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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.

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http://ccr.coriell.org/Sections/Collections/NIGMS/?SsId=8

Highly characterized cell lines and high quality DNA for cell and genetic research representing a variety of disease states, chromosomal abnormalities, apparently healthy individuals and many distinct human populations. The NIGMS Repository contains more than 10,600 cell lines, primarily fibroblasts and transformed lymphoblasts, and over 5,500 DNA samples. The NIGMS Repository has a major emphasis on heritable diseases and chromosomally aberrant cell lines. In addition, it contains a large collection dedicated to understanding human variation that includes samples from populations around the world, the CEPH collection, the Polymorphism Discovery Resource, and many apparently healthy controls. Human induced pluripotent stem cell lines, many of which were derived from NIGMS Repository fibroblasts, have recently become available through the NIGMS Repository. Sample donation facilitates all areas of research by making available well-characterized materials to any qualified researcher who might have otherwise been unable to invest the time and resources to collect needed samples independently. Donations to the Repository have created a resource of unparalleled scope. Samples from the collection have been used in more than 5,500 publications and are distributed to scientists in more than 50 countries. This resource is continuously expanding to support new directions in human genetics.

Proper citation: NIGMS Human Genetic Cell Repository (RRID:SCR_004517) Copy   


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   


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   


  • RRID:SCR_005657

    This resource has 1+ mentions.

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   


  • RRID:SCR_004830

    This resource has 50+ mentions.

http://humanconnectome.org/connectome/connectomeDB.html

Data management platform that houses all data generated by the Human Connectome Project - image data, clinical evaluations, behavioral data and more. ConnectomeDB stores raw image data, as well as results of analysis and processing pipelines. Using the ConnectomeDB infrastructure, research centers will be also able to manage Connectome-like projects, including data upload and entry, quality control, processing pipelines, and data distribution. ConnectomeDB is designed to be a data-mining tool, that allows users to generate and test hypotheses based on groups of subjects. Using the ConnectomeDB interface, users can easily search, browse and filter large amounts of subject data, and download necessary files for many kinds of analysis. ConnectomeDB is designed to work seamlessly with Connectome Workbench, an interactive, multidimensional visualization platform designed specifically for handling connectivity data. De-identified data within ConnectomeDB is publicly accessible. Access to additional data may be available to qualified research investigators. ConnectomeDB is being hosted on a BlueArc storage platform housed at Washington University through the year 2020. This data platform is based on XNAT, an open-source image informatics software toolkit developed by the NRG at Washington University. ConnectomeDB itself is fully open source.

Proper citation: ConnectomeDB (RRID:SCR_004830) Copy   


http://humanconnectome.org/

Consortium to comprehensively map long-distance brain connections and their variability. It is acquiring data and developing analysis pipelines for several modalities of neuroimaging data plus behavioral and genetic data from healthy adults.

Proper citation: Human Connectome Coordination Facility (RRID:SCR_008749) Copy   


  • RRID:SCR_006949

    This resource has 10+ mentions.

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   


  • RRID:SCR_006162

    This resource has 10+ mentions.

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   


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   


http://bbmri-eric.eu

BBMRI is a pan-European and internationally broadly accessible research infrastructure and a network of existing and de novo biobanks and biomolecular resources. The infrastructure will include samples from patients and healthy persons, representing different European populations (with links to epidemiological and health care information), molecular genomic resources and biocomputational tools to optimally exploit this resource for global biomedical research. During the past 3 years BBMRI has grown into a 53-member consortium with over 280 associated organizations (largely biobanks) from over 30 countries, making it the largest research infrastructure project in Europe. During the preparatory phase the concept of a functional pan-European biobank was formulated and has now been presented to Member States of the European Union and for associated states for approval and funding. BBMRI will form an interface between specimens and data (from patients and European populations) and top-level biological and medical research. This can only be achieved through a distributed research infrastructure with operational units in all participating Member States. BBMRI will be implemented under the ERIC (European Research Infrastructure Consortium) legal entity. BBMRI-ERIC foresees headquarters (central coordination) in Graz, Austria, responsible for coordination of the activities of National Nodes established in participating countries. BBMRI is in the process of submitting its application to the European Commission for a legal status under the ERIC regulation, with an expected start date at the end of 2011. Major synergism, gain of statistical power and economy of scale will be achieved by interlinking, standardizing and harmonizing - sometimes even just cross-referencing - a large variety of well-qualified, up-to date, existing and de novo national resources. The network should cover (1) major European biobanks with blood, serum, tissue or other biological samples, (2) molecular methods resource centers for human and model organisms of biomedical relevance, (3) and biocomputing centers to ensure that databases of samples in the repositories are dynamically linked to existing databases and to scientific literature as well as to statistical expertise. Catalog of European Biobanks www.bbmriportal.eu Username: guest / Password: catalogue The catalogue is intended to be used as a reference for scientists seeking information about biological samples and data suitable for their research. The BBMRI catalogue of European Biobanks provides a high-level description of Europe''s biobanks characteristics using a portal solution managing metadata and aggregate data of biobanks. The catalogue can be queried by country, by biobank, by ICD-groups, by specimen types, by specific strengths, by funding and more. A search function is available for all data.

Proper citation: Biobanking and Biomolecular Resources Research Infrastructure (BBMRI) (RRID:SCR_004226) Copy   



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