Tools   Select Another Resource Report Type

http://www.neuroanatomy.ca/

The WEB ATLAS contains photographs of dissected brains showing important structures. The diagrams folder contains drawings showing functionally important parts of the brain as well as drawings of dissections adapted from C.G. Smith. We are particularly pleased to make Nan Cheney''s medical illustrations of the brain and the head available. The STROKE MODEL portion of the website has syndromes associated with strokes of different vessels of the brain as well as extensive diagrams and tables about the vessels of the brain. The 3D RECONSTRUCTIONS featured on this website were made from MRI scans through the brain - where indicated the source material was from the NIH Visible Human Project. The website will also contain material important for the neuroanatomy labs for med students at UBC. Weekly quizzes will help you keep up with studying the material, the podcasts will help you review material presented in the labs, and the weekly wikis will help you share information with your peers.

Proper citation: Neuroanatomy at UBC (RRID:SCR_008744) Copy   

•   Source: SciCrunch Registry

https://portal.dbmi.hms.harvard.edu/projects/GRDR/

Data repository of de-identified patient data, aggregated in a standardized manner, to enable analyses across many rare diseases and to facilitate various research projects, clinical studies, and clinical trials. The aim is to facilitate drug and therapeutics development, and to improve the quality of life for the many millions of people who are suffering from rare diseases. The goal of GRDR is to enable analyses of data across many rare diseases and to facilitate clinical trials and other studies. During the two-year pilot program, a web-based template will be developed to allow any patient organization to establish a rare disease patient registry. At the conclusion of the program, guidance will be available to patient groups to establish a registry and to contribute de-identified patient data to the GRDR repository. A Request for Information (RFI) was released on February 10, 2012 requesting information from patient groups about their interest in participating in a GRDR pilot project. ORDR selected 30 patient organizations to participate in this pilot program to test the different functionalities of the GRDR. Fifteen (15) organizations with established registries and 15 organizations that do not have patient registry. The 15 patient groups, each without a registry, were selected to assist in testing the implementation of the ORDR Common Data Elements (CDEs) in the newly developed registry infrastructure. These organizations will participate in the development and promotion of a new patient registry for their rare disease. The GRDR program will fund the development and hosting of the registry during the pilot program. Thereafter, the patient registry is expected to be self-sustaining.The 15 established patient registries were selected to integrate their de-identified data into the GRDR to evaluate the data mapping and data import/export processes. The GRDR team will assist these organizations in mapping their existing registry data to the CDEs. Participating registries must have a means to export their de-identified registry data into a specified data format that will facilitate loading the data into the GRDR repository on a regular basis. The GRDR will also develop the capability to link patients'''' data and medical information to donated biospecimens by using a Voluntary Global Unique Patient Identifier (GUID). The identifier will enable the creation of an interface between the patient registries that are linked to biorepositories and the Rare Disease Human Biospecimens/Biorepositories (RD-HUB) http://biospecimens.ordr.info.nih.gov/.

Proper citation: GRDR (RRID:SCR_008978) Copy   

•   Source: SciCrunch Registry

http://www.mssm.edu/research/programs/manhattan-hiv-brain-bank/

Biorepository of tissues and fluids relevant for the neurologic, neuropsychologic, psychiatric and neuropathologic manifestations of HIV infection, linked to medical records and an on-going clinical trial for research use by the scientific community. The MHBB conducts a longitudinal, observational study that follows a group of HIV-infected individuals who have agreed to be fluid and organ donors for the purposes of AIDS research. They are currently the largest, multidisciplinary neuroAIDS cohort in New York City, the epicenter of the US HIV epidemic. Research participants undergo regular neurologic, neuropsychologic, and psychiatric evaluations, and provide body fluid samples that are linked to clinical information. Upon their demise, study participants become organ donors. This program has supplied clinical information, tissue, and fluid samples to over 70 qualified AIDS researchers across America, Europe and Australia. In fulfilling its resource mission, the MHBB functions as part of the National NeuroAIDS Tissue Consortium (NNTC). MHBB provides a means by which people living with HIV can be engaged in the struggle to improve our knowledge about HIV infection and the damage it causes to the body.

