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http://HIVBrainSeqDB.org

The HIV Brain Sequence Database (HIVBrainSeqDB) is a public database of HIV envelope sequences, directly sequenced from brain and other tissues from the same patients. For inclusion in the database, sequences must: (i) be deposited in Genbank; (ii) include some portion of the HIV env region; (iii) be clonal, amplified directly from tissue; and (iv) be sampled from the brain, or sampled from a patient for which the database already contains brain sequence. Sequences are annotated with clinical data including viral load, CD4 count, antiretroviral status, neurocognitive impairment, and neuropathological diagnosis, all curated from the original publication. Tissue source is coded using an anatomical ontology, the Foundational Model of Anatomy, to capture the maximum level of detail available, while maintaining ontological relationships between tissues and their subparts. 44 tissue types are represented within the database, grouped into 4 categories: (i) brain, brainstem, and spinal cord; (ii) meninges, choroid plexus, and CSF; (iii) blood and lymphoid; and (iv) other (bone marrow, colon, lung, liver, etc). Currently, the database contains 2517 envelope sequences from 90 patients, obtained from 22 published studies. 1272 sequences are from brain; the remaining 1245 are from blood, lymph node, spleen, bone marrow, colon, lung and other non-brain tissues. The database interface utilizes a faceted interface, allowing real-time combination of multiple search parameters to assemble a meta-dataset, which can be downloaded for further analysis. This online resource will greatly facilitate analysis of the genetic aspects of HIV macrophage tropism, HIV compartmentalization and evolution within the brain and other tissue reservoirs, and the relationship of these findings to HIV-associated neurological disorders and other clinical consequences of HIV infection.

Proper citation: HIV Brain Sequence Database (RRID:SCR_008819) Copy   

•   Source: SciCrunch Registry

http://neuromorphometrics.com/?page_id=23

Collection of neuroanatomically labeled MRI brain scans, created by neuroanatomical experts. Regions of interest include the sub-cortical structures (thalamus, caudate, putamen, hippocampus, etc), along with ventricles, brain stem, cerebellum, and gray and white matter and sub-divided cortex into parcellation units that are defined by gyral and sulcal landmarks.

Proper citation: Manually Labeled MRI Brain Scan Database (RRID:SCR_009604) Copy   

•   Source: SciCrunch Registry

http://mindboggle.info

Mindboggle (http://mindboggle.info) is open source software for analyzing the shapes of brain structures from human MRI data. The following publication in PLoS Computational Biology documents and evaluates the software: Klein A, Ghosh SS, Bao FS, Giard J, Hame Y, Stavsky E, Lee N, Rossa B, Reuter M, Neto EC, Keshavan A. (2017) Mindboggling morphometry of human brains. PLoS Computational Biology 13(3): e1005350. doi:10.1371/journal.pcbi.1005350

Proper citation: Mindboggle (RRID:SCR_002438) Copy   

•   Source: SciCrunch Registry

http://neuromab.ucdavis.edu/

A national mouse monoclonal antibody generating resource for biochemical and immunohistochemical applications in mammalian brain. NeuroMabs are generated from mice immunized with synthetic and recombinant immunogens corresponding to components of the neuronal proteome as predicted from genomic and other large-scale cloning efforts. Comprehensive biochemical and immunohistochemical analyses of human, primate and non-primate mammalian brain are incorporated into the initial NeuroMab screening procedure. This yields a subset of mouse mAbs that are optimized for use in brain (i.e. NeuroMabs): for immunocytochemical-based imaging studies of protein localization in adult, developing and pathological brain samples, for biochemical analyses of subunit composition and post-translational modifications of native brain proteins, and for proteomic analyses of native brain protein networks. The NeuroMab facility was initially funded with a five-year U24 cooperative grant from NINDS and NIMH. The initial goal of the facility for this funding period is to generate a library of novel NeuroMabs against neuronal proteins, initially focusing on membrane proteins (receptors/channels/transporters), synaptic proteins, other neuronal signaling molecules, and proteins with established links to disease states. The scope of the facility was expanded with supplements from the NIH Blueprint for Neuroscience Research to include neurodevelopmental targets, the NIH Roadmap for Medical Research to include epigenetics targets, and NIH Office of Rare Diseases Research to include rare disease targets. These NeuroMabs will then be produced on a large scale and made available to the neuroscience research community on an inexpensive basis as tissue culture supernatants or purified immunoglobulin by Antibodies Inc. The UC Davis/NIH NeuroMab Facility makes NeuroMabs available directly to end users and is unable to accommodate sales to distributors for third party distribution. Note, NeuroMab antibodies are now offered through antibodiesinc.

Proper citation: NeuroMab (RRID:SCR_003086) Copy   

•   Source: SciCrunch Registry

https://www.nitrc.org/projects/neurolabels

This resource was created to host descriptions of protocols, definitions and rules for the reliable identification and localization of human brain anatomy and discussions of best practices in brain labeling. Project for manual anatomical labeling of human brain MRI data, and the visual presentation of labeled brain images.

