The DOI matches its Crossref record; 57 of the 58 references it cites were found in a registry or an index.
Genome-wide atlas of gene expression in the adult mouse brain
Abstract
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.
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“In order to independently validate our findings about the spatial distribution of astrocytes (Figure S5C), we analyzed in situ hybridization images of marker genes obtained from the Allen Mouse Brain Atlas”
From Molecular Architecture of the Mouse Nervous System (2018) · cites this paper as Lein et al., 2007
In the citing paper
“Allen Brain Atlas in situ hybridization data [24] show ATF3 expression only in granular neurons of the olfactory bulb and dentate gyrus”
From Tamoxifen induces cellular stress in the nervous system by inhibiting cholesterol synthesis (2015) · cites this paper as [24]
In the citing paper
“Further in situ hybridization reveals that cerebellar Purkinje cells and neurons of the deep cerebellar nuclei express high levels of Clec16a (Allen Mouse Brain Atlas, http://mouse.brain-map.org/gene/show/50215)242526.”
From Clec16a is Critical for Autolysosome Function and Purkinje Cell Survival (2016) · cites this paper as [24]
In the citing paper
“we analyzed Nlk expression by LacZ staining and found that LacZ staining was strongest in the Purkinje cell layer (Fig.4D)”
From Polyglutamine Disease Toxicity Is Regulated by Nemo-like Kinase in Spinocerebellar Ataxia Type 1 (2013) · cites this paper as Lein et al., 2007
In the citing paper
“In animal studies (rodents and non-human primates), this is feasible through the use of comprehensive, histologically and functionally defined whole-brain areal parcellations (Bezgin et al., 2012; Lein et al., 2007; Paxinos et al., 2000; Saleem and Logothetis, 2007; Swanson, 2015; Van Essen et al., 2012).”
From Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature (2017) · cites this paper as Lein et al., 2007
In the citing paper
“ApoE expression, in both mice and humans, begins relatively late in development [46, 47].”
From ApoE, ApoE Receptors, and the Synapse in Alzheimer's Disease (2017) · cites this paper as [47]
In the citing paper
“To complement and validate the microarray data, several targeted, large-scale in situ hybridization (ISH) data sets were generated using a high-throughput ISH platform1, 8.”
From An anatomically comprehensive atlas of the adult human brain transcriptome (2012) · cites this paper as [1]
In the citing paper
“In rodents, brain- and transcriptome-wide, cellular-resolution maps of transcript distributions are widely useful resources to complement genomic sequence data1, 2, 3.”
From An anatomically comprehensive atlas of the adult human brain transcriptome (2012) · cites this paper as [1]
In the citing paper
“consistent with the percentage of genes expressed in mouse brain by ISH (80%; ref. 1) and fetal human brain by microarrays (76%; ref. 11).”
From An anatomically comprehensive atlas of the adult human brain transcriptome (2012) · cites this paper as [1]
In the citing paper
“expression in human differs from that in mouse (Fig. 5d) and rhesus monkey (Fig. 5e), where CALB1 is robustly expressed in CA1 and CA2 in addition to dentate gyrus.”
From An anatomically comprehensive atlas of the adult human brain transcriptome (2012) · cites this paper as [1]
In the citing paper
“The atlas of the mid-gestational human brain described here, part of the BrainSpan Atlas of the Developing Human Brain, builds on digital molecular brain atlasing efforts in mouse20,22,24 and adult human23 by providing transcriptome resources on prenatal specimens typically inaccessible for research.”
From Transcriptional landscape of the prenatal human brain (2014) · cites this paper as [24]
In the citing paper
“These cell-type-specific expression patterns exhibited specific anatomical localization in the developing cerebellum (Fig. 1c) 26 .”
From Single-cell isoform RNA sequencing characterizes isoforms in thousands of cerebellar cells (2018) · cites this paper as [26]
In the citing paper
“The distribution of specific markers ( Pcp4 and Slc17a7 ) captured by Stereo-seq exhibited the expected similarity to in situ hybridization (ISH) data taken from Allen Brain Atlas (ABA) (Lein et al., 2007) and clearer patterns than HDST (Vickovic et al., 2019) or Slide-seqV2-resolved (Stickels et al., 2021) expression data (Figure S1E).”
From Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays (2022) · cites this paper as Lein et al., 2007
In the citing paper
“The expression patterns of Hes1 and Hes5 are consistent with ISH images taken from ABA (Figure S7H) (Lein et al., 2007).”
From Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays (2022) · cites this paper as Lein et al., 2007
In the citing paper
“These results are in line with ISH images of the Rspo1 and Fgf15 taken from ABA (Lein et al., 2007) (Figure S7F).”
From Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays (2022) · cites this paper as Lein et al., 2007
In the citing paper
“The expression patterns of Erbb4 and Gad2 are consistent with ISH images taken from ABA (Lein et al., 2007) (Figure S6F).”
From Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays (2022) · cites this paper as Lein et al., 2007
In the citing paper
“Finally, we compared all marker genes that we highlight in this paper (those in Table 1 and all figures) to their patterns in a recent spatial transcriptomics analysis of the spinal cord28 and to the Allen29 and Gensat30 expression databases and found general concordance between these resources (Supplementary Table 4).”
From A harmonized atlas of mouse spinal cord cell types and their spatial organization (2021) · cites this paper as [29]
In the citing paper
“Initial clustering identified 106,728 neurons, of which 70.2% were localized to BNST by examination of marker expression in the Allen Brain Atlas (ABA) (Lein et al., 2007) (Figure S3B).”
From Single-Cell Multi-omic Integration Compares and Contrasts Features of Brain Cell Identity (2019) · cites this paper as Lein et al., 2007
In the citing paper
“In situ hybridization and microarray data, for example the Allen Brain Atlases (Hawrylycz et al., 2012; Lein et al., 2007), have also established that mRNA transcripts encoding these five NPPs and that many other NPPs and NP-GPCR genes are expressed differentially in many brain regions.”
From Single-cell transcriptomic evidence for dense intracortical neuropeptide networks (2019) · cites this paper as Lein et al., 2007
In the citing paper
“Inspection of ISHs from the Allen Brain Atlas (Lein et al., 2007) indicated that these neurons were located in the Edinger-Westphal nucleus, which is adjacent to the DRN, confirming that our dissection region spanned most of the DRN along the anterior-posterior axis.”
From Molecular and anatomical organization of the dorsal raphe nucleus (2019) · cites this paper as Lein et al., 2007
In the citing paper
“We leveraged the inclusion of adjacent brain tissue in our atlas to map the boundary between the 3V ChP and developing pineal gland using published ISH (Lein et al., 2007; Visel et al., 2004) of marker genes from our data (Figure S2C).”
From A cellular and spatial map of the choroid plexus across brain ventricles and ages (2021) · cites this paper as Lein et al., 2007
In the citing paper
“Signature scores were distinctly elevated in areas corresponding to the anatomical structures annotated in the Allen brain reference atlas (Figure S3A) (Lein et al., 2007).”
