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http://www.iu.edu/~beca/

Visualization and analysis software for interactive visual exploration and mining of fiber-tracts and brain networks with their genetic determinants and functional outcomes. BECA includes an fMRI and Diseases Analysis version as well as a Genome Explorer version.

Proper citation: BECA (RRID:SCR_015846) Copy   

•   Source: SciCrunch Registry

https://www.icpsr.umich.edu/icpsrweb/content/addep/index.html

Provides access to data including wide range of topics related to disability. ADDEP data can be used to better understand and inform the implementation of Americans with Disabilities Act and other disability policies.

Proper citation: Archive of Data on Disability to Enable Policy (ADDEP) (RRID:SCR_016315) Copy   

•   Source: SciCrunch Registry

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

Software containerized environments for reproducible neuroimaging. Part of ReproNim - Center for Reproducible Neuroimaging Computation. DataLad dataset with collection of popular computational tools provided within ready to use containerized environments.

Proper citation: ReproNim/containers (RRID:SCR_018467) Copy   

•   Source: SciCrunch Registry

https://www.bpforms.org

Software toolkit for unambiguously describing molecular structure of DNA, RNA, and proteins, including non-canonical monomeric forms, crosslinks, nicks, and circular topologies. Aims to help epigenomics, transcriptomics, proteomics, systems biology, and synthetic biology researchers share and integrate information about DNA modification, post-transcriptional modification, post-translational modification, expanded genetic codes, and synthetic parts.

Proper citation: BpForms (RRID:SCR_018653) Copy   

•   Source: SciCrunch Registry

https://www.objtables.org

Software toolkit for creating reusable datasets that are both human and machine readable, combining spreadsheets with schemas including classes, their attributes, type of each attribute, and possible relationships between instances of classes.Consists of format for describing schemas for spreadsheets, numerous data types for science, syntax for indicating class and attribute represented by each table and column in workbook, and software for using schemas to rigorously validate, merge, split, compare, and revision datasets. Used for supplementary materials of journal article, as well as for emerging domains which need to quickly build new formats for new types of data and associated software with minimal effort.

Proper citation: ObjTables (RRID:SCR_018652) Copy   

•   Source: SciCrunch Registry

https://www.biosimulations.org/

Web tool for sharing and re-using biomodels, simulations, and visualizations of simulations results. Supports variety of modeling frameworks including kinetic, constraint based, and logical modeling, model formats including BNGL, CellML, SBML, and simulation tools including COPASI, libRoadRunner/tellurium, NFSim, VCell.

Proper citation: BioSimulations (RRID:SCR_018733) Copy   

•   Source: SciCrunch Registry

http://enigma.ini.usc.edu/protocols/dti-protocols/

Pipeline which provides tools to extract whole-brain average and regional measurements from DTI images including FA, AD, RD and MD. Protocols for preprocessing, ENIGMA-DTI processing (skeletonization and ROI extraction), and GWAS analysis are available. Software tools used for each process are listed within the protocols.

Proper citation: ENIGMA-DTI Pipeline (RRID:SCR_014649) Copy   

•   Source: SciCrunch Registry

http://mrir.med.miami.edu:8000/midas

Software for processing, display, and analysis of magnetic resonance spectroscopic imaging data. MIDAS supports a "whole-brain" MRSI acquisition method that has been implemented on MRI systems from three major manufacturers., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: MIDAS (RRID:SCR_015704) Copy   

•   Source: SciCrunch Registry

http://coins.mrn.org/

A web-based neuroimaging and neuropsychology software suite that offers versatile, automatable data upload/import/entry options, rapid and secure sharing of data among PIs, querying and export all data, real-time reporting, and HIPAA and IRB compliant study-management tools suitable to large institutions as well as smaller scale neuroscience and neuropsychology researchers. COINS manages over over 400 studies, more than 265,000 clinical neuropsychological assessments, and 26,000 MRI, EEG, and MEG scan sessions collected from 18,000 participants at over ten institutions on topics related to the brain and behavior. As neuroimaging research continues to grow, dynamic neuroinformatics systems are necessary to store, retrieve, mine and share the massive amounts of data. The Collaborative Informatics and Neuroimaging Suite (COINS) has been created to facilitate communication and cultivate a data community. This tool suite offers versatile data upload/import/entry options, rapid and secure sharing of data among PIs, querying of data types and assessments, real-time reporting, and study-management tools suitable to large institutions as well as smaller scale researchers. It manages studies and their data at the Mind Research Network, the Nathan Kline Institute, University of Colorado Boulder, the Olin Neuropsychiatry Research Center (at) Hartford Hospital, and others. COINS is dynamic and evolves as the neuroimaging field grows. COINS consists of the following collaboration-centric tools: * Subject and Study Management: MICIS (Medical Imaging Computer Information System) is a centralized PostgreSQL-based web application that implements best practices for participant enrollment and management. Research site administrators can easily create and manage studies, as well as generate reports useful for reporting to funding agencies. * Scan Data Collection: An automated DICOM receiver collects, archives, and imports imaging data into the file system and COINS, requiring no user intervention. The database also offers scan annotation and behavioral data management, radiology review event reports, and scan time billing. * Assessment Data Collection: Clinical data gathered from interviews, questionnaires, and neuropsychological tests are entered into COINS through the web application called Assessment Manager (ASMT). ASMT's intuitive design allows users to start data collection with little or no training. ASMT offers several options for data collection/entry: dual data entry, for paper assessments, the Participant Portal, an online tool that allows subjects to fill out questionnaires, and Tablet entry, an offline data entry tool. * Data Sharing: De-identified neuroimaging datasets with associated clinical-data, cognitive-data, and associated meta-data are available through the COINS Data Exchange tool. The Data Exchange is an interface that allows investigators to request and share data. It also tracks data requests and keeps an inventory of data that has already been shared between users. Once requests for data have been approved, investigators can download the data directly from COINS.

