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http://headit.ucsd.edu

Platform for sharing, download, and re-analysis or meta-analysis of sophisticated, fully annotated, human electrophysiological data sets. It uses EEG Study Schema (ESS) files to provide task, data collection, and subject metadata, including Hierarchical Event Descriptor (HED) tag descriptions of all identified experimental events. Visospatial task data also available from, http://sccn.ucsd.edu/eeglab/data/headit.html: A 238-channel, single-subject EEG data set recorded at the Swartz Center, UCSD, by Arnaud Delorme, Julie Onton, and Scott Makeig is al.

Proper citation: HeadIT (RRID:SCR_005657) Copy   

•   Source: SciCrunch Registry

http://www.cafevariome.org/

Clearinghouse and exchange portal for gene variant (mutation) data produced by diagnostics laboratories, offering users a portal through which to announce, discover and acquire a comprehensive listing of observed neutral and disease-causing gene variants in patients and unaffected individuals. Cafe Variome is not a ''''database'''' for the hosting/display/release of data, but a shop window for finding data. As such, it holds only core info for each record, and uses this merely to enable holistic searching across resources. Diagnostics laboratories routinely assess DNA samples from patients with various inherited disorders, and so produce a great wealth of data on the genetic basis of disease. Unfortunately, those data are not usually shared with others. To address this gross deficiency, a novel system has been developed that aims to facilitate the automated transfer of diagnostic laboratory data to the wider community, via an internet based Cafe for routinely exchanging genetic variation data. The flow of research data concerning the genetic basis of health and disease is critical to understanding and developing treatments for a range of genetic diseases. Overall, the project aims to lower the barriers and provide incentives for a willing community to share data, and thereby facilitate the broader exploitation of diagnostic laboratory data. Cafe Variome aims to address the above data flow problems by: # Minimizing the effort required to publish variant data # Ensuring attribution for data creators working in diagnostic laboratories Key elements of the project strategy are: * Data publication will be automated by endowing standard analysis tools used by laboratories with an online data submission function. Submissions will be received by a central Internet depot, which will serve as a place where published datasets are advertised, and subsequently discovered by diverse 3rd parties. * Each dataset will be unambiguously linked with the data submitter''''s identity, and systems devised to facilitate citation of published variant datasets so they can be cited in the literature. Data creators will thus be credited for their contributions. Data submitters can use Cafe Variome to simply announce or publicize their data to the world. To enable this, only core, non-identifiable data is submitted to the central repository, enabling users to search and discover records of interest in the source repository. The data are not automatically handed on to the user (unless intended by the submitters). Hence, the concept is used to deal with the challenge of maximally sharing data whilst fully respecting ethico-legal considerations.

Proper citation: cafe variome (RRID:SCR_006162) Copy   

•   Source: SciCrunch Registry

http://fcon_1000.projects.nitrc.org/indi/pro/VirginiaTech.html

Dataset including a T1 weighted anatomical image as well as two 10-minute resting state scans acquired during the same session from 25 psychiatrically screened healthy adults (community sample) ranging in age from 18 to 65 years old, with age, sex, education level, and ethnicity provided. Some subjects also returned several weeks after the first scan for a second scanning session. The number of days between scan sessions, for subjects that had two sessions, is indicated in the demographics spreadsheet. The study scanning protocol included: # 13 sec localizer # 4 minute 38 second T1 weighted anatomical # Subject given instructions for resting state scan #1 # 10 minute 4 second resting state scan #1 # Subject given instructions for resting state scan #2 # 10 minute 4 second resting state scan #2 Scanning was performed on one of three different 3T Siemens TIM TRIOs at the Human Neuroimaging Lab at Baylor College of Medicine in Houston, Texas. All scans were acquired using the standard Siemen''s TIM 12-channel head matrix. The resting state scans were acquired with a custom sequence that is a slight modification to the standard Siemen''s EPI sequence that supports real-time fMRI. Images were acquired slightly oblique to minimize dephasing in the orbito-frontal cortex. Detailed scanning parameters are included in separate .pdf files.

Proper citation: Virginia Tech Carilion Research Institute Sample (RRID:SCR_010459) Copy   

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http://www.stsiweb.org/SWGR/

Whole genome sequencing data for 454 unrelated Scripps Wellderly Study participants with European ancestry from a project that is studying the genetic architecture of exceptional healthspan from a cohort comprised of more than 1300 healthy individuals over the age of 80 years. SWGR_v1.0 includes chromosome-specific VCF4.1 bgzipped and tabix indexed files. Annotations for each variant can be found at Scripps Genome ADVISER (SG-ADVISER, http://genomics.scripps.edu/) Additional data releases are expected.

