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

Software for the analysis of multiple diffusion properties along fiber bundle as functions in an infinite dimensional space and their association with a set of covariates of interest, such as age, diagnostic status and gender, in real applications. The resulting analysis pipeline can be used for understanding normal brain development, the neural bases of neuropsychiatric disorders, and the joint effects of environmental and genetic factors on white matter fiber bundles.

Proper citation: Functional Regression Analysis of DTI Tract Statistics (RRID:SCR_002293) Copy   

•   Source: SciCrunch Registry

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

A population-specific DTI template for young adolescent Rhesus Macaque (Macaca mulatta) monkeys using 271 high-quality scans. Using such a large number of animals in generating a template allows it to account for variability in the species. Their DTI template is based on the largest number of animals ever used in generating a computational brain template. It is anticipated that their DTI template will help facilitate voxel-based and tract specific WM analyses in non-human primate species, which in turn may increase our understanding of brain function, development, and evolution.

Proper citation: DTI-TEMPLATE-RHESUS-MACAQUES (RRID:SCR_002482) Copy   

•   Source: SciCrunch Registry

https://brainlife.io/

Free cloud platform for secure neuroscience data analysis. Allows to manage data, processing and results, sharing projects privately with collaborators or publicly with brainlife.io community.Promotes engagement and education in reproducible neuroscience.You can share your neuroimaging data publicly or privately. Data on brainlife.io is organized as Datatypes to allow interoperability between Apps.

Proper citation: brainlife (RRID:SCR_020940) Copy   

•   Source: SciCrunch Registry

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

Software Matlab toolbox for directed functional connectivity analysis of fMRI BOLD signal from predefined regions of interest. It recovers true structure of connections and estimates weights attributed to each connection. Obtains patterns at group and individual levels.

Proper citation: GIMME (RRID:SCR_014115) Copy   

•   Source: SciCrunch Registry

https://doi.org/10.5281/zenodo.592960

Image reconstruction software for MRI. Its library provides common operations on multi-dimensional arrays, Fourier and wavelet transforms, as well as generic implementations of iterative optimization algorithms.

Proper citation: Berkeley Advanced Reconstruction Toolbox (RRID:SCR_016168) Copy   

•   Source: SciCrunch Registry

https://github.com/bids-standard/bids-validator

Software validation tool that checks submitted folder structure for compliance to BIDS data standard. Validates Brain Imaging Data Structure.

Proper citation: BIDS Validator (RRID:SCR_017255) Copy   

•   Source: SciCrunch Registry

http://www.reproducibleimaging.org

Center to help neuroimaging researchers to find and share data in FAIR fashion, to describe their data and analysis workflows in replicable fashion, to manage their computational resource options so that outcomes of neuroimaging research are more reproducible.

Proper citation: ReproNim: A Center for Reproducible Neuroimaging Computation (RRID:SCR_016001) Copy   

•   Source: SciCrunch Registry

https://crispresso.pinellolab.partners.org/submission

Software suite of tools to qualitatively and quantitatively evaluate outcomes of genome editing experiments in which target loci are subject to deep sequencing and provides integrated, user friendly interface. Used for analysis of CRISPR-Cas9 genome editing outcomes from sequencing data. CRISPResso2 provides accurate and rapid genome editing sequence analysis.Used for analysis of deep sequencing data for rapid and intuitive interpretation of genome editing experiments.

Proper citation: CRISPResso (RRID:SCR_021538) Copy   

•   Source: SciCrunch Registry

http://bmsr.usc.edu/software/lysis/

Interactive software of a set of modular programs (each performing a specific task) that provide an integrated computing environment for data analysis and system modeling. Unique capabilities of LYSIS include input-output nonlinear system modeling and the novel methodology of Principal Dynamic Modes (PDMs). LYSIS is currently available in two versions: one for LYSIS 7.1 Windows and one for LYSIS 7.2 Matlab. Early versions are also available for UNIX environments, distributed as source code that can be compiled for each UNIX implementation (e.g., Solaris, HPUX, Linux). Specific features of LYSIS that cannot be found in commercially available packages include the efficient kernel estimation using Laguerre expansions and the use of Principal Dynamic Modes (PDMs). These enable input-output modeling of dynamic nonlinear systems with relatively short data-records (even in the presence of considerable noise). System Requirements * Operating System ** Windows XP/Vista/7 ** Sun/Unix: Solaris 2.x

Proper citation: LYSIS (RRID:SCR_001385) Copy   

•   Source: SciCrunch Registry

https://www.loni.usc.edu/research/software?name=WAIR

A software tool for the quantitative analysis of various n-dimensional (n-D) image registration techniques. The series of 'C' subroutines which comprise the WAIR library can be easily incorporated into the user's site specific programs and adapted to their particular needs. Wavelet-space triangle analysis is applicable for studying a family of warps on single or multiple n-D data sets. For each data set the WAIR routine assigns a positive real number to every warp alignment in the family, and the best warp for the given data will be the one with the smallest value. It uses the original data prior to warping and the target of the warp in determining warp ranking in reduced wavelet space. Cluster group classification (CGC) is applicable for analyzing the overall performance of a family of warps of a group of data sets. A single number is assigned to each registration alignment, based on its group-clustering characteristics. Spread group classification (SGC) gives preference to registration techniques that spread apart baseline versus activation functional signal for group data.

