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https://ncats.nih.gov/grdr/rdhub

A database of biospecimens collected, stored, and distributed by biorepositories in the United States and around the globe. Its goals are: To help and assist interested parties and investigators search, locate, and identify desired biospecimens needed for their research; to facilitate collaboration and sharing of material and data among investigators across the globe; to accelerate research to facilitate the discovery of new treatments, therapeutics and eventually cures for rare diseases as well as common diseases; to identify, locate and increase the awareness of existing biorepositories across the globe; and to link the RD-HUB with the Global Rare Diseases Patient Registry and Data Repository (GRDR).

Proper citation: Biospecimens/Biorepositories: Rare Disease-HUB (RD-HUB) (RRID:SCR_004327) Copy   

•   Source: SciCrunch Registry

http://ki.se/en/meb/twingene-and-genomeeutwin

In collaboration with GenomeEUtwin, the TwinGene project investigates the importance of quantitative trait loci and environmental factors for cardiovascular disease. It is well known that genetic factors are of considerable importance for some familial lipid syndromes and that Type A Behavior pattern and increased lipid levels infer increased risk for cardiovascular disease. It is furthermore known that genetic factors are of importance levels of blood lipid biomarkers. The interplay of genetic and environmental effects for these risk factors in a normal population is less well understood and virtually unknown for the elderly. In the TwinGene project twins born before 1958 are contacted to participate. Health and medication data are collected from self-reported questionnaires, and blood sampling material is mailed to the subject who then contacts a local health care center for blood sampling and a health check-up. In the simple health check-up, height, weight, circumference of waist and hip, and blood pressure are measured. Blood is sampled for DNA extraction, serum collection and clinical chemistry tests of C-reactive protein, total cholesterol, triglycerides, HDL and LDL cholesterol, apolipo��protein A1 and B, glucose and HbA1C. The TwinGene cohort contains more than 10000 of the expected final number of 16000 individuals. Molecular genetic techniques are being used to identify Quantitative Trait Loci (QTLs) for cardiovascular disease and biomarkers in the TwinGene participants. Genome-wide linkage and association studies are ongoing. DZ twins have been genome-scanned with 1000 STS markers and a subset of 300 MZ twins have been genome-scanned with Illumina 317K SNP platform. Association of positional candidate SNPs arising from these genomscans are planned. The TwinGene project is associated with the large European collaboration denoted GenomEUtwin (www.genomeutwin.org, see below) which since 2002 has aimed at gathering genetic data on twins in Europe and setting up the infrastructure needed to enable pooling of data and joint analyses. It has been the funding source for obtaining the genome scan data. Types of samples: * EDTA whole blood * DNA * Serum Number of sample donors: 12 044 (sample collection completed)

Proper citation: KI Biobank - TwinGene (RRID:SCR_006006) Copy   

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http://mind.loni.usc.edu

The MiND: Metadata in NIfTI for DWI framework enables data sharing and software interoperability for diffusion-weighted MRI. This site provides specification details, tools, and examples of the MiND mechanism for representing important metadata for DWI data sets at various stages of post-processing. MiND framework provides a practical solution to the problem of interoperability between DWI analysis tools, and it effectively expands the analysis options available to end users. To assist both users and developers in working with MiND-formatted files, we provide a number of software tools for download. * MiNDHeader A utility for inspecting MiND-extended files. * I/O Libraries Programming libraries to simplify writing and parsing MiND-formatted data. * Sample Files Example files for each MiND schema. * DIRAC LONI''s Diffusion Imaging Reconstruction and Analysis Collection is a DWI processing suite which utilizes the MiND framework.

