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on page 1 showing 20 out of 26 results from 1 sources

Cite this (1000 Functional Connectomes Project, RRID:SCR_005361)

URL: http://fcon_1000.projects.nitrc.org/

Resource Type: Resource, database, image collection, catalog, service resource, storage service resource, image repository, data repository, data or information resource

Database of resting state fMRI (R-fMRI) datasets collected from sites around the world. It demonstrates open sharing of R-fMRI data and aims to emphasize the aggregation and sharing of well-phenotyped datasets.

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Cite this (BEI Resource Repository, RRID:SCR_013698)

URL: https://www.beiresources.org/

Resource Type: Resource, service resource, material storage repository, storage service resource, biobank

Central data repository that supplies organisms and reagents to the broad community of microbiology and infectious diseases researchers.

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    BioGRID

Cite this (BioGRID, RRID:SCR_007393)

URL: http://www.thebiogrid.org/

Resource Type: Resource, database, service resource, storage service resource, software resource, data repository, data or information resource

A curated protein-protein and genetic interaction repository of raw protein and genetic interactions from major model organism species, with data compiled through comprehensive curation efforts. The current version searches over 41,000 publications containing over 720,000 interactions (June 2014) and contributions are welcome. Complete coverage of the entire literature is maintained for budding yeast (S. cerevisiae), fission yeast (S. pombe) and thale cress (A. thaliana), and efforts to expand curation across multiple metazoan species are underway. Current curation drives are focused on particular areas of biology to enable insights into conserved networks and pathways that are relevant to human health. It provides interaction data to several model organism databases, resources such as Entrez-Gene, SGD, TAIR, FlyBase and other interaction meta-databases. The entire BioGRID 3.0 data collection may be downloaded in multiple file formats, including IMEx compatible PSI MI XML. For developers, BioGRID interactions are also available via a REST based Web Service and Cytoscape plugin.

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Cite this (Biologic Specimen and Data Repository Information Coordinating Center, RRID:SCR_013142)

URL: https://biolincc.nhlbi.nih.gov/home/

Resource Type: Resource, data or information resource, database, biomaterial supply resource, biospecimen repository, service resource, storage service resource, data repository, material resource, material storage repository

Repository that serves to coordinate searches across data and biospecimen collections from participants in numerous clinical trials and epidemiologic studies and to provide an electronic means for requests for additional information and the submission of requests for collections. The collections, comprising data from more than 80 trials or studies and millions of biospecimens, are available to qualified investigators under specific terms and conditions consistent with the informed consents provided by the individual study participants. Some datasets are presented with studies and supporting materials to facilitate their use in reuse and teaching. Datasets support basic research, clinical studies, observational studies, and demonstrations. Researchers wishing to apply to submit biospecimen collections to the NHLBI Biorepository for sharing with qualified investigators may also use this website to initiate that process.

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Cite this (CardioVascular Research Grid, RRID:SCR_004472)

URL: http://www.cvrgrid.org/

Resource Type: Resource, data analysis service, production service resource, analysis service resource, service resource, storage service resource, image repository, data repository

An infrastructure for sharing cardiovascular data and data analysis tools. CVRG tools are developed using the Software as a Service model, allowing users to access tools through their browser, thus eliminating the need to install and maintain complex software. A human ExVivo heart data set and canine ExVivo normal and failing heart data sets are available. The canine hearts have an atlas available, in Analyze 7.5 format. There are also human InVivo atlases, in Analyze 7.5 format, showing end systole and end diastole data. * ECG: The ECGrid Toolkit is able to handle a number of different ECG file formats. * Ex vivo data: The CVRG has several sets of canine and human imaging sets available for public use. * Ex vivo atlas data: The CVRG has atlases with analysis of canine heart fiber and sheet angles available for public use. * In vivo data: These datasets include Ischemic (ICM) and non-ischemic cardiomyopathy (NICM) Data. * Protein Microarray data: The following datasets are supporting information for publications which reported on new experimental approaches for using reverse-phase protein microarrays to map the left ventricular transmural proteome. Web services: The CVRG is committed to the delivery of tools, for sharing and analyzing cardiovascular data. Four different groups of tools are under development or have been deployed. These are: 1) an ECG storage and analysis interface; 2) a customized instance of XNAT for cardiovascular imaging & imaging analysis; 3) an optimized representation tool for clinical data; and 4) a workflow tool for data retrieval & analysis. Within these groups, data and analytical services are combined to meet the needs of the Driving Biomedical Projects. Ontologies: CVRG ontology development and application focuses in three major areas. They have developed a preliminary ontology for describing all aspects of ECG data collection, ECG waveform features, and ECG data analysis. They coupled ontology development with the development of an ECG data model. The CVRG award supports the ECG ontology and data model development. The project is based at the Institute for Computational Medicine at the Johns Hopkins University, in collaboration with the Center for Comprehensive Informatics at Emory University, the Image Lab at Wake Forest University and the Computation Institute at The University of Chicago.

