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https://stemcells.nindsgenetics.org/

Cell sources currently include fibroblasts and/or induced pluripotent stem cells for Alzheimer's Disease, Amyotrophic Lateral Sclerosis (ALS), Ataxia-telangiectasia, Frontotemporal Lobar Degeneration (FTD), Huntington's Disease, Parkinson's Disease, and healthy controls. Cell sources, including isogenic cell lines for current and new diseases covered by the NINDS will be added over the next several years.

Proper citation: The NINDS Human Cell and Data Repository (NHCDR) (RRID:SCR_016319) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/validate29/

Atlas was created from MRI scans of squirrel monkey brains. The atlas is currently comprised of multiple anatomical templates, diffusion MRI templates, and ex vivo templates. In addition, the templates are combined with histologically defined cortical labels, and diffusion tractography defined white matter labels.

Proper citation: VALiDATe29 Squirrel Monkey Brain Atlas (RRID:SCR_015542) Copy   

•   Source: SciCrunch Registry

http://www.hms.harvard.edu/research/brain/atlas.html

2D mouse brain atlas of high quality coronal Nissl- and myelin-stained sections with labels, 3D images of hippocampal formation and limited other brain structures. The data for this digital atlas are based on the Atlas of the Mouse Brain and Spinal Cord, authored by Richard L. Sidman, Jay. B. Angevine and Elizabeth Taber Pierce, published as a hard cover book by Harvard University Press in 1971 and currently out of print. C57BL/6J strain adult specimens were used in creating the atlas.

Proper citation: High Resolution Mouse Brain Atlas (RRID:SCR_006063) Copy   

•   Source: SciCrunch Registry

http://llama.mshri.on.ca/funcassociate/

A web-based tool that accepts as input a list of genes, and returns a list of GO attributes that are over- (or under-) represented among the genes in the input list. Only those over- (or under-) representations that are statistically significant, after correcting for multiple hypotheses testing, are reported. Currently 37 organisms are supported. In addition to the input list of genes, users may specify a) whether this list should be regarded as ordered or unordered; b) the universe of genes to be considered by FuncAssociate; c) whether to report over-, or under-represented attributes, or both; and d) the p-value cutoff. A new version of FuncAssociate supports a wider range of naming schemes for input genes, and uses more frequently updated GO associations. However, some features of the original version, such as sorting by LOD or the option to see the gene-attribute table, are not yet implemented. Platform: Online tool

Proper citation: FuncAssociate: The Gene Set Functionator (RRID:SCR_005768) 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://senselab.med.yale.edu/cellpropdb

A repository for data regarding membrane channels, receptor and neurotransmitters that are expressed in specific types of cells. The database is presently focused on neurons but will eventually include other cell types, such as glia, muscle, and gland cells. This resource is intended to: * Serve as a repository for data on gene products expressed in different brain regions * Support research on cellular properties in the nervous system * Provide a gateway for entering data into the cannonical neuron forms in NeuronDB * Identify receptors across neuron types to aid in drug development * Serve as a first step toward a functional genomics of nerve cells * Serve as a teaching aid

Proper citation: Cell Properties Database (RRID:SCR_007285) 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://www.nitrc.org/projects/pennhippoatlas/

Atlas of segmented and normalized high-resolution postmortem MRI of the human hippocampus. Additional data (raw images) is available through the SCM link. It requires knowing how to use CVS.