From Atlas of the aging mouse brain reveals white matter as vulnerable foci (2023) · cites this paper as Lein et al., 2007
In the citing paper
“We compared the expression of marker genes to insitu hybridization (ISH) data from the Allen Mouse Brain Atlas(Lein et al., 2007) and visual landmarks from the H&E microscopy images”
From Atlas of the aging mouse brain reveals white matter as vulnerable foci (2023) · cites this paper as Lein et al., 2007
Citations
Cites
DAVID: Database for Annotation, Visualization, and Integrated Discovery
Dennis, G., Sherman, B. T., Hosack, D. A., Yang, J., Gao, W., Lane, H. C., & Lempicki, R. A. (2003) · Genome Biology · doi:10.1186/gb-2003-4-5-p3 · Cited by 9,327
The Transcriptional Landscape of the Mammalian Genome
Carninci, P., Kasukawa, T., Katayama, S., Gough, J., Frith, M. C., Maeda, N., Oyama, R., Ravasi, T., Lenhard, B., Wells, C. A., et al. (2005) · Science · doi:10.1126/science.1112014 · Cited by 3,492
Interneurons of the neocortical inhibitory system
Markram, H., Toledo-Rodriguez, M., Wang, Y., Gupta, A., Silberberg, G., & Wu, C. (2004) · Nature Reviews Neuroscience · doi:10.1038/nrn1519 · Cited by 2,954
Alignment by Maximization of Mutual Information
Viola, P. A., & Wells, W. M. (1997) · International Journal of Computer Vision · doi:10.1023/a:1007958904918 · Cited by 2,610
Coordinated Transcription of Key Pathways in the Mouse by the Circadian Clock
Panda, S., Antoch, M. P., Miller, B. H., Su, A. I., Schook, A. C., Straume, M., Schultz, P. G., Kay, S. A., Takahashi, J. S., & Hogenesch, J. B. (2002) · Cell · doi:10.1016/s0092-8674(02)00722-5 · Cited by 2,310
The three-dimensional organization of the hippocampal formation: A review of anatomical data
Amaral, D. G., & Witter, M. P. (1989) · Neuroscience · doi:10.1016/0306-4522(89)90424-7 · Cited by 2,180
A gene expression atlas of the central nervous system based on bacterial artificial chromosomes
Gong, S., Zheng, C., Doughty, M. L., Losos, K., Didkovsky, N., Schambra, U. B., Nowak, N. J., Joyner, A., Leblanc, G., Hatten, M. E., et al. (2003) · Nature · doi:10.1038/nature02033 · Cited by 2,108
Zola-Morgan, S., Squire, L., & Amaral, D. (1986) · The Journal of Neuroscience · doi:10.1523/jneurosci.06-10-02950.1986 · Cited by 1,997
de Nó, R. L. (1934) · Cited by 1,974
Brain Maps: Structure of the Rat Brain
Swanson, L. W. (1992) · Medical Entomology and Zoology · Cited by 1,878
Flagged first, then by citations
1 of the 58 references couldn’t be matched to a known paper.
Research works printed but not linked: 1
- Voogd, J., Hess, D. & Marani, E. The Parasagittal Zonation of the Cerebellar Cortex in Cat and Monkey: Topography, Distribution of Acetylcholinesterase, and Development (ed. King, E. S.) (Liss, New York, 1987)
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Hu, F., Padukkavidana, T., Vægter, C. B., Brady, O. A., Zheng, Y., Mackenzie, I. R., Feldman, H. H., Nykjaer, A., & Strittmatter, S. M. (2010) · Neuron · doi:10.1016/j.neuron.2010.09.034 · Cited by 536
Kell, D. B. (2009) · BMC Medical Genomics · doi:10.1186/1755-8794-2-2 · Cited by 554
Standardizing workflows in imaging transcriptomics with the abagen toolbox
Markello, R. D., Arnatkevičiūtė, A., Poline, J., Fulcher, B. D., Fornito, A., & Mišić, B. (2021) · eLife · doi:10.7554/elife.72129 · Cited by 569
Visualizing Hypothalamic Network Dynamics for Appetitive and Consummatory Behaviors
Jennings, J. H., Ung, R. L., Resendez, S. L., Stamatakis, A. M., Taylor, J. G., Huang, J. H., Veleta, K., Kantak, P. A., Aita, M., Shilling-Scrivo, K. V., et al. (2015) · Cell · doi:10.1016/j.cell.2014.12.026 · Cited by 550
m6A facilitates hippocampus-dependent learning and memory through YTHDF1
Shi, H., Zhang, X., Weng, Y.-L., Lu, Z., Liu, Y., Lu, Z., Li, J., Hao, P., Zhang, Y., Zhang, F., et al. (2018) · Nature · doi:10.1038/s41586-018-0666-1 · Cited by 546