Proper citation: Wavelet Analysis of Image Registration (RRID:SCR_000172) Copy   

•   Source: SciCrunch Registry

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

Software library that is a collection of Java classes that enable Java programmers to model, manipulate and visualize geometric shapes and associated data values. It simplifies the creation of application programs by providing a ready-made set of support routines. * File format readers that implement ShapeIO interface (modeled after Java ImageIO) are automatically used when appropriate. * Storage of additional metadata of arbitrary type (other than shape vertices and interconnections) is enabled by the use of data attributes. * Shapes may contain a set of child shapes allowing for the construction and manipulation of complex hierarchies of shapes. * The various components of a shape are specified as interfaces with specific implementations, making it easy to create specialized implementations of a shape component when different performance characteristics are required.

Proper citation: LONI ShapeTools (RRID:SCR_002697) Copy   

•   Source: SciCrunch Registry

http://cng.gmu.edu/brava

A database of digital reconstructions of the human brain arterial arborizations from 61 healthy adult subjects along with extracted morphological measurements. The arterial arborizations include the six major trees stemming from the circle of Willis, namely: the left and right Anterior Cerebral Arteries (ACAs), Middle Cerebral Arteries (MCAs), and Posterior Cerebral Arteries (PCAs).

Proper citation: BraVa (RRID:SCR_001407) Copy   

•   Source: SciCrunch Registry

https://github.com/denisecailab/minian

Software miniscope analysis pipeline that requires low memory and computational demand so it can be run without specialized hardware. Offers interactive visualization that allows users to see how parameters in each step of pipeline affect output.

Proper citation: Minian (RRID:SCR_022601) Copy   

•   Source: SciCrunch Registry

http://nmrresource.ucsd.edu/

Biomedical technology research center that develops new technology for NMR spectroscopy and makes it available to the biomedical research community for structure determination of proteins in biological supramolecular assemblies, such as membrane proteins or virus particles. The principal applications are to membrane-associated proteins; however, the approach is generally applicable to polypeptides that cannot be prepared in forms suitable for X-ray crystallography or multidimensional solution NMR spectroscopy. As a result, there are also applications to viruses and other biological systems. The principal instrumentation consists of high-field NMR spectrometers dedicated to high-resolution solid-state NMR spectroscopy. The spectrometers are capable of the full-range of multiple-resonance experiments on stationary and spinning samples; however, the major emphasis is on methods that utilize mechanically or magnetically oriented samples. Development encompasses preparation of samples, including: * Expression and purification of membrane proteins * Design and construction of instrumentation, especially probes * Implementation of new pulse sequences and other experimental protocols for solid-state NMR spectroscopy * Calculations for the processing of experimental data and protein structure determination from the orientational constraints derived from these data

Proper citation: UCSD Center for NMR Spectroscopy and Imaging of Proteins (RRID:SCR_001401) Copy   

•   Source: SciCrunch Registry

https://med.stanford.edu/lucasmri.html

Biomedical technology research center that develops innovative technologies in five core research areas of magnetic resonance imaging and spectroscopy (MRI/MRS): # image reconstruction, fast imaging and radiofrequency (RF) pulse design methods, # R hardware development, # body imaging methods, # neuroimaging methods. # MR spectroscopy methods. In each of these areas, they capitalize on the long-standing, successful partnership and extensive experience in Stanford's Radiology and Electrical Engineering departments to improve and expand imaging technology for use in basic research and clinical care, and to provide cutting edge opportunities to the extramural community for biomedical research with MRI. Over its more than 18 years of existence, CAMRT has been motivated by and has served a wide base of extramurally sponsored collaborators and service users from leading medical and research institutions. Examples of collaborative projects are the development of real-time functional MRI biofeedback methods for neuroscience and clinical applications such as pain remediation, development of methods to mitigate metal artifacts in musculoskeletal imaging, development of novel RF pulses for many applications, and studies of breast cancer with efficient MRS methods.