Proper citation: LONI MiND (RRID:SCR_004820) Copy   

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http://ccr.coriell.org/Sections/Collections/USIDNET/?SsId=15

The USIDNET DNA and Cell Repository has been established as part of an NIH-funded program - the US Immunodeficiency Network - to provide a resource of DNA and functional lymphoid cells obtained from patients with various primary immunodeficiency diseases. These uncommon disorders include patients with defects in T cell, B cell and/or granulocyte function as well as patients with abnormalities in antibodies / immunoglobulins, complement and other host defense mechanisms. All samples in this Repository have been de-identified to protect the privacy of the individual donors. The USIDNET also operates a Patient Data Registry in addition to this Repository and certain clinical data relating to a specific sample may be available through the Registry for some of the patient samples in the Repository collection. Materials in the collection are being made available at modest cost to qualified investigators in academic and commercial organizations in an effort to stimulate research to increase understanding of these orphan diseases and to promote development of new treatments. Requestors are required to complete a Statement of Research Intent briefly describing their proposed use of materials obtained from the Repository and must sign an Assurance agreeing to conditions established by USIDNET for distribution of samples from its collection. Requestors wishing to obtain additional clinical data specific to individual samples in the Repository collection must make a separate application for that information to the Registry (see www.usidnet.org) Physicians or Patients wishing to submit cell samples for the Repository collection should first contact Coriell to arrange for the Repository to send them the correct sample collection tubes as well as prepaid mailers for returning the collected sample(s) to Coriell. Separate collection and shipping procedures may be involved depending on how many samples are to be shipped at one time and whether the shipment will involve freshly obtained blood or already established cell lines.

Proper citation: USIDNET DNA and Cell Repository (RRID:SCR_004661) Copy   

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http://www.sph.umich.edu/csg/abecasis/CaTS

Software tool for carrying out power calculations for large genetic association studies, including two stage genome wide association studies.

Proper citation: Calculator for Association with Two Stage design (RRID:SCR_007238) Copy   

•   Source: SciCrunch Registry

http://science.education.nih.gov/SciEdBlog

A blog put out by the NIH Office of Science Education.

Proper citation: NIH SciEd Blog (RRID:SCR_005499) 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

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://bard.nih.gov/

Database that allows scientists without specialized training to effectively utilize Molecular Libraries Program (MLP) data. It allows the research community to utilize and develop new chemical probes to explore biological functions by building a central, permanently accessible link to all aspects of chemical biology data and analyses. The project is split into two basic segments, the first segment delivering functionality for a data dictionary, as well as assay protocol and data entry tools. The second builds a data warehouse for analysis and visualization, accessible through a public RESTful API. They will initially deploy two clients that will use this API - a web-based interface and a desktop application. Advanced access to data and the platforms will also be available to support plug-in development and the repackaging of data by others. Initially the project will focus on small molecule assays. Features: * allow scientists to annotate assay data using a common, shared language * provide facile access to data, integrating existing chemical biology and computational resources * enable meaningful analysis and interpretation of discovery data by the research community * support hypothesis generation for iterative probe- and drug-discovery projects * inform the entire small molecule discovery and development process, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: BARD (RRID:SCR_006283) Copy   

•   Source: SciCrunch Registry

http://crcview.hegroup.org/

Web-based microarray data analysis and visualization system powered by CRC, or Chinese Restaurant cluster, a Dirichlet process model-based clustering algorithm recently developed by Dr. Steve Qin. It also incorporates several gene expression analysis programs from Bioconductor, including GOStats, genefilter, and Heatplus. CRCView also installs from the Bioconductor system 78 annotation libraries of microarray chips for human (31), mouse (24), rat (14), zebrafish (1), chicken (1), Drosophila (3), Arabidopsis (2), Caenorhabditis elegans (1), and Xenopus Laevis (1). CRCView allows flexible input data format, automated model-based CRC clustering analysis, rich graphical illustration, and integrated Gene Ontology (GO)-based gene enrichment for efficient annotation and interpretation of clustering results. CRC has the following features comparing to other clustering tools: 1) able to infer number of clusters, 2) able to cluster genes displaying time-shifted and/or inverted correlations, 3) able to tolerate missing genotype data and 4) provide confidence measure for clusters generated. You need to register for an account in the system to store your data and analyses. The data and results can be visited again anytime you log in.

