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http://pdsp.med.unc.edu/snidd/

A database of imaging probes useful for preclinical and clinical studies. The National Institute of Mental Health (NIMH) and the Society for Non-Invasive Imaging in Drug Development (SNIDD) are in the process of creating a centralized, searchable PET, SPECT, and MRI tracer database as a resource for the scientific community. The goal of this effort is to promote the use of imaging probes in preclinical and clinical research and in drug discovery to accelerate the identification and validation of novel targets for therapeutic intervention in human diseases, especially those with central nervous system components. NIMH will maintain the tracer database as part of the Psychoactive Drug Screening Program (PDSP). The database will contain records for each radiotracer with relevant information such as target, research uses, pharmacology, pharmacokinetics, synthesis protocols, toxicology and safety data, dosimetry, other clinical data, IND info, permission to cross-reference pharmacology, toxicology, or safety data in a drug master file (if an IND exists), contact information, patent, etc. with appropriate safeguards in place to protect the intellectual property of proprietary compounds.

Proper citation: NIMH/SNIDD Tracer Database Initiative (RRID:SCR_008105) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/pediatric_mri

A database which contains longitudinal structural MRIs, spectroscopy, DTI and correlated clinical/behavioral data from approximately 500 healthy, normally developing children, ages newborn to young adult.

Proper citation: NIH Pediatric MRI Data Repository (RRID:SCR_014149) Copy   

•   Source: SciCrunch Registry

https://brain-specimenportal.org/

Web application that tracks the status of the BICAN consortium tissue samples and related data.NIMP is developed under NIH BRAIN Initiative's BICAN U24MH130988 award as a part of the coordinating unit for biostatistics, informatics, and engagement (CUBIE) for the BRAIN Initiative Cell Atlas Network (BICAN) program.NIMP consists of two portals for BICAN collaborative data generation: the Specimen Portal and the Sequence Library (SeqLib) Portal. The Specimen Portal focuses on tissue management from donors to brain slabs and annotated brain samples. The SeqLib Portal manages the workflow starting from tissue, all the way downstream to track data deposition to assay-dependent, data-modality-specific archives. Both portals work in tandem to generate multimodal genomic data that can be traced back to their anatomical origins using the Allen Brain Atlas. The portals provide multiple types of data interfaces through dashboards, APIs, faceted queries, and batch data ingestion and exporting. All of the underlying functionalities are achieved through a robust agile development strategy using NHash resource identifiers, metadata standardization, active combinatorial dashboarding, resource provenance linkage and rendering (e.g. Sankey diagrams), and dedicated interfaces with NIH Neuro Biobank, sequencing centers, NeMO, and the larger BICAN data ecosystem.

Proper citation: NIMP: Neuroanatomy-anchored Information Management Platform for Collaborative BICAN Data Generation (RRID:SCR_024684) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.brainscanr.com/

A database of neuroscience-related concepts that utilizes visualization tools for the purpose of research, education and knowledge discovery. The data comes from PubMed abstracts and an algorithm that assumes related terms will appear together. The topics can include computational modeling, behavioral functions and neurological degeneration.

Proper citation: brainSCANr (RRID:SCR_000500) Copy   

•   Source: SciCrunch Registry

http://cng.gmu.edu/brava

A database of digital reconstructions of the human brain arterial arborizations from 61 healthy adult subjects along with extracted morphological measurements. The arterial arborizations include the six major trees stemming from the circle of Willis, namely: the left and right Anterior Cerebral Arteries (ACAs), Middle Cerebral Arteries (MCAs), and Posterior Cerebral Arteries (PCAs).

Proper citation: BraVa (RRID:SCR_001407) Copy   

•   Source: SciCrunch Registry

http://www.jcvi.org/mpidb

Database that collects and provides all known physical microbial interactions. Currently, 24,295 experimentally determined interactions among proteins of 250 bacterial species/strains can be browsed and downloaded. These microbial interactions have been manually curated from the literature or imported from other databases (IntAct, DIP, BIND, MINT) and are linked to 26,578 experimental evidences (PubMed ID, PSI-MI methods). In contrast to these databases, interactions in MPIDB are further supported by 68,346 additional evidences based on interaction conservation, co-purification, and 3D domain contacts (iPfam, 3did). (spoke/matrix) binary interactions inferred from pull-down experiments are not included.

Proper citation: MPIDB (RRID:SCR_001898) 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://rsb.info.nih.gov/

Portal for NIH, NIMH, and NINDS scientific and computer resources including Mac sites, PC sites, Linux sites, intramural programs, intranet and the NIH JumpStart and Directory.

