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http://brancusi.usc.edu/bkms/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 7th, 2019. BAMS is an online resource for information about neural circuitry. The BAMS Nested Regions view focuses on the major brain regions and their relationships.

Proper citation: BAMS Nested Regions (RRID:SCR_000238) Copy   

•   Source: SciCrunch Registry

http://gbrowse.csbio.unc.edu/cgi-bin/gb2/gbrowse/slep/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Database of genetic and gene expression data from the published literature on psychiatric disorders. Users can search the accumulated data to find the evidence in support of the involvement of a particular genomic region with a set of important psychiatric disorders, ADHD, autism, bipolar disorder, eating disorder, major depressive disorder, schizophrenia, and smoking behavior. It contains findings from manual reviews of 144 papers in psychiatric genetics, 136 primary reports and 8 meta-analyses. Disorders covered include schizophrenia (44 papers), autism (24 papers), bipolar disorder (24 papers), smoking behavior (24 papers), major depressive disorder and neuroticism (14 papers), ADHD (8 papers), eating disorders (3 papers), and a combined schizophrenia-bipolar phenotype (3 papers). The unbiased searches integrated into SLEP include genomewide linkage (117 papers), genomewide association (15 papers), copy number variation (9 papers), and gene expression studies of post-mortem brain tissue (3 meta-analyses courtesy of the Stanley Foundation). In total, SLEP captures 3,741 findings from these 144 papers. SLEP also contains over 70,000 SignPosts. These annotations derive from many different sources and are designed to try to capture current state of knowledge about disease associations in the human genome. SignPosts can be searched simultaneously with the psychiatric genetics literature in order to integrate these two bodies of knowledge. The SignPosts include: accumulated GWAS findings from the human genetics literature, the OMIM database, candidate gene association study literature, CNV location and frequency data, SNPs that influence gene expression in brain, genes expressed in brain, genes with evidence of imprinting and random monoalleleic expression, genes mutated in breast or colorectal cancer, and pathway data from BioCyc.

Proper citation: Sullivan Lab Evidence Project (RRID:SCR_000753) Copy   

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http://brainevolutionnews.blogspot.com/

Brain Evolution in the News pulls in blogs from a variety of resources on topic.

Proper citation: Brain Evolution in the News (RRID:SCR_000592) Copy   

•   Source: SciCrunch Registry

http://www.eideneurolearningblog.blogspot.com/

Weekly articles related to brain-based learning and learning styles, problem-solving and creativity, kids, families, and parenting, gifted and visual learners, dyslexia, attention deficit disorders, autism, and more.

Proper citation: Eide Neurolearning Blog (RRID:SCR_000680) Copy   

•   Source: SciCrunch Registry

http://kymata-atlas.org

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. An online atlas of neural function, maintained by Cambridge University and the MRC Cognition and Brain Sciences Unit (CBSU).

Proper citation: Kymata Atlas (RRID:SCR_000269) Copy   

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http://gemma-doc.chibi.ubc.ca/neurocarta/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Neurocarta is a knowledgebase that consolidates information on genes and phenotypes across multiple resources and allows tracking and exploring of the associations. The system enables automatic and manual curation of evidence supporting each association, as well as user-enabled entry of their own annotations. Phenotypes are recorded using controlled vocabularies such as the Disease Ontology to facilitate computational inference and linking to external data sources. The gene-to-phenotype associations are filtered by stringent criteria to focus on the annotations most likely to be relevant. Neurocarta is constantly growing and currently holds more than 30,000 lines of evidence linking over 6,800 genes to 1,800 different phenotypes. Neurocarta is a one-stop shop for researchers looking for candidate genes for any disorder of interest. In Neurocarta, they can review the evidence linking genes to phenotypes and filter out the evidence they're not interested in. In addition, researchers can enter their own annotations from their experiments and analyze them in the context of existing public annotations. Neurocarta's in-depth annotation of neurodevelopmental disorders makes it a unique resource for neuroscientists working on brain development.

