Mats F. Nilsson

The paper establishes a multi-omic PDX resource linking GBM invasion phenotypes to molecular programs and therapeutic responses, identifying two invasion modes and a neurodevelopmental factor associated with tumor growth and survival.

SIMPlex generates matched spatial and single-nucleus transcriptomic profiles from the same tissue section to resolve cell states with spatial signatures in mouse and human cancer tissues.

The paper introduces miR-Space, a method for spatial miRNA profiling at single-cell resolution, revealing new miRNA distributions and cell-type associations in brain tissues.

TERRA is a foundation model for spatial transcriptomics that predicts tissue behavior under perturbation and identifies multi-scale biological insights across tissues.

COSTE embeds spatial relationships into a hierarchical metric space to reveal tissue architecture in spatial omics data, identifying spatially defined cell states and disease-associated patterns.

This paper introduces a method for targeted sequencing of expressed mutations in single cells using RNA-templated gap filling with BstFL polymerase, enabling simultaneous transcriptomic and mutation profiling.

This paper introduces a tool to detect overlapping cells and segmentation errors in 3D spatial transcriptomics data.

This study identifies tissue architecture and immune niches as key factors influencing ctDNA release in colorectal cancer by integrating spatial transcriptomics and in situ mutation detection.

This study maps spatial dynamics in early human heart development using single-cell and spatial transcriptomics, identifying cell states and novel features like cardiac fibroblasts and chromaffin cells.

This paper integrates five vertebrate single-cell multi-omic atlases to reveal a conserved cellular blueprint and dual evolutionary constraints underlying early brain conservation across vertebrates.

This study links TCR clonality in NSCLC to genetic mutations, immune phenotypes, immunotherapy response, and patient survival.

The paper generates a single-cell and spatial transcriptomic atlas of human fetal meninges and finds that meningiomas likely originate from dura lineage cells.

This paper adapts copy number variation inference to image-based spatial transcriptomics data to map malignant clones and tumor microenvironment at single-cell resolution.

The paper uses snRNA-seq and spatial transcriptomics to study oligodendroglia in Parkinson's disease, identifying disease-specific subclasses and transcriptomic changes linked to myelin integrity and cell communication.

This study evaluates the Xenium In Situ spatial transcriptomics platform using mouse brain and human breast cancer datasets, comparing it to other technologies and benchmarking analysis tools.

This study compares the development and evolution of sensory circuits in the pallium of birds, lizards, and mammals, revealing divergent developmental trajectories but functional similarity in sensory processing.

This study maps the spatial organization of the developing human lung using high-parametric protein imaging, revealing cell type composition and temporal changes across five developmental timepoints.

The paper uses snRNA-seq to identify eight interneuron classes in the human dorsal striatum, validates markers with in situ hybridization, and compares them to mouse interneurons.

This study identifies cellular and molecular mechanisms of tertiary lymphoid structure (TLS) formation in glioblastoma, showing TLS correlate with improved survival and are driven by CD4 T cells expressing lymphotoxin β.

The paper introduces an open-source method for high-throughput in-situ transcriptomics and provides a computational workflow for data analysis.

BirthSeq isolates and analyzes cells based on their birth date across vertebrate tissues, enabling temporal studies of cell fate in development.

This paper introduces a spatial multimodal analysis method that integrates histology, mass spectrometry imaging, and spatial transcriptomics to study mRNA and metabolite distributions in brain tissues.

The paper creates a developmental cell atlas of the human spinal cord using single-cell and spatial transcriptomics, revealing spatiotemporal gene regulation and novel insights into ependymoma cancer stem cells.

This study uses in situ sequencing to map oligodendrocyte lineage progression across brain and spinal cord regions in juvenile and adult mice, revealing spatial and temporal heterogeneity.

This study identifies an early wave of oligodendrogenesis in the human forebrain at PCW 8 using single-cell RNA-Seq and ATAC-Seq, supported by spatial gene expression analysis.

The paper creates a comprehensive topographic atlas of early human lung development, identifying cell states, trajectories, and interactions to understand cell heterogeneity origins.

PoSTcode improves transcript decoding from spatial transcriptomic images by reducing mislabeling and doublet signals.

The paper spatially maps human cortical cell types using in situ sequencing and single-nucleus RNA-sequencing to create a first spatial atlas of human cortical cells.

The paper creates a single-cell transcriptome atlas of mouse brain development, identifying over 1000 cell states and linking tumor cells to developmental states.

The paper uses a de novo spatial modeling approach to identify novel cell populations in the developing human heart, revealing previously unreported molecular diversity.