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http://cell.ccrc.uga.edu/world/glycomics/glycomics.php

Biomedical technology research center that develops and implements new technologies to investigate the glycome of cells, including glycoproteomics and glycoconjugate analysis, transcript analysis and bioinformatics. It develops the tools and technology to analyze in detail the glycoprotein and glycolipid expression of mouse embryonic stem cells and the cells into which they differentiate. The technology developed in the Center will allow an understanding of how glycosylation is controlled during differentiation and will allow the development of tools to promote the use of stem cells to treat human disease. In addition, the technology developed will be applicable to the study of other cell types, including cancer cells that are progressing to a more invasive phenotype. The technology developed will also allow others in the scientific community to participate in glycomics research through dissemination of the new methods developed and through the analytical services provided by the resource to other scientists requesting assistance in glycomic analyses.

Proper citation: Integrated Technology Resource for Biomedical Glycomics (RRID:SCR_009003) Copy   

•   Source: SciCrunch Registry

http://www-ssrl.slac.stanford.edu/content/science/ssrl-smb-program

Biomedical technology research center that operates as a integrated center with three primary areas (or cores) of technological research and development and scientific focus: macromolecular crystallography (MC), X-ray absorption spectroscopy (XAS) and small-angle X-ray scattering/diffraction (SAXS) . Central to the core technological developments in all three areas is the development and utilization of improved detectors and instrumentation, especially to be able to take maximum advantage of the high brightness of SSRL?s third-generation synchrotron X-ray storage ring (SPEAR3). A primary focus is the use of enhanced computing and data management tools to provide more user-friendly, real-time and on-line instrumentation control, including full remote access for crystallography, data reduction and analysis.

Proper citation: SSRL Structural Molecular Biology (RRID:SCR_009000) Copy   

•   Source: SciCrunch Registry

http://www.scienceexchange.com/facilities/genomics-core-facility-brown

Provides genomics and proteomics equipment to researchers at Brown University and to entire Rhode Island research community, as well as assistance with experimental design, trouble shooting, and data analysis. Offers Affymetrix microarray and Illumina NextGeneration services to academic community and external customers.

Proper citation: Brown University Genomics Core Facility (RRID:SCR_012217) Copy   

•   Source: SciCrunch Registry

https://www.k-inbre.org/pages/k-inbre_about_bio-core.html

The K-INBRE Bioinformatics Core collaborates with Kansas researchers to perform research on cell and developmental biology. Core aims to serve the needs of investigators engaged in computationally intensive biomedical research, and to promote education in bioinformatics to students and researchers across the state of Kansas.

Proper citation: Kansas State University - INBRE Bioinformatics Core Facility (RRID:SCR_012596) Copy   

•   Source: SciCrunch Registry

http://www.mmrrc.org/

National public repository system for mutant mice. Archives and distributes scientifically valuable spontaneous and induced mutant mouse strains and ES cell lines for use by biomedical research community. Includes breeding/distribution facilities and information coordinating center. Mice strains are cryopreserved, unless live colony must be established. Live mice are supplied from production colony, from colony recovered from cryopreservation, or via micro-injection of cell line into host blastocysts. MMRRC member facilities also develop technologies to improve handling of mutant mice, including advances in assisted reproductive techniques, cryobiology, genetic analysis, phenotyping and infectious disease diagnostics.

Proper citation: Mutant Mouse Resource and Research Center (RRID:SCR_002953) Copy   

