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http://www.ipha.ie/alist/ifpma-clinical-trials-portal.aspx

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. IFPMA Clinical Trials Portal is brought to you by IFPMA on behalf of its Member Companies and Associations. IFPMA Clinical Trials Portal ensures: a free and easy-to-use interface for patients and health professionals alike to ongoing clinical trials, clinical trial results and complementary information on related issues; non-promotional and reliable information; industry's commitment to the transparency of clinical trials. * Search by Medical Condition and Drug Name * Language Interfaces (En, Es, Fr, De, Jp) * Glossary and Easy Explanation of Medical Expressions * Geographical Search

Proper citation: IFPMA Clinical Trials Portal (RRID:SCR_000791) Copy   

•   Source: SciCrunch Registry

https://www.clinicaltrialsregister.eu

Database of European clinical trials containing information on interventional clinical trials on medicines. The information available dates from 1 May 2004 when national medicine regulatory authorities began populating the EudraCT database, the application that is used by national medicine regulatory authorities to enter clinical trial data. The EU Clinical Trials Register website launched on 22 March 2011 enables users to search for information which has been included in the EudraCT database. Users are able to: * view the description of a phase II-IV adult clinical trial where the investigator sites are in European Union member states and the European Economic Area; * view the description of any pediatric clinical trial with investigator sites in the European Union and any trials which form part of a pediatric investigation plan (PIP) including those where the investigator sites are outside the European Union. * download up to 20 results (per request) in a text file (.txt). The details in the clinical trial description include: * the design of the trial; * the sponsor; * the investigational medicine (trade name or active substance identification); * the therapeutic areas; * the status (authorized, ongoing, complete).

Proper citation: EU Clinical Trials Register (RRID:SCR_005956) Copy   

•   Source: SciCrunch Registry

http://yh.genomics.org.cn

This database presents the entire DNA sequence of the first diploid genome sequence of a Han Chinese, a representative of Asian population. The genome, named as YH, represents the start of YanHuang Project, which aims to sequence 100 Chinese individuals in 3 years. It was assembled based on 3.3 billion reads (117.7Gbp raw data) generated by Illumina Genome Analyzer. In total of 102.9Gbp nucleotides were mapped onto the NCBI human reference genome (Build 36) by self-developed software SOAP (Short Oligonucleotide Alignment Program), and 3.07 million SNPs were identified. The personal genome data is illustrated in a MapView, which is powered by GBrowse. A new module was developed to browse large-scale short reads alignment. This module enabled users track detailed divergences between consensus and sequencing reads. In total of 53,643 HGMD recorders were used to screen YH SNPs to retrieve phenotype related information, to superficially explain the donor's genome. Blast service to align query sequences against YH genome consensus was also provided.

Proper citation: YanHuang Project (RRID:SCR_006077) Copy   

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http://research.nhgri.nih.gov/CGD/

Manually curated database of all conditions with known genetic causes, focusing on medically significant genetic data with available interventions. Includes gene symbol, conditions, allelic conditions, inheritance, age in which interventions are indicated, clinical categorization, and general description of interventions/rationale. Contents are intended to describe types of interventions that might be considered. Includes only single gene alterations and does not include genetic associations or susceptibility factors related to more complex diseases.

Proper citation: Clinical Genomic Database (RRID:SCR_006427) Copy   

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https://www.radc.rush.edu/res/ext/home.htm

An Alzheimer's disease center which researches the cause, treatment and prevention of Alzheimer's disease with a focus on four main areas of research: risk factors for Alzheimer's and related disorders, the neurological basis of the disease, diagnosis, and treatment. Data includes a number of computed variables that are available for ROS, MAP and MARS cohorts. These variables are under categories such as affect and personality, chronic medical conditions, and clinical diagnosis. Specimens include ante-mortem and post-mortem samples obtained from subjects evaluated by ROS, MAP and clinical study cores. Specimen categories include: Brain tissue (Fixed and frozen), Spinal cord, Muscles (Post-mortem), and Nerve (Post-mortem), among other types of specimens. Data sharing policies and procedures apply to obtaining ante-mortem and post-mortem specimens from participants evaluated by the selected cohorts of the RADC.

