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http://anya.igsb.anl.gov/Geneways/GeneWays.html

System for automatically extracting, analzying, visualizing and integrating molecular pathway data from the research literature. System focuses on interactions between molecular substances and actions, providing a graphical consensus view on the collected information. GeneWays is designed as open platform, allowing researchers to query, review and critique integrated information.

Proper citation: GeneWays (RRID:SCR_000572) Copy   

•   Source: SciCrunch Registry

https://hdpm.biomedinfolab.com/netmage/

Web tool for automated generation of interactive disease-disease network visualizations given input PheWAS summary data. Given genetic associations from Phenome-Wide Association Study, disease-disease network can be constructed where nodes represent phenotypes and edges represent shared genetic associations between phenotypes.

Proper citation: NETMAGE (RRID:SCR_021843) 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://ncmi.bcm.edu/ncmi/

Biomedical technology research center establishing the infrastructure for fast, routine, atomic structure determination of subcellular complexes by electron cryo-microscopy, computer reconstruction and modeling. Their emphasis is on specimens that cannot currently be studied by conventional structural techniques such as x-ray crystallography or NMR. The ultimate outcome of their research is a three-dimensional image of the complex that can be used for design of drugs and vaccines for a variety of diseases. The center is focused on extending the resolution, speed and flexibility of cryo-electron microscopy for the three-dimensional structure determination of biological macromolecular assemblies. Cryo-electron microscopy can visualize molecules under near-native conditions at resolutions ranging from 0.3 to 5 nm and can yield images of individual molecules in a range of different conformations as they exist in solution. Other cryo-electron mycroscopy techniques, such as cryo-electron tomography, are being developed to capture molecular structures in situ. The equipment, techniques and expertise developed are available to the research community through collaborative projects. The NCMI also provides training through workshops and other forms of dissemination via both traditional and modern Internet-based methods.

Proper citation: National Center for Macromolecular Imaging (RRID:SCR_001445) 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

http://www.macchess.cornell.edu/

MacCHESS Synchrotron Source for Structural Biology advances structural characterization of proteins and biomolecules critical for understanding key biological processes and properties through leveraging both established and emerging X-ray synchrotron technologies. Used to collect data that comprises all or part of research programs.

Proper citation: MacCHESS (RRID:SCR_001443) Copy   

•   Source: SciCrunch Registry

http://bowtie-bio.sourceforge.net/recount/

RNA-seq gene count datasets built using the raw data from 18 different studies. The raw sequencing data (.fastq files) were processed with Myrna to obtain tables of counts for each gene. For ease of statistical analysis, they combined each count table with sample phenotype data to form an R object of class ExpressionSet. The count tables, ExpressionSets, and phenotype tables are ready to use and freely available. By taking care of several preprocessing steps and combining many datasets into one easily-accessible website, we make finding and analyzing RNA-seq data considerably more straightforward.

Proper citation: ReCount - A multi-experiment resource of analysis-ready RNA-seq gene count datasets (RRID:SCR_001774) Copy   

•   Source: SciCrunch Registry

https://ncxt.org/

Biomedical technology research center that develops novel cellular imaging technologies, specifically soft X-ray tomography, for visualizing and quantifying the internal structure of whole, hydrated cells, and high-numerical aperture fluorescence microscopy for locating the position of specific cellular molecules. Data from these two imaging modalities can be combined to form a single, correlated imaging view of a cell.

Proper citation: National Center for X-ray Tomography (RRID:SCR_001433) 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.mc.vanderbilt.edu/root/vumc.php?site=ims

Biomedical technology research center that advances the technology of Imaging Mass Spectrometry, facilitates the application of this novel imaging modality to problems of biological and clinical significance, and promotes the adoption of these technologies by a larger community of scientists and clinicians. Technical innovations include next-generation hardware, software and methods. Technology development is conducted by an interdisciplinary team of scientists and engineers, both within the Resource and through collaborative relationships with other universities, research institutes, and private industry. Development milestones are guided by Driving Biological Projects that require specific advancements in Imaging Mass Spectrometry in order to address biological problems. By working together, they anticipate new insights into these biological systems and a better understanding of health and disease at the molecular level that translates to improved patient care. The training mission of the Resource is accomplished through a variety of educational programs where Resource scientists and collaborators share their knowledge and experience with those interested in learning more about the technology.

Proper citation: VU National Research Resource for Imaging Mass Spectrometry (RRID:SCR_006904) 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://dockground.bioinformatics.ku.edu/

Data sets, tools and computational techniques for modeling of protein interactions, including docking benchmarks, docking decoys and docking templates. Adequate computational techniques for modeling of protein interactions are important because of the growing number of known protein 3D structures, particularly in the context of structural genomics. The first release of the DOCKGROUND resource (Douguet et al., Bioinformatics 2006; 22:2612-2618) implemented a comprehensive database of cocrystallized (bound) protein-protein complexes in a relational database of annotated structures. Additional releases added features to the set of bound structures, such as regularly updated downloadable datasets: automatically generated nonredundant set, built according to most common criteria, and a manually curated set that includes only biological nonobligate complexes along with a number of additional useful characteristics. Also included are unbound (experimental and simulated) protein-protein complexes. Complexes from the bound dataset are used to identify crystallized unbound analogs. If such analogs do not exist, the unbound structures are simulated by rotamer library optimization. Thus, the database contains comprehensive sets of complexes suitable for large scale benchmarking of docking algorithms. Advanced methodologies for simulating unbound conformations are being explored for the next release. The Dockground project is developed by the Vakser lab at the Center for Bioinformatics at the University of Kansas. Parts of Dockground were co-developed by Dominique Douguet from the Center of Structural Biochemistry (INSERM U554 - CNRS UMR5048), Montpellier, France.

Proper citation: Dockground: Benchmarks, Docoys, Templates, and other knowledge resources for DOCKING (RRID:SCR_007412) Copy   

•   Source: SciCrunch Registry

http://necat.chem.cornell.edu/

Biomedical technology research center for macromolecular crystallography at Sector 24 of the Advanced Photon Source at Argonne National Laboratory. The macromolecules studied by resource users often involve large unit cells, small crystals, weakly diffracting crystals and crystals with weak anomalous scattering. Technological research includes use of silicon monochromators, focusing optics, methods of phase determination, radiation damage, X-ray detectors, automated sample mounting, microdiffraction and crystallographic software.

Proper citation: Northeastern Collaborative Access Team (RRID:SCR_008999) Copy   

•   Source: SciCrunch Registry

http://lab.rockefeller.edu/chait/

Biomedical technology research center that develops cutting-edge mass spectrometric tools for analyzing peptides and proteins. It makes its software tools developed for data analysis freely available.

Proper citation: National Resource for the Mass Spectrometric Analysis of Biological Macromolecules (RRID:SCR_009007) Copy   

•   Source: SciCrunch Registry

http://mmbios.org/

Biomedical technology research center that develops and makes available to the scientific community high performance computing algorithms, tools and software to leverage modeling efforts at disparate scales of structural biology, cellular microphysiology and large-scale bioimage processing and analysis, with the goal of advancing understanding of the molecular and cellular organization and functional mechanisms that underlie synaptic signaling and regulation.

Proper citation: National Center for Multiscale Modeling of Biological Systems (RRID:SCR_009005) 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.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://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