Proper citation: Research Services Branch National Institutes of Mental Health (RRID:SCR_001633) Copy   

•   Source: SciCrunch Registry

http://www.fz-juelich.de/ime/spm_anatomy_toolbox

A MATLAB toolbox which uses three dimensional probabilistic cytoarchitechtonic maps to correlate microscopic, anatomic and functional data of the cerebral cortex. Correlating the activation foci identified in functional imaging studies of the human brain with structural (e.g., cytoarchitectonic) information on the activated areas is a major methodological challenge for neuroscience research. We here present a new approach to make use of three-dimensional probabilistic cytoarchitectonic maps, as obtained from the analysis of human post-mortem brains, for correlating microscopical, anatomical and functional imaging data of the cerebral cortex. We introduce a new, MATLAB based toolbox for the SPM2 software package which enables the integration of probabilistic cytoarchitectonic maps and results of functional imaging studies. The toolbox includes the functionality for the construction of summary maps combining probability of several cortical areas by finding the most probable assignment of each voxel to one of these areas. Its main feature is to provide several measures defining the degree of correspondence between architectonic areas and functional foci. The software, together with the presently available probability maps, is available as open source software to the neuroimaging community. This new toolbox provides an easy-to-use tool for the integrated analysis of functional and anatomical data in a common reference space.

Proper citation: SPM Anatomy Toolbox (RRID:SCR_013273) Copy   

•   Source: SciCrunch Registry

http://nunda.northwestern.edu/nunda/app

A resource for managing study data collected by the Northwestern University neuroimaging community. It includes a secure database, automated pipelines for processing managed data, and tools for exploring and accessing the data. Access to data in the NUNDA is restricted to users authorized by the specific study's investigators. The NUNDA is hosted by the Neuroimaging & Applied Computational Anatomy Lab, and it is modeled after the Washington University's Central Neuroimaging Data Archive (CNDA). The NUNDA is powered by XNAT, an open source software package for managing neuroimaging and related data.

Proper citation: NUNDA (RRID:SCR_013664) Copy   

•   Source: SciCrunch Registry

http://tela.biostr.washington.edu/cgi-bin/repos/bmap_repo/main-menu.pl

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 11, 2023. An experiment management system for researchers studying language organization in the brain. Data from thirteen patients are available as a public demo. Language Map EMS

Proper citation: Language Map Experiment Management System (RRID:SCR_004562) Copy   

•   Source: SciCrunch Registry

http://www.scandb.org/newinterface/about.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on March 17, 2022. A large-scale database of genetics and genomics data associated to a web-interface and a set of methods and algorithms that can be used for mining the data in it. The database contains two categories of single nucleotide polymorphism (SNP) annotations: # Physical-based annotation where SNPs are categorized according to their position relative to genes (intronic, inter-genic, etc.) and according to linkage disequilibrium (LD) patterns (an inter-genic SNP can be annotated to a gene if it is in LD with variation in the gene). # Functional annotation where SNPs are classified according to their effects on expression levels, i.e. whether they are expression quantitative trait loci (eQTLs) for that gene. SCAN can be utilized in several ways including: (i) queries of the SNP and gene databases; (ii) analysis using the attached tools and algorithms; (iii) downloading files with SNP annotation for various GWA platforms. . eQTL files and reported GWAS from NHGRI may be downloaded., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: SCAN (RRID:SCR_005185) Copy   

•   Source: SciCrunch Registry

http://www.neuroepigenomics.org/methylomedb/

A database containing genome-wide brain DNA methylation profiles for human and mouse brains. The DNA methylation profiles were generated by Methylation Mapping Analysis by Paired-end Sequencing (Methyl-MAPS) method and analyzed by Methyl-Analyzer software package. The methylation profiles cover over 80% CpG dinucleotides in human and mouse brains in single-CpG resolution. The integrated genome browser (modified from UCSC Genome Browser allows users to browse DNA methylation profiles in specific genomic loci, to search specific methylation patterns, and to compare methylation patterns between individual samples. Two species were included in the Brain Methylome Database: human and mouse. Human postmortem brain samples were obtained from three distinct cortical regions, i.e., dorsal lateral prefrontal cortex (dlPFC), ventral prefrontal cortex (vPFC), and auditory cortex (AC). Human samples were selected from our postmortem brain collection with extensive neuropathological and psychopathological data, as well as brain toxicology reports. The Department of Psychiatry of Columbia University and the New York State Psychiatric Institute have assembled this brain collection, where a validated psychological autopsy method is used to generate Axis I and II DSM IV diagnoses and data are obtained on developmental history, history of psychiatric illness and treatment, and family history for each subject. The mouse sample (strain 129S6/SvEv) DNA was collected from the entire left cerebral hemisphere. The three human brain regions were selected because they have been implicated in the neuropathology of depression and schizophrenia. Within each cortical region, both disease and non-psychiatric samples have been profiled (matching subjects by age and sex in each group). Such careful matching of subjects allows one to perform a wide range of queries with the ability to characterize methylation features in non-psychiatric controls, as well as detect differentially methylated domains or features between disease and non-psychiatric samples. A total of 14 non-psychiatric, 9 schizophrenic, and 6 depression methylation profiles are included in the database.