Proper citation: Rush Alzheimer's Disease Center (RRID:SCR_008763) Copy   

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http://adc.med.nyu.edu/

The NYU Alzheimer's Disease Center is part of the Department of Psychiatry at New York University School of Medicine. The center's goals are to advance current knowledge and understanding of brain aging and Alzheimer's disease, to expand the numbers of scientists working in the field of aging and Alzheimer's research, to work toward better treatment options and care for patients, and to apply and share its findings with healthcare providers, researchers, and the general public. The ADC's programs and services extend to other research facilities and to healthcare professionals through the use of its core facilities. The NYU ADC is made up of seven core facilities: Administrative Core, Clinical Core, Neuropathology Core, Education Core, Data Management and Biostatistics Core, Neuroimaging Core, and Psychosocial Core.

Proper citation: NYU Alzheimer's Disease Center (RRID:SCR_008754) Copy   

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https://www.bannerhealth.com/research/locations/sun-health-institute/programs/body-donation

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 11, 2023. An autopsy-based, research-devoted brain bank, biobank and biospecimen bank that derives its human donors from the Arizona Study of Aging and Neurodegenerative Disease (AZSAND), a longitudinal clinicopathological study of the health and diseases of elderly volunteers living in Maricopa county and metropolitan Phoenix, Arizona. Their function is studied during life and their organs and tissue after death. To date, they have concentrated their studies on Alzheimer's disease, Parkinson's disease, heart disease and cancer. They share the banked tissue, biomaterials and biospecimens with qualified researchers worldwide. Registrants with suitable scientific credentials will be allowed access to a database of available tissue linked to relevant clinical information, and will allow tissue requests to be initiated., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Brain and Body Donation Program (RRID:SCR_004822) Copy   

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https://ctsi.ucsf.edu

An institute which provides infrastructure, services, and training to support clinical and translational research. It develops broad coalitions and partnerships at the local and national levels to enable a transformation of the research environment.

Proper citation: UCSF Clinical and Translational Science Institute (RRID:SCR_014711) Copy   

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http://www.icpsr.umich.edu/icpsrweb/NACDA/studies/02744/version/1

Data set of a follow-up study (one of four Established Populations for Epidemiologic Studies of the Elderly - EPESE) that obtains information on four primary outcome variables (cognitive status, depression, functional status, and mortality) and four primary independent variables (social support, social class, social location, and chronic illness); and examines the relationships between social factors and chronic disease on the one hand and health outcomes on the other. This data set complements the other three sites providing a population which is both urban and rural and contains approximately equal numbers of black and white participants across a broad socioeconomic base. The Duke site was originally funded by the NIA Epidemiology, Demography and Biometry Program (EDBP) to complete seven waves of data collection (three in-person and four telephone interviews) in order to examine the health of a sample of 4,162 persons aged 65+, and factors that influence their health and use of health services. The cohort was originally interviewed in 1986/87 and followed annually for 6 years thereafter. The study design consisted of a random stratified household sample with an over-sampling of blacks. Questionnaire topics include the following: Demographics, Alcohol Use, Independence, Health condition, Cognition, Personal mastery, Health Service Utilization, Activity of daily living, Social Support, Hearing and Vision, Incontinence, Social Interaction, Weight and Height, Smoking, Religion, Nutrition, Life Satisfaction, Self Esteem, Sleep, Medications, Economic Status, Depression, Life Changes, Blood pressure. National Death Index files have been searched and death certificates obtained for the members of this study. Sample members have been matched with Medicare Part A files to obtain information on hospitalizations, and will be matched on Medicare Part B (outpatient) files. Data from the first wave of the survey is in the public domain and can be obtained from NACDA or from the National Archives, Center for Electronic Records in Washington, DC. * Dates of Study: 1996-1997 * Study Features: Longitudinal, Oversampling * Sample Size: 1986-1988: 4,162 Links: * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/02744 * National Archives: http://www.archives.gov/research/electronic-records/