Proper citation: Penn Hippocampus Atlas (RRID:SCR_000421) Copy   

•   Source: SciCrunch Registry

http://neurosurgery.ucsf.edu/index.php/research_tissue_bank.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 4th,2023. Brain Tumor Research Center Tissue Bank began collecting tissue in 1978 and has established an organized repository of characterized tissues--frozen, paraffin-embedded, blood and cultures--that are maintained in a manner useful for a wide range of studies. Samples are collected only from patients who have agreed to have their tissues banked and used for future research. Consent documents are maintained in a secure area and associated clinical data are held in a double-password protected computer database. Each sample received into the Tissue Bank is non-identifying number. No protected health information (PHI) is released. To obtain samples, investigators submit a request form to the Manager. The request form requires an explanation of the tissue requested (type, number of samples, justification), description of the study, CHR approval (see new policy regarding human vs. non-human research) and Project Leader authorization. The Manager reviews each request for feasibility before presentation to the Scientific Core Committee. The UCSF Neurosurgery Tissue Bank makes its inventory of stock cell lines available to all investigators. Requested cells are grown in T-25 flasks and shipped FedEx Priority Overnight at the receipient's expense. However, if you prefer, we can ship the frozen cells, packed in dry ice. (Note: some countries restrict dry ice shipments.)

Proper citation: UCSF Brain Tumor Tissue Bank (RRID:SCR_000647) Copy   

•   Source: SciCrunch Registry

http://med.emory.edu/ADRC/research/tissue_biospecimen_banking_facility.html

The Alzheimer's Disease Research Center at Emery University maintains an active brain bank to facilitate the acquisition, storage, handling and distribution of well-characterized autopsy brain tissue and other materials to investigators. It contains frozen tissue and brain specimens, formalin fixed tissue, paraformaldehyde fixed tissue, and cryopreserved tissue. The ADRC also has access to tissues and samples related to other neurodegenerative diseases. It contains plasma samples, serum samples, lymphoblast cell lines, and cerebrospinal fluid.

Proper citation: Emory ADRC Tissue and Biospecimen Banking Facility (RRID:SCR_000551) 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://mus.well.ox.ac.uk/gscandb/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Database / display tool of genome scans, with a web interface that lets the user view the data. It does not perform any analyses - these must be done by other software, and the results uploaded into it. The basic features of GSCANDB are: * Parallel viewing of scans for multiple phenotypes. * Parallel analyses of the same scan data. * Genome-wide views of genome scans * Chromosomal region views, with zooming * Gene and SNP Annotation is shown at high zoom levels * Haplotype block structure viewing * The positions of known Trait Loci can be overlayed and queried. * Links to Ensembl, MGI, NCBI, UCSC and other genome data browsers. In GSCANDB, a genome scan has a wide definition, including not only the usual statistical genetic measures of association between genetic variation at a series of loci and variation in a phenotype, but any quantitative measure that varies along the genome. This includes for example competitive genome hybridization data and some kinds of gene expression measurements.

Proper citation: WTCHG Genome Scan Viewer (RRID:SCR_001635) Copy   

•   Source: SciCrunch Registry

http://nifti.nimh.nih.gov/

Coordinated and targeted service, training, and research to speed the development and enhance the utility of informatics tools related to neuroimaging. The initial focus will be on tools that are used in fMRI. If NIfTI proves useful in addressing informatics issues in the fMRI research community, it may be expanded to address similar issues in other areas of neuroimaging. Objectives of NIfTI * Enhancement of existing informatics tools used widely in neuroimaging research * Dissemination of neuroimaging informatics tools and information about them * Community-based approaches to solving common problems, such as lack of interoperability of tools and data * Unique training activities and research career development opportunities to those in the tool-user and tool-developer communities * Research and development of the next generation of neuroimaging informatics tools

Proper citation: Neuroimaging Informatics Technology Initiative (RRID:SCR_003141) 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

https://rmats.sourceforge.io

Software tool to detect differential alternative splicing events from RNA-Seq data. Calculates P-value and false discovery rate that difference in isoform ratio of gene between two conditions exceeds given user-defined threshold. From RNA-Seq data can automatically detect and analyze alternative splicing events corresponding to all major types of alternative splicing patterns. Handles replicate RNA-Seq data from both paired and unpaired study design.

Proper citation: rMATS (RRID:SCR_023485) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/

Software repository for comparing structural (MRI) and functional neuroimaging (fMRI, PET, EEG, MEG) software tools and resources. NITRC collects and points to standardized information about structural or functional neuroimaging tool or resource.