Proper citation: Manhattan HIV Brain Bank (RRID:SCR_010520) Copy   

•   Source: SciCrunch Registry

http://homer.ucsd.edu/

Software tools for Motif Discovery and next-gen sequencing analysis. Used for analyzing ChIP-Seq, GRO-Seq, RNA-Seq, DNase-Seq, Hi-C and numerous other types of functional genomics sequencing data sets. Collection of command line programs for unix style operating systems written in Perl and C++.

Proper citation: HOMER (RRID:SCR_010881) Copy   

•   Source: SciCrunch Registry

http://www.rcsb.org/#Category-welcome

Collection of structural data of biological macromolecules. Database of information about 3D structures of large biological molecules, including proteins and nucleic acids. Users can perform queries on data and analyze and visualize results.

Proper citation: Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) (RRID:SCR_012820) Copy   

•   Source: SciCrunch Registry

http://ciliate.org/index.php/home/welcome

TGD Wiki is a user-updatable database of information about the Tetrahymena thermophila genome sequence determined at The Institute for Genomic Research (TIGR). TGD Wiki provides information on the genome, genes, and proteins of Tetrahymena collected from the scientific literature, research community and many other resources. In order to keep the information in our database as current as possible, we will soon be inviting the members of the Tetrahymena community to add and update these annotations to reflect published research. TGD Wiki currently offers the following features: * Free, unrestricted read access to all available data * Sequence and annotation data for 24,725 genes (TIGR v.2008) * GBrowse genome browser with links to and from each gene page (TIGR v.2006) * BLAST searching of the TIGR gene models and genome sequence (TIGR v.2006) Tetrahymena Genome Database (TGD) Wiki began in 2004 at Stanford University using the schema and programs of its parent project, Saccharomyces Genome Database. TGD Wiki is now a collaboration between Bradley University, Stanford University, and Cornell University. As we begin TGD Wiki at its new home at Bradley University, the TGD Wiki database contains the following data from TGD: * Gene Names and Aliases * Gene Descriptions * Gene Ontology (GO) Annotations * Homologs (similar genes in selected organisms) * Protein Domains * Associated Literature * Paragraphs (longer, free-text descriptions of gene function, structure, and significance) * Coding and Protein Sequences We have updated the following fields to match the newest gene model sequences (TIGR v.2008): Coding and Protein Sequences, Protein Domains and Gene Descriptions. We will also be recalculating the GO Annotations (IEA evidence code) and Homologs as part of our effort to keep the annotations in TGD Wiki as current as possible. We will be relying on members of the Tetrahymena community to maintain high-quality, updated annotations in the remainder of the fields using our annotation interface. Also setting up new database superdb - for unpublished data Look at Ciliate.org for news on this and other new databases

Proper citation: TGD (RRID:SCR_012803) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/pmc/about/pubreader/

A web application which serves as an alternate way to read scientific literature in PubMed Central and Bookshelf. PubReader features an easy-to-read multi-column display, a figure strip for access to figures, and a search function. It is designed especially to support reading on tablets and other smaller devices but is available for reading on laptops and desktops.

Proper citation: PubReader (RRID:SCR_013814) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/gscca_2013/

Group Sparse Canonical Correlation Analysis is a method designed to study the mutual relationship between two different types of data.

Proper citation: Group Sparse Canonical Correlation Analysis (RRID:SCR_014977) Copy   

•   Source: SciCrunch Registry

http://cerebrovascularportal.org

Portal enables browsing, searching, and analysis of human genetic information linked to cerebrovascular disease and related traits, while protecting the integrity and confidentiality of the underlying data.

Proper citation: Cerebrovascular Disease Knowledge Portal (RRID:SCR_015628) Copy   

•   Source: SciCrunch Registry

http://ftp://ftp.ncbi.nlm.nih.gov/pub/mhc/rbc/Final Archive

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 23, 2019.BGMUT was database that provided publicly accessible platform for DNA sequences and curated set of blood mutation information. Data Archive are available at ftp://ftp.ncbi.nlm.nih.gov/pub/mhc/rbc/Final Archive.

Proper citation: Blood Group Antigen Gene Mutation Database (RRID:SCR_002297) Copy   

•   Source: SciCrunch Registry

http://www.biostars.org/

A question answer forum for scientists, focusing on methods in bioinformatics, computational genomics and biological data analysis. They welcome detailed and specific posts, written clearly and simply.

