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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://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/whs-sd-atlas/

Open access volumetric atlas of anatomical delineations of rat brain based on structural contrast in isotropic magnetic resonance and diffusion tensor images acquired ex vivo from 80 day old male Sprague Dawley rat at Duke Center for In Vivo Microscopy. Spatial reference is provided by Waxholm Space coordinate system. Location of bregma and lambda are identified as anchors towards stereotaxic space. Application areas include localization of signal in non structural images. Atlas, MRI and DTI volumes, and diffusion tensor data are shared in NIfTI format.

Proper citation: Waxholm Space Atlas of the Sprague Dawley Rat Brain (RRID:SCR_017124) Copy   

•   Source: SciCrunch Registry

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

Software repository of custom extensions to the GForge collaborative environment.

Proper citation: NITRC GForge Extensions (RRID:SCR_002495) 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://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

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://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.nitrc.org/projects/dicomconvert/

A DICOM image converter based on the ITK IO mechanism for reading and writing images. The formats currently supported by the converter are DICOM to: Analyze (*.hdr); MetaImage (*.mhd); Nrrd (*.nhdr, *.nrrd).

Proper citation: DICOMConvert (RRID:SCR_014100) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/moca_2015/

Collection of software tools for the computational analysis of brain anatomy with MRI data. It includes automated software tools from surface reconstruction to their mapping via metric optimization in the Laplace-Beltrami embedding space. It is general and can be applied to a wide range of anatomical structures including cortical, sub-cortical, and fiber bundle surfaces.

Proper citation: MOCA (RRID:SCR_015524) Copy   

•   Source: SciCrunch Registry

https://github.com/ReproNim/reproschema

Software standardized framework for creating, sharing, and reusing cognitive and clinical assessments. Standardized form generation and data collection schema to harmonize results by design across projects. Used for enhancing research reproducibility through standardized survey data collection.

Proper citation: ReproSchema (RRID:SCR_027848) Copy   

•   Source: SciCrunch Registry