Proper citation: NeuroImaging Tools and Resources Collaboratory (NITRC) (RRID:SCR_003430) Copy   

•   Source: SciCrunch Registry

http://krasnow1.gmu.edu/cn3/index3.html

Multidisciplinary research team devoted to the study of basic neuroscience with a specific interest in the description and generation of dendritic morphology, and in its effect on neuronal electrophysiology. In the long term, they seek to create large-scale, anatomically plausible neural networks to model entire portions of a mammalian brain (such as a hippocampal slice, or a cortical column). Achievements by the CNG include the development of software for the quantitative analysis of dendritic morphology, the implementation of computational models to simulate neuronal structure, and the synthesis of anatomically accurate, large scale neuronal assemblies in virtual reality. Based on biologically plausible rules and biophysical determinants, they have designed stochastic models that can generate realistic virtual neurons. Quantitative morphological analysis indicates that virtual neurons are statistically compatible with the real data that the model parameters are measured from. Virtual neurons can be generated within an appropriate anatomical context if a system level description of the surrounding tissue is included in the model. In order to simulate anatomically realistic neural networks, axons must be grown as well as dendrites. They have developed a navigation strategy for virtual axons in a voxel substrate.

Proper citation: Computational Neuroanatomy Group (RRID:SCR_007150) Copy   

•   Source: SciCrunch Registry

http://brainml.org/goto.do?page=.home

Set of standards and practices for using XML to facilitate information exchange between user application software and neuroscience data repositories. It allows for common shared library routines to handle most of the data processing, but also supports use of structures specialized to the needs of particular neuroscience communities. This site also serves as a repository for BrainML models. (A BrainML model is an XML Schema and optional vocabulary files describing a data model for electronic representation of neuroscience data, including data types, formats, and controlled vocabulary. ) It focuses on layered definitions built over a common core in order to support community-driven extension. One such extension is provided by the new NIH-supported neuroinformatics initiative of the Society for Neuroscience, which supports the development of expert-derived terminology sets for several areas of neuroscience. Under a cooperative agreement, these term lists will be made available Open Source on this site.
The repository function of this site includes the following features:
* BrainML models are published in searchable, browsable form.
* Registered users may submit new models or new versions of existing models to accommodate data of interest. * BrainML model schema and vocabulary files are made available at fixed URLs to allow software applications to reference them.
* Users can check models and/or instance documents for correct format before submitting them using an online validation service.
To complement the BrainML modeling language, a set of protocols have been developed for BrainML document exchange between repositories and clients, for indexing of repositories, and for data query.

Proper citation: BrainML (RRID:SCR_007087) Copy   

•   Source: SciCrunch Registry

http://senselab.med.yale.edu/modeldb/

Curated database of published models so that they can be openly accessed, downloaded, and tested to support computational neuroscience. Provides accessible location for storing and efficiently retrieving computational neuroscience models.Coupled with NeuronDB. Models can be coded in any language for any environment. Model code can be viewed before downloading and browsers can be set to auto-launch the models. The model source code has to be available from publicly accessible online repository or WWW site. Original source code is used to generate simulation results from which authors derived their published insights and conclusions.

Proper citation: ModelDB (RRID:SCR_007271) Copy   

•   Source: SciCrunch Registry

http://trans.nih.gov/CEHP/

Trans-NIH project to assess the state of longitudinal and epidemiological research on demographic, social and biologic determinants of cognitive and emotional health in aging adults and the pathways by which cognitive and emotional health may reciprocally influence each other. A database of large scale longitudinal study relevant to healthy aging in 4 domains was created based on responses of investigators conducting these studies and is available for query. The four domains are: * Cognitive Health * Emotional Health * Demographic and Social Factors * Biomedical and Physiologic Factors

Proper citation: Cognitive and Emotional Health Project: The Healthy Brain (RRID:SCR_007390) Copy   

•   Source: SciCrunch Registry