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http://www.nitrc.org/projects/eegdataanimal

A collection of 32-channel data from 14 subjects (7 males, 7 females) acquired using the Neuroscan software. Subjects are performing a go-nogo categorization task and a go-no recognition task on natural photographs presented very briefly (20 ms). Each subject responded to a total of 2500 trials. Data is CZ referenced and is sampled at 1000 Hz (total data size is 4Gb; more details are given later).

Proper citation: EEG human categorization data (RRID:SCR_009468) Copy   

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http://coordinatingcenter.ucsf.edu/pride/

Randomized controlled trial being conducted at two clinical centers in the United States to learn more about the effects of weight loss on urinary incontinence. About 330 overweight women aged 30 or older will participate and will be followed for 18 months. Efficacy of weight reduction as a treatment for urinary incontinence will be examined at 6 months following the intensive weight control program, and the sustained impact of the intervention will be examined at 18 months. To increase the maintenance of weight reduction and facilitate evaluation of the enduring impact of weight loss on urinary incontinence, they propose to study a motivation-based weight maintenance program. At the end of the intensive weight control program, women randomized to the weight loss program will be randomized to either a 12-month skill-based maintenance intervention or to a motivation-based maintenance intervention. The maintenance interventions maximize the potential for sustained weight loss and will allow them to determine if long-term weight reduction will produce continued improvement in urinary incontinence.

Proper citation: Program to Reduce Incontinence by Diet and Exercise (RRID:SCR_009018) Copy   

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https://www.accordtrial.org/public

Study testing whether strict glucose control lowers the risk of heart disease and stroke in adults with type 2 diabetes. In addition the study is exploring: 1) Whether in the context of good glycemic control the use of different lowering lipid drugs will further improve these outcomes and 2) If strict control of blood pressure will also have additional beneficial effects on reducing cardiovascular disease. The design was a randomized, multicenter, double 2 X 2 factorial trial in 10,251 patients with type 2 diabetes mellitus. It was designed to test the effects on major CVD events of intensive glycemia control, of fibrate treatment to increase HDL-cholesterol and lower triglycerides (in the context of good LDL-C and glycemia control), and of intensive blood pressure control (in the context of good glycemia control), each compared to an appropriate control. All 10,251 participants were in an overarching glycemia trial. In addition, one 2 X 2 trial addressed the lipid question in 5,518 of the participants and the other 2 X 2 trial addressed the blood pressure question in 4,733 of the participants. The glycemia trial was terminated early due to higher mortality in the intensive compared with the standard glycemia treatment strategies. The results were published in June 2008 (N Eng J Med 2008;358:2545-59). Study-delivered treatment for all ACCORD participants was stopped on June 30, 2009, and the participants were assisted as needed in transferring their care to a personal physician. The lipid and blood pressure results (as well as the microvascular outcomes and eye substudy results) were published in 2010. All participants are continuing to be followed in a non-treatment observational study.

Proper citation: ACCORD (RRID:SCR_009015) Copy   

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https://neuinfo.org/mynif/search.php?q=nlx_144644&t=indexable&list=cover&nif=nlx_144509-1

Dataset from an investigation of biochemical evidence of myocardial strain, oxidative stress, and cardiomyocyte injury in 55 acute KD subjects (30 with paired convalescent samples), 54 febrile control (FC), and 50 healthy control (HC) children by measuring concentrations of cardiovascular biomarkers. NT-proBNP and sST2 were elevated in acute KD subjects and correlated with impaired myocardial relaxation. These findings, combined with elevated levels of cTnI, suggest that both cardiomyocyte stress and cell death are associated with myocardial inflammation in acute KD.

