Introduction
Allen Human Brain Atlas is an important component in the neurobiology of neurodegenerative diseases. This page provides detailed information about its structure, function, and role in disease processes.
Overview
Mermaid diagram (expand to render)
The Allen Human Brain Atlas is a comprehensive map of gene expression across the human brain, produced by the [Allen Institute for Brain Science](/institutions/allen-institute). The atlas is particularly valuable for [Alzheimer's disease](/diseases/alzheimers-disease) and [Parkinson's disease](/diseases/parkinsons-disease) research, providing gene expression data that helps identify [vulnerable neuronal populations](/cell-types/dopaminergic-neurons), [molecular pathways](/mechanisms/neuronal-death), and [therapeutic targets](/therapeutics/donepezil). The ability to compare gene expression across brain regions enables researchers to identify region-specific vulnerabilities in neurodegenerative diseases.](/institutions/allen-institute) [@fromer2016]. This atlas provides unprecedented insight into the molecular organization of the human brain and how it differs from model organisms [@psychencode2019]. [@fromer2016]
Background
The study of Allen Human Brain Atlas has evolved significantly over the past decades. Research in this area has revealed important insights into the underlying mechanisms of neurodegeneration and continues to drive therapeutic development. [@gandal2018]
Historical context and key discoveries in this field have shaped our current understanding and will continue to guide future research directions. [@allen]
Key Datasets [@gandal2018]
The Allen Human Brain Atlas comprises multiple interconnected datasets that together provide a comprehensive picture of human brain transcriptomics:
Main Datasets
The atlas is part of a broader suite of brain atlases available through the Allen Institute. [@hawrylycz2012]
1. Adult Human Brain Transcriptome
- Gene expression data for >20,000 protein-coding genes across >300 brain regions including the [cortex](/brain-regions/cerebral-cortex), [hippocampus](/brain-regions/hippocampus), and [basal ganglia](/brain-regions/basal-ganglia)
- Samples from multiple donors (typically 6+ donors) for each brain region
- High-quality RNA sequencing (RNA-seq) with detailed metadata
- Whole genome microarray data for ~500,000 transcripts providing complementary coverage
2. Targeted Microarray Dataset
- Detailed expression data for ~1,000 genes with known importance in brain function
- Higher sensitivity for low-abundance transcripts
- Includes neuropathology-associated genes and candidate therapeutic targets
- Covers all major [neurotransmitter systems](/mechanisms/neurotransmitter-signaling) and [neuronal markers](/cell-types/cortical-neurons-alzheimers)
3. Connectivity Atlas
- Anatomical connectivity data from tract-tracing studies
- Diffusion tensor imaging (DTI) for white matter tract mapping
- Integration of structural and functional connectivity patterns
- Links gene expression to brain network organization
4. Single-Cell Genomics Integration
- Compatible with single-nucleus RNA-seq datasets
- Cell type-specific expression reference for deconvolution
- Supports spatial transcriptomics interpretation
- Enables cell-type specific analysis of disease-relevant genes
Brain Region Sampling
The atlas includes comprehensive coverage of: [@miller2014]
- Cerebral cortex (see also: cortical layers) (all 6 layers)
- Subcortical structures (hippocampus, amygdala, basal ganglia)
- Thalamus and hypothalamus
- Cerebellum (including deep nuclei)
- Brainstem (midbrain, pons, medulla)
- White matter regions
Donor Demographics
The Allen Human Brain Atlas is built on tissue from carefully characterized adult human brain donors. Understanding donor demographics is crucial for interpreting gene expression data and ensuring representation across populations.
Donor Selection Criteria
All donors met stringent inclusion criteria to ensure high-quality, neurologically normal brain tissue:
- Age: 24-57 years (mean ~42 years), spanning young adult to middle-aged donors
- Sex: Both male and female donors (typically 2-4 donors of each sex per region)
- Clinical History: Detailed neurological and psychiatric history screening
- Post-mortem Interval (PMI): Limited to 2-24 hours to preserve RNA integrity
- RNA Integrity Number (RIN): All samples required RIN >7.0 for inclusion
Demographic Distribution
- Sex Distribution: Balanced representation of male and female donors
- Ancestry: Primarily of European ancestry, with efforts to increase diversity in newer cohorts
- Clinical Characterization: Comprehensive neuropathological examination to exclude neurodegenerative changes
- Cause of Death: Primarily sudden cardiac death or accident, minimizing disease-related changes
Sample Quality Metrics
Each donor provides:
- Complete medical history review
- Toxicological screening
- Neuropathological assessment
- Standardized brain region dissection
- Rapid tissue processing and flash freezing
This rigorous characterization ensures that gene expression patterns reflect normal brain biology rather than disease-related artifacts.
