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Database information

Allen Brain Map

General information

Description: The Allen Brain Atlas provides a unique online public resource integrating extensive gene expression data,connectivity data and neuroanatomical information with powerful search and viewing tools for the adult and developing brain in mouse,human and non-human primate.
Year founded: 2003
Last update: 2017
Version: v1.0
Real time : Checking...
Country/Region: United States
Data type:
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Contact information

University/Institution: Allen Institute for Brain Science
Address: 551 North 34th Street, Seattle, WA 98103, USA
City: Seattle
Province/State: WA
Country/Region: United States
Contact name (PI/Team): Susan M. Sunkin
Contact email (PI/Helpdesk):

Record metadata

Created on: 2015-06-20
Curated by:
Dong Zou [2020-01-13]
Lina Ma [2018-06-04]
Dong Zou [2018-03-08]
Mengwei Li [2016-03-31]
Mengwei Li [2016-03-28]
Mengwei Li [2015-11-23]
Mengwei Li [2015-06-26]


All databases:
24/4549 (99.494%)
4/799 (99.625%)
Gene genome and annotation:
13/1212 (99.01%)
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Neuropathological and transcriptomic characteristics of the aged brain. [PMID: 29120328]
Miller JA, Guillozet-Bongaarts A, Gibbons LE, Postupna N, Renz A, Beller AE, Sunkin SM, Ng L, Rose SE, Smith KA, Szafer A, Barber C, Bertagnolli D, Bickley K, Brouner K, Caldejon S, Chapin M, Chua ML, Coleman NM, Cudaback E, Cuhaciyan C, Dalley RA, Dee N, Desta T, Dolbeare TA, Dotson NI, Fisher M, Gaudreault N, Gee G, Gilbert TL, Goldy J, Griffin F, Habel C, Haradon Z, Hejazinia N, Hellstern LL, Horvath S, Howard K, Howard R, Johal J, Jorstad NL, Josephsen SR, Kuan CL, Lai F, Lee E, Lee F, Lemon T, Li X, Marshall DA, Melchor J, Mukherjee S, Nyhus J, Pendergraft J, Potekhina L, Rha EY, Rice S, Rosen D, Sapru A, Schantz A, Shen E, Sherfield E, Shi S, Sodt AJ, Thatra N, Tieu M, Wilson AM, Montine TJ, Larson EB, Bernard A, Crane PK, Ellenbogen RG, Keene CD, Lein E.

As more people live longer, age-related neurodegenerative diseases are an increasingly important societal health issue. Treatments targeting specific pathologies such as amyloid beta in Alzheimer's disease (AD) have not led to effective treatments, and there is increasing evidence of a disconnect between traditional pathology and cognitive abilities with advancing age, indicative of individual variation in resilience to pathology. Here, we generated a comprehensive neuropathological, molecular, and transcriptomic characterization of hippocampus and two regions cortex in 107 aged donors (median = 90) from the Adult Changes in Thought (ACT) study as a freely-available resource ( We confirm established associations between AD pathology and dementia, albeit with increased, presumably aging-related variability, and identify sets of co-expressed genes correlated with pathological tau and inflammation markers. Finally, we demonstrate a relationship between dementia and RNA quality, and find common gene signatures, highlighting the importance of properly controlling for RNA quality when studying dementia.

Elife. 2017:6() | 6 Citations (from Europe PMC, 2020-05-30)
Neuroinformatics of the Allen Mouse Brain Connectivity Atlas. [PMID: 25536338]
Kuan L, Li Y, Lau C, Feng D, Bernard A, Sunkin SM, Zeng H, Dang C, Hawrylycz M, Ng L.

The Allen Mouse Brain Connectivity Atlas is a mesoscale whole brain axonal projection atlas of the C57Bl/6J mouse brain. Anatomical trajectories throughout the brain were mapped into a common 3D space using a standardized platform to generate a comprehensive and quantitative database of inter-areal and cell-type-specific projections. This connectivity atlas has several desirable features, including brain-wide coverage, validated and versatile experimental techniques, a single standardized data format, a quantifiable and integrated neuroinformatics resource, and an open-access public online database ( Meaningful informatics data quantification and comparison is key to effective use and interpretation of connectome data. This relies on successful definition of a high fidelity atlas template and framework, mapping precision of raw data sets into the 3D reference framework, accurate signal detection and quantitative connection strength algorithms, and effective presentation in an integrated online application. Here we describe key informatics pipeline steps in the creation of the Allen Mouse Brain Connectivity Atlas and include basic application use cases.