•   Source: SciCrunch Registry

http://braininfo.rprc.washington.edu

Portal to neuroanatomical information on the Web that helps you identify structures in the brain and provides a variety of information about each structure by porting you to the best of 1500 web pages at 100 other neuroscience sites. BrainInfo consists of three basic components: NeuroNames, a developing database of definitions of neuroanatomic structures in four species, their most common acronyms and their names in eight languages; NeuroMaps, a digital atlas system based on 3-D canonical stereotaxic atlases of rhesus macaque and mouse brains and programs that enable one to map data to standard surface and cross-sectional views of the brains for presentation and publication; and the NeuroMaps precursor: Template Atlas of the Primate Brain, a 2-D stereotaxic atlas of the longtailed (fascicularis) macaque brain that shows the locations of some 250 architectonic areas of macaque cortex. The NeuroMaps atlases will soon include a number of overlays showing the locations of cortical areas and other neuroscientific data in the standard frameworks of the macaque and mouse atlases. Viewers are encouraged to use NeuroNames as a stable source of unique standard terms and acronyms for brain structures in publications, illustrations and indexing systems; to use templates extracted from the NeuroMaps macaque and mouse brain atlases for presenting neuroscientific information in image format; and to use the Template Atlas for warping to MRIs or PET scans of the macaque brain to estimate the stereotaxic locations of structures.

Proper citation: BrainInfo (RRID:SCR_003142) Copy   

•   Source: SciCrunch Registry

http://www.socr.ucla.edu/

A hierarchy of portable online interactive aids for motivating, modernizing probability and statistics applications. The tools and resources include a repository of interactive applets, computational and graphing tools, instructional and course materials. The core SOCR educational and computational components include the following suite of web-based Java applets: * Distributions (interactive graphs and calculators) * Experiments (virtual computer-generated games and processes) * Analyses (collection of common web-accessible tools for statistical data analysis) * Games (interfaces and simulations to real-life processes) * Modeler (tools for distribution, polynomial and spectral model-fitting and simulation) * Graphs, Plots and Charts (comprehensive web-based tools for exploratory data analysis), * Additional Tools (other statistical tools and resources) * SOCR Java-based Statistical Computing Libraries * SOCR Wiki (collaborative Wiki resource) * Educational Materials and Hands-on Activities (varieties of SOCR educational materials), * SOCR Statistical Consulting In addition, SOCR provides a suite of tools for volume-based statistical mapping (http://wiki.stat.ucla.edu/socr/index.php/SOCR_EduMaterials_AnalysesCommandLine) via command-line execution and via the LONI Pipeline workflows (http://www.nitrc.org/projects/pipeline). Course instructors and teachers will find the SOCR class notes and interactive tools useful for student motivation, concept demonstrations and for enhancing their technology based pedagogical approaches to any study of variation and uncertainty. Students and trainees may find the SOCR class notes, analyses, computational and graphing tools extremely useful in their learning/practicing pursuits. Model developers, software programmers and other engineering, biomedical and applied researchers may find the light-weight plug-in oriented SOCR computational libraries and infrastructure useful in their algorithm designs and research efforts. The three types of SOCR resources are: * Interactive Java applets: these include a number of different applets, simulations, demonstrations, virtual experiments, tools for data visualization and analysis, etc. All applets require a Java-enabled browser (if you see a blank screen, see the SOCR Feedback to find out how to configure your browser). * Instructional Resources: these include data, electronic textbooks, tutorials, etc. * Learning Activities: these include various interactive hands-on activities. * SOCR Video Tutorials (including general and tool-specific screencasts).

