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

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On page 477 showing 9521 ~ 9540 out of 26,883 results
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http://www.cau.edu.cn/cie/en/

Proper citation: China Agricultural University; Beijing; China (RRID:SCR_003426) Copy   


  • RRID:SCR_002852

    This resource has 1000+ mentions.

http://www.panlab.com/panlabWeb/Software/php/displaySoft.php?nameSoft=SMART%20VIDEO-TRACKING

Software for the automated evaluation of behavior in a range of pre-clinical and neuroscience applications in basic and clinical psychopharmacology. Applications include phenotype characterization and studying the behavioral effects of pharmacologic substances.

Proper citation: SMART Video-tracking (RRID:SCR_002852) Copy   


http://www.cmrr.umn.edu/

Biomedical technology research center that focuses on development of unique magnetic resonance (MR) imaging and spectroscopy methodologies and instrumentation for the acquisition of structural, functional, and biochemical information non-invasively in humans, and utilizing this capability to investigate organ function in health and disease. The distinctive feature of this resource is the emphasis on ultrahigh magnetic fields (7 Tesla and above), which was pioneered by this BTRC. This emphasis is based on the premise that there exists significant advantages to extracting biomedical information using ultrahigh magnetic fields, provided difficulties encountered by working at high frequencies corresponding to such high field strengths can be overcome by methodological and engineering solutions. This BTRC is home to some of the most advanced MR instrumentation in the world, complemented by human resources that provide unique expertise in imaging physics, engineering, and signal processing. No single group of scientists can successfully carry out all aspects of this type of interdisciplinary biomedical research; by bringing together these multi-disciplinary capabilities in a synergistic fashion, facilitating these interdisciplinary interactions, and providing adequate and centralized support for them under a central umbrella, this BTRC amplifies the contributions of each of these groups of scientists to basic and clinical biomedical research. Collectively, the approaches and instrumentation developed in this BTRC constitute some of the most important tools used today to study system level organ function and physiology in humans for basic and translational research, and are increasingly applied world-wide. CMRR Faculty conducts research in a variety of areas including: * High field functional brain mapping in humans; methodological developments, mechanistic studies, and neuroscience applications * Metabolism, bioenergetics, and perfusion studies of human pathological states (tumors, obesity, diabetes, hepatic encephalopathy, cystic fibrosis, and psychiatric disorders) * Cardiac bioenergetics under normal and pathological conditions * Automated magnetic field shimming methods that are critical for spectroscopy and ultrafast imaging at high magnetic fields * Development of high field magnetic resonance imaging and spectroscopy techniques for anatomic, physiologic, metabolic, and functional studies in humans and animal models * Radiofrequency (RF) pulse design based on adiabatic principles * Development of magnetic resonance hardware for high fields (e.g. RF coils, pre-amplifiers, digital receivers, phased arrays, etc.) * Development of software for data analysis and display for functional brain mapping.

Proper citation: Center for Magnetic Resonance Research (RRID:SCR_003148) Copy   


http://fcon_1000.projects.nitrc.org/indi/pro/Quiron-Valencia.html

Resting state datasets, including an anatomical as well as a resting state fMRI scan, collected from a community sample in Valencia, Spain. The first release includes data for 45 participants. Participants were instructed to keep their eyes open during the resting state scan, no visual stimulus was presented. The following data are released for every participant: * Scanner Type: Philips Achieva 3T-TX * One high-resolution T1-weighted mprage, defaced to protect patient confidentiality * At least one 6-minute resting state fMRI scan (R-fMRI), eyes open, no visual stimulus presented * Demographic Information

Proper citation: Quiron-Valencia Sample (RRID:SCR_003538) Copy   


  • RRID:SCR_003658

http://www.linked-neuron-data.org/

Neuroscience data and knowledge from multiple scales and multiple data sources that has been extracted, linked, and organized to support comprehensive understanding of the brain. The core is the CAS Brain Knowledge base, a very large scale brain knowledge base based on automatic knowledge extraction and integration from various data and knowledge sources. The LND platform provides services for neuron data and knowledge extraction, representation, integration, visualization, semantic search and reasoning over the linked neuron data. Currently, LND extracts and integrates semantic data and knowledge from the following resources: PubMed, INCF-CUMBO, Allen Reference Atlas, NIF, NeuroLex, MeSH, DBPedia/Wikipedia, etc.