Proper citation: Piedmont Health Survey of the Elderly (RRID:SCR_006349) Copy   

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http://www.ifs.org.uk/ELSA

An interdisciplinary data resource on health, economic position and quality of life as people age. Longitudinal multidisciplinary data from a representative sample of the English population aged 50 and older have been collected. Both objective and subjective data are collected relating to health and disability, biological markers of disease, economic circumstance, social participation, networks and well-being. Participants are surveyed every two years to see how people''s health, economic and social circumstances may change over time. One of the study''s aims is to determine the relationships between functioning and health, social networks, resources and economic position as people plan for, move into and progress beyond retirement. It is patterned after the Health and Retirement Study, a similar study based in the United States. ELSA''s method of data collection includes face-to-face interview with respondents aged 50+; self-completion; and clinical, physical, and performance measurements (e.g., timed walk). Wave 2 added questions about quality of health care, literacy, and household consumption, and a visit by a nurse to obtain anthropometric, blood pressure, and lung function measurements, as well as saliva and blood samples, and to record results from tests of balance and muscle strength. Another new aspect of Wave 2 is the ''Exit Interview'' carried out with proxy informants to collect data about respondents who have died since Wave 1. This interview includes questions about the respondents'' physical and psychological health, the care and support they received, their memory and mood in the last year of their life, and details of what has happened to their finances after their death. Wave 3 data added questions related to mortgages and pensions. The intention is to conduct interviews every 2 years, and to have a nurse visit every 4 years. It also is envisioned that the ELSA data will ultimately be linked to available administrative data, such as death registry data, a cancer register, NHS hospital episodes data, National Insurance contributions, benefits, and tax credit records. The survey data are designed to be used for the investigation of a broad set of topics relevant to understanding the aging process. These include: * health trajectories, disability and healthy life expectancy; * the determinants of economic position in older age; * the links between economic position, physical health, cognition and mental health; * the nature and timing of retirement and post-retirement labour market activity; * household and family structure, social networks and social supports; * patterns, determinants and consequences of social, civic and cultural participation; * predictors of well-being. Current funding for ELSA will extend the panel to 12 years of study, giving significant potential for longitudinal analyses to examine causal processes. * Dates of Study: 2002-2007 * Study Features: Longitudinal, International, Anthropometric Measures * Sample Size: ** 2000-2003 (Wave 1): 12,100 ** 2004-2005 (Wave 2): 9,433 ** 2006-2007 (Wave 3): 9,771 ** 2008-2009 (Wave 4): underway Links * Economic and Social Data Service (ESDS): http://www.esds.ac.uk/longitudinal/about/overview.asp * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/00139#scope-of-study

Proper citation: English Longitudinal Study of Ageing (RRID:SCR_006727) Copy   

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http://www.rand.org/labor/FLS/MHSS.html

A data set of the health and socioeconomic factors that affect the elderly in Matlab, a region of rural Bangladesh. The survey captures measurements and statistics such as adult survival, health status, health care utilization, resource flows between generations and the impact of community services and infrastructure on adult health care. Data was collected through surveys that touch on four topics: household and individual information; determinants of natural fertility; migration out of the community; and community and provider survey of healthcare and education infrastructure.

Proper citation: Matlab Health and Socio-Economic Survey (RRID:SCR_008942) Copy   

•   Source: SciCrunch Registry

https://www.clinicalgenome.org

Genomics knowledgebase for clinical relevance of genes and variants for use in research. ClinGen's primary function is to store and share information for the benefit of the scientific community. Laboratory scientists, clinicians, and patients can share and access data.

Proper citation: ClinGen (RRID:SCR_014968) Copy   

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

Datasets including a collection of scans from 49 psychiatrically evaluated neurotypical adults, ranging in age from 6 to 55 years old, with age, gender and intelligence quotient (IQ) information provided. Future releases will include more comprehensive phenotypic information, and child and adolescent datasets, as well as individuals from clinical populations. The following data are released for every participant: * At least one 6-minute resting state fMRI scan (R-fMRI) * * One high-resolution T1-weighted mprage, defaced to protect patient confidentiality * Two 64-direction diffusion tensor imaging scans * Demographic information (age, gender) and IQ-measures (Verbal, Performance, and Composite; Weschler Abbreviated Scale of Intelligence - WASI) * Most participants have 2 R-fMRI scans, collected less than 1 hour apart in the same scanning session. Rest_1 is always collected first.

Proper citation: NYU Institute for Pediatric Neuroscience Sample (RRID:SCR_010458) Copy   

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http://fcon_1000.projects.nitrc.org/indi/retro/cobre.html