Proper citation: Statistics Online Computational Resource (RRID:SCR_003378) Copy   

•   Source: SciCrunch Registry

http://www.loni.usc.edu/BIRN/Projects/Mouse/

Animal model data primarily focused on mice including high resolution MRI, light and electron microscopic data from normal and genetically modified mice. It also has atlases, and the Mouse BIRN Atlasing Toolkit (MBAT) which provides a 3D visual interface to spatially registered distributed brain data acquired across scales. The goal of the Mouse BIRN is to help scientists utilize model organism databases for analyzing experimental data. Mouse BIRN has ended. The next phase of this project is the Mouse Connectome Project (https://www.nitrc.org/projects/mcp/). The Mouse BIRN testbeds initially focused on mouse models of neurodegenerative diseases. Mouse BIRN testbed partners provide multi-modal, multi-scale reference image data of the mouse brain as well as genetic and genomic information linking genotype and brain phenotype. Researchers across six groups are pooling and analyzing multi-scale structural and functional data and integrating it with genomic and gene expression data acquired from the mouse brain. These correlated multi-scale analyses of data are providing a comprehensive basis upon which to interpret signals from the whole brain relative to the tissue and cellular alterations characteristic of the modeled disorder. BIRN's infrastructure is providing the collaborative tools to enable researchers with unique expertise and knowledge of the mouse an opportunity to work together on research relevant to pre-clinical mouse models of neurological disease. The Mouse BIRN also maintains a collaborative Web Wiki, which contains announcements, an FAQ, and much more.

Proper citation: Mouse Biomedical Informatics Research Network (RRID:SCR_003392) Copy   

•   Source: SciCrunch Registry

http://portal.ncibi.org/gateway/mimiplugin.html

The Cytoscape MiMI Plugin is an open source interactive visualization tool that you can use for analyzing protein interactions and their biological effects. The Cytoscape MiMI Plugin couples Cytoscape, a widely used software tool for analyzing bimolecular networks, with the MiMI database, a database that uses an intelligent deep-merging approach to integrate data from multiple well-known protein interaction databases. The MiMI database has data on 119,880 molecules, 330,153 interactions, and 579 complexes. By querying the MiMI database through Cytoscape you can access the integrated molecular data assembled in MiMI and retrieve interactive graphics that display protein interactions and details on related attributes and biological concepts. You can interact with the visualization by expanding networks to the next nearest neighbors and zooming and panning to relationships of interest. You also can perceptually encode nodes and links to show additional attributes through color, size and the visual cues. You can edit networks, link out to other resources and tools, and access information associated with interactions that has been mined and summarized from the research literature information through a biology natural language processing database (BioNLP) and a multi-document summarization system, MEAD. Additionally, you can choose sub-networks of interest and use SAGA, a graph matching tool, to match these sub-networks to biological pathways.

Proper citation: MiMI Plugin for Cytoscape (RRID:SCR_003424) Copy   

•   Source: SciCrunch Registry

http://caties.cabig.upmc.edu/

The Cancer Text Information Extraction System (caTIES) provides tools for de-identification and automated coding of free-text structured pathology reports. It also has a client that can be used to search these coded reports. The client also supports Tissue Banking and Honest Broker operations. caTIES focuses on two important challenges of bioinformatics * Information extraction (IE) from free text * Access to tissue. Regarding the first challenge, information from free-text pathology documents represents a vital and often underutilized source of data for cancer researchers. Typically, extracting useful data from these documents is a slow and laborious manual process requiring significant domain expertise. Application of automated methods for IE provides a method for radically increasing the speed and scope with which this data can be accessed. Regarding the second challenge, there is a pressing need in the cancer research community to gain access to tissue specific to certain experimental criteria. Presently, there are vast quantities of frozen tissue and paraffin embedded tissue throughout the country, due to lack of annotation or lack of access to annotation these tissues are often unavailable to individual researchers. caTIES has three goals designed to solve these problems: * Extract coded information from free text Surgical Pathology Reports (SPRs), using controlled terminologies to populate caBIG-compliant data structures. * Provide researchers with the ability to query, browse and create orders for annotated tissue data and physical material across a network of federated sources. With caTIES the SPR acts as a locator to tissue resources. * Pioneer research for distributed text information extraction within the context of caBIG. caTIES focuses on IE from SPRs because they represent a high-dividend target for automated analysis. There are millions of SPRs in each major hospital system, and SPRs contain important information for researchers. SPRs act as tissue locators by indicating the presence of tissue blocks, frozen tissue and other resources, and by identifying the relationship of the tissue block to significant landmarks such as tumor margins. At present, nearly all important data within SPRs are embedded within loosely-structured free-text. For these reasons, SPRs were chosen to be coded through caTIES because facilitating access to information contained in SPRs will have a powerful impact on cancer research. Once SPR information has been run through the caTIES Pipeline, the data may be queried and inspected by the researcher. The goal of this search may be to extract and analyze data or to acquire slides of tissue for further study. caTIES provides two query interfaces, a simple query dashboard and an advanced diagram query builder. Both of these interfaces are capable of NCI Metathesaurus, concept-based searching as well as string searching. Additionally, the diagram interface is capable of advanced searching functionalities. An important aspect of the interface is the ability to manage queries and case sets. Users are able to vet query results and save them to case sets which can then be edited at a later time. These can be submitted as tissue orders or used to derive data extracts. Queries can also be saved, and modified at a later time. caTIES provides the following web services by default: MMTx Service, TIES Coder Service