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Small, S. A., & Duff, K. (2008) · Neuron · doi:10.1016/j.neuron.2008.11.007 · Cited by 546
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Soldatov, R., Kaucka, M., Kastriti, M. E., Petersen, J., Chontorotzea, T., Englmaier, L., Akkuratova, N., Yang, Y., Häring, M., Dyachuk, V., et al. (2019) · Science · doi:10.1126/science.aas9536 · Cited by 546
Single-cell methylomes identify neuronal subtypes and regulatory elements in mammalian cortex
Luo, C., Keown, C. L., Kurihara, L., Zhou, J., He, Y., Li, J., Castanon, R., Lucero, J., Nery, J. R., Sandoval, J. P., et al. (2017) · Science · doi:10.1126/science.aan3351 · Cited by 545
Wiśniewski, J. R., Zougman, A., & Mann, M. (2009) · Journal of Proteome Research · doi:10.1021/pr900748n · Cited by 545
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Dorr, A. E., Lerch, J. P., Spring, S., Kabani, N. J., & Henkelman, R. M. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.03.037 · Cited by 539
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Lee, J. H., Daugharthy, E. R., Scheiman, J., Kalhor, R., Ferrante, T. C., Terry, R., Turczyk, B. M., Yang, J. L., Lee, H. S., Aach, J., et al. (2015) · Nature Protocols · doi:10.1038/nprot.2014.191 · Cited by 529
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Stuber, G. D., & Wise, R. A. (2016) · Nature Neuroscience · doi:10.1038/nn.4220 · Cited by 544
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Xu, M., Chung, S., Zhang, S., Zhong, P., Ma, C., Chang, W.-C., Weissbourd, B., Sakai, N., Luo, L., Nishino, S., et al. (2015) · Nature Neuroscience · doi:10.1038/nn.4143 · Cited by 514
Acetyl-CoA synthetase regulates histone acetylation and hippocampal memory
Mews, P., Donahue, G., Drake, A. M., Luczak, V., Abel, T., & Berger, S. L. (2017) · Nature · doi:10.1038/nature22405 · Cited by 514
Molecularly defined and spatially resolved cell atlas of the whole mouse brain
Zhang, M., Pan, X., Jung, W., Halpern, A. R., Eichhorn, S. W., Lei, Z., Cohen, L., Smith, K. A., Tasic, B., Yao, Z., et al. (2023) · Nature · doi:10.1038/s41586-023-06808-9 · Cited by 531
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Li, H., Wetten, S., Li, L., St. Jean, P. L., Upmanyu, R., Surh, L., Hosford, D., Barnes, M. R., Briley, J. D., Borrie, M., et al. (2008) · Archives of Neurology · doi:10.1001/archneurol.2007.3 · Cited by 499
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Ren, J., Friedmann, D., Xiong, J., Liu, C. D., Ferguson, B. R., Weerakkody, T., DeLoach, K. E., Ran, C., Pun, A., Sun, Y., et al. (2018) · Cell · doi:10.1016/j.cell.2018.07.043 · Cited by 498
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Mayer, C., Hafemeister, C., Bandler, R. C., Machold, R., Batista Brito, R., Jaglin, X., Allaway, K., Butler, A., Fishell, G., & Satija, R. (2018) · Nature · doi:10.1038/nature25999 · Cited by 492
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Gradinaru, V., Thompson, K. R., Zhang, F., Mogri, M., Kay, K., Schneider, M. B., & Deisseroth, K. A. (2007) · Journal of Neuroscience · doi:10.1523/jneurosci.3578-07.2007 · Cited by 482
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Alon, S., Goodwin, D., Sinha, A., Wassie, A. T., Chen, F., Daugharthy, E. R., Bando, Y., Kajita, A., Xue, A. G., Marrett, K., et al. (2021) · Science · doi:10.1126/science.aax2656 · Cited by 421
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Self-citationGrayson, D. S., & Fair, D. A. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.01.079 · Cited by 411
“In animal studies (rodents and non-human primates), this is feasible through the use of comprehensive, histologically and functionally defined whole-brain areal parcellations (Bezgin et al., 2012; Lein et al., 2007; Paxinos et al., 2000; Saleem and Logothetis, 2007; Swanson, 2015; Van Essen et al., 2012).”