Proper citation: Kawasaki Disease Dataset2 (RRID:SCR_008839) Copy   

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http://www.icpsr.umich.edu/icpsrweb/NACDA/studies/09813/version/1

A longitudinal study which follows the cohort of current residents and discharged residents sampled from the 1985 National Nursing Home Survey (NNHS), thus permitting study of nursing home and hospital utilization over time. The study was conducted in three waves. To supplement the current and discharged resident components, the 1985 NNHS included a new component - the Next-of-Kin (NOK). The NOK, using a Computer Assisted Telephone Interviewing (CATI) system, was designed to collect information about current and former nursing home residents that is not generally available from patient records or other sources in the nursing home. The NNHSF obtains additional information on a portion of the residents for whom a Current Resident Questionnaire (CRQ) or a Discharged Resident Questionnaire (DRQ) was completed. In September 1994, the NNHSF Mortality Public Use Data Tape was released, covering the years 1984-1990. It contains the multiple cause-of-death information for 6,507 subjects from the NNHSF found to be deceased after linking and matching of files with the National Death Index. Information on the mortality tape includes the date of death, region of occurrence and residence, etc. All NNHSF tapes include a patient identification number common across files to allow linkage among them. Data Availability: Public Use data tapes for each wave and the mortality tape are available through the National Technical Information Office (NTIS), NACDA and the ICPSCR at the University of Michigan. The 1985 survey tape includes eight files: the facility questionnaire, nursing staff questionnaire, current resident questionnaire, discharged resident questionnaire, expense questionnaire, nursing staff sampling list, current resident sampling list, discharged resident sampling list. The next-of-kin questionnaire is available on a separate tape. * Dates of Study: 1987-1990 * Study Features: Longitudinal * Sample Size: ** 1987: 6,001 (Wave I) ** 1988: 3,868 (Wave II) ** 1990: 3,041 (Wave III) Links: * Wave I (ICPSR): http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/09813 * Wave II (ICPSR): http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/09838 * Wave III (ICPSR): http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06142

Proper citation: National Nursing Home Survey Follow-Up (RRID:SCR_008948) Copy   

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http://gero.usc.edu/CBPH/nujlsoa/index.htm

Longitudinal data set of a nationally representative sample of the population aged 65 and over in Japan, comparable to that collected in the US and other countries. The first two waves of data are now available to the international research community. The sample is refreshed with younger members at each wave so it remains representative of the population at each wave. The study was designed primarily to investigate health status of the Japanese elderly and changes in health status over time. An additional aim is to investigate the impact of long-term care insurance system on the use of services by the Japanese elderly and to investigate the relationship between co-residence and the use of long term care. While the focus of the survey is health and health service utilization, other topics relevant to the aging experience are included such as intergenerational exchange, living arrangements, caregiving, and labor force participation. The initial questionnaire was designed to be comparable to the (US) Longitudinal Study of Aging II (LSOAII), and to the Asset and Health Dynamics Among the Oldest Old (AHEAD, a pre-1924 birth cohort) sample of the Health and Retirement Study (HRS), which has now been merged with the HRS. The sample was selected using a multistage stratified sampling method to generate 340 primary sampling units (PSUs). The sample of individuals was selected for the most part by using the National Residents Registry System, considered to be universal and accurate because it is a legal requirement to report any move to local authorities within two weeks. From each of the 340 PSUs, 6-11 persons aged 65-74 were selected and 8-12 persons aged 75+ were sampled. The population 75+ was oversampled by a factor of 2. Weights have been developed for respondents to the first wave of the survey to reflect sampling probabilities. Weights for the second wave are under development. With these weights, the sample should be representative of the 65+ Japanese population. In fall 1999, 4,997 respondents aged 65+ were interviewed, 74.6 percent of the initial target. Twelve percent of responses were provided by proxies, because of physical or mental health problems. The second wave of data was collected in November 2001. The third wave was collected in November 2003. Questionnaire topics include family structure, and living arrangements; subjects'''' parents/spouse''''s parents/children; socioeconomic status; intergenerational exchange; health behaviors, chronic conditions, physical functioning; activities of daily living and instrumental activities of daily living; functioning in the community; mental health depression measures; vision and hearing; dental health; health care and other service utilization. A CD is available which include the codebook and data files for the first and second waves of the national sample. The third wave of data will be released at a later date. * Dates of Study: 1999-2003 * Study Features: Longitudinal, International * Sample Size: ** 4,997 Nov/Dec 1999 Wave 1 ** 3,992 Nov 2001 Wave 2 ** Nov 2003 Wave 3 Link: * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/00156