Data set of raw anatomical and functional MR data from 72 patients with Schizophrenia and 75 healthy controls (ages ranging from 18 to 65 in each group). All subjects were screened and excluded if they had: history of neurological disorder, history of mental retardation, history of severe head trauma with more than 5 minutes loss of consciousness, history of substance abuse or dependence within the last 12 months. Diagnostic information was collected using the Structured Clinical Interview used for DSM Disorders (SCID). A multi-echo MPRAGE (MEMPR) sequence was used with the following parameters: TR/TE/TI = 2530/(1.64, 3.5, 5.36, 7.22, 9.08)/900 ms, flip angle = 7��, FOV = 256x256 mm, Slab thickness = 176 mm, Matrix = 256x256x176, Voxel size =1x1x1 mm, Number of echos = 5, Pixel bandwidth =650 Hz, Total scan time = 6 min. With 5 echoes, the TR, TI and time to encode partitions for the MEMPR are similar to that of a conventional MPRAGE, resulting in similar GM/WM/CSF contrast. Rest data was collected with single-shot full k-space echo-planar imaging (EPI) with ramp sampling correction using the intercomissural line (AC-PC) as a reference (TR: 2 s, TE: 29 ms, matrix size: 64x64, 32 slices, voxel size: 3x3x4 mm3). Slice Acquisition Order: Rest scan - collected in the Axial plane - series ascending - multi slice mode - interleaved MPRAGE - collected in the Sag plane - series interleaved - multi slice mode - single shot The following data are released for every participant: * Resting fMRI * Anatomical MRI * Phenotypic data for every participant including: gender, age, handedness and diagnostic information.

Proper citation: COBRE (RRID:SCR_010482) Copy   

•   Source: SciCrunch Registry

http://mips.gsf.de/services/genomes/uwe25/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 15, 2013. This is the official database of the environmental chlamydia genome project. This resource provides access to finished sequence for Parachlamydia-related symbiont UWE25 and to a wide range of manual annotations, automatical analyses and derived datasets. Functional classification and description has been manually annotated according to the Annotation guidelines. Chlamydiae are the major cause of preventable blindness and sexually transmitted disease. Genome analysis of a chlamydia-related symbiont of free-living amoebae revealed that it is twice as large as any of the pathogenic chlamydiae and had few signs of recent lateral gene acquisition. We showed that about 700 million years ago the last common ancestor of pathogenic and symbiotic chlamydiae was already adapted to intracellular survival in early eukaryotes and contained many virulence factors found in modern pathogenic chlamydiae, including a type III secretion system. Ancient chlamydiae appear to be the originators of mechanisms for the exploitation of eukaryotic cells. Environmental chlamydiae have recently been recognized as obligate endosymbionts of free-living amoebae and have been implicated as potential human pathogens. Environmental chlamydiae form a deep branching evolutionary lineage within the medically important order Chlamydiales. Despite their high diversity and ubiquitous distribution in clinical and environmental samples only limited information about genetics and ecology of these microorganisms is available. The Parachlamydia-related Acanthamoeba symbiont UWE25 was therefore selected as representative environmental chlamydia strain for whole genome sequencing. Comparative genome analysis was performed using PEDANT and simap. Sponsors: The environmental chlamydia genome project was funded by the bmb+f (German Federal Ministry of Education and Research) and is part of the Competence Network PathoGenoMiK.

Proper citation: Protochlamydia amoebophila UWE25 (RRID:SCR_008222) Copy   

•   Source: SciCrunch Registry

http://www.ohsu.edu/xd/research/centers-institutes/neurology/alzheimers/research/data-tissue/clinical-data.cfm

A database housing longitudinal relational research data from over 4,000 research subjects. The database includes the following types of data: physical and neurological exam findings, neurocognitive test scores, personal and family history of dementia, personal demographic genotypes (APOE, HLA), age at service evaluations, age at onset, age at death, clinical diagnosis, neuropathology diagnosis, tissue inventory information (when available), health status, medications, laboratory tests, and MRI data.

Proper citation: Layton Center Clinical Data Resources (RRID:SCR_008822) Copy   

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http://www.vaccineinjury.info/vaccine-damage-reports-2010.html

Database of case reports of adverse reactions to vaccinations. There are 806 reports (May 2013). If you would like to report a case, please go to report your own vaccine reaction. The user may search by keywords or sort by vaccine, country, age, outcome, gender and hospital admission.

Proper citation: Vaccine damage reports database (RRID:SCR_010740) Copy   

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http://tcm.lifescience.ntu.edu.tw/index.html

TCMGeneDIT is a database system providing association information about traditional Chinese medicines (TCMs), genes, diseases, TCM effects and TCM ingredients automatically mined from vast amount of biomedical literature. Integrated protein-protein interaction and biological pathways information collected from public databases are also available. In addition, the transitive relationships among genes, TCMs and diseases could be inferred through the shared intermediates. Furthermore, TCMGeneDIT is useful in deducing possible synergistic or antagonistic contributions of the prescription components to the overall therapeutic effects. TCMGeneDIT is a unique database of various association information about TCMs. The database integrating TCMs with life sciences and biomedical studies would facilitate the modern clinical research and the understanding of therapeutic mechanisms of TCMs and gene regulations.