Proper citation: BrainColor: Collaborative Open Labeling Online Resource (RRID:SCR_006377) Copy   

•   Source: SciCrunch Registry

http://nimhstemcells.org/

Induced Pluripotent Stem Cell (iPSC) and Source Cells available for distribution for postnatal-to-adult human control and patient-derived cells and their reprogrammed derivatives in support of stem cell research relevant to mental disorders. This includes but is not limited to anxiety disorders, attention deficit hyperactivity disorder, autism spectrum disorders, bipolar disorder, borderline personality disorder, depression, eating disorders, obsessive-compulsive disorder, panic disorder, post-traumatic stress disorder, and schizophrenia. The capabilities of the repository range from derivation and banking of primary source cells from postnatal through adult human subject tissue to more comprehensive banking and validation of induced pluripotent stem cells (iPSCs) or similar reprogrammed / de-differentiated cells. Please send a message with the Contact page if you wish to contribute source cells or iPSC.

Proper citation: NIMH Stem Cell Center (RRID:SCR_006682) Copy   

•   Source: SciCrunch Registry

http://nimh-repository.rti.org/

A program that synthesizes, purifies, and distributes otherwise unavailable essential compounds to stimulate basic and clinical research in psychopharmacology relevant to mental health in areas such as the molecular pharmacology and signaling of CNS receptors, longitudinal studies to evaluate the molecular, biochemical, and behavioral actions of psychoactive compounds, and functional brain imaging in both primates and humans. WHAT IS AVAILABLE: * Ligands for CNS receptors, radiolabeled compounds for autoradiography and neuroimaging, biochemical markers, drug analogs and metabolites, and reference standards * Synthesis (including GMP) of promising compounds for mental health research, including preclinical toxicology and safety studies, especially compounds for PET neuroimaging * A listing of currently available NIMH CSDSP compounds is available online at www.nimh-repository.rti.org. RTI International scientists can provide investigators with technical assistance and additional information about the compounds on request. Data sheets containing purity, storage, and handling information are supplied with all NIMH CSDSP compounds. WHO IS ELIGIBLE: Investigators involved in basic or clinical research relevant to mental health are eligible to submit requests. To learn more about current NIMH research areas, please visit the NIMH website at www.nimh.nih.gov. NIMH CSDSP compounds are free to qualified academic investigators, but payment may be required from nonacademic requestors. Investigators interested in obtaining radiolabeled compounds but uncertain about what type of label or specific activity would work best for them may obtain help by communicating with the technical contacts listed on the website.

Proper citation: NIMH Chemical Synthesis and Drug Supply Program (RRID:SCR_004921) Copy   

•   Source: SciCrunch Registry

http://senselab.med.yale.edu

The SenseLab Project is a long-term effort to build integrated, multidisciplinary models of neurons and neural systems. It was founded in 1993 as part of the original Human Brain Project, which began the development of neuroinformatics tools in support of neuroscience research. It is now part of the Neuroscience Information Framework (NIF) and the International Neuroinformatics Coordinating Facility (INCF). The SenseLab project involves novel informatics approaches to constructing databases and database tools for collecting and analyzing neuroscience information, using the olfactory system as a model, with extension to other brain systems. SenseLab contains seven related databases that support experimental and theoretical research on the membrane properties: CellPropDB, NeuronDB, ModelDB, ORDB, OdorDB, OdorMapDB, BrainPharmA pilot Web portal that successfully integrates multidisciplinary neurocience data.

Proper citation: SenseLab (RRID:SCR_007276) Copy   

•   Source: SciCrunch Registry

http://www.agre.org/index.cfm

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 11, 2023. A private repository of clinical and genetic information on families with autism. Genetic and clinical data are obtained from families that have more than one family member diagnosed with an Autism Spectrum Disorder. The biological samples, along with the accompanying clinical data, are made available to AGRE-approved researchers worldwide. As they become available, additional family pedigrees will be posted in the online catalog. Cell lines have been established for the majority of families in this collection and serum/plasma is available on a subset of the subjects until stocks are depleted. The diagnosis of autism has been made using the standard Autism Diagnostic Interview-Revised (ADI-R) algorithm and the Autism Diagnostic Observation Scale (ADOS-G). Detailed birth and medical histories (including basic dysmorphology assessments) on children as well as family and medical information for parents and unaffected siblings, are available for nearly all families. DNA, cell lines, serum, plasma and clinical information are made available to AGRE-approved researchers for analysis.