Methods. 2015:73() | 47 Citations (from Europe PMC, 2020-05-30)
A mesoscale connectome of the mouse brain. [PMID: 24695228]
Oh SW, Harris JA, Ng L, Winslow B, Cain N, Mihalas S, Wang Q, Lau C, Kuan L, Henry AM, Mortrud MT, Ouellette B, Nguyen TN, Sorensen SA, Slaughterbeck CR, Wakeman W, Li Y, Feng D, Ho A, Nicholas E, Hirokawa KE, Bohn P, Joines KM, Peng H, Hawrylycz MJ, Phillips JW, Hohmann JG, Wohnoutka P, Gerfen CR, Koch C, Bernard A, Dang C, Jones AR, Zeng H.

Comprehensive knowledge of the brain's wiring diagram is fundamental for understanding how the nervous system processes information at both local and global scales. However, with the singular exception of the C. elegans microscale connectome, there are no complete connectivity data sets in other species. Here we report a brain-wide, cellular-level, mesoscale connectome for the mouse. The Allen Mouse Brain Connectivity Atlas uses enhanced green fluorescent protein (EGFP)-expressing adeno-associated viral vectors to trace axonal projections from defined regions and cell types, and high-throughput serial two-photon tomography to image the EGFP-labelled axons throughout the brain. This systematic and standardized approach allows spatial registration of individual experiments into a common three dimensional (3D) reference space, resulting in a whole-brain connectivity matrix. A computational model yields insights into connectional strength distribution, symmetry and other network properties. Virtual tractography illustrates 3D topography among interconnected regions. Cortico-thalamic pathway analysis demonstrates segregation and integration of parallel pathways. The Allen Mouse Brain Connectivity Atlas is a freely available, foundational resource for structural and functional investigations into the neural circuits that support behavioural and cognitive processes in health and disease.

Nature. 2014:508(7495) | 592 Citations (from Europe PMC, 2020-05-30)
Transcriptional landscape of the prenatal human brain. [PMID: 24695229]
Miller JA, Ding SL, Sunkin SM, Smith KA, Ng L, Szafer A, Ebbert A, Riley ZL, Royall JJ, Aiona K, Arnold JM, Bennet C, Bertagnolli D, Brouner K, Butler S, Caldejon S, Carey A, Cuhaciyan C, Dalley RA, Dee N, Dolbeare TA, Facer BA, Feng D, Fliss TP, Gee G, Goldy J, Gourley L, Gregor BW, Gu G, Howard RE, Jochim JM, Kuan CL, Lau C, Lee CK, Lee F, Lemon TA, Lesnar P, McMurray B, Mastan N, Mosqueda N, Naluai-Cecchini T, Ngo NK, Nyhus J, Oldre A, Olson E, Parente J, Parker PD, Parry SE, Stevens A, Pletikos M, Reding M, Roll K, Sandman D, Sarreal M, Shapouri S, Shapovalova NV, Shen EH, Sjoquist N, Slaughterbeck CR, Smith M, Sodt AJ, Williams D, Zöllei L, Fischl B, Gerstein MB, Geschwind DH, Glass IA, Hawrylycz MJ, Hevner RF, Huang H, Jones AR, Knowles JA, Levitt P, Phillips JW, Sestan N, Wohnoutka P, Dang C, Bernard A, Hohmann JG, Lein ES.