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Papp, E. A., Leergaard, T. B., Calabrese, E., Johnson, G. A., & Bjaalie, J. G. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.04.001 · Cited by 411
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Thompson, C. L., Pathak, S. D., Jeromin, A., Ng, L. L., MacPherson, C. R., Mortrud, M. T., Cusick, A., Riley, Z. L., Sunkin, S. M., Bernard, A., et al. (2008) · Neuron · doi:10.1016/j.neuron.2008.12.008 · Cited by 403
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Fornito, A., Arnatkevičiūtė, A., & Fulcher, B. (2018) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2018.10.005 · Cited by 381
A transcriptomic and epigenomic cell atlas of the mouse primary motor cortex
Yao, Z., Liu, H., Xie, F., Fischer, S., Adkins, R. S., Aldridge, A. I., Ament, S. A., Bartlett, A., Behrens, M. M., Van den Berge, K., et al. (2021) · Nature · doi:10.1038/s41586-021-03500-8 · Cited by 398
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Notaras, M. J., & van den Buuse, M. (2020) · Molecular Psychiatry · doi:10.1038/s41380-019-0639-2 · Cited by 404
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Peña, C. J., Kronman, H. G., Walker, D. M., Cates, H. M., Bagot, R. C., Purushothaman, I., Issler, O., Loh, Y.-H. E., Leong, T., Kiraly, D. D., et al. (2017) · Science · doi:10.1126/science.aan4491 · Cited by 394
Characterizing transcriptional heterogeneity through pathway and gene set overdispersion analysis
Fan, J., Salathia, N. S., Liu, R., Kaeser, G. E., Yung, Y. C., Herman, J. L., Kaper, F., Fan, J., Zhang, K., Chun, J. J. M., et al. (2016) · Nature Methods · doi:10.1038/nmeth.3734 · Cited by 376
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Greger, I. H., Watson, J. F., & Cull-Candy, S. G. (2017) · Neuron · doi:10.1016/j.neuron.2017.04.009 · Cited by 392
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Deng, Y., Bartosovic, M., Kukanja, P., Zhang, D., Liu, Y., Su, G., Enninful, A., Bai, Z., Castelo-Branco, G., & Fan, R. (2022) · Science · doi:10.1126/science.abg7216 · Cited by 393
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Bakken, T. E., Miller, J. A., Ding, S., Sunkin, S. M., Smith, K. A., Ng, L., Szafer, A., Dalley, R. A., Royall, J. J., Lemon, T. A., et al. (2016) · Nature · doi:10.1038/nature18637 · Cited by 387
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Dani, N., Herbst, R. H., McCabe, C., Green, G. S., Kaiser, K., Head, J. P., Cui, J., Shipley, F. B., Jang, A., Dionne, D., et al. (2021) · Cell · doi:10.1016/j.cell.2021.04.003 · Cited by 388
CATMAID: collaborative annotation toolkit for massive amounts of image data
Saalfeld, S., Cardona, A., Hartenstein, V., & Tomančák, P. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp266 · Cited by 384
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Lein, E., Borm, L. E., & Linnarsson, S. (2017) · Science · doi:10.1126/science.aan6827 · Cited by 383
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Ponomarev, I., Wang, S., Zhang, L., Harris, R. A., & Mayfield, R. D. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.3136-11.2012 · Cited by 387
Cell Densities in the Mouse Brain: A Systematic Review
Keller, D., Erö, C., & Markram, H. (2018) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2018.00083 · Cited by 380