Proper citation: caTIES - Cancer Text Information Extraction System (RRID:SCR_003444) Copy   

•   Source: SciCrunch Registry

http://www.isi.edu/integration/karma/

An information integration software tool that enables users to integrate data from a variety of data sources including databases, spreadsheets, delimited text files, XML, JSON, KML and Web APIs. Users integrate information by modeling it according to an ontology of their choice using a graphical user interface that automates much of the process. Karma learns to recognize the mapping of data to ontology classes and then uses the ontology to propose a model that ties together these classes. Users then interact with the system to adjust the automatically generated model. During this process, users can transform the data as needed to normalize data expressed in different formats and to restructure it. Once the model is complete, users can publish the integrated data as RDF or store it in a database.

Proper citation: Karma (RRID:SCR_003732) Copy   

•   Source: SciCrunch Registry

http://psf.cobre.ku.edu/cores/ppg/about

Core focuses on cloning, expression and purification of prokaryotic and eukaryotic proteins for COBRE and other investigators in Kansas and region. Laboratory maintains equipment to support production of properly folded proteins in quantities suitable for structural studies (X-ray and NMR), functional studies (catalytic or biological), label-free binding studies (SPR) and/or high throughput (HTP) screening studies.

Proper citation: Kansas University at Lawrence Protein Production Group Core Facility (RRID:SCR_017749) Copy   

•   Source: SciCrunch Registry

http://bioimaging.dbi.udel.edu

Microscopy facility that houses equipment including confocal microscopes: LSM780 confocal microscope (Located at CBBI),LSM880 confocal microscope (Located at DBI 117),electron microscopes and their accessory instrumentation:Thermo Scientific Apreo VS SEM microscope,Hitachi S-4700, Leica EM ACE600 and Tousimis Autosamdri-815B,CX7 high content analysis system. Our staff has technical expertise across different microscopy platforms and methodologies.

Proper citation: University of Delaware BioImaging Center Core Facility (RRID:SCR_017814) Copy   

•   Source: SciCrunch Registry

http://crl.berkeley.edu/molecular-imaging-center/

Microscopy core specializing in laser based fluorescence techniques. Offers training and expertise in 20 different microscope systems, including live cell and in vivo imaging, laser scanning (LSM) and spinning disk (SDC) confocal, multi-photon (2p), fluorescent lifetime imaging (FLIM), light-sheet microscopy (SPIM), super resolution (Airyscan), slide scanning and patterned illumination for optogenetic manipulation and readout. Provides offline computer analysis workstations for image processing, visualization and analysis, including GPU workstations. MIC operates in 3 different buildings on campus, with primary locations in Life Sciences Addition (LSA), North-side core in Barker Hall, and small outpost in Li Ka Shing Center for Biomedical and Health Sciences (LKS).Provides equipment in categories:Confocal and multi photon laser scanning microscopes,Spinning disk confocal microscopes,Lightsheet (SPIM) microscopes,Epifluorescence/widefield scopes and Computer workstations.