Proper citation: Richard M. Lucas Center for Imaging (RRID:SCR_001406) Copy   

•   Source: SciCrunch Registry

http://web.mit.edu/fbml/cmr.shtml#

Biomedical technology research center designated as a biotechnology nuclear magnetic resonance (NMR) resource that hosts research efforts into cancer, neurological diseases, and many other areas. The heart of the 900 MHz magnetic resonance instrument is a superconducting magnet with a field strength of 21 Tesla, the highest field currently available for magnetic resonance spectroscopy, roughly 400,000 times stronger than the earth's magnetic field. Magnetic resonance is a powerful tool for determining the structure of molecules, and has proven especially useful for elucidating the role of proteins in biological processes and diseases. The state of the art facility includes two 17.6 T magnets with a third to be delivered in 2000. With multiple 17.6 T NMR magnets, the CMR is a valuable resource in New England and will continue to serve this research community for years to come. The advent of high magnetic fields has placed demands on the hardware needed to run experiments in these very high fields. The CMR has recently produced new advances in NMR probe technology, in electron magnetic resonance, and in using microwaves to enhance NMR experiments. The results are powerful new methods for performing biological research and they are looking forward to the continued growth of these exciting new areas!

Proper citation: MIT/ Harvard Center for Magnetic Resonance (RRID:SCR_001412) Copy   

•   Source: SciCrunch Registry

http://www.nrims.harvard.edu/

Biomedical technology research center with the focus on the application to biomedical research of a new generation of secondary ion mass spectrometer (SIMS), the Multi-Isotope Imaging Mass Spectrometer (MIMS). MIMS is an ion microscope and an ion counter. MIMS provides high mass separation at high transmission (M/lambdaM > 10,000), high spatial resolution (< 40 nm) and has the unique capability of simultaneously recording several atomic mass images. Of the utmost importance, MIMS makes it possible for the first time (and at the intracellular level) to simultaneously image the distribution and measure the accumulation of molecules labeled with any isotopes, in particular with stable isotopes, for example with 15N. Thus, MIMS allows one to study localization, accumulation and turnover of proteins, fats, sugars and foreign molecules in cellular microdomains, donor-receiver cellular trafficking, stem cell nesting and localization of drugs. Their aim is to be a technological, methodological, and intellectual resource for researchers from a variety of disciplines. They seek to explore and develop the unique capabilities of MIMS and to bring cutting-edge information to biology and medicine that is currently unobtainable using existing technologies.

Proper citation: National Resource for Imaging Mass Spectrometry (RRID:SCR_001416) Copy   

•   Source: SciCrunch Registry

http://bmsr.usc.edu/

Biomedical technology resource center dedicated to the advancement of the state-of-the-art in biomedical modeling and simulation through Core and Collaborative Research projects, as well as the dissemination of this knowledge and related software through Service, Training and Dissemination activities aimed at the biomedical community at large. The BMSR includes four core research projects: * Pharmacokinetic/Pharmacodynamic Systems Analysis * Nonlinear Modeling of Complex Biomedical Systems * Modeling of Autonomic, Metabolic and Vascular Control Interactions * Nonlinear Modeling of the Hippocampus Fifteen Collaborative Research Projects serve as challenging test grounds for the Resource's methodologies and expertise.

Proper citation: Biomedical Simulations Resource (RRID:SCR_001952) Copy   

•   Source: SciCrunch Registry

http://www.nmr.mgh.harvard.edu/CFNT/index

Biomedical technology research center that develops and applies innovative neuroimaging technologies and techniques to enable closer examination of the human brain, and thereby contribute to better understanding of the brain in health and disease. They develop new techniques and advance existing technologies for acquisition and analysis of functionally specific images of the working brain, with unprecedented physiological precision and spatiotemporal resolution. The research and development aims to improve and extend existing methods for non-invasive magnetic resonance image analysis and acquisition, electromagnetic source imaging, optical neuroimaging, and most recently, combined MR-PET neuroimaging. The Resource provides an essential interactive environment, within which an interdisciplinary team of highly skilled scientists, engineers, and clinicians with diverse expertise in multiple modalities and disciplines. The resource supports service use of the Center's facilities by neuroscientists throughout the country, provide extensive training opportunities for students, fellows, and staff scientists, and seek to advance the field of brain mapping through active dissemination of new knowledge and technology.

Proper citation: Center for Functional Neuroimaging Technologies (RRID:SCR_001423) Copy   

•   Source: SciCrunch Registry

http://www.utsouthwestern.edu/education/medical-school/departments/airc/southwestern-nmr-center/index.html

Biomedical technology research center that develops and applies new methods for analysis of metabolic networks in intact tissues, animals and human patients. The importance of understanding abnormal metabolism in common diseases such as cancer, diabetes and heart disease has long been appreciated. Because of constraints in technology, however, much of this research has been conducted in isolated systems where clinical relevance may be uncertain. Progress in magnetic resonance technology provides a foundation for major advances towards new ways of imaging metabolism in patients. These new techniques offer the advantage of imaging biochemical pathways without radiation. The focus of this Resource is to bring these technologies to a level where clinical research is feasible through the development of new MR contrast agents, NMR spectroscopy at high fields, and imaging of hyperpolarized 13C.

Proper citation: Southwestern NMR Center for In Vivo Metabolism (RRID:SCR_001429) Copy   

•   Source: SciCrunch Registry