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Hunt-Newbury, R., Viveiros, R., Johnsen, R. C., Mah, A. K., Anastas, D., Fang, L. L., Halfnight, E., Lee, D., Lin, J., Lorch, A. H., et al. (2007) · PLoS Biology · doi:10.1371/journal.pbio.0050237 · Cited by 372
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de Wit, J., Sylwestrak, E., O’Sullivan, M. L., Otto, S. J., Tiglio, K., Savas, J. N., Yates, J. R., Comoletti, D., Taylor, P., & Ghosh, A. (2009) · Neuron · doi:10.1016/j.neuron.2009.12.019 · Cited by 376
LANG, R., Gundlach, A. L., & Kofler, B. (2007) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2007.05.009 · Cited by 382
Ponjavic, J., Oliver, P. L., Lunter, G. A., & Ponting, C. P. (2009) · PLoS Genetics · doi:10.1371/journal.pgen.1000617 · Cited by 371
Sathyamurthy, A., Johnson, K. R., Matson, K. J. E., Dobrott, C. I., Li, L., Ryba, A. R., Bergman, T. B., Kelly, M. C., Kelley, M. W., & Levine, A. J. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.02.003 · Cited by 370
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Maret, S., Dorsaz, S., Gurcel, L., Pradervand, S., Petit, B., Pfister, C., Hagenbüchle, O., O’Hara, B. F., Franken, P., & Tafti, M. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0710131104 · Cited by 375
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Buffington, S. A., Huang, W., & Costa-Mattioli, M. (2014) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-071013-014100 · Cited by 348
Dougherty, J. D., Schmidt, E. F., Nakajima, M., & Heintz, N. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq130 · Cited by 352
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Xu, C., Jin, X., Wei, S., Wang, P., Luo, M., Xu, Z., Yang, W., Cai, Y., Xiao, L., Lin, X., et al. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac901 · Cited by 374
A new function for the fragile X mental retardation protein in regulation of PSD-95 mRNA stability
Zalfa, F., Eleuteri, B., Dickson, K. S., Mercaldo, V., Rubeis, S. D., di Penta, A., Tabolacci, E., Chiurazzi, P., Neri, G., Grant, S. G. N., et al. (2007) · Nature Neuroscience · doi:10.1038/nn1893 · Cited by 370
Genomic–anatomic evidence for distinct functional domains in hippocampal field CA1
Dong, H., Swanson, L. W., Chen, L., Fanselow, M. S., & Toga, A. W. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0812608106 · Cited by 361
Self-citationWu, P., Zuo, X., Deng, H., Liu, X., Liu, L., & Ji, A. (2013) · Brain Research Bulletin · doi:10.1016/j.brainresbull.2013.06.001 · Cited by 363
DNA repair deficiency in neurodegeneration
Jeppesen, D. K., Bohr, V. A., & Stevnsner, T. (2011) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2011.04.013 · Cited by 374
Nanotools for Neuroscience and Brain Activity Mapping
Alivisatos, A. P., Andrews, A. M., Boyden, E. S., Chun, M., Church, G. M., Deisseroth, K. A., Donoghue, J. P., Fraser, S. E., Lippincott‐Schwartz, J., Looger, L. L., et al. (2013) · ACS Nano · doi:10.1021/nn4012847 · Cited by 359
A transcriptomic atlas of mouse cerebellar cortex comprehensively defines cell types
Kozareva, V., Martin, C., Osorno, T., Rudolph, S., Guo, C., Vanderburg, C. R., Nadaf, N. M., Regev, A., Regehr, W. G., & Macosko, E. Z. (2021) · Nature · doi:10.1038/s41586-021-03220-z · Cited by 380
