Michael Hawrylycz

Discrete Morse Graph Construction for High-Dimensional Transcriptomic Data

This paper introduces scDMGC, a method to analyze high-dimensional transcriptomic data using topological data analysis, revealing cell-type organization and transcriptional gradients in brain datasets.

Iterative co-creation of harmonized human and non-human primate cellular and structural ontologies and 3D common coordinate frameworks for the basal ganglia

The paper describes the iterative creation of harmonized ontologies and 3D frameworks for the basal ganglia across human and non-human primates to enable cross-species comparisons of cellular and molecular data.

Multiregional single-cell profiling reveals shared and specialized cellular vulnerability in Alzheimer's disease

This study uses single-nucleus RNA-seq, ATAC-seq, and Multiome to analyze Alzheimer's disease across multiple brain regions, revealing shared and region-specific cellular vulnerabilities.

Connecting single neuron transcriptomes to the projectome in mouse visual cortex

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

A layered standards framework for integrating single-cell and spatial omics data into brain cell atlases

This paper introduces a standards framework for integrating single-cell and spatial omics data into brain cell atlases, enabling interoperable and reusable knowledge-ready resources.

A Community Standard Multispecies Cell Atlas of the Basal Ganglia

The paper presents a cross-species, multimodal atlas of the basal ganglia using single-cell transcriptomics and integrates epigenomic and spatial genomic data to enable cross-species comparisons.

MapMyCells: High-performance mapping of unlabeled cell-by-gene data to reference brain taxonomies

MapMyCells maps unlabeled single-cell datasets to reference brain taxonomies, enabling cross-study integration and reproducible cell-type annotation.

B-BIND: Biophysical Bayesian Inference forNeurodegenerative Dynamics

This paper introduces a Bayesian framework to infer continuous disease states from discrete pathological protein measurements in Alzheimer's Disease, using pseudotime to model progression.

An Integrated Single-Cell and Epigenomic Resource for Comparative Analysis of the Basal Ganglia

The paper presents an integrated single-cell and epigenomic resource for exploring basal ganglia datasets across species, enabling multi-omics and comparative analysis.

The Caudate Nucleus Exhibits Distinct Pathology and Cell Type-Specific Responses Across Alzheimer's Disease

The paper maps AD-related pathological changes in the caudate nucleus at cellular resolution, identifying distinct features and cell type-specific responses.

Continuous cell type diversification throughout the embryonic and postnatal mouse visual cortex development

The paper constructs a high-resolution transcriptomic and epigenomic atlas of the developing mouse visual cortex, revealing continuous cell type diversification across embryonic and postnatal stages.

The transcriptomic architecture of the human cerebral cortex

This study uses machine learning to define the transcriptomic architecture of the human cerebral cortex, revealing a multi-resolution organization and identifying core regions linked to higher cognitive functions.

A high-resolution transcriptomic and spatial atlas of cell types in the whole mouse brain

This paper creates a high-resolution transcriptomic and spatial cell type atlas of the whole adult mouse brain, revealing spatial organization and transcription factor codes for cell types.

Whole Human-Brain Mapping of Single Cortical Neurons for Profiling Morphological Diversity and Stereotypy

The paper maps single cortical neurons across the human brain to profile morphological diversity and stereotypy using a new tomography approach.

Neuronal Connectivity as a Determinant of Cell Types and Subtypes

The paper defines neuron connectivity types (c-types) using morphology and connectivity data, showing they better capture subtype distinctions than other features.

BigNeuron: A resource to benchmark and predict best-performing algorithms for automated reconstruction of neuronal morphology

BigNeuron benchmarks automatic neuron reconstruction algorithms using gold standard annotations and image quality metrics, showing that consensus methods outperform individual algorithms.

Brain Data Standards - A method for building data-driven cell-type ontologies

The paper introduces a data-driven method to extend cell ontologies for multi-modal single-cell omics data, focusing on the Primary Motor Cortex in humans, mice, and marmosets.

The BRAIN Initiative Cell Census Data Ecosystem: A User's Guide

The paper provides a guide to the BRAIN Initiative Cell Census Network (BICCN) data ecosystem, its tools, and resources for analyzing brain cell types across species.

Transcriptional Network Orchestrating Regional Patterning of Cortical Progenitors

The paper identifies a transcription factor network and enhancers involved in cortical regional patterning using mouse embryonic data.

Evolution of cellular diversity in primary motor cortex of human, marmoset monkey, and mouse

The paper compares cellular diversity in the primary motor cortex across human, marmoset, and mouse using single-nucleus transcriptomics and epigenomics, finding conserved cell types and species-specific adaptations.

A multimodal cell census and atlas of the mammalian primary motor cortex

The paper generates a multimodal cell census and atlas of the mammalian primary motor cortex, revealing a unified molecular genetic landscape and cross-species taxonomy of cell types.

An integrated transcriptomic and epigenomic atlas of mouse primary motor cortex cell types

The paper creates a comprehensive atlas of mouse primary motor cortex cell types using integrated transcriptomic and epigenomic data from over 600,000 samples.

Cellular Anatomy of the Mouse Primary Motor Cortex

The paper provides a detailed cellular-resolution map of the mouse primary motor cortex, defining cell types and their connectivity.

Single-cell RNA-seq uncovers shared and distinct axes of variation in dorsal LGN neurons in mice, non-human primates and humans

The paper uses single-cell RNA-seq to analyze relay neurons in the dLGN across species, finding subtle transcriptomic differences compared to morphological and functional distinctions.

A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation

This study defines a comprehensive transcriptomic cell type taxonomy of the adult mouse isocortex and hippocampal formation using single-cell RNA-sequencing.

Structural and cellular transcriptome foundations of human brain disease

The paper identifies five major transcriptional patterns of brain disease risk genes across the adult human brain and highlights species-specific differences in psychiatric and substance abuse-related diseases.

Consistent cross-modal identification of cortical neurons with coupled autoencoders

The paper develops coupled autoencoders to identify cortical neurons across modalities and finds consistent cell types in transcriptomic and electrophysiological data.

Single Cell Enhancer Activity Maps Neuronal Lineages in Embryonic Mouse Basal Ganglia

The paper uses scRNA-seq and enhancer-based labeling to map neuronal lineages in embryonic mouse basal ganglia and identifies novel lineage specification paths.

MorphoHub: A Platform for Petabyte-Scale Multi-Morphometry Generation

The paper introduces MorphoHub, a platform for generating petabyte-scale multi-morphometry data, enabling high-quality analysis of neuronal structures in whole brain datasets.

Toward an integrated classification of neuronal cell types: morphoelectric and transcriptomic characterization of individual GABAergic cortical neurons

The paper characterizes transcriptomic and physiological properties of GABAergic cortical neurons in mice, identifying 20 interneuron met-types with consistent features across modalities.