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Cite this (Database of Interacting Proteins, RRID:SCR_003167)

URL: http://dip.doe-mbi.ucla.edu/

Resource Type: Resource, data analysis service, production service resource, analysis service resource, database, service resource, storage service resource, data repository, data or information resource

Database to catalog experimentally determined interactions between proteins combining information from a variety of sources to create a single, consistent set of protein-protein interactions that can be downloaded in a variety of formats. The data were curated, both, manually and also automatically using computational approaches that utilize the the knowledge about the protein-protein interaction networks extracted from the most reliable, core subset of the DIP data. Because the reliability of experimental evidence varies widely, methods of quality assessment have been developed and utilized to identify the most reliable subset of the interactions. This CORE set can be used as a reference when evaluating the reliability of high-throughput protein-protein interaction data sets, for development of prediction methods, as well as in the studies of the properties of protein interaction networks. Tools are available to analyze, visualize and integrate user's own experimental data with the information about protein-protein interactions available in the DIP database. The DIP database lists protein pairs that are known to interact with each other. By interact they mean that two amino acid chains were experimentally identified to bind to each other. The database lists such pairs to aid those studying a particular protein-protein interaction but also those investigating entire regulatory and signaling pathways as well as those studying the organization and complexity of the protein interaction network at the cellular level. Registration is required to gain access to most of the DIP features. Registration is free to the members of the academic community. Trial accounts for the commercial users are also available.

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Cite this (EuPathDB - Eukaryotic Pathogen Database Resources, RRID:SCR_004512)

URL: http://eupathdb.org/eupathdb/

Resource Type: Resource, topical portal, data access protocol, database, web service, service resource, portal, storage service resource, software resource, data repository, data or information resource

EuPathDB Bioinformatics Resource Center for Biodefense and Emerging/Re-emerging Infectious Diseases is a portal for accessing genomic-scale datasets associated with the eukaryotic pathogens (Babesia, Cryptosporidium, Encephalitozoon, Entamoeba, Enterocytozoon, Giardia, Leishmania, Neospora, Plasmodium, Theileria, Toxoplasma, Trichomonas and Trypanosoma). It provides a unified entry point for the Eukaryotic Pathogen integrating AmoebaDB, CryptoDB, GiardiaDB, MicrosporidiaDB, PiroplasmaDB, PlasmoDB, ToxoDB, TrichDB, and TriTrypDB. While each of these groups is supported by a taxon-specific database built upon the same infrastructure, the EuPathDB portal offers an entry point to all these resources, and the opportunity to leverage orthology for searches across genera. EuPathDB currently supports more than 80 searches and the recently-implemented "search strategy" system enables users to construct complex multi-step searches via a graphical interface. Search results are dynamically displayed as the strategy is constructed or modified, and can be downloaded, saved, revised, or shared with other database users. EuPathDB provides programmatic access to its searches, via REST Web Services

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Cite this (FITBIR Informatics System, RRID:SCR_006856)

URL: https://fitbir.nih.gov/

Resource Type: Resource, topical portal, database, standard specification, narrative resource, service resource, portal, storage service resource, data repository, data or information resource

An extensible, scalable informatics platform for TBI relevant data and for all data types (text, numeric, image, time series, etc.). This informatics system was developed to share data across the entire TBI research field and to facilitate collaboration between laboratories and interconnectivity between informatics platforms. FITBIR implements the interagency Common Data Elements for TBI research and provides tools and resources to extend the data dictionary. It has also established a two-tiered submission strategy to ensure high quality and to provide maximum benefit to investigators. Qualified researchers can request access to data stored in FITBIR and/or data stored at federated repositories.