Distinct Representations and Theta Dynamics in Dorsal and Ventral Hippocampus
Royer, S., Sirota, A., Patel, J., & Buzsáki, G. (2010) · Journal of Neuroscience · doi:10.1523/jneurosci.4681-09.2010 · Cited by 356
Active control of arousal by a locus coeruleus GABAergic circuit
Breton‐Provencher, V., & Sur, M. (2019) · Nature Neuroscience · doi:10.1038/s41593-018-0305-z · Cited by 377
Kay, J. N., la Huerta, I. D., Kim, I.-J., Zhang, Y., Yamagata, M., Chu, M. W., Meister, M., & Sanes, J. R. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.0907-11.2011 · Cited by 351
Hedgehog-responsive candidate cell of origin for diffuse intrinsic pontine glioma
Monje, M., Mitra, S., Freret, M., Raveh, T., Kim, J., Masek, M., Attema, J., Li, G., Haddix, T., Edwards, M. S., et al. (2011) · Proceedings of the National Academy of Sciences of the United States of America · doi:10.1073/pnas.1101657108 · Cited by 316
Fuhrmann, F., Justus, D., Sosulina, L., Kaneko, H., Beutel, T., Friedrichs, D., Schoch, S., Schwarz, M. K., Fuhrmann, M., & Remy, S. (2015) · Neuron · doi:10.1016/j.neuron.2015.05.001 · Cited by 362
Bioimage informatics: a new area of engineering biology
Peng, H. (2008) · Bioinformatics · doi:10.1093/bioinformatics/btn346 · Cited by 344
Single-cell isoform RNA sequencing characterizes isoforms in thousands of cerebellar cells
Gupta, I., Collier, P. G., Haase, B., Mahfouz, A., Joglekar, A., Floyd, T., Koopmans, F., Barres, B., Smit, A. B., Sloan, S. A., et al. (2018) · Nature Biotechnology · doi:10.1038/nbt.4259 · Cited by 343
Adam, M., Potter, A. S., & Potter, S. S. (2017) · Development · doi:10.1242/dev.151142 · Cited by 343
Dulken, B. W., Leeman, D. S., Boutet, S. C., Hebestreit, K., & Brunet, A. (2017) · Cell Reports · doi:10.1016/j.celrep.2016.12.060 · Cited by 334
Presynaptic partners of dorsal raphe serotonergic and GABAergic neurons
Weissbourd, B., Ren, J., DeLoach, K. E., Guenthner, C. J., Miyamichi, K., & Luo, L. (2014) · Neuron · doi:10.1016/j.neuron.2014.06.024 · Cited by 337
Nuclear and cytosolic JNK signalling in neurons
Coffey, E. T. (2014) · Nature reviews. Neuroscience · doi:10.1038/nrn3729 · Cited by 351
TDP‐43, the signature protein of FTLD‐U, is a neuronal activity‐responsive factor
Wang, I., Wu, L., Chang, H., & Shen, C. ‐. J. (2007) · Journal of Neurochemistry · doi:10.1111/j.1471-4159.2007.05190.x · Cited by 345
Evolution of the Aging Brain Transcriptome and Synaptic Regulation
Loerch, P. M., Lu, T., Dakin, K. A., Vann, J. M., Isaacs, A., Geula, C., Wang, J., Pan, Y., Gabuzda, D. H., Li, C., et al. (2008) · PLoS ONE · doi:10.1371/journal.pone.0003329 · Cited by 334
Rediscovering area CA2: unique properties and functions
Dudek, S. M., Alexander, G. M., & Farris, S. (2016) · Nature reviews. Neuroscience · doi:10.1038/nrn.2015.22 · Cited by 333
A High-Resolution Spatiotemporal Atlas of Gene Expression of the Developing Mouse Brain
Thompson, C. L., Ng, L., Menon, V., Martı́nez, S., Lee, C., Glattfelder, K. J., Sunkin, S. M., Henry, A. M., Lau, C., Dang, C., et al. (2014) · Neuron · doi:10.1016/j.neuron.2014.05.033 · Cited by 332
Self-citation
Metadata
- Authors