Proper citation: Nihon University Japanese Longitudinal Study of Aging (RRID:SCR_008974) Copy   

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https://joslinresearch.org/drc-cores/Advanced-Genomics-and-Genetics-Core

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 27,2023. Core that provides services for genetic and genomic analysis, including DNA extraction from blood, access to DNA collections from the Core?s repository, SNP genotyping, and support for gene expression studies based on both high-density oligonucleotide arrays and real-time quantitative PCR.

Proper citation: Joslin Diabetes Center Advanced Genomics and Genetics Core Facility (RRID:SCR_009873) Copy   

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https://hddc.hms.harvard.edu/core-b

Core facility that provides service for paraffin embedding, sectioning, staining, and frozen sectioning; shared equipment and service for confocal, widefield, photodocumentation, electron microscopy, and digital image processing; and an immunostaining service.

Proper citation: Harvard Digestive Diseases Center Biomedical CORE B: Microscopy and Histopathology (RRID:SCR_009836) Copy   

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http://www.med.upenn.edu/idom/drc/cores/ria.html

Core which offers high quality immunoassay services to basic, translational, and clinical investigators performing diabetes and related metabolic disease research. The core also provides consultation and training and education services.

Proper citation: Penn Diabetes Research Center Radioimmunoassay and Biomarkers Core Facility (RRID:SCR_010028) Copy   

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http://toppcluster.cchmc.org/

A tool for performing multi-cluster gene functional enrichment analyses on large scale data (microarray experiments with many time-points, cell-types, tissue-types, etc.). It facilitates co-analysis of multiple gene lists and yields as output a rich functional map showing the shared and list-specific functional features. The output can be visualized in tabular, heatmap or network formats using built-in options as well as third-party software. It uses the hypergeometric test to obtain functional enrichment achieved via the gene list enrichment analysis option available in ToppGene.

Proper citation: ToppCluster (RRID:SCR_001503) Copy   

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https://sourceforge.net/projects/viste/

Open source, platform-independent application for the visualization and analysis of complex, high-dimensional imaging data such as Diffusion Tensor Imaging (DTI) and High Angular Resolution Diffusion Imaging (HARDI). It has a plugin-based architecture which allows third parties to develop new plugins to extend the tool. Overview of the many features: * vIST/e is programmed in C++. It uses the Visualization Toolkit for visualization and pipelined data processing, as well as the cross-platform toolkit Qt Framework for an easy-to-use Graphical User Interface. * vIST/e introduces a powerful new plugin system, which allows for modular development with increased extensibility and stability. * Powerful GPU-based visualization techniques allow for smooth, real-time visualization of large data sets. Using custom ray tracing algorithms created with OpenGL, vIST/e can render DTI ellipsoids and HARDI spherical harmonics glyphs up to 4th order. The high frame rates offered by modern GPU technology allows for interactive exploration of this complex data. * Diffusion Tensor Imaging data can be visualized and interactively explored in a number of ways, including multiple cross-sections, volume rendering, and tensor glyphs. Derived scalar volumes, including various different anisotropy measures, can be computed and visualized. Data from other modalities, such as structural MRI, can be shown alongside the DTI data. * Various fiber tracking methods allow for fast and accurate reconstruction of fiber pathways. Interactively defined Regions of Interest (ROIs) can be used for seeding and filtering of fibers. Fibers are visualized either as lines, optionally using a powerful, GPU-based lighting engine, or as 3D structures such as tubes. * Scalar volumes, glyphs, and fibers can be colored using a wide array of coloring option. Customizable color loop-up tables allow for highly flexible visualization of scalar data. * Visualization and processing of various different HARDI formats is supported. HARDI data is interactively visualized using highly detailed glyphs rendered on the GPU. HARDI glyphs can be visualized in combination with DTI glyphs, for a better overview of complex diffusion data. * vIST/e includes support for NVIDIA's Compute Unified Device Architecture (CUDA), which enables highly parallel, GPU-based data processing, allowing for significant speed-up of computationally expensive algorithms.