Proper citation: Neurocarta (RRID:SCR_000617) Copy   

•   Source: SciCrunch Registry

http://bodymap.genes.nig.ac.jp/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 17, 2013. A taxonomical and anatomical database of latest cross species animal EST data, clustered by UniGene and inter connected by Inparanoid. Users can search by Unigene, RefSeq, or Entrez Gene ID, or search for Gene Name or Tissue type. Data is also sortable and viewable based on qualities of normal, Neoplastic, or other. The last data import appears to be from 2008

Proper citation: BodyMap-Xs (RRID:SCR_001147) Copy   

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http://netbio.bgu.ac.il/tissuenet/

Database of human tissue protein-protein interactions (PPIs) that associates each interaction with human tissues that express both pair mates. This was achieved by integrating current data of experimentally detected PPIs with extensive data of gene and protein expression across 16 main human tissues. Users can query TissueNet using a protein and retrieve its PPI partners per tissue, or using a PPI and retrieve the tissues expressing both pair mates. The graphical representation of the output highlights tissue-specific and tissue-wide PPIs. Thus, TissueNet provides a unique platform for assessing the roles of human proteins and their interactions across tissues.

Proper citation: TissueNet - The Database of Human Tissue Protein-Protein Interactions (RRID:SCR_002052) Copy   

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http://www.cabiatl.com/mricro/anatomy/home.html

Annotated magnetic resonance brain images, both slices and surface views, normalized to Talairach space, along with annotations and a nice tutorial on image normalization. A viewer for MRI images (MRicro) is available and is described in a separate entry. Series of coronal, axial and sagittal brain slices along with some rendered volumes with major brain structures delineated. Slices are presented as static series with partial overlap of slices, so they are not suitable for 3d reconstruction. This neuroanatomy atlas shows regions on normalized MRI scans. Normalization is the process of warping a brain to match a standard size, orientation and shape of other brains. You can normalize MRI scans using programs like AIR, FLIRT or SPM. Once normalized, the overall shape of your MRI scan will approximately match those in this atlas. However, normalization preserves the unique sulcal features of each brain, so there will be some variation between your image and the images shown in this atlas. There is a great deal of individual variability even after normalization, so any atlas is only a rough guide to the shape and location of structures in an individuals brain. As I have noted before, secondary and tertiary sulci are not found in all individuals (Ono et al. 1990, Atlas of Cerebral Sulci). Another benefit of normalizing brains is it makes it easy to complete an accurate "scalp stripping" with brain extracting software (my MRIcro software implements Steve Smith's BET for this task). You can then create a useful volume rendering of the cortical surface. Typically, it is much easier to identify cortical sulci and gyri by looking at a rendered image of the brain's surface. This atlas shows you how to recognize these landmarks on a rendered MRI scan.

Proper citation: Neuroanatomy Atlas (RRID:SCR_002402) Copy   

•   Source: SciCrunch Registry

http://www.genes2cognition.org/db/Search

Database of protein complexes, protocols, mouse lines, and other research products generated from the Genes to Cognition project, a project focused on understanding molecular complexes involved in synaptic transmission in the brain.

Proper citation: Genes to Cognition Database (RRID:SCR_002735) Copy   

•   Source: SciCrunch Registry

https://bams1.org/cells/list.php, https://bams1.org/cells/search_bams_ref.php, https://bams1.org/cells/search_by_brain_region.php

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 6, 2023.BAMS is an online resource for information about neural circuitry. The BAMS Cell view focuses on the major brain regions and which cells are contained therein.

Proper citation: BAMS Cells (RRID:SCR_003531) Copy   

•   Source: SciCrunch Registry

http://www.emouseatlas.org

Detailed multidimensional digital multimodal atlas of C57BL/6J mouse nervous system with data and informatics pipeline that can automatically register, annotate, and visualize large scale neuroanatomical and connectivity data produced in histology, neuronal tract tracing, MR imaging, and genetic labeling. MAP2.0 interoperates with commonly used publicly available databases to bring together brain architecture, gene expression, and imaging information into single, simple interface.Resource to visualise mouse development, identify anatomical structures, determine developmental stage, and investigate gene expression in mouse embryo. eMouseAtlas portal page allows access to EMA Anatomy Atlas of Mouse Development and EMAGE database of gene expression.EMAGE is freely available, curated database of gene expression patterns generated by in situ techniques in developing mouse embryo. EMA, e-Mouse Atlas, is 3-D anatomical atlas of mouse embryo development including histology and includes EMAP ontology of anatomical structure, provides information about shape, gross anatomy and detailed histological structure of mouse, and framework into which information about gene function can be mapped.

