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http://biositemaps.ncbcs.org/rds/search.html

Resource Discovery System is a web-accessible and searchable inventory of biomedical research resources. Powered by the Resource Discovery System (RDS) that includes a standards-based informatics infrastructure * Biositemaps Information Model * Biomedical Resource Ontology Extensions * Web Services distributed web-accessible inventory framework * Biositemap Resource Editor * Resource Discovery System Source code and project documentation to be made available on an open-source basis. Contributing institutions: University of Pittsburgh, University of Michigan, Stanford University, Oregon Health & Science University, University of Texas Houston. Duke University, Emory University, University of California Davis, University of California San Diego, National Institutes of Health, Inventory Resources Working Group Members

Proper citation: Resource Discovery System (RRID:SCR_005554) Copy   

•   Source: SciCrunch Registry

http://www.informatics.jax.org/home/recombinase

Curated data about all recombinase-containing transgenes and knock-ins developed in mice providing a comprehensive resource delineating known activity patterns and allows users to find relevant mouse resources for their studies.

Proper citation: Recombinase (cre) Activity (RRID:SCR_006585) Copy   

•   Source: SciCrunch Registry

https://open.med.harvard.edu/display/SHRINE/Community

Software providing a scalable query and aggregation mechanism that enables federated queries across many independently operated patient databases. This platform enables clinical researchers to solve the problem of identifying sufficient numbers of patients to include in their studies by querying across distributed hospital electronic medical record systems. Through the use of a federated network protocol, SHRINE allows investigators to see limited data about patients meeting their study criteria without compromising patient privacy. This software should greatly enable population-based research, assessment of potential clinical trials cohorts, and hypothesis formation for followup study by combining the EHR assets across the hospital system. In order to obtain the maximum number of cases representing the study population, it is useful to aggregate patient facts across as many sites as possible. Cutting across institutional boundaries necessitates that each hospital IRB remain in control, and that their local authority is recognized for each and every request for patient data. The independence, ownership, and legal responsibilities of hospitals predetermines a decentralized technical approach, such as a federated query over locally controlled databases. The application comes with the SHRINE Core Ontology but it can be used with any ontology, even one that is disease specific. The Core Ontology is designed to enable the widest range of studies possible using facts gathered in the EMR during routine patient care. SHRINE allows multiple ontologies to be used for different research purposes on the same installed systems.

Proper citation: SHRINE (RRID:SCR_006293) Copy   

•   Source: SciCrunch Registry

http://www.wakehealth.edu/Research/WFUPC/Cynomolgus-Breeding-Colony-Request-Form-Instructions.htm

The Wake Forest Cynomolgus Breeding Colony (CBC) is a colony of cynomolgus macaques (crab-eating macaques, Macaca fascicularis). The cynomolgus colony is designed to produce specific pathogen free (SPF) cynomolgus monkeys for use in biomedical research. The colony, supported by a grant from the NCRR, addresses the growing need for investigators to use in their protocols animals defined for the absence of specific diseases including CHV-1 (Herpes B), simian immunodeficiency virus, and simian retroviruses. An additional important characteristic of this colony is that, unlike many breeding colonies, the NHPs will be fed two defined diets. The first diet is a soy-free diet, not commercial monkey chow. The second diet has the same macronutrients but the protein source is from soy; similar in isoflavone content. A drawback of chow diets is that the exact nutritional product composition is unknown from lot to lot. However, they are always rich in soy bean meal, isoflavones and other constituents of soy bean meal that are known confounders of several types of research projects. All research using the cynomolgus colony must be reviewed and approved by the colony''s scientific board and the Wake Forest Animal Care and Use Committee (ACUC) before any work can be initiated. The scientific board meets regularly to assess the scientific value of each request and to determine whether or not animals/samples/data can be made available. This includes all requests for: # The purchase of animals for use outside the colony # The use of animals within the colony for the collection of blood/tissue samples, behavioral observations or other kinds of testing # The use of the CBC sample/tissue repository # The use of the CBC data repository

Proper citation: Wake Forest Cynomolgus Breeding Colony (RRID:SCR_006605) Copy   

•   Source: SciCrunch Registry

http://code.google.com/p/lapdftext/

Software that facilitates accurate extraction of text from PDF files of research articles for use in text mining applications. It is intended for both scientists and natural language processing (NLP) engineers interested in getting access to text within specific sections of research articles. The system extracts text blocks from PDF-formatted full-text research articles and classifies them into logical units based on rules that characterize specific sections. The LA-PDFText system focuses only on the textual content of the research articles. The current version of LA-PDFText is a baseline system that extracts text using a three-stage process: * identification of blocks of contiguous text * classification of these blocks into rhetorical categories * extraction of the text from blocks grouped section-wise.