The anatomical and functional architecture of the human brain is mainly determined by prenatal transcriptional processes. We describe an anatomically comprehensive atlas of the mid-gestational human brain, including de novo reference atlases, in situ hybridization, ultra-high-resolution magnetic resonance imaging (MRI) and microarray analysis on highly discrete laser-microdissected brain regions. In developing cerebral cortex, transcriptional differences are found between different proliferative and post-mitotic layers, wherein laminar signatures reflect cellular composition and developmental processes. Cytoarchitectural differences between human and mouse have molecular correlates, including species differences in gene expression in subplate, although surprisingly we find minimal differences between the inner and outer subventricular zones even though the outer zone is expanded in humans. Both germinal and post-mitotic cortical layers exhibit fronto-temporal gradients, with particular enrichment in the frontal lobe. Finally, many neurodevelopmental disorder and human-evolution-related genes show patterned expression, potentially underlying unique features of human cortical formation. These data provide a rich, freely-accessible resource for understanding human brain development.

Nature. 2014:508(7495) | 350 Citations (from Europe PMC, 2020-05-30)
A high-resolution spatiotemporal atlas of gene expression of the developing mouse brain. [PMID: 24952961]
Thompson CL, Ng L, Menon V, Martinez S, Martinez S, Lee CK, Glattfelder K, Sunkin SM, Henry A, Lau C, Dang C, Garcia-Lopez R, Martinez-Ferre A, Pombero A, Rubenstein JLR, Wakeman WB, Hohmann J, Dee N, Sodt AJ, Young R, Smith K, Nguyen TN, Kidney J, Kuan L, Jeromin A, Kaykas A, Miller J, Page D, Orta G, Bernard A, Riley Z, Smith S, Wohnoutka P, Hawrylycz MJ, Puelles L, Jones AR.

To provide a temporal framework for the genoarchitecture of brain development, we generated in situ hybridization data for embryonic and postnatal mouse brain at seven developmental stages for ?2,100 genes, which were processed with an automated informatics pipeline and manually annotated. This resource comprises 434,946 images, seven reference atlases, an ontogenetic ontology, and tools to explore coexpression of genes across neurodevelopment. Gene sets coinciding with developmental phenomena were identified. A temporal shift in the principles governing the molecular organization of the brain was detected, with transient neuromeric, plate-based organization of the brain present at E11.5 and E13.5. Finally, these data provided a transcription factor code that discriminates brain structures and identifies the developmental age of a tissue, providing a foundation for eventual genetic manipulation or tracking of specific brain structures over development. The resource is available as the Allen Developing Mouse Brain Atlas (

Neuron. 2014:83(2) | 73 Citations (from Europe PMC, 2020-05-30)
Allen Brain Atlas: an integrated spatio-temporal portal for exploring the central nervous system. [PMID: 23193282]
Sunkin SM, Ng L, Lau C, Dolbeare T, Gilbert TL, Thompson CL, Hawrylycz M, Dang C.

The Allen Brain Atlas ( provides a unique online public resource integrating extensive gene expression data, connectivity data and neuroanatomical information with powerful search and viewing tools for the adult and developing brain in mouse, human and non-human primate. Here, we review the resources available at the Allen Brain Atlas, describing each product and data type [such as in situ hybridization (ISH) and supporting histology, microarray, RNA sequencing, reference atlases, projection mapping and magnetic resonance imaging]. In addition, standardized and unique features in the web applications are described that enable users to search and mine the various data sets. Features include both simple and sophisticated methods for gene searches, colorimetric and fluorescent ISH image viewers, graphical displays of ISH, microarray and RNA sequencing data, Brain Explorer software for 3D navigation of anatomy and gene expression, and an interactive reference atlas viewer. In addition, cross data set searches enable users to query multiple Allen Brain Atlas data sets simultaneously. All of the Allen Brain Atlas resources can be accessed through the Allen Brain Atlas data portal.

Nucleic Acids Res. 2013:41(Database issue) | 146 Citations (from Europe PMC, 2020-05-30)
An anatomically comprehensive atlas of the adult human brain transcriptome. [PMID: 22996553]
Hawrylycz MJ, Lein ES, Guillozet-Bongaarts AL, Shen EH, Ng L, Miller JA, van de Lagemaat LN, Smith KA, Ebbert A, Riley ZL, Abajian C, Beckmann CF, Bernard A, Bertagnolli D, Boe AF, Cartagena PM, Chakravarty MM, Chapin M, Chong J, Dalley RA, David Daly B, Dang C, Datta S, Dee N, Dolbeare TA, Faber V, Feng D, Fowler DR, Goldy J, Gregor BW, Haradon Z, Haynor DR, Hohmann JG, Horvath S, Howard RE, Jeromin A, Jochim JM, Kinnunen M, Lau C, Lazarz ET, Lee C, Lemon TA, Li L, Li Y, Morris JA, Overly CC, Parker PD, Parry SE, Reding M, Royall JJ, Schulkin J, Sequeira PA, Slaughterbeck CR, Smith SC, Sodt AJ, Sunkin SM, Swanson BE, Vawter MP, Williams D, Wohnoutka P, Zielke HR, Geschwind DH, Hof PR, Smith SM, Koch C, Grant SGN, Jones AR.

