Omer Ali Bayraktar

The paper identifies a mid-gestational molecular mechanism linking cortical size and ADHD through genetic and single-cell RNA sequencing analyses.

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

The paper provides a high-resolution molecular and cellular analysis of Broca's area and motor cortex across developmental stages, identifying distinct cellular signatures and vulnerabilities to neurodevelopmental disorders.

This study uses spatial transcriptomics to map Pseudomonas aeruginosa niches in lung tissue from CF and COPD patients, revealing distinct bacterial states and host interactions linked to infection persistence.

The paper benchmarks dopaminergic stem cell models and cell therapy candidates using a human brain atlas to identify off-target populations and lineage plasticity.

Human Developmental Cell Atlas integrates ~4.6 million cells/nuclei from 4-22 post-conception weeks into 454 refined cell types and maps 114 spatial niches across 6PCW whole-embryo sections.

The paper introduces TGlow, a high-content imaging platform for single-cell phenotyping of human lymphocytes, revealing distinct morphological states and drug responses.

DISCO-seq enables 3D single-cell transcriptomics of whole tissues and organisms by combining tissue-clearing chemistry with imaging and transcriptomic profiling.

The paper presents a spatial transcriptomic atlas of autism-associated genes in the developing human brain, identifying convergence in the thalamus and germinal zones.

This study uses single-cell transcriptomics to compare in vitro and in vivo chondrocyte differentiation, identifies off-target differentiation, and improves in vitro protocols by inhibiting FOXO1.

MintFlow is a generative AI algorithm that predicts how tissue perturbations reprogram cell states in disease, revealing novel cell populations and therapeutic targets in three human conditions.

The paper identifies a spatiotemporal cancer cell trajectory in glioblastoma that explains tumor heterogeneity across regions and subclones.

This study uses single-cell multiomics to identify regulatory programs and plasticity regulators in glioblastoma, revealing MYT1L as a key repressor of malignant plasticity.

The paper introduces scCellFie, a framework to infer metabolic activities from single-cell and spatial transcriptomics data, revealing organ-specific metabolic programs and disease-associated alterations.

The paper identifies FOXO1 as a key regulator of inhibitory neuron differentiation in mouse and human cerebellar progenitors, showing its conservation and regulation by WNT signaling.

This study integrates single-cell and spatial transcriptomics with histopathology to identify cellular and molecular changes in lung alveolar damage during COVID-19 progression.

The paper maps the spatial organization of the human thymus across developmental stages using a multimodal atlas and identifies key cellular and molecular features of T cell development.

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 introduces NicheCompass, a graph deep learning method for characterizing cell niches in spatial omics data, showing improved performance in identifying and analyzing niches across multiple biological contexts.

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

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.

The paper introduces cell2fate, a model-based RNA velocity method that improves cell fate prediction by decomposing velocity solutions into modules and applying it to human brain development data.

This paper describes OME-Zarr, a cloud-optimized bioimaging file format developed through community collaboration to improve scalability and data access.

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.

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.

cell2location uses a Bayesian model to integrate single-cell and spatial transcriptomics, mapping cell types in situ across mouse brain regions and human lymph node immune compartments.

This study maps the temporal and spatial dynamics of the human endometrium using single-cell and spatial reference maps, identifying key signaling pathways regulating cell fate in vivo and in vitro.

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