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Proper citation: Chungbuk National University; Cheongju; South Korea (RRID:SCR_003570) Copy
http://phewas.mc.vanderbilt.edu/
Catalog of phenome-wide association study (PheWAS) results for 3,144 single-nucleotide polymorphisms (SNPs) present in the NHGRI GWAS Catalog as of 4/17/2012 in 13,835 European-ancestry individuals from five sites of the Electronic Medical Records and Genomics (eMERGE) network. A total of 1,358 EMR-derived phenotypes were analyzed for each SNP. This PheWAS replicated 66% (51/77) of sufficiently powered prior GWAS associations, and 210/751 of all prior GWAS associations. They also identified 63 potentially pleiotropic associations with p < 4.6x10-6 (false discovery rate < 0.1); the strongest of these novel associations replicated in an independent cohort (n=7,406). The catalog contains all associations with p < 0.05 (uncorrected)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: PheWAS Catalog (RRID:SCR_003562) Copy
Public research university in Sha Tin, New Territories, Hong Kong.
Proper citation: Chinese University of Hong Kong; Hong Kong; China (RRID:SCR_003440) Copy
Biomedical technology research center that develops new algorithms, visualizations and conceptual frameworks to study biological networks at multiple levels and scales, from protein-protein and genetic interactions to cell-cell communication and vast social networks. They are developing freely available, open-source suite of software technology that broadly enables network-based visualization, analysis, and biomedical discovery for NIH-funded researchers. This software is enabling researchers to assemble large-scale biological data into models of networks and pathways and to use these networks to better understand how biological systems operate under normal conditions and how they fail in disease. The National Resource for Network Biology is organized around the following key components: Technology Research and Development, Driving Biomedical Projects, Outreach, Training and Dissemination of Tools. The NRNB supports several types of training events, including both virtual and live workshops; tutorials sessions for clinicians, biologists and bioinformaticians; presentations and demonstrations at conferences; online tutorials and webcasts; and annual symposium.
Proper citation: National Resource for Network Biology (RRID:SCR_004259) Copy
http://www.broad.mit.edu/annotation/fungi/fgi/
Produces and analyzes sequence data from fungal organisms that are important to medicine, agriculture and industry. The FGI is a partnership between the Broad Institute and the wider fungal research community, with the selection of target genomes governed by a steering committee of fungal scientists. Organisms are selected for sequencing as part of a cohesive strategy that considers the value of data from each organism, given their role in basic research, health, agriculture and industry, as well as their value in comparative genomics.
Proper citation: Fungal Genome Initiative (RRID:SCR_003169) Copy
http://www.proteinbiotechnologies.com/
Protein Biotechnologies Inc., a San Diego, California based company, provides global pharmaceutical, biotechnology, government and academic institutions with human clinical specimen derivatives and high-throughput protein and tissue microarrays. With the largest collection of ready-to-use, clinically defined, pathology-validated human specimen derivatives on the market, Protein Biotechnologies facilitates biomedical research and drug discovery efforts for cancer, neurodegenerative diseases, cardiovascular diseases, diabetes / obesity and autoimmune disease research. To facilitate high-throughput screening of human clinical specimens, Protein Biotechnologies provides its tissue lysate library on ready-to-use protein microarrays. And, for protein localization, immunohistochemical and in-situ hybridization studies, Protein Biotechnologies'' tissue microarrays are an ideal method for studying multiple human cancer / normal tissues in a single assay. Key Products & Services: * Reverse Phase Protein Microarrays * Human Clinical Tissue Lysates * Tissue Microarrays * Primary & Secondary Antibodies * Supplemental Research Reagents * Protein, RNA and DNA Isolation and Purification * Peptide Synthesis * Custom Protein and Peptide Microarray Design and Manufacturing * Custom Antibody Production
Proper citation: Protein Biotechnologies (RRID:SCR_004893) Copy
Proper citation: University of Ljubljana; Ljubljana; Slovenia (RRID:SCR_004498) Copy
Proper citation: University of Lausanne; Lausanne; Switzerland (RRID:SCR_004773) Copy
http://sccn.ucsd.edu/~arno/fam2data/publicly_available_EEG_data.html
A collection of 32-channel EEG / ERP data from 14 subjects (7 males, 7 females) acquired using the Neuroscan software (3.6 Gb), made available by the laboratory of Arnaud Delormes, along with electrode files and images presented in the experiment. Subjects are performing a go-nogo categorization task and a go-no recognition task on natural photographs presented very briefly (20 ms). Images are only available for viewing. Each subject responded to a total of 2500 trials. Data is CZ referenced and is sampled at 1000 Hz (total data size is 4Gb). Alternate datasets are also compiled including one from the EEGLAB software tutorial.
Proper citation: EEG / ERP Data Set (RRID:SCR_004890) Copy
http://ranchobiosciences.com/gse4922/
Curated data set of a study that investigated the expression profiles of 347 primary invasive breast tumors on Affymetrix microarrays. Three separate breast cancer cohorts were analyzed: 1) Uppsala (n=249), 2) Stockholm (n=58), 3) Singapore (n=40). The Uppsala and Singapore data can be accessed in GSE4922. The Stockholm cohort data can be accessed at GEO Series GSE1456.