Proper citation: Scripps Wellderly Genome Reference (RRID:SCR_010250) Copy   

•   Source: SciCrunch Registry

http://dgv.tcag.ca/

Collection of curated structural variation in the human genome. Catalogue of human genomic structural variation identified in healthy control samples for studies aiming to correlate genomic variation with phenotypic data. It is continuously updated with new data from peer reviewed research studies. The Database is no longer accepting direct submission of data as they are currently part of a collaboration with two new archival CNV databases at EBI and NCBI, called DGVa and dbVAR, respectively. One of the changes to DGV as part of this collaborative effort is that they will no longer be accepting direct submissions, but rather obtain the datasets from DGVa (short for DGV archive). This will ensure that the three databases are synchronized, and will allow for an official accessioning of variants.

Proper citation: Database of Genomic Variants (RRID:SCR_007000) Copy   

•   Source: SciCrunch Registry

http://centerforaging.duke.edu/index.php?option=com_content&view=article&id=115&Itemid=152

The project has been collecting detailed panel data about the health, disability, demographic, family, socioeconomic, and behavioral risk-factors for mortality and healthy longevity of the oldest old, with a comparative sub-sample of younger elders, to examine the factors in healthy longevity. The baseline survey was conducted in 1998 and the follow-up surveys with replacement to compensate for deceased elders were conducted in 2000, 2002, 2005, and 2008, For each centenarian, one near-by octogenarian (aged 80-89) and one near-by nonagenarian (aged 90-99) of pre-designated age and sex were interviewed. Near-by is loosely defined it could be in the same village or street if available, or in the same town or in the same county or city. The idea was to have comparable numbers of male and female octogenarians and nonagenarians at each age from 80 to 99. In 2002, the study added a refresher sub-sample of 4,845 interviewees aged 65-79, and a sub-sample of 4,478 adult children (aged 35-65) of the elderly interviewees aged 65-110 in eight provinces Comparative study of intergenerational relationships in the context of rapid aging and healthy longevity between Mainland China and Taiwan is possible. At each wave, the longitudinal survivors were re-interviewed, and the deceased interviewees were replaced by additional participants. Data on mortality and health status before dying for the 12,136 elders aged 65-112 who died between the waves were collected in interviews with a close family member of the deceased. The study also included interviews and follow-ups with 4,478 elderly interviewees'''' children aged 35-65. * Dates of Study: 1998-2005 * Study Features: Longitudinal, International * Sample Size: ** 1998: 8,993 ** 2000: 11,199 ** 2002: 16,064 ** 2005: 14,923 Links * Data Archive, http://www.geri.duke.edu/china_study/CLHLS6.htm * ICPSR, http://www.icpsr.umich.edu/icpsrweb/NACDA/studies/03891

Proper citation: Chinese Longitudinal Healthy Longevity Survey (CLHLS) (RRID:SCR_008904) Copy   

•   Source: SciCrunch Registry

http://genomics.senescence.info/species/

Curated database of aging and life history in animals, including extensive longevity records and complementary traits for > 4000 vertebrate species. AnAge was primarily developed for comparative biology studies, in particular studies of longevity and aging, but can also be useful for ecological and conservation studies and as a reference for zoos and field biologists.

Proper citation: anage (RRID:SCR_001470) 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://miriad.drc.ion.ucl.ac.uk/

A database of volumetric MRI brain-scans of 46 Alzheimer's sufferers and 23 healthy elderly people. Many scans were collected of each participant at intervals from 2 weeks to 2 years, the study was designed to investigate the feasibility of using MRI as an outcome measure for clinical trials of Alzheimer's treatments. It includes a total of 708 scans and should be of particular interest for work on longitudinal biomarkers and image analysis.

Proper citation: MIRIAD (RRID:SCR_002422) Copy   

•   Source: SciCrunch Registry

http://www.theearlab.org

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 13, 2026. Computationally oriented experimental laboratory interested in the encoding of auditory information in the cerebral cortex and brainstem, and in the mechanisms of tinnitus and the effect of various drugs (Lidocaine, steroids, anti-oxidants) in relieving noise trauma induced tinnitus. The ferret (Mustela putorius) and the rat serve as their system model. Through chronic implants, they obtain electrophysiological data from awake behaving animals in order to investigate the response properties and functional organization of the auditory system, both in health and after noise trauma that induces tinnitus in rats. Projects: * Response Modulation to Ongoing Broadband Sounds in Primary Auditory Cortex * Neuronal Response Characteristics in the Inferior Colliculus of the Awake Ferret and Rat * Spectro-Temporal Representation of Feature Onsets in Primary Auditory Cortex * Targeting the changes in inferior colliculus induced by tinnitus

Proper citation: Ear Lab (RRID:SCR_002531) Copy   

•   Source: SciCrunch Registry

https://simtk.org/home/cv-gmodels

Repository of geometric models collected from on-going and past research projects in the Cardiovascular Biomechanics Research Laboratory at Stanford University. The geometric models are mostly built from imaging data of healthy and diseased individuals. For each of the models, a short description is given with a reference. The geometric models are in VTK PolyData XML .vtp format. * Audience: Biomechanical and computational researchers interested in complex models of cardiovascular applications * Long Term Goals and Related Uses: Allow users to download geometric models for cardiovascular applications. These geometric models can be used for research purposes, such as meshing and scientific visualization. Users are welcome to contact the project administrator, join the project and contribute additional models.