Proper citation: eMouseAtlas (RRID:SCR_002981) Copy   

•   Source: SciCrunch Registry

https://confluence.crbs.ucsd.edu/display/NIF/DRG

Gene expression data from published journal articles that test hypotheses relevant to neuroscience of addiction and addictive behavior. Data types include effects of particular drug, strain, or knock out on particular gene, in particular anatomical region. Focuses on gene expression data and exposes data from investigations using DNA microarrays, polymerase chain reaction, immunohistochemistry and in-situ hybridizations. Data are available for query through NIF interface.Data submissions are welcome.

Proper citation: Drug Related Gene Database (RRID:SCR_003330) Copy   

•   Source: SciCrunch Registry

http://hendrix.imm.dtu.dk/services/jerne/brede/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 4th, 2023. A database of human data from functional neuroimaging scientific articles containing Talairach coordinates that provides data for novel information retrieval techniques and automated meta-analyses. Each article in this database is identified by a unique number: A WOBIB. Some of the structure of the Brede database is similar to the structure of the BrainMap database (Research Imaging Center, San Antonio). The database is inspired by the hierarchical structure of BrainMap with scientific articles (bib structures) on the highest level containing one or more experiments (exp structure, corresponding to a contrast in general linear model analyses), these in turn comprising one or more locations (loc structures). The information on the bib level (author, title, ...) is setup automatically from PubMed while the rest of the information is entered manually in a Matlab graphical user interface. On the loc level this includes the 3D stereotactic coordinates in either Talairach or MNI space, the brain area (functional, anatomical or cytoarchitectonic area) and magnitude values such as Z-score and P-value. On the exp level information such as modality, scanner and behavioral domain are recorded with external components (such as face recognition or kinetic boundaries) organized in a directed graph and marked up with Medical Subject Headings (MeSH) where possible. The database is distributed as part of the Brede neuroinformatics toolbox (hendrix.imm.dtu.dk/software/brede/) which also provides the functions to manipulate and analyze the data. The Brede Toolbox is a program package primarily written in Matlab. As of 2006/11, 186 papers with 586 experiments.

Proper citation: Brede Database (RRID:SCR_003327) Copy   

•   Source: SciCrunch Registry

http://pepr.cnmcresearch.org/

An experiment in web-database access to large multi-dimensional data sets using a standardized experimental platform to determine if the larger scientific community can be given simple, intuitive, and user-friendly web-based access to large microarray data sets. All data in PEPR is also available via NCBI GEO. The structure and goals of PEPR differ from other mRNA expression profiling databases in a number of important ways. * The experimental platform in PEPR is standardized, and is an Affymetrix - only database. All microarrays available in the PEPR web database should ascribe to quality control and standard operating procedures. A recent publication has described the QC/SOP criteria utilized in PEPR profiles ( The Tumor Analysis Best Practices Working Group 2004 ). * PEPR permits gene-based queries of large Affymetrix array data sets without any specialized software. For example, a number of large time series projects are available within PEPR, containing 40-60 microarrays, yet these can be simply queried via a dynamic web interface with no prior knowledge of microarray data analysis. * Projects in PEPR originate from scientists world-wide, but all data has been generated by the Research Center for Genetic Medicine, Children''''s National Medical Center, Washington DC. Future developments of PEPR will allow remote entry of Affymetrix data ascribing to the same QC/SOP protocols. They have previously described an initial implementation of PEPR, and a dynamic web-queried time series graphical interface ( Chen et al. 2004 ). A publication showing the utility of PEPR for pharmacodynamic data has recently been published ( Almon et al. 2003 ).

Proper citation: Public Expression Profiling Resource (RRID:SCR_007274) Copy   

•   Source: SciCrunch Registry

http://www.geneatlas.org/gene/main.jsp

This website allows visitors to search for genes of interest based on their spatial expression patterns in the Postnatal Day 7 mouse brain. Geneatlas provides two searching tools: A graphical interface for customized spatial queries; A textual interface for querying annotated structures. Geneatlas is the product of a collaboration between researchers at Baylor College of Medicine, Rice University, and University of Houston.

