Tools   Select Another Resource Report Type

http://superfly.ucsd.edu/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on June 23, 2013. Homophila utilizes the sequence information of human disease genes from the NCBI OMIM (Online Mendelian Inheritance in Man) database in order to determine if sequence homologs of these genes exist in the current Drosophila sequence database (FlyBase). Sequences are compared using NCBI's BLAST program. The database is updated weekly and can be searched by human disease, gene name, OMIM number, title, subtitle and/or allelic variant descriptions.

Proper citation: Homophila (RRID:SCR_007717) Copy   

•   Source: SciCrunch Registry

http://www.geneatlas.org/gene/main.jsp

This website allows visitors to search for genes of interest based on their spatial expression patterns in the Postnatal Day 7 mouse brain. Geneatlas provides two searching tools: A graphical interface for customized spatial queries; A textual interface for querying annotated structures. Geneatlas is the product of a collaboration between researchers at Baylor College of Medicine, Rice University, and University of Houston.

Proper citation: Gene Atlas (RRID:SCR_008089) Copy   

•   Source: SciCrunch Registry

http://mouseatlas.caltech.edu/

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone.. Documented on October, 01, 2019.
3D digital atlas of normal mouse development constructed from magnetic resonance image data. The download is a zipped file containing the six atlases Theiler Stages (ts) 13, 21,23, 24, 25 and 26 and MRI data for an unlabeled ts19 embryo. To view the atlases, download and install MBAT from: http://mbat.loni.ucla.edu Specimens were prepared in aqueous, isotonic solutions to avoid tissue shrinkage. Limited specimen handling minimized physical perturbation of the embryos to ensure accurate geometric representations of developing mouse anatomy. Currently, the atlas contains orthogonal sections through MRI volumes, three stages of embryos that have annotated anatomy, photographs of several stages of development, lineage trees for annotated embryos and a gallery of images and movies derived from the annotations. Anatomical annotations can be viewed by selecting a transverse section and selecting a pixel on the displayed slice.

Proper citation: 3D MRI Atlas of Mouse Development (RRID:SCR_008090) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/validate29/

Atlas was created from MRI scans of squirrel monkey brains. The atlas is currently comprised of multiple anatomical templates, diffusion MRI templates, and ex vivo templates. In addition, the templates are combined with histologically defined cortical labels, and diffusion tractography defined white matter labels.

Proper citation: VALiDATe29 Squirrel Monkey Brain Atlas (RRID:SCR_015542) Copy   

•   Source: SciCrunch Registry

http://www.loni.usc.edu/Software/Debabeler

Software to manage the conversion of imaging data from one file format and convention to another. It consists of a graphical user interface to visually program the translations, and a data translation engine to read, sort and translate the input files, and write the output files to disk. The data translation engine: (1) Reads metadata from a set of image files on disk to identify the source that produced each file; (2) Groups the image files into user-defined collections using image metadata values; (3) Translates each image file collection by reading metadata and pixel data and mapping the data into the appropriate output file format through a programmable set of connected modules. The Debabeler uses the Java Image I/O Plugin Architecture to read and write a wide variety of common medical image file formats, including ANALYZE, MINC, and most variations of DICOM.

Proper citation: LONI Debabeler (RRID:SCR_001160) Copy   

•   Source: SciCrunch Registry

https://github.com/SciKnowEngine/kefed.io

Knowledge engineering software for reasoning with scientific observations and interpretations. The software has three parts: (a) the KEfED model editor - a design editor for creating KEfED models by drawing a flow diagram of an experimental protocol; (b) the KEfED data interface - a spreadsheet-like tool that permits users to enter experimental data pertaining to a specific model; (c) a "neural connection matrix" interface that presents neural connectivity as a table of ordinal connection strengths representing the interpretations of tract-tracing data. This tool also allows the user to view experimental evidence pertaining to a specific connection. The KEfED model is designed to provide a lightweight representation for scientific knowledge that is (a) generalizable, (b) a suitable target for text-mining approaches, (c) relatively semantically simple, and (d) is based on the way that scientist plan experiments and should therefore be intuitively understandable to non-computational bench scientists. The basic idea of the KEfED model is that scientific observations tend to have a common design: there is a significant difference between measurements of some dependent variable under conditions specified by two (or more) values of some independent variable.