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    FlyBase

Cite this (FlyBase, RRID:SCR_006549)

URL: http://flybase.org/

Resource Type: Resource, topical portal, organism-related portal, analysis service resource, database, data analysis service, service resource, portal, production service resource, storage service resource, data repository, data or information resource

Database of Drosophila genetic and genomic information with information about stock collections and fly genetic tools. Gene Ontology (GO) terms are used to describe three attributes of wild-type gene products: their molecular function, the biological processes in which they play a role, and their subcellular location. Additionally, FlyBase accepts data submissions. FlyBase can be searched for genes, alleles, aberrations and other genetic objects, phenotypes, sequences, stocks, images and movies, controlled terms, and Drosophila researchers using the tools available from the "Tools" drop-down menu in the Navigation bar.

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Cite this (GeneNetwork, RRID:SCR_002388)

URL: http://www.genenetwork.org/

Resource Type: Resource, service resource, data or information resource, data repository, storage service resource, database

A group of linked data sets and tools used to study complex networks of genes, molecules, and higher order gene function and phenotypes. It combines more than 25 years of legacy data generated by hundreds of scientists together with sequence data (SNPs) and massive transcriptome data sets (expression genetic or eQTL data sets). The quantitative trait locus (QTL) mapping module that is built into GN is optimized for fast on-line analysis of traits that are controlled by combinations of gene variants and environmental factors. GeneNetwork can be used to study humans, mice (BXD, AXB, LXS, etc.), rats (HXB), Drosophila, and plant species (barley and Arabidopsis). Most of these population data sets are linked with dense genetic maps (genotypes) that can be used to locate the genetic modifiers that cause differences in expression and phenotypes, including disease susceptibility. Users are welcome to enter their own private data directly into GeneNetwork to exploit the full range of analytic tools and to map modulators in a powerful environment. This combination of data and fast analytic functions enable users to study relations between sequence variants, molecular networks, and function. What can be done with GeneNetwork? * QTL Mapping: ** Interval Mapping ** Simple interval mapping ** Composite interval mapping ** Pair-scan * Correlation Analysis ** Correlation Matrix / Principal Components Analysis ** QTL Heatmaps ** Compare Correlates ** Network Graph * Systems Genetics and Complex Trait Analysis Source code is available and is written in Python, C, and JavaScript. The QTL Reaper module of GeneNetwork that is used by several mapping modules of GeneNetwork is also available.

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    GRDR

Cite this (GRDR, RRID:SCR_008978)

URL: http://www.grdr.info/

Resource Type: Resource, database, people resource, service resource, patient registry, storage service resource, data repository, data or information resource

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/.

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    iDASH

Cite this (iDASH, RRID:SCR_003524)

URL: http://idash.ucsd.edu/

Resource Type: Resource, organization portal, production service resource, analysis service resource, database, data analysis service, catalog, service resource, portal, storage service resource, software resource, data repository, data or information resource

National Center for Biomedical Computing (NCBC) that develops new algorithms, opensource tools, computational infrastructure, and services for biomedical and behavioral researchers nationwide to promote the secure sharing and consuming of biomedical and behavioral resources (software, data, and computing systems) with iDASH collaborators. The center addresses fundamental challenges to research progress by providing a secure, privacypreserving environment in which researchers can analyze genomic, transcriptomic, clinical, behavioral, and social data relevant to health. Three driving biological projects in iDASH (Molecular Phenotyping of Kawasaki Disease, Post-Marketing Surveillance of Hematologic Medications, and Individualized Intervention to Enhance Physical Activity) span the molecular-individualpopulation spectrum, and they will motivate, inform, and support tool development. iDASH will collaborate with other NCBCs and will disseminate tools via annual workshops, presentations at major conferences, and scientific publications.