Proper citation: MethylomeDB (RRID:SCR_005583) Copy   

•   Source: SciCrunch Registry

https://balsa.wustl.edu/

Database for hosting and sharing neuroimaging and neuroanatomical datasets for human and primate species. Includes 1) curated, user created Study datasets, extensively analyzed neuroimaging data associated with published figures/manuscripts, 2) Reference datasets mapped to brain atlas surfaces and volumes in human and nonhuman primates for use as general resources (e.g., published cortical parcellations), and 3) ConnectomeDB powered by BALSA for distributing HCP-Young Adult and related HCP-style processed imaging and phenotypic datasets. Datasets in BALSA may include PMID and/or DOI that links them directly to relevant publications.

Proper citation: BALSA (RRID:SCR_022960) Copy   

•   Source: SciCrunch Registry

http://www.nihpromis.org/

Repository of person centered measures that evaluates and monitors physical, mental, and social health in adults and children.

Proper citation: Patient-Reported Outcomes Measurement Information System (RRID:SCR_004718) Copy   

•   Source: SciCrunch Registry

http://ki.se/meb/star

Large, ongoing, multifactorial study based on nation-wide ascertainment of patients with schizophrenia and bipolar disorder through the Swedish Twin Registry to include both neuroimaging data, neurocognitive function, molecular genetic data and early adverse environmental factors in the same model in a genetic sensitive design. Swedish schizophrenia research will benefit from this large study database of in total 240 affected and healthy twin pairs collected over a 5 year period. The specific aims are: * To elucidate neural endophenotypes for schizophrenia and bipolar disorder and to clarify the extent of overlap in these features between the two syndromes. * To investigate candidate genes and genomic regions for linkage and association with neural endophenotypes for schizophrenia and bipolar disease. * To determine the contributions of adverse prenatal and perinatal conditions to neural changes associated with schizophrenia and bipolar disease. Types of samples * EDTA whole blood * DNA * RNA Number of sample donors: 251 (June 2010)

Proper citation: KI Biobank - STAR (RRID:SCR_005923) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000674.v1.p1

Human genetics data from an immense (78,000) and ethnically diverse population available for secondary analysis to qualified researchers through the database of Genotypes and Phenotypes (dbGaP). It offers the opportunity to identify potential genetic risks and influences on a broad range of health conditions, particularly those related to aging. The GERA cohort is part of the Research Program on Genes, Environment, and Health (RPGEH), which includes more than 430,000 adult members of the Kaiser Permanente Northern California system. Data from this larger cohort include electronic medical records, behavioral and demographic information from surveys, and saliva samples from 200,000 participants obtained with informed consent for genomic and other analyses. The RPGEH database was made possible largely through early support from the Robert Wood Johnson Foundation to accelerate such health research. The genetic information in the GERA cohort translates into more than 55 billion bits of genetic data. Using newly developed techniques, the researchers conducted genome-wide scans to rapidly identify single nucleotide polymorphisms (SNPs) in the genomes of the people in the GERA cohort. These data will form the basis of genome-wide association studies (GWAS) that can look at hundreds of thousands to millions of SNPs at the same time. The RPGEH then combined the genetic data with information derived from Kaiser Permanente''s comprehensive longitudinal electronic medical records, as well as extensive survey data on participants'' health habits and backgrounds, providing researchers with an unparalleled research resource. As information is added to the Kaiser-UCSF database, the dbGaP database will also be updated.

Proper citation: Resource for Genetic Epidemiology Research on Adult Health and Aging (RRID:SCR_010472) Copy   

•   Source: SciCrunch Registry

http://web.stanford.edu/group/barres_lab/brain_rnaseq.html

Database containing RNA-Seq transcriptome and splicing data from glia, neurons, and vascular cells of cerebral cortex. Collection of RNA-Seq transcriptome and splicing data from glia, neurons, and vascular cells of mouse cerebral cortex. RNA-Seq of cell types isolated from mouse and human brain.

Proper citation: Brain RNA-Seq (RRID:SCR_013736) Copy   

•   Source: SciCrunch Registry