Proper citation: Knowledge Engineering from Experimental Design (RRID:SCR_001238) Copy   

•   Source: SciCrunch Registry

http://www.michr.umich.edu/services/biorepository

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 24,2025. In 2009, the Medical School and the Michigan Institute for Clinical & Health Research (MICHR) unveiled a new biorepository for U-M researchers in need of a controlled storage environment for biological samples. MICHR is pleased to be able to add to its many services for the research community a centralized biological repository for controlled storage of biological samples, and related services (including DNA, RNA, and other downstream preparation) within the U-M campus. The biorepository, located in the CAP/CLIA-certified Michigan Center for Translational Pathology (MCTP) laboratory at the U-M Traverwood facility on Huron Parkway, will store biologic material, including blood and urine. Sample accessioning and tracking will be accomplished using the caTISSUE suite of programs, and samples will be processed and stored in compliance with CAP/CLIA guidelines. Initially, all samples will be used only with the authorization of the individual investigator who directed the project under which the samples were obtained. Samples will be used in accordance with the relevant informed consent. Long-term plans include federating the database in order to facilitate sharing of data and samples between research teams.

Proper citation: University of Michigan Biorepository (RRID:SCR_004643) Copy   

•   Source: SciCrunch Registry

http://brainmap.wisc.edu/monkey.html

NO LONGER AVAILABLE. Documented on September 17, 2019. A set of multi-subject atlas templates to facilitate functional and structural imaging studies of the rhesus macaque. These atlases enable alignment of individual scans to improve localization and statistical power of the results, and allow comparison of results between studies and institutions. This population-average MRI-based atlas collection can be used with common brain mapping packages such as SPM or FSL.

Proper citation: Rhesus Macaque Atlases for Functional and Structural Imaging Studies (RRID:SCR_008650) Copy   

•   Source: SciCrunch Registry

http://proteogenomics.musc.edu/ma/arrayQuest.php?page=home&act=manage

A web-accessible program for the analysis of DNA microarray data. ArrayQuest is designed to apply any type of DNA microarray analysis program executable on a Linux system (i.e., Bioconductor statistical and graphical methods written in R as well as BioPerl and C++ based scripts) to DNA microarray data stored in the MUSC DNA Microarray Database, the Gene Expression Omnibus (GEO) or in a password protected private database uploaded to the center point server. ArrayQuest analyses are performed on a computer cluster.

Proper citation: ArrayQuest (RRID:SCR_010935) Copy   

•   Source: SciCrunch Registry

https://www.eagle-i.net/

Web application to discover resources available at participating networked universities. This distributed platform for creating and sharing semantically rich data is built around semantic web technologies and follows linked open data principles.

Proper citation: Eagle I (RRID:SCR_013153) Copy   

•   Source: SciCrunch Registry

http://www.nbcr.net/

Biomedical technology research center that conducts, catalyzes and enables multiscale biomedical research, focusing on four key activities: 1) integrating computational, data and visualization resources in a transparent, advanced grid environment to enable better access to distributed data, computational resources, instruments and people; 2) developing and deploying advanced computational tools for modeling and simulation, data analysis, query and integration, three-dimensional image processing and interactive visualization; 3) delivering and supporting advanced grid/cyberinfrastructure for biomedical researchers; and 4) training a cadre of new researchers to have an interdisciplinary, working knowledge of computational technology relevant to biomedical scientists. NBCR enables biomedical scientists to address the challenge of integrating detailed structural measurements from diverse scales of biological organization that range from molecules to organ systems in order to gain quantitative understanding of biological function and phenotypes. Predictive multi-scale models and their driving biological research problems together address issues in modeling of sub-cellular biophysics, building molecular modeling tools to accelerate discovery, and defining tools for patient-specific multi-scale modeling. NBCR furthers these driving problems by developing tools and models based on rapid advances in mathematics and information technology, incorporating them into NBCR pipelines or problem solving environments, and addressing the inevitable changes in the underlying cyber-infrastructure technologies and continually adapting codes over time. Their technology focus integrates both the biological applications and the underlying support software into reproducible science workflows that can function across a number of physical infrastructures.