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Cite this (Immune Epitope Database and Analysis Resource, RRID:SCR_006604)

URL: http://www.immuneepitope.org/

Resource Type: Resource, data analysis service, data access protocol, production service resource, analysis service resource, database, web service, service resource, software resource, data or information resource

The IEDB contains data related to antibody and T cell epitopes for humans, non-human primates, rodents, and other animal species. Curation of peptidic and non-peptidic epitope data relating to all infectious diseases (including NIAID Category A, B, and C priority pathogens and NIAID Emerging and Re-emerging infectious diseases), allergens, autoimmune diseases, and transplant/alloantigens is current and constantly being updated. The database also contains Major Histocompatibility Complex (MHC) binding data from a variety of different antigenic sources and immune epitope data from the FIMM (Brusic), HLA Ligand (Hildebrand), TopBank (Sette), and MHC binding (Buus) databases. These databases and their investigators are hereby acknowledged as major contributors to the IEDB. Curation of epitopes related to allergies and other infectious diseases is in progress. Curation of autoimmune epitopes started in 2009. This site provides a collection of tools for the prediction and analysis of immune epitopes. It serves as a companion site to the Immune Epitope Database (IEDB), a manually curated database of experimentally characterized immune epitopes. The tools contained fall into the following categories: * T Cell Epitope Prediction Tools: This set of tools includes MHC class I & II binding predictions, as well as peptide processing predictions. * B Cell Epitope Prediction Tools: The tools here are intended to predict regions of proteins that are likely to be recogized as epitopes in the context of a B cell response. * Analysis Tools: The epitope analysis tools are intended for the detailed analysis of a known epitope sequence or group of sequences. Several IEDB Analysis tools can now be accessed via the RESTful (REpresentational State Transfer) Web Services. IEDB is located in the La Jolla Institute for Allergy and Immunology

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Cite this (Mouse Genome Informatics, RRID:SCR_006460)

URL: http://www.informatics.jax.org

Resource Type: Resource, data or information resource, database

An international database for the laboratory mouse, providing integrated genetic, genomic, and biological data to facilitate the study of human health and disease. Its primary mission is to facilitate the use of the mouse as a model system for understanding human biology and disease. MGI creates and maintains an integrated representation of mouse genetic, genomic, expression, and phenotype data and develops definitive reference data set and consensus data views. MGI also synthesizes comparative genomic data between the mouse and other mammals, maintains a set of links and collaborations with other bioinformatics resources, develops and supports analysis and data submission tools, and provides extensive technical support for database users. The projects contributing to this resource are: Mouse Genome Database (MGD) Project, Gene Expression Database (GXD) Project, Mouse Tumor Biology (MTB) Database Project, Gene Ontology (GO) Project at MGI, and MouseCyc Project at MGI.

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Cite this (National Institute on Drug Abuse Center for Genetic Studies, RRID:SCR_013061)

URL: http://zork.wustl.edu/nida/

Resource Type: Resource, data set, data or information resource

An umbrella site for the collection and distribution of clinical data related to the genetic analysis of drug abuse phenotypes. Anonymous data on family structure, age, sex, clinical status, and diagnosis (clinical data), DNA samples and cell line cultures (biomaterials), and data derived from genotyping and other genetic analyses of these clinical data and biomaterials (genetic analysis data), are distributed to qualified researchers studying the genetics of mental disorders and other complex diseases at recognized biomedical research facilities. Phenotypic and Genetic data will be made available to the general public on the release dates through distribution mechanisms specified on the website. Participating studies are as follows: * Genetics of Opioid Dependence * Mapping of Susceptibility Loci for Nicotine Dependence * Molecular Genetics of Heroin Dependence * Addictions: Genotypes, Polymorphisms, and Function * Genetics of Vulnerability to Nicotine Addiction * Family Study of Cocaine Dependence * Heroin Dependence * Differentiation of Phenotypes for Smoking * Pharmacokinetics of Nicotine in Twins * Adolescent Drug Dependence * Substance Abuse * Genetics of Cocaine Induced Psychosis * Genome-Wide Analysis for Addiction Susceptibility Genes * The Collaborative Genetic Study of Nicotine Dependence * Nicotine Dependence * Cocaine Dependence * Opiate Dependence: Candidate Genes and G x E Effects * Genetic Studies of Substance Abuse in Iowa Adoptees * Innovative Approaches for Cocaine Pharmacotherapy * Twin Family Study of Vulnerability to Substance Abuse * Drug Use * Substance Use Disorder Liability: Candidate Gene System * START (Starting Treatment with Agonist Replacement Therapies) * GEDI (The Genes, Environment, and Development Initiative) * GEDI (The Genes, Environment, and Development Initiative) * Youth Drug Abuse, ADHD and Related Disorders The investigators contact information, release dates, and description of the study are available on the website.