Proper citation: vIST/e (RRID:SCR_001627) Copy   

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http://coins.mrn.org/

A web-based neuroimaging and neuropsychology software suite that offers versatile, automatable data upload/import/entry options, rapid and secure sharing of data among PIs, querying and export all data, real-time reporting, and HIPAA and IRB compliant study-management tools suitable to large institutions as well as smaller scale neuroscience and neuropsychology researchers. COINS manages over over 400 studies, more than 265,000 clinical neuropsychological assessments, and 26,000 MRI, EEG, and MEG scan sessions collected from 18,000 participants at over ten institutions on topics related to the brain and behavior. As neuroimaging research continues to grow, dynamic neuroinformatics systems are necessary to store, retrieve, mine and share the massive amounts of data. The Collaborative Informatics and Neuroimaging Suite (COINS) has been created to facilitate communication and cultivate a data community. This tool suite offers versatile data upload/import/entry options, rapid and secure sharing of data among PIs, querying of data types and assessments, real-time reporting, and study-management tools suitable to large institutions as well as smaller scale researchers. It manages studies and their data at the Mind Research Network, the Nathan Kline Institute, University of Colorado Boulder, the Olin Neuropsychiatry Research Center (at) Hartford Hospital, and others. COINS is dynamic and evolves as the neuroimaging field grows. COINS consists of the following collaboration-centric tools: * Subject and Study Management: MICIS (Medical Imaging Computer Information System) is a centralized PostgreSQL-based web application that implements best practices for participant enrollment and management. Research site administrators can easily create and manage studies, as well as generate reports useful for reporting to funding agencies. * Scan Data Collection: An automated DICOM receiver collects, archives, and imports imaging data into the file system and COINS, requiring no user intervention. The database also offers scan annotation and behavioral data management, radiology review event reports, and scan time billing. * Assessment Data Collection: Clinical data gathered from interviews, questionnaires, and neuropsychological tests are entered into COINS through the web application called Assessment Manager (ASMT). ASMT's intuitive design allows users to start data collection with little or no training. ASMT offers several options for data collection/entry: dual data entry, for paper assessments, the Participant Portal, an online tool that allows subjects to fill out questionnaires, and Tablet entry, an offline data entry tool. * Data Sharing: De-identified neuroimaging datasets with associated clinical-data, cognitive-data, and associated meta-data are available through the COINS Data Exchange tool. The Data Exchange is an interface that allows investigators to request and share data. It also tracks data requests and keeps an inventory of data that has already been shared between users. Once requests for data have been approved, investigators can download the data directly from COINS.

Proper citation: Mind Research Network - COINS (RRID:SCR_000805) Copy   

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http://burgundy.cmmt.ubc.ca/cgi-bin/RAVEN/a?rm=home

Tool to search for putative regulatory genetic variation in your favorite gene. Single nucleotide polymorphisms (SNPs) (from dbSNP and user defined) are analyzed for overlap with potential transcription factor binding sites (TFBS) and phylogenetic footprinting using UCSC phastCons scores from multiple alignments of 8 vertebrate genomes., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: RAVEN (RRID:SCR_001937) Copy   

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http://pennadc.org

A national Alzhiemer's disease research center funded by the National Institute on Aging, and the research arm of the Penn Memory Center.

