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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://ccb.loni.usc.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 31, 2022. Center focused on the development of computational biological atlases of different populations, subjects, modalities, and spatio-temporal scales with 3 types of resources: (1) Stand-alone computational software tools (image and volume processing, analysis, visualization, graphical workflow environments). (2) Infrastructure Resources (Databases, computational Grid, services). (3) Web-services (web-accessible resources for processing, validation and exploration of multimodal/multichannel data including clinical data, imaging data, genetics data and phenotypic data). The CCB develops novel mathematical, computational, and engineering approaches to map biological form and function in health and disease. CCB computational tools integrate neuroimaging, genetic, clinical, and other relevant data to enable the detailed exploration of distinct spatial and temporal biological characteristics. Generalizable mathematical approaches are developed and deployed using Grid computing to create practical biological atlases that describe spatiotemporal change in biological systems. The efforts of CCB make possible discovery-oriented science and the accumulation of new biological knowledge. The Center has been divided into cores organized as follows: - Core 1 is focused on mathematical and computational research. Core 2 is involved in the development of tools to be used by Core 3. Core 3 is composed of the driving biological projects; Mapping Genomic Function, Mapping Biological Structure, and Mapping Brain Phenotype. - Cores 4 - 7 provide the infrastructure for joint structure within the Center as well as the development of new approaches and procedures to augment the research and development of Cores 1-3. These cores are: (4)Infrastructure and Resources, (5) Education and Training, (6) Dissemination, and (7) Administration and Management. The main focus of the CCB is on the brain, and specifically on neuroimaging. This area has a long tradition of sophisticated mathematical and computational techniques. Nevertheless, new developments in related areas of mathematics and computational science have emerged in recent years, some from related application areas such as Computer Graphics, Computer Vision, and Image Processing, as well as from Computational Mathematics and the Computational Sciences. We are confident that many of these ideas can be applied beneficially to neuroimaging.

Proper citation: Center for Computational Biology at UCLA (RRID:SCR_000334) Copy   

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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   

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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   

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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   

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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   

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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   

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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   

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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

http://ohsu.eagle-i.net/i/0000012e-5e56-c3be-4106-535b80000000

THIS RESOURCE IS NO LONGER IN SERVICE.Documented on December 6th,2022. The Oregon Alzheimer?s Disease Center?s (OADC) Clinical Core program, directed by Dr. Jeffrey Kaye, performs longitudinal studies of the natural history of brain aging and Alzheimer''s disease in patients and healthy control volunteers. These studies which are performed through standardized neurological, neuro-psychological, and brain-imaging assessments are carried out in the Alzheimer''s Disease and Memory Assessment Clinics as well as through community-based assessments conducted in the homes of study volunteers. The Layton Center Neuroimaging Lab conducts brain-imaging MRI brain scans to assist in diagnosis of brain disease. Typically, MRI images are taken from three different planes. These planes are known as the coronal plane, sagittal plane and the axial plane. Each series of MRI images is named after the plane from which they were obtained. The Clinical Core?s research is focused on preclinical and early Alzheimer?s disease (AD) yet is also poised to participate in other relevant new research as it arises. The OADC Clinical Core recruits, assesses and follows individuals from population groups at high risk for dementia such as: the healthy ?oldest old?, subjects with family history of AD, and subjects with Mild Cognitive Impairment (MCI). Research with underserved populations The Oregon Alzheimer?s Disease Center also maintains two Satellite programs to enhance understanding of underserved populations: The Klamath Exceptional Aging Project (KEAP) is a community-based study of brain aging being conducted in Klamath Falls. The African American Dementia and Aging Project (AADAPt) s a Portland-based cohort of 100 African American seniors.

Proper citation: Layton Alzheimers Disease Center Clinical Core (RRID:SCR_009912) Copy   

•   Source: SciCrunch Registry

http://www.geneatlas.org/gene/main.jsp

This website allows visitors to search for genes of interest based on their spatial expression patterns in the Postnatal Day 7 mouse brain. Geneatlas provides two searching tools: A graphical interface for customized spatial queries; A textual interface for querying annotated structures. Geneatlas is the product of a collaboration between researchers at Baylor College of Medicine, Rice University, and University of Houston.

Proper citation: Gene Atlas (RRID:SCR_008089) Copy   

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http://brainmap.wisc.edu/monkey.html

NO LONGER AVAILABLE. Documented on September 17, 2019. A set of multi-subject atlas templates to facilitate functional and structural imaging studies of the rhesus macaque. These atlases enable alignment of individual scans to improve localization and statistical power of the results, and allow comparison of results between studies and institutions. This population-average MRI-based atlas collection can be used with common brain mapping packages such as SPM or FSL.

Proper citation: Rhesus Macaque Atlases for Functional and Structural Imaging Studies (RRID:SCR_008650) 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   

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http://proteogenomics.musc.edu/ma/arrayQuest.php?page=home&act=manage

A web-accessible program for the analysis of DNA microarray data. ArrayQuest is designed to apply any type of DNA microarray analysis program executable on a Linux system (i.e., Bioconductor statistical and graphical methods written in R as well as BioPerl and C++ based scripts) to DNA microarray data stored in the MUSC DNA Microarray Database, the Gene Expression Omnibus (GEO) or in a password protected private database uploaded to the center point server. ArrayQuest analyses are performed on a computer cluster.

Proper citation: ArrayQuest (RRID:SCR_010935) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/validate29/

Atlas was created from MRI scans of squirrel monkey brains. The atlas is currently comprised of multiple anatomical templates, diffusion MRI templates, and ex vivo templates. In addition, the templates are combined with histologically defined cortical labels, and diffusion tractography defined white matter labels.

Proper citation: VALiDATe29 Squirrel Monkey Brain Atlas (RRID:SCR_015542) Copy   

•   Source: SciCrunch Registry

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

Software to manage the conversion of imaging data from one file format and convention to another. It consists of a graphical user interface to visually program the translations, and a data translation engine to read, sort and translate the input files, and write the output files to disk. The data translation engine: (1) Reads metadata from a set of image files on disk to identify the source that produced each file; (2) Groups the image files into user-defined collections using image metadata values; (3) Translates each image file collection by reading metadata and pixel data and mapping the data into the appropriate output file format through a programmable set of connected modules. The Debabeler uses the Java Image I/O Plugin Architecture to read and write a wide variety of common medical image file formats, including ANALYZE, MINC, and most variations of DICOM.

Proper citation: LONI Debabeler (RRID:SCR_001160) 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

https://sleepdata.org/datasets/cfs

Portal for family based study of sleep apnea. Contains data for quantifying the familial aggregation of sleep apnea. The polysomnographic (PSG) montage signals: EEG, ECG, EOG, EMG, SpO2, plethysmography, airflow (thermistor), nasal pressure, respiratory effort, position, snore.

Proper citation: Cleveland Family Study (RRID:SCR_016585) Copy   

•   Source: SciCrunch Registry