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Cite this (NIA Genetics of Alzheimers Disease Data Storage Site, RRID:SCR_007314)

URL: https://www.niagads.org/

Resource Type: Resource, database, data set, service resource, storage service resource, data repository, data or information resource

A genetics data repository that facilitates access of genotypic data to qualified investigators for the study of the genetics of late-onset Alzheimer's disease. NIAGADS is a resource supported by the National Institute on Aging to serve as a repository for many types of data generated from NIA supported grants and/or NIA funded biological samples. The types of data include, but are not limited to, DNA marker genotypes, DNA sequencing data, RNA expression data, etc. It is the policy of the NIA that all genetic data derived from NIA-funded studies for the genetics of late-onset Alzheimer's disease be deposited at NIAGADS, another NIA-approved site, or both. NIAGADS, along with other NIA-approved sites, will make these Genetic Data and Associated Phenotypic Data available to qualified investigators in the scientific community for secondary analysis.

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Cite this (NIDDK Information Network, RRID:SCR_001606)

URL: http://dknet.org/

Resource Type: Resource, portal, database, community building portal, data or information resource

A community-based network to serve the needs of basic and clinical investigators that includes large pools of data and research resources relevant to the mission of NIDDK (National Institute of Diabetes and Digestive and Kidney Disease).

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Cite this (NIH Human Connectome Project, RRID:SCR_006942)

URL: http://humanconnectome.org/consortia/

Resource Type: Resource, organization portal, portal, consortium, data or information resource

Project to map the neural pathways that underlie human brain function for several modalities of neuroimaging data including fMRI. The purpose of the Project is to acquire and share data about the structural and functional connectivity of the human brain. It will greatly advance the capabilities for imaging and analyzing brain connections, resulting in improved sensitivity, resolution, and utility, thereby accelerating progress in the emerging field of human connectomics. Altogether, the Human Connectome Project will lead to major advances in the understanding of what makes us uniquely human and will set the stage for future studies of abnormal brain circuits in many neurological and psychiatric disorders. The sixteen institutes and centers of the NIH Blueprint for Neuroscience have funded two major grants that will take complementary approaches to deciphering the brain's amazingly complex wiring diagram. An 11-institution consortium led by Washington University in St. Louis and the University of Minnesota received a 5-year grant to enable development and utilization of advanced Magnetic Resonance Imaging (MRI) methods to chart brain circuitry. A consortium led by Massachusetts General Hospital and the University of California at Los Angeles received a grant to enable building and refining a next-generation 3T MR scanner that improves the quality and spatial resolution with which brain connectivity data can be acquired at this field strength.

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Cite this (NIH MRI Study of Normal Brain Development, RRID:SCR_003394)

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

Resource Type: Resource, data set, narrative resource, experimental protocol, data or information resource

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.

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Cite this (Parkinson's Progression Markers Initiative, RRID:SCR_006431)

URL: http://www.ppmi-info.org/

Resource Type: Resource, organization portal, database, biomaterial supply resource, consortium, portal, material resource, clinical trial, data or information resource

An observational longitudinal clinical study partnership to identify and validate biomarkers of Parkinson disease (PD) progression and provide easy and open web-based access to the comprehensive set of correlated clinical data and biospecimens, information, and biosamples acquired from PD and age and gender matched healthy control subjects to the research community. The data and specimens have been collected in a standardized manner under strict protocols and includes clinical (demographic, motor and non-motor, cognitive and neurobehavioral), imaging (raw and processed MRI, SPECT and DAT), and blood chemistry and hematology subject assessments and biospecimen inventories (serum, plasma, whole blood, CSF, DNA, RNA and urine). All data are de-identified to protect patient privacy. PPMI will be carried out over five years at 21 clinical sites in the United States and Europe and requires the participation of 400 Parkinson's patients and 200 control participants. The PPMI database provides researchers with access to correlated clinical and imaging data, along with annotated biospecimens, all available within an open access system that encourages data sharing (http://www.ppmi-info.org/access-data-specimens/). The website hosts an Ongoing Analysis section to keep the scientific community apprised of analyses being completed, in hopes of stimulating collaborations between researchers who are using PPMI data and specimens.

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