Proper citation: CRCView (RRID:SCR_007092) Copy   

•   Source: SciCrunch Registry

http://www.cpc.unc.edu/projects/addhealth

Longitudinal study of a nationally representative sample of adolescents in grades 7-12 in the United States during the 1994-95 school year. Public data on about 21,000 people first surveyed in 1994 are available on the first phases of the study, as well as study design specifications. It also includes some parent and biomarker data. The Add Health cohort has been followed into young adulthood with four in-home interviews, the most recent in 2008, when the sample was aged 24-32. Add Health combines longitudinal survey data on respondents social, economic, psychological and physical well-being with contextual data on the family, neighborhood, community, school, friendships, peer groups, and romantic relationships, providing unique opportunities to study how social environments and behaviors in adolescence are linked to health and achievement outcomes in young adulthood. The fourth wave of interviews expanded the collection of biological data in Add Health to understand the social, behavioral, and biological linkages in health trajectories as the Add Health cohort ages through adulthood. The restricted-use contract includes four hours of free consultation with appropriate staff; after that, there''s a fee for help. Researchers can also share information through a listserv devoted to the database.

Proper citation: Add Health (National Longitudinal Study of Adolescent Health) (RRID:SCR_007434) Copy   

•   Source: SciCrunch Registry

http://compbio.soe.ucsc.edu/yeast_introns.html

Database of information about the spliceosomal introns of the yeast Saccharomyces cerevisiae. Listed are known spliceosomal introns in the yeast genome and the splice sites actually used are documented. Through the use of microarrays designed to monitor splicing, they are beginning to identify and analyze splice site context in terms of the nature and activities of the trans-acting factors that mediate splice site recognition. In version 3.0, expression data that relates to the efficiency of splicing relative to other processes in strains of yeast lacking nonessential splicing factors is included. These data are displayed on each intron page for browsing and can be downloaded for other types of analysis.

Proper citation: Yeast Intron Database (RRID:SCR_007144) Copy   

•   Source: SciCrunch Registry

https://github.com/YuanXue1993/SegAN

Image analysis software for medical image segmentation. The software is fueled by an end-to-end adversarial neural network that generates segmentation label maps.

Proper citation: SegAN (RRID:SCR_016215) Copy   

•   Source: SciCrunch Registry

https://cic.ini.usc.edu/

Project to create complete mesoscale connectivity atlas of the C57Black/6 mouse brain and to subsequently generate its global neural networks.

Proper citation: Mouse Connectome Project (RRID:SCR_017313) Copy   

•   Source: SciCrunch Registry

http://nhprtr.org/

Nonhuman Primate reference transcriptome resource consisting of deep sequencing complete transcriptomes (RNA-seq) from multiple NHP species.

Proper citation: Nonhuman Primate Reference Transcriptome Resource (RRID:SCR_017534) Copy   

•   Source: SciCrunch Registry

https://mibig.secondarymetabolites.org/

MIBiG is genomic standards consortium project and biosynthetic gene cluster database used as reference dataset. Provides community standard for annotations and metadata on biosynthetic gene clusters and their molecular products. Standardised data format that describes minimally required information to uniquely characterise biosynthetic gene clusters. MIBiG 2.0 is expended repository for biosynthetic gene clusters of known function. MIBiG 3.0 is database update comprising large scale validation and re-annotation of existing entries and new entries. Community driven effort to annotate experimentally validated biosynthetic gene clusters.

Proper citation: Minimum Information about Biosynthetic Gene cluster (RRID:SCR_023660) Copy   