Proper citation: GSE4922 (RRID:SCR_003557) Copy
https://reich.hms.harvard.edu/software
XP-CLR (Chen et al. 2010) uses allele frequency differentiation at linked loci to detect selective sweeps. Source code and documentation are available.
Proper citation: XP-CLR (RRID:SCR_004961) Copy
http://www4.wiwiss.fu-berlin.de/bizer/d2r-server/
D2R Server is a tool for publishing relational databases on the Semantic Web. It enables RDF and HTML browsers to navigate the content of the database, and allows applications to query the database using the SPARQL query language. Data on the Semantic Web is modeled and represented in RDF. D2R Server uses a customizable D2RQ mapping to map database content into this format, and allows the RDF data to be browsed and searched the two main access paradigms to the Semantic Web. D2R Server''s Linked Data interface makes RDF descriptions of individual resources available over the HTTP protocol. An RDF description can be retrieved simply by accessing the resource''s URI over the Web. Using a Semantic Web browser like Tabulator (slides) or Disco, you can follow links from one resource to the next, surfing the Web of Data. The SPARQL interface enables applications to search and query the database using the SPARQL query language over the SPARQL protocol. Requests from the Web are rewritten into SQL queries via the mapping. This on-the-fly translation allows publishing of RDF from large live databases and eliminates the need for replicating the data into a dedicated RDF triple store. The latest source code is available from the project''s CVS repository and can be browsed online.
Proper citation: D2R Server - Publishing Relational Databases on the Semantic Web (RRID:SCR_004963) Copy
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
https://neuinfo.org/mynif/search.php?q=nlx_149462&t=indexable&list=cover&nif=nlx_144509-1
A virtual database that indexes both BioNOT for negation data, and the Resource Discovery Pipeline: an automated resource discovery and semi-automated type characterization with text-mining scripts that facilitate curation team efforts to discover, integrate and display new content. This virtual database currently indexes the following resources: * BioNOT, http://snake.ims.uwm.edu/bionot/index.php?searchterm=mecp2+autism&submit=Search * Resource Discovery Pipeline, http://lucene1.neuinfo.org/nif_resource/current/
Proper citation: Integrated Auto-Extracted Annotation (RRID:SCR_005892) Copy
http://www.t1diabetes.nih.gov/T1D-PTP/
THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. Investigator access is provided to the established facilities and expertise needed to extend, enhance and validate preclinical studies of promising new therapeutics in cases where additional preclinical testing is needed to validate potential therapies under disease-specific conditions and in multiple animal models before therapeutics can enter the Type 1 Diabetes Rapid Access to Intervention Development (T1D-RAID) development pipeline. The T1D-RAID program provides resources for pre-clinical development of drugs, natural products, and biologics that will be tested as new therapeutics in type 1 diabetes clinical trials. The T1D-RAID program is not currently accepting applications. The T1D-PTP program currently supports two contracts, which are separate from each other and from the T1D-RAID NCI contract resources, to assist in preclinical development of therapeutics for T1D: * Agents to be tested for Preclinical Efficacy in Prevention or Reversal of Type 1 Diabetes in Rodent Models. Type 1 Diabetes Preclinical Testing Program (T1D-PTP) (NOT-DK-09-006) * Needs for Preclinical Efficacy Testing of Promising Agents to Prevent or Reverse Diabetic Complications (NOT-DK-09-009) The T1D-RAID and T1D-PTP are programs intended to remove the most common barriers to progress in identification and development of new therapies for Type 1 Diabetes. The common goal of these programs is to support and provide for the preclinical work necessary to obtain proof of principle establishing that a new molecule or novel approach will be a viable candidate for expanded clinical evaluation.
Proper citation: Type 1 Diabetes Preclinical Testing Program (RRID:SCR_006861) Copy
http://www.zv.uni-leipzig.de/en/
Proper citation: University of Leipzig; Saxony; Germany (RRID:SCR_004960) Copy
A targeting model that defines where mutations occur (by specifying the relative rates at which DNA motifs in the Ig sequence are mutated), and a nucleotide substitution model that defines the resulting mutation (by specifying the probability of each base mutating to each of the other three possibilities as a function of the surrounding bases).
Proper citation: Models of SHM Targeting and Substitution (RRID:SCR_005250) Copy
http://www.cs.tau.ac.il/~shlomito/tissue-net/
THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. Network visualizations in which the expression and predicted flux data are projected over the global human network. These network visualizations are accessible through the supplemental website using the publicly available Cytoscape software (Cline, Smoot et al. 2007). Since many high degree nodes exist in the network, special layouts are required to produce network visualizations that are readily interpretable. To this end we produced network visualizations in which hub nodes are repeated multiple times and hence layouts with a small number of edge crossings can be generated. Contains entries for brain compartments and brain pathways.
Proper citation: Network-based Prediction of Human Tissue-specific Metabolism (RRID:SCR_007392) Copy
Proper citation: University of Pisa; Pisa; Italy (RRID:SCR_006616) Copy
http://www.meduniwien.ac.at/homepage/1/
Proper citation: Medical University of Vienna; Vienna; Austria (RRID:SCR_005007) Copy
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