Neuroanatomically precise, genome-wide maps of transcript distributions are critical resources to complement genomic sequence data and to correlate functional and genetic brain architecture. Here we describe the generation and analysis of a transcriptional atlas of the adult human brain, comprising extensive histological analysis and comprehensive microarray profiling of ?900 neuroanatomically precise subdivisions in two individuals. Transcriptional regulation varies enormously by anatomical location, with different regions and their constituent cell types displaying robust molecular signatures that are highly conserved between individuals. Analysis of differential gene expression and gene co-expression relationships demonstrates that brain-wide variation strongly reflects the distributions of major cell classes such as neurons, oligodendrocytes, astrocytes and microglia. Local neighbourhood relationships between fine anatomical subdivisions are associated with discrete neuronal subtypes and genes involved with synaptic transmission. The neocortex displays a relatively homogeneous transcriptional pattern, but with distinct features associated selectively with primary sensorimotor cortices and with enriched frontal lobe expression. Notably, the spatial topography of the neocortex is strongly reflected in its molecular topography-the closer two cortical regions, the more similar their transcriptomes. This freely accessible online data resource forms a high-resolution transcriptional baseline for neurogenetic studies of normal and abnormal human brain function.

Nature. 2012:489(7416) | 677 Citations (from Europe PMC, 2020-05-30)
Divergent and nonuniform gene expression patterns in mouse brain. [PMID: 20956311]
Morris JA, Royall JJ, Bertagnolli D, Boe AF, Burnell JJ, Byrnes EJ, Copeland C, Desta T, Fischer SR, Goldy J, Glattfelder KJ, Kidney JM, Lemon T, Orta GJ, Parry SE, Pathak SD, Pearson OC, Reding M, Shapouri S, Smith KA, Soden C, Solan BM, Weller J, Takahashi JS, Overly CC, Lein ES, Hawrylycz MJ, Hohmann JG, Jones AR.

Considerable progress has been made in understanding variations in gene sequence and expression level associated with phenotype, yet how genetic diversity translates into complex phenotypic differences remains poorly understood. Here, we examine the relationship between genetic background and spatial patterns of gene expression across seven strains of mice, providing the most extensive cellular-resolution comparative analysis of gene expression in the mammalian brain to date. Using comprehensive brainwide anatomic coverage (more than 200 brain regions), we applied in situ hybridization to analyze the spatial expression patterns of 49 genes encoding well-known pharmaceutical drug targets. Remarkably, over 50% of the genes examined showed interstrain expression variation. In addition, the variability was nonuniformly distributed across strain and neuroanatomic region, suggesting certain organizing principles. First, the degree of expression variance among strains mirrors genealogic relationships. Second, expression pattern differences were concentrated in higher-order brain regions such as the cortex and hippocampus. Divergence in gene expression patterns across the brain could contribute significantly to variations in behavior and responses to neuroactive drugs in laboratory mouse strains and may help to explain individual differences in human responsiveness to neuroactive drugs.

Proc Natl Acad Sci U S A. 2010:107(44) | 16 Citations (from Europe PMC, 2020-05-30)
Molecular and anatomical signatures of sleep deprivation in the mouse brain. [PMID: 21088695]
Thompson CL, Wisor JP, Lee CK, Pathak SD, Gerashchenko D, Smith KA, Fischer SR, Kuan CL, Sunkin SM, Ng LL, Lau C, Hawrylycz M, Jones AR, Kilduff TS, Lein ES.