Proper citation: University of California at Berkeley Cancer Research Laboratory Molecular Imaging Center Core Facility (RRID:SCR_017852) Copy   

•   Source: SciCrunch Registry

https://med.virginia.edu/molecular-electron-microscopy-core/

Facility dedicated to high resolution electron cryomicroscopy and electron cryotomography. It houses three electron microscopes,120kV Spirit, 200kV F20, and 300kV Titan Krios. These microscopes are available to researchers either for direct use, or aided by MEMC personnel, to collect data aimed at high resolution structural biology projects.

Proper citation: University of Virginia School of Medicine Molecular Electron Microscopy Core Facility (RRID:SCR_019031) Copy   

•   Source: SciCrunch Registry

http://www.med.uvm.edu/mic

Core provides imaging equipment including JEOL 1400 transmission electron microscope with AMT 11 megapixel digital camera,JEOL JSM 6060 scanning electron microscope with attached Oxford INCA energy dispersive spectroscopy detector for element analysis,Nikon Air HD confocal scanning laser microscope, Nikon C2 confocal scanning laser microscope, Andor Spinning Disk confocal microscope, Zeiss LSM 7 Multiphoton confocal microscope, Nikon STORM super-resolution light microscope, Olympus BX50 research microscope for transmitted light, phase contrast, and epi-fluorescence microscopy, Asylum Research MFP-3D BIO atomic force microscope, Asylum Research Cypher Environmental atomic force microscope,Arcturus XT-Ti Laser Capture Microdissector system, Olympus IX70 inverted microscope with associated Applied BioPhysics Electri Cell-Substrate Impedance Sensing (ECIS Ztheta) system, Leica VERSA 8 whole slide imager, Dell workstations containing Molecular Devices MetaMorph image analysis software for complex quantitative image analysis, Indica Labs HALO software, Improvision Volocity, MBR StereoInvestigator.

Proper citation: Vermont University Larner College of Medicine Microscopy Imaging Center Core Facility (RRID:SCR_018821) Copy   

•   Source: SciCrunch Registry

http://nemoursresearch.org/cores/bcl/

Develops research projects in pediatric genetics and provides essential services in molecular biology and genetics to Nemours clinicians and research staff and to affiliates researchers of University of Delaware and Thomas Jefferson University. Resource for staff of Alfred I. duPont Hospital for Children, Nemours affiliates, COBRE / INBRE investigators and outside customers. Offers expertise in molecular genetics and genomics. Operates according to policies set forth by federal CLIA standards.Services provided include Ion Torrent PGM Next Generation Sequencing, QuantStudio (QS) 3D Digital PCR, Cell Line Authentication, Nucleic Acid Quality Number (AATI Fragment Analyzer),Genotyping including Allelic Discrimination Probes (SNP Real-Time PCR), Affymetrix Microarray (CNV CytoScan, SNP arrays), Fragment Analysis (Capillary Electrophoresis up to 1200 bp), DNA Sequencing (Sanger Sequencing), Expression Analysis including Affymetrix Microarray (global gene expression, transcriptome assays), Pathway-focused Real-Time qPCR (mRNA and miRNA). Shared Instrumentation including Beckman Biomek 3000 Liquid Handler, NanoDrop 2000c, ABI7900 384-well Real-Time Genetic Analyzer, PCR Tamer, Thermocyclers.

Proper citation: Nemours Biomolecular Core Facility (RRID:SCR_018265) Copy   

•   Source: SciCrunch Registry

http://www.oasis-brains.org/

Project aimed at making neuroimaging data sets of brain freely available to scientific community. By compiling and freely distributing neuroimaging data sets, future discoveries in basic and clinical neuroscience are facilitated.

Proper citation: Open Access Series of Imaging Studies (RRID:SCR_007385) Copy   

•   Source: SciCrunch Registry

http://www.mrmatlas.org/

Resource of targeted proteomics assays to detect and quantify proteins in complex proteome digests by mass spectrometry. Used to quantify the complete human proteome.

Proper citation: SRMAtlas (RRID:SCR_016996) Copy   

•   Source: SciCrunch Registry

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