotating spatially-resolved transcriptomics data, enabling fast exploration of large images and their features.