Proper citation: TCMGeneDIT (RRID:SCR_013396) Copy   

•   Source: SciCrunch Registry

http://dtp.nci.nih.gov/docs/3d_database/dis3d.html

The NCI DIS 3D database is a collection of 3D structures for over 400,000 drugs. The database is an extension of the NCI Drug Information System. The structural information stored in the DIS is only the connection table for each drug. The connection table is just a list of which atoms are connected and how they are connected. It is essentially a searcheable database of three-dimensional structures has been developed from the chemistry database of the NCI Drug Information System (DIS), a file of about 450,000 primarily organic compounds which have been tested by NCI for anticancer activity. The DIS database is very similar in size and content to the proprietary databases used in the pharmaceutical industry; its development began in the 1950s; and this history led to a number of problems in the generation of 3D structures. This information can be searched to find drugs that share similar patterns of connections, which can correlate with similar biological activity. But the cellular targets for drug action, as well as the drugs themselves, are 3 dimensional objects and advances in computer hardware and software have reached the point where they can be represented as such. In many cases the important points of interaction between a drug and its target can be represented by a 3D arrangement of a small number of atoms. Such a group of atoms is called a pharmacophore. The pharmacophore can be used to search 3D databases and drugs that match the pharmacophore could have similar biological activity, but have very different patterns of atomic connections. Having a diverse set of lead compounds increases the chances of finding an active compound with acceptable properties for clinical development. Sponsor: The ICBG are supported by the Cooperative Agreement mechanism, with funds from nine components of the NIH, the National Science Foundation, and the Foreign Agricultural Service of the USDA.

Proper citation: National Cancer Institute 3D Structure Database (RRID:SCR_008211) Copy   

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http://www.commondataelements.ninds.nih.gov

The purpose of the NINDS Common Data Elements (CDEs) Project is to standardize the collection of investigational data in order to facilitate comparison of results across studies and more effectively aggregate information into significant metadata results. The goal of the National Institute of Neurological Disorders and Stroke (NINDS) CDE Project specifically is to develop data standards for clinical research within the neurological community. Central to this Project is the creation of common definitions and data sets so that information (data) is consistently captured and recorded across studies. To harmonize data collected from clinical studies, the NINDS Office of Clinical Research is spearheading the effort to develop CDEs in neuroscience. This Web site outlines these data standards and provides accompanying tools to help investigators and research teams collect and record standardized clinical data. The Institute still encourages creativity and uniqueness by allowing investigators to independently identify and add their own critical variables. The CDEs have been identified through review of the documentation of numerous studies funded by NINDS, review of the literature and regulatory requirements, and review of other Institute''s common data efforts. Other data standards such as those of the Clinical Data Interchange Standards Consortium (CDISC), the Clinical Data Acquisition Standards Harmonization (CDASH) Initiative, ClinicalTrials.gov, the NINDS Genetics Repository, and the NIH Roadmap efforts have also been followed to ensure that the NINDS CDEs are comprehensive and as compatible as possible with those standards. CDEs now available: * General (CDEs that cross diseases) Updated Feb. 2011! * Congenital Muscular Dystrophy * Epilepsy (Updated Sept 2011) * Friedreich''s Ataxia * Parkinson''s Disease * Spinal Cord Injury * Stroke * Traumatic Brain Injury CDEs in development: * Amyotrophic Lateral Sclerosis (Public review Sept 15 through Nov 15) * Frontotemporal Dementia * Headache * Huntington''s Disease * Multiple Sclerosis * Neuromuscular Diseases ** Adult and pediatric working groups are being finalized and these groups will focus on: Duchenne Muscular Dystrophy, Facioscapulohumeral Muscular Dystrophy, Myasthenia Gravis, Myotonic Dystrophy, and Spinal Muscular Atrophy The following tools are available through this portal: * CDE Catalog - includes the universe of all CDEs. Users are able to search the full universe to isolate a subset of the CDEs (e.g., all stroke-specific CDEs, all pediatric epilepsy CDEs, etc.) and download details about those CDEs. * CRF Library - (a.k.a., Library of Case Report Form Modules and Guidelines) contains all the CRF Modules that have been created through the NINDS CDE Project as well as various guideline documents. Users are able to search the library to find CRF Modules and Guidelines of interest. * Form Builder - enables users to start the process of assembling a CRF or form by allowing them to choose the CDEs they would like to include on the form. This tool is intended to assist data managers and database developers to create data dictionaries for their study forms.

Proper citation: NINDS Common Data Elements (RRID:SCR_006577) Copy   

•   Source: SciCrunch Registry