Proper citation: Mind Research Network - COINS (RRID:SCR_000805) Copy   

•   Source: SciCrunch Registry

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

Simulation software that generates pathological ground truth from a healthy ground truth. The software requires an input directory that describes a healthy anatomy (anatomical probabilities, mesh, diffusion tensor image, etc) and then outputs simulation images.

Proper citation: TumorSim (RRID:SCR_002604) Copy   

•   Source: SciCrunch Registry

http://www.physionet.org/

Collection of dissemination and exchange recorded biomedical signals and open-source software for analyzing them. Provides facilities for cooperative analysis of data and evaluation of proposed new algorithm. Providies free electronic access to PhysioBank data and PhysioToolkit software. Offers service and training via on-line tutorials to assist users at entry and more advanced levels. In cooperation with annual Computing in Cardiology conference, PhysioNet hosts series of challenges, in which researchers and students address unsolved problems of clinical or basic scientific interest using data and software provided by PhysioNet. All data included in PhysioBank, and all software included in PhysioToolkit, are carefully reviewed. Researchers are further invited to contribute data and software for review and possible inclusion in PhysioBank and PhysioToolkit. Please review guidelines before submitting material.

Proper citation: PhysioNet (RRID:SCR_007345) Copy   

•   Source: SciCrunch Registry

http://www.mcw.edu/EPRCenter.htm

Biomedical technology research center focusing on technological innovation and application of new techniques to biological problems. The main areas of research are free radicals, spin labeling, metal complexes, and metallo proteins. Spectrometers are available for S-, X-, L-, Q- , and W-band EPR, many with ENDOR, ELDOR, saturation-transfer, saturation-recovery, and multiquantum capabilities. * Development of multiquantum Q- and W-band spectrometers, including multiquantum ELDOR, development of time-locked sub-sampling (TLSS) for broadband detection of periodically modulated signals * Development of loop-gap resonators using finite element modeling of Maxwell''s equations * Application of multifrequency (1 to 100 GHz) electron paramagnetic resonance (EPR) to characterize paramagnetic centers * Study of relaxation processes using multifrequency pulse saturation recovery * Use of nitroxide radical spin labels to measure translational and rotational diffusion in biological systems, site-directed spin labeling (SDSL), and use of EPR for the detection of nitric oxide and oxy radicals

Proper citation: National Biomedical Electron Paramagnetic Resonance Center (RRID:SCR_006601) Copy   

•   Source: SciCrunch Registry

http://mialab.mrn.org/data/index.html

An MRI data set that demonstrates the utility of a mega-analytic approach by identifying the effects of age and gender on the resting-state networks (RSNs) of 603 healthy adolescents and adults (mean age: 23.4 years, range: 12-71 years). Data were collected on the same scanner, preprocessed using an automated analysis pipeline based in SPM, and studied using group independent component analysis. RSNs were identified and evaluated in terms of three primary outcome measures: time course spectral power, spatial map intensity, and functional network connectivity. Results revealed robust effects of age on all three outcome measures, largely indicating decreases in network coherence and connectivity with increasing age. Gender effects were of smaller magnitude but suggested stronger intra-network connectivity in females and more inter-network connectivity in males, particularly with regard to sensorimotor networks. These findings, along with the analysis approach and statistical framework described, provide a useful baseline for future investigations of brain networks in health and disease.

Proper citation: MIALAB - Resting State Data (RRID:SCR_008914) Copy   

•   Source: SciCrunch Registry

http://nac.spl.harvard.edu/

Biomedical Technology Resource Center that develops image processing and analysis techniques for basic and clinical neurosciences. The NAC research approach emphasizes both specific core technologies and collaborative application projects. The core activity of the center is the development of algorithms and techniques for postprocessing of imaging data. New segmentation techniques aid identification of brain structures and disease. Registration methods are used for relating image data to specific patient anatomy or one set of images to another. Visualization tools allow the display of complex anatomical and quantitative information. High-performance computing hardware and associated software techniques further accelerate algorithms and methods. Digital anatomy atlases are developed for the support of both interactive and algorithmic computational tools. Although the emphasis of the NAC is on the dissemination of concepts and techniques, specific elements of the core software technologies have been made available to outside researchers or the community at large. The NAC's core technologies serve the following major collaborative projects: Alzheimer's disease and the aging brain, morphometric measures in schizophrenia and schizotypal disorder, quantitative analysis of multiple sclerosis, and interactive image-based planning and guidance in neurosurgery. One or more NAC researchers have been designated as responsible for each of the core technologies and the collaborative projects.