Proper citation: National Biomedical Computation Resource (RRID:SCR_002656) Copy   

•   Source: SciCrunch Registry

http://ncmir.ucsd.edu/

Biomedical technology research center that develops computer-aided, advanced microscopy for the acquisition of structural and functional data in the dimensional range of 1 nm to 100 um, a range encompassing macromolecules, subcellular structures and cells. Novel specimen-staining methods, imaging instrumentsincluding intermediate high-voltage transmission electron microscopes (IVEMs) and high-speed, large-format laser-scanning light microscopesand computational capabilities are available for addressing mesoscale biological microscopy of proteins and macromolecular complexes in their cellular and tissue environments. These technologies are developed to bridge understanding of biological systems between the gross anatomical and molecular scales and to make these technologies broadly available to biomedical researchers. NCMIR provides expertise, infrastructure, technological development, and an environment in which new information about the 3D ultrastructure of tissues, cells, and macromolecular complexes may be accurately and easily obtained and analyzed. NCMIR fulfills its mission through technology development, collaboration, service, training, and dissemination. It aims to develop preparative methods and analytical approaches to 3D microscopy applicable to neurobiology and cell biology, incorporating equipment and implementing software that expand the analysis of 3D structure. The core research activities in the areas of specimen development, instrument development, and software infrastructures maximize the advantages of higher voltage electron microscopy and correlated light microscopies to make ambitious imaging studies across scales routine, and to facilitate the use of resources by biomedical researchers. NCMIR actively recruits outside users who will not only make use of these resources, but who also will drive technology development and receive training.

Proper citation: National Center for Microscopy and Imaging Research (RRID:SCR_002655) Copy   

•   Source: SciCrunch Registry

https://www.bio.aps.anl.gov/

Biomedical technology research center and training resource for the study of the structure of partially ordered biological molecules, complexes of biomolecules and cellular structures under conditions similar to those present in living cells and tissues. The goal of research at BioCAT is to determine the detailed structure and mechanism of action of biological systems at the molecular level. The techniques used are X-ray fiber diffraction, X-ray solution scattering and X-ray micro-emission and micro-absorption spectroscopy, with an emphasis on time-resolved studies and the development of novel techniques.

Proper citation: BioCAT (RRID:SCR_001440) Copy   

•   Source: SciCrunch Registry

https://www.colorado.edu/facility/ems/

Core provides access to instruments including:FEI Tecnai 12 Spirit TEM, FEI Tecnai F20 (200kV) FEG-TEM 200kV FEG-TEM,Gatan US4000 4k x 4k CCD, bottom-mount,CryoTEM and electron tomography,High-resolution TEM;FEI Tecnai F20 (200kV) FEG-TEM,300kV FEG-TEM,Gatan US4000 4k x 4k CCD, bottom-mount,CryoTEM and electron tomography,High-resolution TEM,FEI/Phillips CM100 (100kV) TEM,100kV, tungsten TEM,2k x 2k AMT CCD, bottom-mount.

Proper citation: Colorado University at Boulder EM Services Core Facility (RRID:SCR_001432) Copy   

•   Source: SciCrunch Registry

http://mus.well.ox.ac.uk/mouse/INBREDS/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 19,2025. Data set of genotypes available for 480 strains and 13370 successful SNP assays that are mapped to build34 of the mouse genome, including 107 SNPs that are mapped to random unanchored sequence 13374 SNPs are mapped onto Build 33 of the mouse genome. You can access the data relative to Build 33 or Build 34.