Data Components
This atlas complements other brain mapping technologies and neuroscience datasets. [@markenscoffpapadimitriou2014]
| Component | Description | Applications | [@allena]
|-----------|-------------|--------------|
| RNA-seq | Whole transcriptome for each sample | Gene expression analysis |
| Microarray | Complementary gene expression data | Historical comparison |
| Donor Metadata | Age, sex, clinical information | Demographic studies |
| Anatomical Ontology | Standardized brain region terms | Data integration |
Research Applications [@allen]
The Allen Human Brain Atlas enables research in:
Comparative Neuroscience - Understanding human-specific brain features
Neurodegenerative Disease - Gene expression changes in AD, PD, ALS
Psychiatric Research - Molecular basis of schizophrenia, depression
Brain Development - Comparison with developmental data (BrainSpan)
Drug Discovery - Target validation and brain penetrationScientific Impact [@hawrylycz2012]
The Allen Human Brain Atlas has transformed our understanding of the human brain and become one of the most cited resources in neuroscience:
Citation Metrics and Community Adoption
Since its initial release in 2012, the atlas has been referenced in over 5,000 peer-reviewed publications, making it one of the most widely used neuroscience resources globally. The atlas has enabled:
- Standardization of brain region terminology across institutions
- Development of new computational methods for transcriptomic analysis
- Cross-validation of findings across independent studies
Transcriptomic Cartography [@miller2014]
The atlas provides:
- The first comprehensive genome-wide map of gene expression in the adult human brain
- Cell-type specific expression data across cortical and subcortical regions
- Insights into the molecular architecture of the human cerebral cortex
- Novel classification of brain regions based on molecular profiles
Disease Research [@markenscoffpapadimitriou2014]
Researchers use this resource to:
- Identify genes associated with neurological and psychiatric disorders
- Understand molecular changes in Alzheimer's, Parkinson's, and other neurodegenerative diseases
- Discover novel therapeutic targets based on region-specific expression patterns
- Compare molecular signatures between healthy and diseased brains
- Validate findings from GWAS studies in brain-relevant tissue
Key Disease Applications
- Alzheimer's Disease: Characterizing molecular changes in hippocampus and prefrontal cortex
- Parkinson's Disease: Mapping dopaminergic neuron vulnerability patterns
- Amyotrophic Lateral Sclerosis (ALS): Identifying motor neuron-specific expression
- Schizophrenia: Investigating layer-specific cortical dysregulation
- Major Depressive Disorder: Profiling mood-related brain regions
Brain Evolution Studies [@allena]
The atlas enables:
- Comparative analysis between human and mouse brain transcriptomes
- Identification of human-specific gene expression patterns
- Understanding of what makes the human brain unique among mammals
- Insights into expanded cortical regions in human brain
Integration with Other Datasets
The Allen Human Brain Atlas integrates with:
- BrainSpan Atlas - Developmental transcriptome data from prenatal to adult stages
- Allen Mouse Brain Atlas - For cross-species comparisons
- Allen Brain Cell (ABC) Atlas - Cell type-specific data
- UK Biobank - For linking genetic variation to brain structure and function
Data Access
The Allen Human Brain Atlas provides multiple access points for researchers:
Primary Web Interface
- Main Atlas: [human.brain-map.org](https://human.brain-map.org)
- Interactive gene expression heatmaps
- Anatomical visualization tools
- Sample metadata browser
- differential expression analysis tools
Application Programming Interface (API)
The Allen Institute provides a comprehensive REST API for programmatic access:
- Data API: Query gene expression by region, donor, or gene
- Metadata API: Access sample information, donor demographics, anatomical ontology
- Image API: Retrieve histological images and reference atlases
- Bulk Download: Large-scale data exports for computational analysis
- Rate-limited to ensure fair access; bulk data available via AWS S3
Download Options
- Full Dataset Downloads: Complete transcriptome matrices
- Custom Downloads: Filtered subsets by region, gene, or donor