Proper citation: Neuroimage Analysis Center (RRID:SCR_008998) Copy   

•   Source: SciCrunch Registry

http://mimic.physionet.org/

Collection of comprising deidentified health related data associated with patients who stayed in critical care units of Beth Israel Deaconess Medical Center between 2001 and 2012. Database includes information such as demographics, vital sign measurements made at bedside (~1 data point per hour), laboratory test results, procedures, medications, caregiver notes, imaging reports, and mortality (both in and out of hospital).

Proper citation: Medical Information Mart for Intensive Care-III (RRID:SCR_017384) Copy   

•   Source: SciCrunch Registry

http://web.mit.edu/spectroscopy/facilities/lbrc.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. Biomedical technology research center that develops basic scientific understanding and new techniques required for advancing clinical applications of lasers and spectroscopy. LBRC merges optical spectroscopy, imaging, scattering, and interferometry techniques to study biophysics and biochemistry of healthy and diseased biological structures from subcellular to entire-organ scale.

Proper citation: Laser Biomedical Research Center (RRID:SCR_000106) Copy   

•   Source: SciCrunch Registry

http://rover.bsd.uchicago.edu/lfepr/

Biomedical technology research center that develops instrumentation, analysis techniques, spin probes and spin traps, and methodologies for imaging physiologically relevant aspects of tissue fluids, including high-resolution oxygen maps, with very low frequency electron paramagnetic resonance imaging (EPRI). Novel bridges and high-access, low-field magnet/gradient systems have produced physiologically relevant measurements and accommodate a number of resonant structures. The Center is a consortium between the University of Chicago, the University of Denver, the University of Maryland and Novosibirsk Institute of Organic Chemistry (NIOC), Russia.

Proper citation: Center for EPR Imaging in Vivo Physiology (RRID:SCR_001410) Copy   

•   Source: SciCrunch Registry

https://bli.uci.edu/laser-microbeam-program/

Biomedical technology research center dedicated to the use of lasers and optics in biology and medicine with activities in technological research and development, collaborative research, service, training, and dissemination. One of the primary goals of LAMMP is to facilitate translational research by rapidly moving basic science and technology discoveries from blackboard to benchtop to bedside. This is accomplished by combining state of the art optical technologies with specialized resource facilities for cell and tissue engineering, histopathology, pre-clinical animal models, and clinical care. The resource center has been organized into 3 cores: * Microscopy and Microbeam Technologies (MMT) for high-resolution functional imaging and manipulation of living cells and tissues * Medical Translational Technologies (MTT) for non- and minimally-invasive monitoring, treating, and imaging pre-clinical animal models and human subjects, and * Virtual Photonics Technologies (VPT) for developing computational models and methods that advance the performance of biophotonic technologies, and enhance the information content derived from optical measurements. LAMMP cores contain complementary technologies that are capable of quantitatively characterizing, imaging, and perturbing structure and biochemical function in cells and tissues with scalable resolution and depth sensitivity ranging from micrometers to centimeters.

Proper citation: Laser Microbeam and Medical Program (RRID:SCR_001409) Copy   

•   Source: SciCrunch Registry

http://www.cmu.edu/nmr-center/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on March 19,2024. Biomedical Technology Research Center that develops methodologies for the acquisition of morphological, biochemical, cellular, and functional information in living animals using nuclear magnetic resonance imaging (MRI) and spectroscopy (MRS). Novel techniques utilizing multidimensional MR imaging, magnetic resonance microscopy (MRM), and multinuclear in vivo spectroscopy are being applied to a wide range of problems in the biomedical sciences.

Proper citation: Pittsburgh NMR Center for Biomedical Research (RRID:SCR_001408) Copy   

•   Source: SciCrunch Registry

http://www.radiology.ucsf.edu/research/labs/hyperpolarized-mri-tech

Biomedical technology research center developing, investigating, and disseminating new hyperpolarized MR techniques, new 13C agents and specialized analysis open-source software for data reconstruction and interpretation. The Technology Research & Development projects will leverage the extensive DNP facilities and experience of the project leaders to develop improved, robust hyperpolarized MRI methods. These technology developments will be driven by Collaborative Projects led by outstanding clinical and basic scientists who aim to use hyperpolarized 13C MRI to accomplish the scientific goals of their funded research. These technical developments will also be disseminated to the Service Project investigators for extramural feedback and then widely to the scientific community via a dedicated website and onsite training. This center will provide state-of-the-art training in this new metabolic imaging field and sponsor a yearly symposium focused on hyperpolarized MR technology development.

Proper citation: Hyperpolarized MRI Technology Resource Center (RRID:SCR_001405) Copy   

•   Source: SciCrunch Registry