Proper citation: Wellcome-CTC Mouse Strain SNP Genotype Set (RRID:SCR_003216) Copy   

•   Source: SciCrunch Registry

http://rlbl.chem.upenn.edu

Biomedical technology research center and training resource that develops time-resolved laser technologies and instrumentation, with a focus on 2-D IR spectroscopy. The technologies enable atomic-level measurements of the fastest steps in biological processes to elucidate structure and dynamics in biological macromolecules, assemblies and cells. The Center makes most of its instrumentation available for service research projects to outside users nation-wide.

Proper citation: Ultrafast Optical Processes Laboratory (RRID:SCR_006582) Copy   

•   Source: SciCrunch Registry

http://www.nrcam.uchc.edu/

Biomedical technology research center that develops new technologies for modeling cell biological processes. The technologies are integrated through Virtual Cell, a problem-solving environment built on a central database and disseminated as a Web application for the analysis, modeling and simulation of cell biological processes. NRCAM resides at the Center for Cell Analysis and Modeling, CCAM, and provides a vast array of laboratory equipment that can be used for obtaining experimental data needed to create and enhance Virtual Cell models. Microscopy instrumentation includes three confocal laser scanning microscopes including UV excitation, nonlinear optical microscopy utilizing a titanium sapphire pulsed laser, confocal-based fluorescence correlation spectroscopy, wide-field imaging workstation with cooled CCD and rapid excitation filter wheel, and dual-wavelength spectrofluorometer. Access to the facilities and technical staff is open to all researchers., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: NRCAM (RRID:SCR_006134) Copy   

•   Source: SciCrunch Registry

http://www.mri-resource.kennedykrieger.org/

Biomedical technology research center that provides expertise for the design of quantitative magnetic resonance imaging (MRI) and spectroscopy (MRS) data acquisition and processing technologies that facilitate the biomedical research of a large community of clinicians and neuroscientists in Maryland and throughout the USA. These methods allow noninvasive assessment of changes in brain anatomy as well as in tissue metabolite levels, physiology, and brain functioning while the brain is changing size during early development and during neurodegeneration, i.e. the changing brain throughout the life span. The Kirby Center has 3 Tesla and 7 Tesla state of the art scanners equipped with parallel imaging (8, 16, and 32-channel receive coils) and multi-transmit capabilities. CIS has an IBM supercomputer that is part of a national supercomputing infrastructure. Resources fall into the following categories: * MRI facilities, image acquisition, and processing * Computing facilities and image analysis * Novel statistical methods for functional brain imaging * Translating laboratory discoveries to patient treatment

Proper citation: National Resource for Quantitative Functional MRI (RRID:SCR_006716) Copy   

•   Source: SciCrunch Registry

http://www.kojak-ms.org/

Software tool for identification of cross-linked peptides from mass spectra. Used for analysis of chemically cross-linked protein complexes. Used to analyze both novel and existing data sets.

Proper citation: Kojak (RRID:SCR_021028) Copy   

•   Source: SciCrunch Registry

http://mind.loni.usc.edu

The MiND: Metadata in NIfTI for DWI framework enables data sharing and software interoperability for diffusion-weighted MRI. This site provides specification details, tools, and examples of the MiND mechanism for representing important metadata for DWI data sets at various stages of post-processing. MiND framework provides a practical solution to the problem of interoperability between DWI analysis tools, and it effectively expands the analysis options available to end users. To assist both users and developers in working with MiND-formatted files, we provide a number of software tools for download. * MiNDHeader A utility for inspecting MiND-extended files. * I/O Libraries Programming libraries to simplify writing and parsing MiND-formatted data. * Sample Files Example files for each MiND schema. * DIRAC LONI''s Diffusion Imaging Reconstruction and Analysis Collection is a DWI processing suite which utilizes the MiND framework.

Proper citation: LONI MiND (RRID:SCR_004820) Copy   

•   Source: SciCrunch Registry