- Pre-computed Analyses: Differential expression results, co-expression networks
- Reference Files: Brain region ontology, sample metadata, normalization parameters
Expression Search
The atlas provides powerful search capabilities for exploring gene expression patterns:
Search Parameters
- Search for gene expression by:
- Gene name or symbol: Entrez gene ID, official gene symbols, aliases
- Anatomical region: Hierarchical ontology from broad (cortex) to specific (CA1 hippocampus)
- Expression level: Filter by minimum/maximum expression thresholds
- Donor characteristics: Age range, sex, brain hemisphere
- Gene ontology: Filter by molecular function, biological process
- Pathway membership: KEGG, Reactome pathway associations
- Gene Detail Page: Comprehensive expression summary for each gene
- Heatmap Viewer: Visual representation of expression across all sampled regions
- Correlate Genes: Find genes with similar expression patterns
- Differential Expression: Compare expression between brain regions or donor groups
- Basket Search: Upload multiple genes for batch analysis
Advanced Features
- Co-expression Analysis: Identify genes with coordinated expression patterns
- Cell Type Enrichment: Estimate cell type composition from bulk data
- Cross-dataset Comparison: Compare with Mouse Brain Atlas, BrainSpan
- API Access: Programmatic queries for high-throughput analysis
Relationship to Other Resources
- Allen Mouse Brain Atlas - Mouse brain for comparison
- BrainSpan Atlas - Human developmental data
- SEA-AD - Alzheimer's disease cell atlas
- Allen Brain Cell (ABC) Atlas-atlas)-atlas)-atlas)-atlas)-atlas)-atlas)-atlas)-atlas)-atlas)-atlas)-atlas)-atlas)-atlas)-atlas)-atlas)-atlas)-atlas)-atlas)-atlas)-atlas) - Cell type-specific data
Technical Details
- RNA-seq: Illumina HiSeq, paired-end reads
- Quality Control: Rigorous QC for all samples
- Normalization: Multiple normalization methods available
- Metadata: Comprehensive donor and sample information
Significance for Human Neuroscience
The Allen Human Brain Atlas provides critical insights into the molecular basis of human brain function and disease. Unlike mouse models, the human brain has unique features including expanded cortical regions, specialized neuronal types, and distinct patterns of connectivity.
Species-Specific Features
The atlas reveals human-specific gene expression patterns:
- Expanded expression of certain neuronal markers
- Unique patterns in cortical layer organization
- Species-specific isoforms and splice variants
- Distinctive glial cell type distributions
Disease Research Applications
Neurodegenerative Diseases
- Alzheimer's Disease: Identifying vulnerable neuron populations
- Parkinson's Disease: Understanding dopaminergic neuron function
- ALS: Characterizing motor neuron vulnerability
- FTD: Studying frontotemporal degeneration patterns
Psychiatric Disorders
The Allen Human Brain Atlas has become an essential resource for investigating the molecular basis of psychiatric disorders, providing normative gene expression data across brain regions that can be compared with postmortem brain tissue from individuals with psychiatric conditions.
Schizophrenia Research
The atlas has been instrumental in schizophrenia research, enabling comparison between gene expression patterns in patients and healthy controls. Studies have utilized the atlas to identify region-specific dysregulation of GABAergic and glutamatergic signaling genes in the prefrontal cortex and hippocampus. The normal developmental trajectory data from the atlas serves as a critical reference for understanding how schizophrenia-associated changes diverge from typical brain maturation.
Depression and Mood Disorders
Gene expression data from the Allen Human Brain Atlas has informed understanding of major depressive disorder and bipolar disorder through comparison with patient brain tissue. Researchers have identified altered expression of neuropeptide systems, hypothalamic-pituitary-adrenal (HPA) axis regulators, and inflammatory response genes in mood disorder patients.
Autism Spectrum Disorder
The atlas enables investigation of autism spectrum disorder (ASD) by providing baseline gene expression across critical developmental periods. Studies have examined synaptic plasticity genes, chromatin remodeling factors, and cell adhesion molecules that are implicated in ASD pathophysiology.
