Sarah Amalia Teichmann

The paper integrates single-cell RNA-seq datasets across the GI tract to identify epithelial metaplasia in inflammatory diseases, showing its role in inflammation through immune cell interactions.

Genes2Genes aligns single-cell trajectories using a Bayesian DP framework, revealing gene-level mismatches and highlighting differences in T cell differentiation between in vitro and in vivo states.

The paper traces the origin of four synchronous renal tumours in a child to an early embryonic MTOR mutation, showing its role in tumour development and clinical implications.

Bin2cell reconstructs cells from high-resolution Visium HD data by integrating morphology and gene expression, improving downstream analysis on mouse brain and human colorectal cancer data.

WebAtlas integrates single cell and spatial transcriptomic data into a cloud-optimised format for interactive exploration.

This study constructs a multiomic atlas of human early skeletal development using single-nuclei transcriptomics, epigenomics, and spatial transcriptomics to uncover regulatory mechanisms and cell states involved in bone and joint formation.

The paper creates a single-cell reference map of NK cells and identifies tumor-associated states predictive of patient outcomes in melanoma and osteosarcoma.

The paper introduces mvTCR, a multimodal generative model for integrating TCR and transcriptome data to improve analysis of single-cell immune profiling data.

This study identifies polybacterial intracellular co-infection in human periodontal epithelial cells, revealing its proinflammatory effects and potential role in chronic diseases.

This study develops a multi-omic reference of human cardiac development and identifies disruptions in Trisomy 21 hearts.

The paper creates a high-resolution human developing heart atlas using single-cell and spatial transcriptomics, identifies new cell types, and benchmarks in vitro models.

This study investigates how scRNA-seq data can predict the clinical success of drug targets by analyzing cell type and disease-specific expression patterns.

The paper creates a multi-scale spatial atlas of healthy human skin and basal cell carcinoma using various omics and imaging techniques, revealing cell population localization and origins.

This paper creates a human embryonic limb cell atlas using single-cell and spatial transcriptomics, identifying novel cell populations and developmental patterns.

CellHint harmonizes cell types across Human Cell Atlas datasets, revealing new cell states and providing a cross-tissue database with 3.7 million cells.

The paper identifies Th2-like malignant cells in CTCL supported by a B cell-rich microenvironment through single-cell and spatial transcriptomics analysis.

This study creates a prenatal human skin cell atlas, revealing immune cells' role in skin development and showing their impact on vascular and hair follicle formation.

spinDrop improves single-cell sequencing by reducing noise and increasing detection rates, enabling high-quality molecular atlases of mouse brain development and organogenesis.

RNA sequencing in bronchial biopsies from wheezing infants and children < 2 years shows evidence for an airway epithelial hillock-to-squamous differentiation pathway that marks the development of asthma.

This paper uses spatial transcriptomics and single-cell data to identify cellular niches in the human heart, revealing new insights into cardiac function and potential drug targets.

The paper develops GASPACHO to identify dynamic eQTLs in antiviral responses using single-cell RNA-seq, uncovering thousands of eQTLs and linking them to disease risk loci.

The paper constructs a human fetal lung cell atlas from 5-22 post conception weeks, identifying new cell states and regulators of epithelial fates.

The paper compares using cell atlases versus matched controls for identifying disease-associated cell states in scRNA-seq data, finding that combining atlas data with matched controls improves accuracy.

This study creates a spatially resolved single-cell multiomics atlas of human trophoblast differentiation in early pregnancy, revealing key regulatory programs and cell-cell communication events involved in EVT invasion and arterial transformation.

This study uses single-cell transcriptomics to identify gene regulatory networks and lineage trajectories in human fetal thymic epithelial cells, revealing interferon response pathways that distinguish thymic epithelium from other anterior foregut-derived organs.

This study creates a single-cell atlas of human liver development, identifying pathways and factors that guide hepatic cell fates and improving hepatocyte-like cell functionality.

The paper maps the multi-organ functions of the human yolk sac during early development, revealing its roles in hematopoiesis, nutrition, and oxygen regulation.

This study creates a single-cell and single-nucleus transcriptomic atlas of human skeletal muscle ageing, revealing mechanisms in muscle stem cells, myofibers, and the microenvironment.

scMoMaT integrates single-cell multi-omics data under mosaic integration using matrix tri-factorization, uncovering modality-specific biomarkers for improved cell type annotation.

The paper quantifies how chromatin context affects transcription factor binding affinities genome-wide and shows DNA accessibility is the main determinant.