•   Source: SciCrunch Registry

http://ki-su-arc.se/dementia-in-swedish-twins-harmony/

A twin study characterizing the importance of genetic factors for dementia and using discordant twin pairs to study other putative risk factors which control for genetic propensity to develop the disease. Molecular genetic studies have identified a number of mutations and other markers associated with early age of onset Alzheimer''''s disease. However, most cases of late age of onset dementia are considered sporadic, that is, without a clear genetic basis. Twin studies provide a unique opportunity to characterize the importance of genetic factors for dementia. Discordant twin pairs additionally provide the opportunity to study other putative risk factors which controlling for genetic propensity to develop the disease. In the first wave of the Study of Dementia in Swedish Twins, all SATSA twins born before 1935 have been screened for dementia symptoms. Over 190 suspects have been identified. This pilot study has been expanded to the entire registry in the study known as HARMONY. All twins aged 65 and older were invited to participate in a computer assisted telephone screening interview. A total of 13,519 individuals completed the interview (response rate = 75.9%). Dementia screening was based on the TELE, which includes the 10-item MSQ, other cognitive items (counting backwards, recalling three words, and similarities), and questions about health and daily functioning; or on Blessed scores obtained from a proxy interview. Among those screened, 1565 were positive for suspicion of dementia and were referred for complete clinical evaluation by a physician and a nurse. Once the preliminary in-person evaluation suggested that the suspected case was demented, the twin partner was also invited for an identical clinical work-up. Response rate for clinical evaluations is 71.4%. Approximately half of those visited for evaluation have been diagnosed as demented according to DSM-IV criteria, of which two-thirds have Alzheimer''''s disease. An extensive assessment of probable risk exposure is also included. Longitudinal follow-up is yet another feature of the study. Association studies with candidate genes are also being performed. Types of samples * DNA Number of sample donors * 1154 (sample collection completed)

Proper citation: KI Biobank - HARMONY (RRID:SCR_008884) Copy   

•   Source: SciCrunch Registry

https://www.pathology.umn.edu/research/liver-tissue-cell-distribution-system

Tissue bank that provides human liver tissue from regional centers for distribution to scientific investigators throughout the United States. These USA regional centers have active liver transplant programs with human subjects approval to provide portions of the resected pathologic liver for which the transplant is performed.

Proper citation: Minnesota Liver Tissue Cell Distribution System (RRID:SCR_004840) Copy   

•   Source: SciCrunch Registry

http://udn.nichd.nih.gov/brainatlas_home.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 1, 2019. The first brain atlas for the common marmoset to be made available since a printed atlas by Stephan, Baron and Schwerdtfeger published in 1980. It is a combined histological and magnetic resonance imaging (MRI) atlas constructed from the brains of two adult female marmosets. Histological sections were processed from Nissl staining and digitized to produce an atlas in a large format that facilitates visualization of structures with significant detail. Naming of identifiable brain structures was performed utilizing current terminology. For the present atlas, an adult female was perfused through the heart with PBS followed by 10% formalin. The brain was then sent to Neuroscience Associates of Knoxville, TN, who prepared the brain for histological analysis. The brain was cut in the coronal (frontal) plane at 40 microns, every sixth section stained for Nissl granules with thionine and every seventh section stained for myelinated fibers with the Weil technique. The mounted sections were photographed at the NIH (Medical Arts and Photography Branch). The equipment used was a Nikon Multiphot optical bench with Zeiss Luminar 100 mm lens, and scanned with a Better Light 6100 scan back driven by Better Light Viewfinder 5.3 software. The final images were saved as arrays of 6000x8000 pixels in Adobe Photoshop 6.0. A scale in mm provided with these images permitted construction of the final Nissl atlas files with a horizontal and vertical scale. Some additional re-touching (brightness and contrast) was done with Adobe Photoshop Elements 2.0. The schematic (labeled) atlas plates were created from the Nissl images. The nomenclature came almost exclusively from brainmaps.org, where a rhesus monkey brain with structures labeled can be found. The labels for the MRI images were placed by M. R. Zametkin, under supervision from Dr. Newman.

Proper citation: Brain atlas of the common marmoset (RRID:SCR_005135) Copy   

•   Source: SciCrunch Registry

http://frederick.cancer.gov/

A federally funded research and development center dedicated to biomedical research. NCI-Frederick partners with university, government, and corporate scientists to speed the translation of laboratory research into new diagnostic tests and treatments for cancer and HIV/AIDS. NCI-Frederick is comprised of more than 2,800 government- and contractor-employed biomedical researchers, laboratory technicians, and support staff and several cancer research centers. The FNLCR provides quick response capabilities and meets special long-term research and development needs for NCI that cannot be met as effectively by existing in-house or contractor resources.

Proper citation: NCI-Frederick (RRID:SCR_004880) Copy   

•   Source: SciCrunch Registry