Proper citation: BioStar (RRID:SCR_002580) Copy   

•   Source: SciCrunch Registry

http://www.cbil.upenn.edu/RAD

THIS RESOURCE IS NO LONGER IN SERVICE, Documented on March 24, 2014. A resource for gene expression studies, storing highly curated MIAME-compliant studies (i.e. experiments) employing a variety of technologies such as filter arrays, 2-channel microarrays, Affymetrix chips, SAGE, MPSS and RT-PCR. Data were available for querying and downloading based on the MGED ontology, publications or genes. Both public and private studies (the latter viewable only by users having appropriate logins and permissions) were available from this website. Specific details on protocols, biomaterials, study designs, etc., are collected through a user-friendly suite of web annotation forms. Software has been developed to generate MAGE-ML documents to enable easy export of studies stored in RAD to any other database accepting data in this format. RAD is part of a more general Genomics Unified Schema (http://gusdb.org), which includes a richly annotated gene index (http://allgenes.org), thus providing a platform that integrates genomic and transcriptomic data from multiple organisms. NOTE: Due to changes in technology and funding, the RAD website is no longer available. RAD as a schema is still very much active and incorporated in the GUS (Genomics Unified Schema) database system used by CBIL (EuPathDB, Beta Cell Genomics) and others. The schema for RAD can be viewed along with the other GUS namespaces through our Schema Browser.

Proper citation: RNA Abundance Database (RRID:SCR_002771) Copy   

•   Source: SciCrunch Registry

http://www.credrivermice.org/

Project to provide Neuroscience Community with mouse strains that are suitable for tissue and cell-type-specific perturbation of gene function in nervous system. NIH Neuroscience Blueprint has established three centers in the USA for generation of genetically modified mice expressing CRE recombinases in nervous system on the C57BJ/6 genetic background. Mouse lines are generated at Cold Spring Harbor Lab, at Scripps Research Institute, and at Baylor College of Medicine.

Proper citation: CRE Driver Network (RRID:SCR_002720) Copy   

•   Source: SciCrunch Registry

http://insitu.fruitfly.org/cgi-bin/ex/insitu.pl

Database of embryonic expression patterns using a high throughput RNA in situ hybridization of the protein-coding genes identified in the Drosophila melanogaster genome with images and controlled vocabulary annotations. At the end of production pipeline gene expression patterns are documented by taking a large number of digital images of individual embryos. The quality and identity of the captured image data are verified by independently derived microarray time-course analysis of gene expression using Affymetrix GeneChip technology. Gene expression patterns are annotated with controlled vocabulary for developmental anatomy of Drosophila embryogenesis. Image, microarray and annotation data are stored in a modified version of Gene Ontology database and the entire dataset is available on the web in browsable and searchable form or MySQL dump can be downloaded. So far, they have examined expression of 7507 genes and documented them with 111184 digital photographs.

Proper citation: Patterns of Gene Expression in Drosophila Embryogenesis (RRID:SCR_002868) Copy   

•   Source: SciCrunch Registry

https://github.com/sqjin/CellChat

Software R toolkit for inference, visualization and analysis of cell-cell communication from single cell data.Quantitatively infers and analyzes intercellular communication networks from single-cell RNA-sequencing data. Predicts major signaling inputs and outputs for cells and how those cells and signals coordinate for functions using network analysis and pattern recognition approaches. Classifies signaling pathways and delineates conserved and context specific pathways across different datasets.

Proper citation: CellChat (RRID:SCR_021946) Copy   

•   Source: SciCrunch Registry

http://disco.neuinfo.org

DISCO is an information integration approach designed to facilitate interoperation among Internet resources. It consists of a set of tools and services that allows resource providers who maintain information to share it with automated systems such as NIF. NIF is then able to harvest the information and keep those sets of information up-to-date. How is this accomplished? By using a series of files and/or scripts which are then placed in the root directory of the resource developer''s resource. (NIF can also host the files on its servers and crawl for changes there.) Once the files of the resource providers are in place, and DISCO is notified, the DISCO server can then recognize and consume the information shared, providing machine understandable information to NIF Integrator Servers (also known as Aggregators) about your resource. What can DISCO do for my resource? * Inform search engines about your resource and keep your NIF Registry resource description up-to-date. * Expose your data (semi-structured datasets or fields within your structured database) through NIF''s Data Federation you choose what data will be shared. * Create links from an NCBI database (e.g., PubMed, Protein, Nucleotide, etc.) to your data records in NIF using Entrez LinkOut. * Advertise your terminology or ontological information. * Share your resource''s news with the NIF community., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: DISCO (RRID:SCR_004586) Copy   