Key Findings
Key psychiatric disorder research using the atlas includes:
- GABAergic dysfunction: Reduced expression of GAD1 and SLC32A1 in prefrontal cortex
- Synaptic gene alterations: Dysregulation of NLGN1, NRXN1, and SHANK family genes
- Immune-related changes: Altered expression of complement system components and microglia markers
- Neurodevelopmental timing: Abnormal patterns of synaptic formation and pruning genes
References
[Human Brain Transcriptome project - Schizophrenia](https://pubmed.ncbi.nlm.nih.gov/23840452/)
[Gene expression in depression](https://pubmed.ncbi.nlm.nih.gov/29293519/)
[Autism brain transcriptomics](https://pubmed.ncbi.nlm.nih.gov/25789630/)
[PsychENCODE consortium](https://pubmed.ncbi.nlm.nih.gov/29142224/)Schizophrenia Research
The atlas has been extensively used to investigate gene expression alterations in schizophrenia, particularly in the prefrontal cortex (PFC) and anterior cingulate cortex (ACC). Studies have identified dysregulation of genes involved in synaptic transmission, GABAergic signaling, and mitochondrial function [1](https://pubmed.ncbi.nlm.nih.gov/20673236/). The PsychENCODE consortium has leveraged this resource to identify co-expression modules enriched for schizophrenia risk genes, revealing tissue-specific patterns of dysfunction in the dorsolateral prefrontal cortex [2](https://pubmed.ncbi.nlm.nih.gov/29483667/).
Key findings include:
- Reduced expression of synaptic protein genes (SNAP25, SYT1, SYP)
- Alterations in GABAergic interneuron markers (GAD1, PVALB, SST)
- Dysregulation of immune-related genes in certain cohorts
Major Depressive Disorder
Gene expression studies in depression using the Allen Human Brain Atlas have focused on mood-related regions including the amygdala, hippocampus, and prefrontal cortex. Research has identified alterations in genes involved in hypothalamic-pituitary-adrenal (HPA) axis regulation, neuroplasticity, and inflammation [3](https://pubmed.ncbi.nlm.nih.gov/22071412/).
Notable findings include:
- Elevated expression of stress-responsive genes in the prefrontal cortex
- Altered circadian rhythm gene expression in the amygdala
- Changes in neurotrophic factor signaling (BDNF, NTRK2)
Autism Spectrum Disorder
The atlas has been used to characterize developmental gene expression patterns relevant to autism, particularly in the frontal cortex and temporal lobe. Studies have examined genes implicated in synaptic function, chromatin remodeling, and neuronal development [4](https://pubmed.ncbi.nlm.nih.gov/23999550/).
Key research directions include:
- Temporal analysis of cortical development (prenatal to adult)
- Cell type-specific expression patterns
- Comparison with autism risk genes from genetic studies
Future Directions
Integration of single-cell RNA-seq data with the Allen Human Brain Atlas is enabling cell type-specific analyses in psychiatric disorders. The PsychENCODE and Brain Initiative cell census projects are providing unprecedented resolution into cell-type composition of the human brain.
Single-Cell Resolution
The atlas is being integrated with single-nucleus RNA-seq (snRNA-seq) datasets to provide cell-type specific expression references:
- Cell Type Decomposition: Using atlas data to deconvolve bulk tissue expression into cell type contributions
- Neuronal Subtypes: Characterizing expression patterns in specific GABAergic and glutamatergic neuron subtypes
- Glial Cell Populations: Detailed mapping of astrocytes, microglia, and oligodendrocyte gene expression
Multi-Omics Integration
Future iterations will incorporate additional omics layers:
- Epigenomic Data: ATAC-seq and ChIP-seq for chromatin accessibility and TF binding
- Proteomics: Mass spectrometry-based protein expression mapping
- Metabolomics: Metabolic profiling across brain regions
BrainSpan Developmental Data
Integration with the BrainSpan atlas enables developmental trajectory analysis:
- Prenatal to Adult Trajectories: Gene expression changes across the lifespan
- Developmental Disorders: Understanding when during development psychiatric risk genes are expressed
- Critical Periods: Identifying windows of vulnerability for different brain regions
Aging and Disease Cohorts
Expansion to include diseased and aged brains:
- Alzheimer's Disease: Gene expression changes in AD-affected brains
- Parkinson's Disease: Lewy body disease progression markers
- Aging Consortium: Longitudinal aging cohorts to capture age-related changes
Advanced computational tools are being developed:
- Spatial Transcriptomics: Integrating spatially-resolved gene expression with anatomical atlases
- Interactive Visualizations: Web-based tools for exploring gene expression patterns
- API Access: Programmatic access for custom analyses and integration with other resources
Single-Cell Resolution
The atlas is being integrated with single-cell and single-nucleus RNA-seq datasets to create a cell-type-resolved model of the human brain transcriptome. This integration enables identification of cell-type-specific expression patterns for neurological and psychiatric disease genes, revealing previously obscured cellular vulnerabilities. The Human Cell Atlas project provides complementary data that enhances interpretation of brain cell-type specificity [2](https://pubmed.ncbi.nlm.nih.gov/32485749/).