Proper citation: Cardiovascular Model Repository (RRID:SCR_002679) Copy   

•   Source: SciCrunch Registry

http://irc.cchmc.org/software/pedbrain.php

Brain imaging data collected from a large population of normal, healthy children that have been used to construct pediatric brain templates, which can be used within statistical parametric mapping for spatial normalization, tissue segmentation and visualization of imaging study results. The data has been processed and compiled in various ways to accommodate a wide range of possible research approaches. The templates are made available free of charge to all interested parties for research purposes only. When processing imaging data from children, it is important to take into account the fact that the pediatric brain differs significantly from the adult brain. Therefore, optimized processing requires appropriate reference data be used because adult reference data will introduce a systematic bias into the results. We have shown that, in the in the case of spatial normalization, the amount of non-linear deformation is dramatically less when a pediatric template is used (left, see also HBM 2002; 17:48-60). We could also show that tissue composition is substantially different between adults and children, and more so the younger the children are (right, see also MRM 2003; 50:749-757). We thus believe that the use of pediatric reference data might be more appropriate.

Proper citation: CCHMC Pediatric Brain Templates (RRID:SCR_003276) Copy   

•   Source: SciCrunch Registry

http://www.pediatricmri.nih.gov/

Data sets of clinical / behavioral and image data are available for download by qualified researchers from a seven year, multi-site, longitudinal study using magnetic resonance technologies to study brain maturation in healthy, typically-developing infants, children, and adolescents and to correlate brain development with cognitive and behavioral development. The information obtained in this study is expected to provide essential data for understanding the course of normal brain development as a basis for understanding atypical brain development associated with a variety of developmental, neurological, and neuropsychiatric disorders affecting children and adults. This study enrolled over 500 children, ranging from infancy to young adulthood. The goal was to study each participant at least three times over the course of the project at one of six Pediatric Centers across the United States. Brain MR and clinical/behavioral data have been compiled and analyzed at a Data Coordinating Center and Clinical Coordinating Center. Additionally, MR spectroscopy and DTI data are being analyzed. The study was organized around two objectives corresponding to two age ranges at the time of enrollment, each with its own protocols. * Objective 1 enrolled children ages 4 years, 6 months through 18 years (total N = 433). This sample was recruited across the six Pediatric Study Centers using community based sampling to reflect the demographics of the United States in terms of income, race, and ethnicity. The subjects were studied with both imaging and clinical/behavioral measures at two year intervals for three time points. * Objective 2 enrolled newborns, infants, toddlers, and preschoolers from birth through 4 years, 5 months, who were studied three or more times at two Pediatric Study Centers at intervals ranging from three months for the youngest subjects to one year as the children approach the Objective 1 age range. Both imaging and clinical/behavioral measures were collected at each time point. Participant recruitment used community based sampling that included hospital venues (e.g., maternity wards and nurseries, satellite physician offices, and well-child clinics), community organizations (e.g., day-care centers, schools, and churches), and siblings of children participating in other research at the Pediatric Study Centers. At timepoint 1, of those enrolled, 114 children had T1 scans that passed quality control checks. Staged data release plan: The first data release included structural MR images and clinical/behavioral data from the first assessments, Visit 1, for Objective 1. A second data release included structural MRI and clinical/behavioral data from the second visit for Objective 1. A third data release included structural MRI data for both Objective 1 and 2 and all time points, as well as preliminary spectroscopy data. A fourth data release added cortical thickness, gyrification and cortical surface data. Yet to be released are longitudinally registered anatomic MRI data and diffusion tensor data. A collaborative effort among the participating centers and NIH resulted in age-appropriate MR protocols and clinical/behavioral batteries of instruments. A summary of this protocol is available as a Protocol release document. Details of the project, such as study design, rationale, recruitment, instrument battery, MRI acquisition details, and quality controls can be found in the study protocol. Also available are the MRI procedure manual and Clinical/Behavioral procedure manuals for Objective 1 and Objective 2.

Proper citation: NIH MRI Study of Normal Brain Development (RRID:SCR_003394) Copy   

•   Source: SciCrunch Registry

http://ki.se/ki/jsp/polopoly.jsp?d=29350&a=24030&l=en

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. Aims to investigate the relation between specific genetic variations, personality factors and pain experience in healthy subjects.