- Lein, E. S., Hawrylycz, M. J., Ao, N., Ayres, M., Bensinger, A., Bernard, A., Boe, A. F., Boguski, M. S., Brockway, K. S., Byrnes, E. J., Chen, L., Chen, L., Chen, T.-M., Chi Chin, M., Chong, J., Crook, B. E., Czaplinska, A., Dang, C. N., Datta, S., Dee, N. R., Desaki, A. L., Desta, T., Diep, E., Dolbeare, T. A., Donelan, M. J., Dong, H.-W., Dougherty, J. G., Duncan, B. J., Ebbert, A. J., Eichele, G., Estin, L. K., Faber, C., Facer, B. A., Fields, R., Fischer, S. R., Fliss, T. P., Frensley, C., Gates, S. N., Glattfelder, K. J., Halverson, K. R., Hart, M. R., Hohmann, J. G., Howell, M. P., Jeung, D. P., Johnson, R. A., Karr, P. T., Kawal, R., Kidney, J. M., Knapik, R. H., Kuan, C. L., Lake, J. H., Laramee, A. R., Larsen, K. D., Lau, C., Lemon, T. A., Liang, A. J., Liu, Y., Luong, L. T., Michaels, J., Morgan, J. J., Morgan, R. J., Mortrud, M. T., Mosqueda, N. F., Ng, L. L., Ng, R., Orta, G. J., Overly, C. C., Pak, T. H., Parry, S. E., Pathak, S. D., Pearson, O. C., Puchalski, R. B., Riley, Z. L., Rockett, H. R., Rowland, S. A., Royall, J. J., Ruiz, M. J., Sarno, N. R., Schaffnit, K., Shapovalova, N. V., Sivisay, T., Slaughterbeck, C. R., Smith, S. C., Smith, K. A., Smith, B. I., Sodt, A. J., Stewart, N. N., Stumpf, K.-R., Sunkin, S. M., Sutram, M., Tam, A., Teemer, C. D., Thaller, C., Thompson, C. L., Varnam, L. R., Visel, A., Whitlock, R. M., Wohnoutka, P. E., Wolkey, C. K., Wong, V. Y., Wood, M., Yaylaoglu, M. B., Young, R. C., Youngstrom, B. L., Feng Yuan, X., Zhang, B., Zwingman, T. A., & Jones, A. R.
- Affiliations
- Allen Institute for Brain Science (US)
- Baylor College of Medicine (US)
- Novartis (Switzerland) (CH)
- Lawrence Berkeley National Laboratory (US)
- Corresponding author
- Lein, Ed S.
- Jones, Allan R.
- ORCID
- Lein, Ed S.
- Hawrylycz, Michael J.
- Bernard, Amy
- Chen, Lin
- Chong, Jimmy
- Dee, Nick R.
- Desta, Tsega
- Dolbeare, Tim A.
- Dong, Hong-Wei
- Fliss, Tim P.
- Glattfelder, Katie J.
- Hart, Matthew R.
- Hohmann, John G.
- Liu, Ying
- Ng, Lydia L.
- Puchalski, Ralph B.
- Shapovalova, Nadiya V.
- Smith, Kimberly A.
- Sunkin, Susan M.
- Thompson, Carol L.
- Visel, Axel
- Wohnoutka, Paul E.
- Wood, Matthew
- Zhang, Bin
- Zwingman, Theresa A.
- Jones, Allan R.
- Venue
- Nature
- Published
- 2006-12-06
- Volume
- 445
- Issue
- 7124
- Pages
- 168-176
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W2123491442
- Cited by
- 5,572
- References
- 58
- Citations by year
- 2026: 237 · 2025: 327 · 2024: 368 · 2023: 347 · 2022: 409 · 2021: 435 · 2020: 398 · 2019: 342 · 2018: 320 · 2017: 296 · 2016: 280 · 2015: 236 · 2014: 252 · 2013: 203 · 2012: 223
- FWCI
- 68.18
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Max Planck Institute for Plasma Physics (submittedVersion)
- Max Planck Digital Library (submittedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Developmental Biology and Gene Regulation
- Keywords
- gene expression atlas, mouse brain, Allen Brain Atlas, cellular resolution, in situ hybridization, brain region-specific gene expression, cell markers, brain organization
- MeSH terms
- Animals, Brain, Gene Expression Regulation, Hippocampus, Male, Mice, Inbred C57BL, Organ Specificity, RNA, Messenger, Genome, Computational Biology, Gene Expression Profiling, Genomics, Mice
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