Multi-Omics Integration
Future versions of the atlas will incorporate epigenomic data (ATAC-seq, ChIP-seq), proteomic data, and spatial transcriptomics to provide a more complete picture of gene regulation and function. Integration with GWAS summary statistics enables identification of cell types and brain regions implicated in psychiatric and neurological disorders through Mendelian randomization. The PsychENCODE consortium has produced multi-omic data from brain tissue that is being integrated with the Allen Atlas [3](https://pubmed.ncbi.nlm.nih.gov/31302604/).
BrainSpan Developmental Data
The BrainSpan atlas of the developing human brain provides temporal resolution across prenatal and postnatal development, enabling analysis of developmental trajectories of disease risk genes. Comparison between adult and developmental transcriptomes reveals critical periods for psychiatric disorder risk. Integration with the Allen Adult Atlas enables cross developmental stage analyses [4](https://pubmed.ncbi.nlm.nih.gov/23925245/).
Aging and Disease Cohorts
Expansion of the atlas to include more aged individuals and those with neurodegenerative diseases will enhance understanding of age-related molecular changes. The religious orders study and rush memory and aging project provide tissue with extensive clinical characterization. These additions will enable better comparison between normal aging and Alzheimer's disease progression.
New web-based platforms are being developed to facilitate integration of atlas data with user-provided datasets. These platforms enable researchers to upload their own expression data and compare against the atlas reference, identify similar brain regions or cell types, and generate hypotheses. The Allen Brain Atlas API provides programmatic access for computational analyses [5](https://pubmed.ncbi.nlm.nih.gov/22887059/).
Data Quality and Validation
Quality Control Pipeline
RNA Quality Assessment: All samples screened for RNA integrity
Technical Replicates: Multiple samples per region for validation
Biological Replicates: Multiple donors to account for variation
Cross-Platform Validation: RNA-seq validated against microarrayStandardization
The Allen Human Brain Atlas employs rigorous standardization protocols to ensure data quality, reproducibility, and comparability across samples and studies.
Sample Preparation Quality Control
All tissue samples undergo stringent quality control to ensure molecular integrity:
- Post-mortem Interval (PMI) Control: Brain tissue is collected with PMI typically under 24 hours to minimize RNA degradation
- RNA Integrity Number (RIN): Samples require RIN >7.0 for inclusion, ensuring high-quality RNA for expression analysis
- Neuropathological Assessment: Detailed postmortem examination rules out neurodegenerative changes or significant pathology
- Demographic Documentation: Complete donor metadata including age, sex, cause of death, and medical history
Anatomical Sampling Protocols
Standardized anatomical sampling ensures consistent coverage:
- Brodmann Area Mapping: Precise anatomical localization using histological staining and established neuroanatomical boundaries
- Regional Dissection: Systematic dissection following standardized templates for each brain region
- Sample Quantity: Multiple tissue blocks per region to capture local heterogeneity
- Left/Right Hemisphere: Balanced sampling from both hemispheres when available
Data Processing Pipeline
The atlas employs consistent computational methods:
- RNA Extraction: Standardized RNA extraction protocols using commercial kits
- Sequencing/Array Platforms: Affymetrix GeneChip arrays for microarray data; RNA-seq for newer releases
- Normalization: Robust multichip averaging (RMA) for microarrays; TPM/FPKM normalization for RNA-seq
- Quality Metrics: Comprehensive QC including sample correlation, PCA, and outlier detection
Each sample includes extensive metadata:
- Donor demographics and clinical history
- Tissue collection details and processing times
- Anatomical coordinates and regional annotations
- RNA quality metrics and processing batch information
- Full provenance tracking for reproducibility
Sample Preparation Quality Control
All brain tissue samples undergo stringent quality control before inclusion in the atlas. Samples are evaluated for RNA integrity number (RIN), with only samples exceeding RIN > 7 included in the transcriptome analysis. Neuropathological examination confirms absence of significant comorbid pathology. Tissue pH is measured to ensure adequate preservation, with pH 6.0-7.0 as the acceptable range. Donor demographics, including age, sex, race, and postmortem interval (PMI), are documented to enable appropriate statistical control in comparative analyses [1](https://pubmed.ncbi.nlm.nih.gov/22887059/).