Proper citation: KI Biobank - PAIN (RRID:SCR_000610) Copy   

•   Source: SciCrunch Registry

http://ki.se/en/research/ki-biobank

KI Biobank is an accredited core facility offering sample collection services. KI Biobank is located at the Department of Medical Epidemiology and Biostatistics. KI Biobank offer infrastructure for pre analytical sample handling and provide researchers guidance on how samples should be taken and labeled. The processes comprise registration, handling, storage and distribution of samples. KI Biobank also offers DNA-extraction from blood and saliva. In order to insure complete traceability on samples and belonging information all processes are controlled by a Laboratory Information Management System (LIMS). For every new study a contract is established describing the study and the disposition rights. We also help in writing Biobank agreements including multicenteravtal and Material Transfer Agreement. KI Biobank is, according to the Biobank law, responsible for all sample collections handled within the core facility and those that are stored on the departments on KI campus. Clinical sample collections are handled by the Biobank units at the respective hospitals within the Stockholm County Council. Besides the samples that are stored centrally at KI Biobank, KI Biobank is also the administrative biobank for research sample collections at Karolinska Institutet that are stored and administrated at the departments. All research sample collections must be reported to KI Biobank. The following types of sample collections are registered in the biobank; sample collections taken within the regular health care that has been transferred to Karolinska Institutet with an agreement of transfer, samples taken from healthy individuals or other persons out of the regular health care and samples that have been taken abroad.

Proper citation: Karolisnka Biobank (RRID:SCR_004355) Copy   

•   Source: SciCrunch Registry

https://www.davincieuropeanbiobank.org/

BioBank that collects, stores, processes and distributes biospecimens and the associated data. The biospecimens are human and non-human genetic materials, proteins, cells, tissues and biofluids. The data are the biological information associated to the samples and, in the case of human samples, the clinical information pertaining to the donor. The da Vinci European BioBank (daVEB) is a multicenter biobank with a centralized IT infrastructure and a main repository located at the Polo Scientifico (Scientific Campus of the University of Florence) in Sesto Fiorentino (Florence, Italy). Hosted by the Magnetic Resonance Center (CERM), an expert center on protein structure and metabolomics, daVEB's aim is to host as rich as possible biological human sample collections, stored accordingly to EU guidelines, in order to offer a powerful tool in the study of complex diseases. At the end of July 2011, the da Vinci European BioBank of the Pharmacogenomics FiorGen Onlus Foundation has been audited and got the quality certification according to UNI EN ISO 9001:2008 for Collection, storage and distribution of biological samples and the associated data for scientific research. Besides the samples stored at da Vinci European BioBank in Sesto Fiorentino (Florence), the daVEB is also the administrative biobank for research sample collections that are stored in the delocalized repositories. All the sample collections must be registered in the biobank: * sample collections taken within the regular health care * samples taken from healthy individuals or other persons out of the regular health care * samples that have been taken in hospitals within research protocols on specific pathologies all transferred to daVEB endowed with a transfer agreement signed by the donor. The Research Units actually afferent to daVEB are delocalized in the Florence, Prato, Pisa and Siena provinces. Delocalized repositories are under construction in Tuscany.

Proper citation: da Vinci European Biobank (RRID:SCR_004908) Copy   

•   Source: SciCrunch Registry

http://www.hemacare.com/

Collects, processes, and distributes human blood products to hospitals and research-related organizations. They operate donor centers and mobile donor vehicles to collect transfusable blood products from healthy donors, and offer human-derived blood products to research organizations. HemaCare also provides blood related services, principally therapeutic apheresis procedures, stem cell collection and other blood treatments, to patients and in connection with clinical trials.

Proper citation: HemaCare Corp. (RRID:SCR_004803) 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://ki.se/ki/jsp/polopoly.jsp?d=29350&a=31589&l=en

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. The aim of EXT (extinction) is to investigate the relation between specific genetic variations and cognitive control process in fear. Blood samples will be collected from about 300 healthy, young individuals (age 18-35).

Proper citation: KI Biobank - EXT (RRID:SCR_008875) Copy   

•   Source: SciCrunch Registry

http://physionet.org/physiobank/

Archive of well-characterized digital recordings of physiologic signals and related data for use by the biomedical research community. PhysioBank currently includes databases of multi-parameter cardiopulmonary, neural, and other biomedical signals from healthy subjects and patients with a variety of conditions with major public health implications, including sudden cardiac death, congestive heart failure, epilepsy, gait disorders, sleep apnea, and aging. The PhysioBank Archives now contain over 700 gigabytes of data that may be freely downloaded. PhysioNet is seeking contributions of data sets that can be made freely available in PhysioBank. Contributions of digitized and anonymized (deidentified) physiologic signals and time series of all types are welcome. If you have a data set that may be suitable, please review PhysioNet''s guidelines for contributors and contact them.

Proper citation: Physiobank (RRID:SCR_006949) Copy   

•   Source: SciCrunch Registry