Proper citation: lapdftext (RRID:SCR_006167) 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://msf.ucsf.edu/

Provides high-performance tandem mass spectrometry and proteomics, including multiplexed quantitative comparative analysis of protein and post-translational modifications, and a suite of tools for the analysis of mass spectrometry proteomics data. It provides both scientific and technical expertise and state-of-the-art high-performance, tandem mass spectrometric instrumentation. The facility also provides a service for small molecule analysis. Significant instrumentation in the facility includes three QSTAR quadrupole orthogonal time of flight instruments, and both an LTQ-Orbitrap platform with electron transfer dissociation (ETD) and an LTQ-FT linear ion trap FT-ICR instrument equipped with the ability to perform electron capture dissociation (ECD). The Center also has a 4700 Proteomic Analyzer MALDI tandem time of flight instrument; as well as a QTRAP 5500 hybrid triple quadrupole linear ion trap instrument; and a Thermo Fisher LTQ Orbitrap Velos. Major research focuses within the Center are the analysis of post-translational modifications, including phosphorylation and O-GlcNAcylation and development of methods for quantitative comparative analysis of protein and post-translational modification levels. The program also continues to develop one of the leading suites of tools for analysis of mass spectrometry proteomics data, Protein Prospector. The current web-based release allows unrestricted searching of MS and MSMS data, as well as the ability to perform comparative quantitative analysis of samples using isotopic-labeling reagents. It is the only freely-available web-based resource that allows this type of analysis.

Proper citation: National Bio-Organic Biomedical Mass Spectrometry Resource Center (RRID:SCR_009004) Copy   

•   Source: SciCrunch Registry

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

Software application for removing patient-identifying information from medical image files. Removing this information is often necessary for enabling investigators to share image files in a HIPAA compliant manner.

Proper citation: LONI De-identification Debablet (RRID:SCR_009593) Copy   

•   Source: SciCrunch Registry

http://www.sci.utah.edu/cibc/software/231-biomesh3d.html

A free, easy to use program for generating quality meshes for use in biological simulations. It is currently integrated with SCIRun and uses the SCIRun system to visualize the intermediate results. The BioMesh3D program uses a particle system to distribute nodes on the separating surfaces that separate the different materials and then uses the TetGen software package to generate a full tetrahedral mesh.

Proper citation: BioMesh3D (RRID:SCR_009534) Copy   

•   Source: SciCrunch Registry

http://researchiq.bmi.osumc.edu

THIS RESOURCE IS NO LONGER IN SERVICE, documented March 14, 2016. Research Integrative Query (ResearchIQ) tool, a semantically anchored resource discovery platform that facilitates semantic discovery of local and publicly available data through a single web portal designed for researchers in the biomedical informatics domain within The Ohio State University.

Proper citation: ResearchIQ (RRID:SCR_014304) Copy   

•   Source: SciCrunch Registry

http://amp.pharm.mssm.edu/X2K/

Software tool to produce inferred networks of transcription factors, proteins, and kinases predicted to regulate the expression of the inputted gene list by combining transcription factor enrichment analysis, protein-protein interaction network expansion, with kinase enrichment analysis. It provides the results as tables and interactive vector graphic figures.

Proper citation: eXpression2Kinases (RRID:SCR_016307) Copy   

•   Source: SciCrunch Registry

https://data.broadinstitute.org/alkesgroup/Eagle/

Software package for statistical estimation of haplotype phase either within a genotyped cohort or using a phased reference panel in large scale sequencing. The package includes Eagle1 (to harness identity-by-descent among distant relatives to rapidly call phase using a fast scoring approach) and Eagle2 (to analyze a full probabilistic model similar to the diploid Li-Stephens model used by previous HMM-based methods.

Proper citation: Eagle (RRID:SCR_015991) Copy   

•   Source: SciCrunch Registry

http://ohsu.eagle-i.net/i/0000012e-5e3a-7084-4106-535b80000000

In cooperation with the Data and Clinical Cores at the Layton Center, the Biomarkers and Genetics Core generates and maintains biomarker data for select biomarkers which have established roles in the characterization of subjects with or at risk of dementia. Biological markers of brain aging, dementia risk, and neurodegeneration have the potential to accelerate the identification of disease mechanisms and treatment strategies. Biomarkers may include genes, proteins, or other metabolites, and may be identified in DNA, cerebrospinal fluid (CSF), or plasma. Apolipoprotein E (APOE) genotype is generated for all research subjects. Sub-groups of subjects have other types of biomarker data. Many subjects have had genome-wide SNP data generated. In order to foster collaborative research as well as expand resources and expertise, samples (DNA, CSF, and plasma) and data are distributed to qualified investigators worldwide. Most of these researchers are pursuing the causes and modifiers of dementia. Data and samples are collected from well characterized research subjects including the healthy elderly and dementia patients.

Proper citation: Layton Alzheimers Disease Center Biomarkers and Genetics Core Lab (RRID:SCR_009911) Copy   

•   Source: SciCrunch Registry