Anatomical Sampling Protocols
Standardized sampling protocols ensure consistent anatomical coverage across all brains. The brain is divided into regions according to a validated atlas template (typically based on the Dartmouth or UCLA parcellation schemes). Each region is sampled from standardized coordinates to minimize within-region variation. A minimum of three tissue samples per region is collected to capture regional heterogeneity. Tissue blocks are sectioned at consistent thicknesses (e.g., 100 μm for RNA isolation) to standardize RNA yield.
Data Processing Pipeline
Raw expression data (RNA-seq and microarray) undergo unified processing through the RPKM/FPKM normalization pipeline. Batch effects are corrected using ComBat or similar algorithms. Quality metrics assessed include: average read depth (>50 million reads per sample), mapping rate (>80%), and gene detection rate (>15,000 expressed genes). Expression values are log2-transformed for downstream analyses. The BrainSpan transcriptome data provides developmental time course data with consistent processing across age groups [2](https://pubmed.ncbi.nlm.nih.gov/23925245/).
Comprehensive metadata accompanies all samples, including: donor medical history, cause of death, toxicology findings, medication history, and cognitive assessment scores (where available). Tissue storage conditions (frozen at -80°C) and processing timeline are documented. Gene expression data is linked to corresponding histology images in the Allen Brain Atlas portal. All metadata follows the MINSE standards for brain bank data sharing [3](https://pubmed.ncbi.nlm.nih.gov/25607351/).
Integration with Single-Cell Data
The atlas is increasingly integrated with single-cell approaches:
- SEA-AD - Single-nucleus data for Alzheimer's
- Allen Brain Cell (ABC) Atlas - Cell type taxonomy
- Spatial transcriptomics data
Future Directions
Integration of single-cell RNA-seq data with the Allen Human Brain Atlas is enabling cell type-specific analyses in psychiatric disorders. The PsychENCODE and Brain Initiative cell census projects are providing unprecedented resolution into cell-type composition of the human brain.
Single-Cell Resolution
The atlas is being integrated with single-nucleus RNA-seq (snRNA-seq) datasets to provide cell-type specific expression references:
- Cell Type Decomposition: Using atlas data to deconvolve bulk tissue expression into cell type contributions
- Neuronal Subtypes: Characterizing expression patterns in specific GABAergic and glutamatergic neuron subtypes
- Glial Cell Populations: Detailed mapping of astrocytes, microglia, and oligodendrocyte gene expression
Multi-Omics Integration
Future iterations will incorporate additional omics layers:
- Epigenomic Data: ATAC-seq and ChIP-seq for chromatin accessibility and TF binding
- Proteomics: Mass spectrometry-based protein expression mapping
- Metabolomics: Metabolic profiling across brain regions
BrainSpan Developmental Data
Integration with the BrainSpan atlas enables developmental trajectory analysis:
- Prenatal to Adult Trajectories: Gene expression changes across the lifespan
- Developmental Disorders: Understanding when during development psychiatric risk genes are expressed
- Critical Periods: Identifying windows of vulnerability for different brain regions
Aging and Disease Cohorts
Expansion to include diseased and aged brains:
- Alzheimer's Disease: Gene expression changes in AD-affected brains
- Parkinson's Disease: Lewy body disease progression markers
- Aging Consortium: Longitudinal aging cohorts to capture age-related changes
Advanced computational tools are being developed:
- Spatial Transcriptomics: Integrating spatially-resolved gene expression with anatomical atlases
- Interactive Visualizations: Web-based tools for exploring gene expression patterns
- API Access: Programmatic access for custom analyses and integration with other resources
External Links
- [Allen Human Brain Atlas - Official Site](https://human.brain-map.org)
- [Allen Institute for Brain Science](/institutions/allen-institute)
- [Human Brain Transcriptome Database](https://human.brain-map.org/humanbrain)
- [Allen Institute Data Portal](https://portal.brain-map.org/)
- [BrainSpan Atlas of the Developing Human Brain](https://brainspan.org/)