•   Source: SciCrunch Registry

http://www.essentialtremor.us/

Finding a cure for any neurological disorder begins with the scientific study of the disorder''s causes, processes, and development in the brain. For essential tremor (ET), rigorous study of this kind had not been undertaken until 2003, when the Essential Tremor Centralized Brain Repository (ETCBR) was established at Columbia University. For the past five years, brain tissue from ET donors has been collected, processed and compared alongside age-matched control brains at the ETCBR, and already several significant findings have been made. However, there is still much to learn and a severe shortage of ET brains for scientific study. If you have been diagnosed with essential tremor, donating your brain tissue in the hours immediately after your death is of utmost importance in providing crucial information about what causes ET. Direct analysis of the shape and number of nerve cells and their content will provide medical researchers with the information they need in order to understand this complex illness. By advancing our medical knowledge of ET, the gift of brain tissue is a central piece of the puzzle in the search to develop better treatments and find a cure.

Proper citation: Essential Tremor Centralized Brain Repository (RRID:SCR_004464) Copy   

•   Source: SciCrunch Registry

http://www.na-mic.org/

The National Alliance for Medical Image Computing (NA-MIC) is a multi-institutional, interdisciplinary team of computer scientists, software engineers, and medical investigators who develop computational tools for the analysis and visualization of medical image data. The purpose of the Center is to provide the infrastructure and environment for the development of computational algorithms and open-source technologies, and then oversee the training and dissemination of these tools to the medical research community. Electronic resources provided by NA-MIC include software, data, tutorials, presentations, and more.

Proper citation: National Alliance for Medical Image Computing (RRID:SCR_004460) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/biosystems/

Database that provides access to biological systems and their component genes, proteins, and small molecules, as well as literature describing those biosystems and other related data throughout Entrez. A biosystem, or biological system, is a group of molecules that interact directly or indirectly, where the grouping is relevant to the characterization of living matter. BioSystem records list and categorize components, such as the genes, proteins, and small molecules involved in a biological system. The companion FLink tool, in turn, allows you to input a list of proteins, genes, or small molecules and retrieve a ranked list of biosystems. A number of databases provide diagrams showing the components and products of biological pathways along with corresponding annotations and links to literature. This database was developed as a complementary project to (1) serve as a centralized repository of data; (2) connect the biosystem records with associated literature, molecular, and chemical data throughout the Entrez system; and (3) facilitate computation on biosystems data. The NCBI BioSystems Database currently contains records from several source databases: KEGG, BioCyc (including its Tier 1 EcoCyc and MetaCyc databases, and its Tier 2 databases), Reactome, the National Cancer Institute's Pathway Interaction Database, WikiPathways, and Gene Ontology (GO). It includes several types of records such as pathways, structural complexes, and functional sets, and is desiged to accomodate other record types, such as diseases, as data become available. Through these collaborations, the BioSystems database facilitates access to, and provides the ability to compute on, a wide range of biosystems data. If you are interested in depositing data into the BioSystems database, please contact them.

Proper citation: NCBI BioSystems Database (RRID:SCR_004690) Copy   

•   Source: SciCrunch Registry

http://www.proconsortium.org/pro/

An ontological representation of protein-related entities by explicitly defining them and showing the relationships between them. Each PRO term represents a distinct class of entities (including specific modified forms, orthologous isoforms, and protein complexes) ranging from the taxon-neutral to the taxon-specific. The ontology has a meta-structure encompassing three areas: proteins based on evolutionary relatedness (ProEvo); protein forms produced from a given gene locus (ProForm); and protein-containing complexes (ProComp). NOTICE: The PRO ID format has changed from PRO: to PR: (e.g. PRO:000000563 is now PR:000000563).

Proper citation: PR (RRID:SCR_004964) Copy   

•   Source: SciCrunch Registry