Sleep deprivation (SD) leads to a suite of cognitive and behavioral impairments, and yet the molecular consequences of SD in the brain are poorly understood. Using a systematic immediate-early gene (IEG) mapping to detect neuronal activation, the consequences of SD were mapped primarily to forebrain regions. SD was found to both induce and suppress IEG expression (and thus neuronal activity) in subregions of neocortex, striatum, and other brain regions. Laser microdissection and cDNA microarrays were used to identify the molecular consequences of SD in seven brain regions. In situ hybridization (ISH) for 222 genes selected from the microarray data and other sources confirmed that robust molecular changes were largely restricted to the forebrain. Analysis of the ISH data for 222 genes (publicly accessible at provided a molecular and anatomic signature of the effects of SD on the brain. The suprachiasmatic nucleus (SCN) and the neocortex exhibited differential regulation of the same genes, such that in the SCN genes exhibited time-of-day effects while in the neocortex, genes exhibited only SD and waking (W) effects. In the neocortex, SD activated gene expression in areal-, layer-, and cell type-specific manner. In the forebrain, SD preferentially activated excitatory neurons, as demonstrated by double-labeling, except for striatum which consists primarily of inhibitory neurons. These data provide a characterization of the anatomical and cell type-specific signatures of SD on neuronal activity and gene expression that may account for the associated cognitive and behavioral effects.

Front Neurosci. 2010:4() | 30 Citations (from Europe PMC, 2020-05-30)
Genome-wide atlas of gene expression in the adult mouse brain. [PMID: 17151600]
Lein ES, Hawrylycz MJ, Ao N, Ayres M, Bensinger A, Bernard A, Boe AF, Boguski MS, Brockway KS, Byrnes EJ, Chen L, Chen L, Chen TM, Chin MC, Chong J, Crook BE, Czaplinska A, Dang CN, Datta S, Dee NR, Desaki AL, Desta T, Diep E, Dolbeare TA, Donelan MJ, Dong HW, Dougherty JG, Duncan BJ, Ebbert AJ, Eichele G, Estin LK, Faber C, Facer BA, Fields R, Fischer SR, Fliss TP, Frensley C, Gates SN, Glattfelder KJ, Halverson KR, Hart MR, Hohmann JG, Howell MP, Jeung DP, Johnson RA, Karr PT, Kawal R, Kidney JM, Knapik RH, Kuan CL, Lake JH, Laramee AR, Larsen KD, Lau C, Lemon TA, Liang AJ, Liu Y, Luong LT, Michaels J, Morgan JJ, Morgan RJ, Mortrud MT, Mosqueda NF, Ng LL, Ng R, Orta GJ, Overly CC, Pak TH, Parry SE, Pathak SD, Pearson OC, Puchalski RB, Riley ZL, Rockett HR, Rowland SA, Royall JJ, Ruiz MJ, Sarno NR, Schaffnit K, Shapovalova NV, Sivisay T, Slaughterbeck CR, Smith SC, Smith KA, Smith BI, Sodt AJ, Stewart NN, Stumpf KR, Sunkin SM, Sutram M, Tam A, Teemer CD, Thaller C, Thompson CL, Varnam LR, Visel A, Whitlock RM, Wohnoutka PE, Wolkey CK, Wong VY, Wood M, Yaylaoglu MB, Young RC, Youngstrom BL, Yuan XF, Zhang B, Zwingman TA, Jones AR.

Molecular approaches to understanding the functional circuitry of the nervous system promise new insights into the relationship between genes, brain and behaviour. The cellular diversity of the brain necessitates a cellular resolution approach towards understanding the functional genomics of the nervous system. We describe here an anatomically comprehensive digital atlas containing the expression patterns of approximately 20,000 genes in the adult mouse brain. Data were generated using automated high-throughput procedures for in situ hybridization and data acquisition, and are publicly accessible online. Newly developed image-based informatics tools allow global genome-scale structural analysis and cross-correlation, as well as identification of regionally enriched genes. Unbiased fine-resolution analysis has identified highly specific cellular markers as well as extensive evidence of cellular heterogeneity not evident in classical neuroanatomical atlases. This highly standardized atlas provides an open, primary data resource for a wide variety of further studies concerning brain organization and function.

Nature. 2007:445(7124) | 2177 Citations (from Europe PMC, 2020-05-30)