Proper citation: Linked Neuron Data (RRID:SCR_003658) Copy   


  • RRID:SCR_003210

    This resource has 10000+ mentions.

http://www.sigmaplot.com/products/sigmaplot/

Statistical analysis and scientific graphing software for Windows OS.

Proper citation: SigmaPlot (RRID:SCR_003210) Copy   


  • RRID:SCR_004544

    This resource has 1+ mentions.

http://noble.gs.washington.edu/proj/genomedata/

A format for efficient storage of multiple tracks of numeric data anchored to a genome. The format allows fast random access to hundreds of gigabytes of data, while retaining a small disk space footprint. They have also developed utilities to load data into this format. Retrieving data from this format is more than 2900 times faster than a naive approach using wiggle files. A reference implementation in Python and C components is available here under the GNU General Public License. The software has only been tested on Linux and Mac systems.

Proper citation: Genomedata (RRID:SCR_004544) Copy   


http://imkhp2.physik.uni-karlsruhe.de/~muehr/wetterwerte.html

Data sets of current German weather stations updated hourly or every twelve hours. Data sets, in German, include: * Daily mean values ??of temperature, updated hourly. Daily archive since 29.1.2008 * Daily maximum and minimum temperature, updated every 12 hours. Daily archive since 21.7.2008 * Monthly mean values ??of temperature and deviation, updated daily . * Rainfall in the last 12 hours and monthly total, updated every 12 hours . * Monthly totals of precipitation and relative to langj. means in%, updated every 12 hours. Monthly Archive since Feb. 2008 * Air pressure and pressure tendency, updated hourly.

Proper citation: Current German Weather Stations (RRID:SCR_003611) Copy   


  • RRID:SCR_002763

    This resource has 10+ mentions.

http://www.bioinf.uni-leipzig.de/Software/RNAplex/

Software tool to rapidly search for short interactions between two long RNAs.

Proper citation: RNAplex (RRID:SCR_002763) Copy   


  • RRID:SCR_004663

    This resource has 1+ mentions.

http://www.ebi.ac.uk/uniprot-das

The distributed annotation system (DAS) is a client-server system in which a single client integrates information from multiple servers. The UniProt DAS server provides access to sequence and annotation from UniProt, UniParc and IPI. Researchers can then provide annotation of their own results in the context of UniProt annotation, IPI annotation and UniParc cross references through the use of suitable DAS client such as Dasty2, the Ensembl DAS client or SPICE. The server also gives access to Gene Ontology Annotation of UniProt sequences (GOA) and theoretical tryptic digests of protein sequences in UniProt and IPI. An extremely useful resource for users of DAS is the DAS Registration Server that supports registry and discovery of DAS services. The datasources provided by the UniProt DAS server are all registered with this service.

Proper citation: UniProt DAS (RRID:SCR_004663) Copy   


http://www.cbnu.ac.kr/eng/

Proper citation: Chungbuk National University; Cheongju; South Korea (RRID:SCR_003570) Copy   


  • RRID:SCR_003562

    This resource has 1+ mentions.

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   


http://www.cuhk.edu.hk/

Public research university in Sha Tin, New Territories, Hong Kong.

Proper citation: Chinese University of Hong Kong; Hong Kong; China (RRID:SCR_003440) Copy   


http://nrnb.org/index.html

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   


  • RRID:SCR_003169

    This resource has 10+ mentions.

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   


  • RRID:SCR_004893

    This resource has 1+ mentions.

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   


http://www.uni-lj.si/en/

Proper citation: University of Ljubljana; Ljubljana; Slovenia (RRID:SCR_004498) Copy   


http://www.unil.ch/central

Proper citation: University of Lausanne; Lausanne; Switzerland (RRID:SCR_004773) Copy   


  • RRID:SCR_004890

    This resource has 1+ mentions.

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   


  • RRID:SCR_003557

    This resource has 100+ mentions.

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   



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