Proper citation: Autism Genetic Resource Exchange (RRID:SCR_004403) Copy   

•   Source: SciCrunch Registry

http://surfer.nmr.mgh.harvard.edu/fswiki/Tracula

Software tool developed for automatically reconstructing a set of major white matter pathways in the brain from diffusion weighted images using probabilistic tractography. This method utilizes prior information on the anatomy of the pathways from a set of training subjects. By incorporating this prior knowledge in the reconstruction procedure, our method obviates the need for manual intervention with the tract solutions at a later stage and thus facilitates the application of tractography to large studies. The trac-all script is used to preprocess raw diffusion data (correcting for eddy current distortion and B0 field inhomogenities), register them to common spaces, model and reconstruct major white matter pathways (included in the atlas) without any manual intervention. trac-all may be used to execute all the above steps or parts of it depending on the dataset and user''''s preference for analyzing diffusion data. Alternatively, scripts exist to execute chunks of each processing pipeline, and individual commands may be run to execute a single processing step. To explore all the options in running trac-all please refer to the trac-all wiki. In order to use this script to reconstruct tracts in Diffusion images, all the subjects in the dataset must have Freesurfer Recons.

Proper citation: TRACULA (RRID:SCR_013152) Copy   

•   Source: SciCrunch Registry

http://becs.aalto.fi/en/research/bayes/drifter/

Model based Bayesian method for eliminating physiological noise from fMRI data. This algorithm uses image voxel analysis to isolate the cardiac and respiratory noise from the relevant data.

Proper citation: DRIFTER (RRID:SCR_014937) Copy   

•   Source: SciCrunch Registry

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

A software application developed to support computational anatomy and shape analysis. The capabilities of CAWorks include: interactive landmark placement to create segmentation (mask) of desired region of interest; specialized landmark placement plugins for subcortical structures such as hippocampus and amygdala; support for multiple Medical Imaging data formats, such as Nifti, Analyze, Freesurfer, DICOM and landmark data; Quadra Planar view visualization; and shape analysis plugin modules, such as Large Deformation Diffeomorphic Metric Mapping (LDDMM). Specific plugins are available for landmark placement of the hippocampus, amygdala and entorhinal cortex regions, as well as a browser plugin module for the Extensible Neuroimaging Archive Toolkit.

Proper citation: CAWorks (RRID:SCR_014185) Copy   

•   Source: SciCrunch Registry

https://github.com/kstreet13/slingshot

Software R package for identifying and characterizing continuous developmental trajectories in single cell data. Cell lineage and pseudotime inference for single-cell transcriptomics.

Proper citation: Slingshot (RRID:SCR_017012) Copy   

•   Source: SciCrunch Registry

https://community.brain-map.org/t/allen-human-reference-atlas-3d-2020-new/405

Parcellation of adult human brain in 3D, labeling every voxel with brain structure spanning 141 structures. These parcellations were drawn and adapted from prior 2D version of adult human brain atlas.

Proper citation: Allen Human Reference Atlas, 3D, 2020 (RRID:SCR_017764) Copy   

•   Source: SciCrunch Registry

https://openwetware.org/wiki/HughesLab:JTK_Cycle

Software R package for Detecting Rhythmic Components in Genome-Scale Data Sets. Non-parametric algorithm to identify rhythmic components in large datasets. Identifies and characterizes cycling variables in large datasets.

Proper citation: JTK_CYCLE (RRID:SCR_017962) Copy   

•   Source: SciCrunch Registry

https://cloudreg.neurodata.io/

Software automated, terascale, cloud based image analysis pipeline for preprocessing and cross modal, nonlinear registration between volumetric datasets with artifacts. Automatic terabyte scale cross modal brain volume registration.

Proper citation: CloudReg (RRID:SCR_022795) Copy   

•   Source: SciCrunch Registry

http://autopatcher.org/

Software tool for neuronal recording in intact brain.

Proper citation: Autopatcher (RRID:SCR_017464) Copy   

•   Source: SciCrunch Registry

https://github.com/vlchaplin/pyRayleighCuda

Python Rayleigh-Sommerfeld integral for acoustics with optional CUDA graphics processing unit (GPU) implementation.

Proper citation: pyRayleighCuda (RRID:SCR_017453) Copy   

•   Source: SciCrunch Registry

https://yeatmanlab.github.io/pyAFQ/

Software package focused on automated delineation of major fiber tracts in individual human brains, and quantification of tissue properties within the tracts.Software for automated processing and analysis of diffusion MRI data. Automates tractometry.

Proper citation: Automated Fiber Quantification in Python (RRID:SCR_023366) Copy   

•   Source: SciCrunch Registry

https://portal.brain-map.org/atlases-and-data/bkp/mapmycells

MapMyCells maps single cell and spatial transcriptomics data sets to massive, high-quality, and high-resolution cell type taxonomies. It enables speeding up the creation of brain reference atlases by facilitating the integration of datasets from the scientific community with a shared reference. MapMyCells is part of the growing Brain Knowledge Platform. Its key advantage is scale: researchers can provide up to 327 million cell-gene pairs from their own data, a huge leap forward for working with whole-brain datasets. Allen Institute and its collaborators continue to add new reference taxonomies and algorithms to MapMyCells.

Proper citation: MapMyCells (RRID:SCR_024672) Copy   

•   Source: SciCrunch Registry