Proper citation: Gene Atlas (RRID:SCR_008089) Copy   

•   Source: SciCrunch Registry

http://phm.utoronto.ca/~jeffh/surgical.htm

3D interactive atlas of two mouse brains, 129S1/SvImJ and C57Bl/6J. The aim of this resource is to enhance comparative morphometric analyses and stereotactic surgical procedures in mice. These representations of the murine brain and skull, in conjunction with the resource''s development of a new, more dynamic master coordinate system, provide improved accuracy with respect to targeting CNS structures during surgery compared with previous systems. The interactive three-dimensional nature of these atlases also provide users with stereotactic information necessary to perform accurate off-axis surgical procedures, as is commonly required for experiments such as in vivo micro-electroporation. In addition, three-dimensional analysis of the brain and skull shape in C57Bl, 129Sv, CD1, and additional murine strains, suggests that a stereotactic coordinate system based upon the lambda and rostral confluence of the sinuses at the sagittal midline, provides improved accuracy compared with the traditional lambdabregma landmark system. These findings demonstrate the utility of developing highly accurate and robust three-dimensional representations of the murine brain and skull, in which experimental outputs can be directly compared using a unified coordinate system.

Proper citation: 3D surgical atlases of the murine head (RRID:SCR_008039) Copy   

•   Source: SciCrunch Registry

http://www.loni.usc.edu/ICBM/Downloads/Downloads_DTI-81.shtml

A stereotaxic probabilistic white matter atlas that fuses DTI-based white matter information with an anatomical template (ICBM-152). This atlas is based on probabilistic tensor maps obtained from 81 normal subjects acquired under an initiative of the International Consortium of Brain Mapping (ICBM). The subjects were normal right-handed adults ranging from 18 to 59 years of age. A hand-segmented white matter parcellation map was created from this averaged map. This map can be used for automated white matter parcellation. The precision of the affine-based image normalization and automated parcellation was measured for a group of normal subjects using manually defined anatomical landmarks. The raw diffusion-weighted images (DWIs) were first co-registered to one of the least diffusion-weighted images and corrected for subject motion with 6-mode rigid transformation with Automated Image Registgration (AIR). The average of all DWIs (aDWI) was calculated and used for a DTI-based anatomic image. For anatomical images to drive the normalization process, aDWIs were used. These images were normalized to the template (ICBM-152) using a 12-mode affine or 4th order polynomial non-linear transformation of AIR. The transformation matrix was then applied to the calculated diffusion tensor field. In the white matter parcellation map (WMPM), deep white matter regions were manually segmented into various anatomic structures based on fiber orientation information.

Proper citation: International Consortium of Brain Mapping DTI-81 Atlas (RRID:SCR_008066) Copy   

•   Source: SciCrunch Registry

http://vox.pharmacology.ucla.edu/home.html

Two-dimensional images of gene expression for 20,000 genes in a coronal slice of the mouse brain at the level of the striatum by using microarrays in combination with voxelation at a resolution of 1 cubic mm gene expression patterns in the brain obtained through voxelation. Voxelation employs high-throughput analysis of spatially registered voxels (cubes) to produce multiple volumetric maps of gene expression analogous to the images reconstructed in biomedical imaging systems.

Proper citation: Voxelation Map of Gene Expression in a Coronal Section of the Mouse Brain (RRID:SCR_008065) Copy   

•   Source: SciCrunch Registry

http://www.nesys.uio.no/Database/

This site contains the NeSys archive on structure and structure-function data about brain map transformations in the cerebellar system of the rat. This archive presents data not illustrated in the original publications, downloadable original data sets, interactive illustration sequences, including 3-D models. The repository is based on 5 original publications. The publications deal with: - organization of projections to the pontine nuclei from three cortical areas: primary and secondary somatosensory areas (SI and SII), and the primary motor cortex (MI) - organization of pontine neurons projecting to somatosensory representations in the posterior cerebellum The data are also included in the FACCS application, a relational database application with embedded analytical tools, available via the The Rodent Brain Workbench (www.rbwb.org). Sponsors: NeSys Research and Database development is supported by The Research Council of Norway, The European Community (grants QLRT-2000-02256 and QLG3-CT 1999-00763), The Norwegian Consortium for High Performance Computing, and The Jahre Foundation.

Proper citation: Database on Brain Map Transformations in Cerebellar Systems (RRID:SCR_008052) Copy   

•   Source: SciCrunch Registry