Proper citation: Penn Alzheimer's Disease Center (RRID:SCR_004444) Copy   

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http://cobre.mrn.org/megsim/

Realistic simulated MEG datasets ranging from basic sensory to oscillatory sets that mimic functional connectivity; as well as basic visual, auditory, and somatosensory empirical sets. The simulated sets were created for the purpose of testing analysis algorithms across the different MEG systems when the truth is known. MEG baseline recordings were obtained from 5 healthy participants, using three MEG systems: VSM/CTF Omega, Elekta Neuromag Vectorview, 4-D Magnes 3600. Simulated signals were embedded within the CTF and Neuromag 306 baseline recordings (4-D to be added). Participant MRIs are available. Averaged simulation files are available as netcdf files. Neuromag 306 averaged simulations are also available in fif format. Also available: single trials of data where the simulated signal is jittered about a mean value, continuous fif files where the simulated signal is marked by a trigger, and simulations with oscillations added to mimic functional connectivity.

Proper citation: MEGSIM (RRID:SCR_002420) Copy   

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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   

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http://www.GeneWeaver.org

Freely accessible phenotype-centered database with integrated analysis and visualization tools. It combines diverse data sets from multiple species and experiment types, and allows data sharing across collaborative groups or to public users. It was conceived of as a tool for the integration of biological functions based on the molecular processes that subserved them. From these data, an empirically derived ontology may one day be inferred. Users have found the system valuable for a wide range of applications in the arena of functional genomic data integration.

Proper citation: Gene Weaver (RRID:SCR_003009) Copy   

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http://crdd.osdd.net/servers/virsirnadb/

VIRsiRNAdb is a curated database of experimentally validated viral siRNA / shRNA targeting diverse genes of 42 important human viruses including influenza, SARS and Hepatitis viruses. Submissions are welcome. Currently, the database provides detailed experimental information of 1358 siRNA/shRNA which includes siRNA sequence, virus subtype, target gene, GenBank accession, design algorithm, cell type, test object, test method and efficacy (mostly quantitative efficacies). Further, wherever available, information regarding alternative efficacies of above 300 siRNAs derived from different assays has also been incorporated. The database has facilities like search, advance search (using Boolean operators AND, OR) browsing (with data sorting option), internal linking and external linking to other databases (Pubmed, Genbank, ICTV). Additionally useful siRNA analysis tools are also provided e.g. siTarAlign for aligning the siRNA sequence with reference viral genomes or user defined sequences. virsiRNAdb would prove useful for RNAi researchers especially in siRNA based antiviral therapeutics development.

Proper citation: VIRsiRNAdb (RRID:SCR_006108) Copy   

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http://snpeffect.vib.be/

A database for phenotyping human single nucleotide polymorphisms (SNPs)that primarily focuses on the molecular characterization and annotation of disease and polymorphism variants in the human proteome. They provide a detailed variant analysis using their tools such as: * TANGO to predict aggregation prone regions * WALTZ to predict amylogenic regions * LIMBO to predict hsp70 chaperone binding sites * FoldX to analyse the effect on structure stability Further, SNPeffect holds per-variant annotations on functional sites, structural features and post-translational modification. The meta-analysis tool enables scientists to carry out a large scale mining of SNPeffect data and visualize the results in a graph. It is now possible to submit custom single protein variants for a detailed phenotypic analysis., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: SNPeffect (RRID:SCR_005091) Copy   

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http://jilab.biostat.jhsph.edu/database/cgi-bin/hmChIP.pl

A database of genome-wide chromatin immunoprecipitation (ChIP) data in human and mouse. Currently, the database contains >2000 samples from >500 ChIP-seq and ChIP-chip experiments, representing a total of >170 proteins and >10,000,000 protein-DNA interactions (March 2014). A web server provides an interface for database query. Protein-DNA binding intensities can be retrieved from individual samples for user-provided genomic regions. The retrieved intensities can be used to cluster samples and genomic regions to facilitate exploration of combinatorial patterns, cell type dependencies, and cross-sample variability of protein-DNA interactions.

Proper citation: hmChIP (RRID:SCR_005407) Copy   

•   Source: SciCrunch Registry