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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   

•   Source: SciCrunch Registry

http://www.wakehealth.edu/Research/WFUPC/Cynomolgus-Breeding-Colony-Request-Form-Instructions.htm

The Wake Forest Cynomolgus Breeding Colony (CBC) is a colony of cynomolgus macaques (crab-eating macaques, Macaca fascicularis). The cynomolgus colony is designed to produce specific pathogen free (SPF) cynomolgus monkeys for use in biomedical research. The colony, supported by a grant from the NCRR, addresses the growing need for investigators to use in their protocols animals defined for the absence of specific diseases including CHV-1 (Herpes B), simian immunodeficiency virus, and simian retroviruses. An additional important characteristic of this colony is that, unlike many breeding colonies, the NHPs will be fed two defined diets. The first diet is a soy-free diet, not commercial monkey chow. The second diet has the same macronutrients but the protein source is from soy; similar in isoflavone content. A drawback of chow diets is that the exact nutritional product composition is unknown from lot to lot. However, they are always rich in soy bean meal, isoflavones and other constituents of soy bean meal that are known confounders of several types of research projects. All research using the cynomolgus colony must be reviewed and approved by the colony''s scientific board and the Wake Forest Animal Care and Use Committee (ACUC) before any work can be initiated. The scientific board meets regularly to assess the scientific value of each request and to determine whether or not animals/samples/data can be made available. This includes all requests for: # The purchase of animals for use outside the colony # The use of animals within the colony for the collection of blood/tissue samples, behavioral observations or other kinds of testing # The use of the CBC sample/tissue repository # The use of the CBC data repository

Proper citation: Wake Forest Cynomolgus Breeding Colony (RRID:SCR_006605) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Atlases

Probabilistic atlases covering 48 cortical and 21 subcortical structural areas, derived from structural data and segmentations kindly provided by the Harvard Center for Morphometric Analysis. T1-weighted images of 21 healthy male and 16 healthy female subjects (ages 18-50) were individually segmented by the CMA using semi-automated tools developed in-house. The T1-weighted images were affine-registered to MNI152 space using FLIRT (FSL), and the transforms then applied to the individual labels. Finally, these were combined across subjects to form population probability maps for each label. Segmentations used to create these atlases were provided by: David Kennedy and Christian Haselgrove, Centre for Morphometric Analysis, Harvard; Bruce Fischl, the Martinos Center for Biomedical Imaging, MGH; Janis Breeze and Jean Frazier from the Child and Adolescent Neuropsychiatric Research Program, Cambridge Health Alliance; Larry Seidman and Jill Goldstein from the Department of Psychiatry of Harvard Medical School.

Proper citation: Harvard - Oxford Cortical Structural Atlas (RRID:SCR_001476) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.bumc.bu.edu/cardiovascularproteomics/cpctools/strap/

Software program that automatically annotates a protein list with information that helps in the meaningful interpretation of data from mass spectrometry and other techniques. It takes protein lists as input, in the form of plain text files, protXML files (usually from the TPP), or Dat files from MASCOT search results. From this, it generates protein annotation tables, and a variety of GO charts to aid individual and differential analysis of proteomics data. It downloads information from mainly the Uniprot and EBI QuickGO databases. STRAP requires Windows XP or higher with at least version 3.5 of the Microsoft .NET Framework installed. Platform: Windows compatible

Proper citation: STRAP (RRID:SCR_005675) Copy   

•   Source: SciCrunch Registry

http://www.zfatlas.psu.edu/

Atlas containing 2- and 3-dimensional, anatomical reference slides of the lifespan of the zebrafish to support research and education worldwide. Hematoxylin and eosin histological slides, at various points in the lifespan of the zebrafish, have been scanned at 40x resolution and are available through a virtual slide viewer. 3D models of the organs are reconstructed from plastic tissue sections of embryo and larvae. The size of the zebrafish, which allows sections to fall conveniently within the dimensions of the common 1 x 3 glass slide, makes it possible for this anatomical atlas to become as high resolution as for any vertebrate. That resolution, together with the integration of histology and organ anatomy, will create unique opportunities for comparisons with both smaller and larger model systems that each have their own strengths in research and educational value. The atlas team is working to allow the site to function as a scaffold for collaborative research and educational activity across disciplines and model organisms. The Zebrafish Atlas was created to answer a community call for a comprehensive, web-based, anatomical and pathological atlas of the zebrafish, which has become one of the most widely used vertebrate animal models globally. The experimental strengths of zebrafish as a model system have made it useful for a wide range of investigations addressing the missions of the NIH and NSF. The Zebrafish Atlas provides reference slides for virtual microscopic viewing of the zebrafish using an Internet browser. Virtual slide technology allows the user to choose their own field of view and magnification, and to consult labeled histological sections of zebrafish. We are planning to include a complete set of embryos, larvae, juveniles, and adults from approximately 25 different ages. Future work will also include a variety of comparisons (e.g. normal vs. mutant, normal vs. diseased, multiple stages of development, zebrafish with other organisms, and different types of cancer)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Zebrafish Atlas (RRID:SCR_006722) Copy   

•   Source: SciCrunch Registry

http://www.autopack.org/

An open-source general packing algorithm that packs 3D objects onto surfaces, into volumes, and around volumes. It provides a general architecture to allow various packing algorithms to interoperate efficiently in the same model. autoPack can incorporate any packing solution into its modular python program architecture, but is currently optimized to provide a novel solution to the loose packing problem which places objects of discrete size into place (compared to advancing front, popcorn, or other fast tight-packing solutions that allow objects to scale to arbitrary masses.) Most popular 3D software programs now contain robust physics engines based on Bullet that can separate small collections of overlapping objects or allow volumes to be filled by pouring shapes from generators, but these approaches fails for large complex systems and result in either overlapping geometry, crashed software, or non-random gradients. Most packing algorithms are designed to position objects as efficiently as possible, but autoPack allows the user to select from random loose packing to highly organized packing methods����??even to choose both methods at the same time. autoPack positions 3D geometries into, onto, and around volumes with minimal to zero overlap. autoPack mixes several packing approaches and procedural growth algorithms. autoPack can thus place objects with forces and constraints to allow a high degree of control ranging from completely random distributions to highly ordered structures. * zero to minimal overlaps depending on the method used * accuracy vs speed parameters selected by the user * zero edge effects * complete control, from fully random to fully ordered distributions * agent-based interaction, weighting, and collision control

Proper citation: Autopack (RRID:SCR_006830) Copy   

•   Source: SciCrunch Registry

http://www.imagevis3d.org/

A new volume rendering program developed by the NIH/NCRR Center for Integrative Biomedical Computing (CIBC). The main design goals of ImageVis3D are: simplicity, scalability, and interactivity. Simplicity is achieved with a new user interface that gives an unprecedented level of flexibility (as shown in the images). Scalability and interactivity for ImageVis3D mean that both on a notebook computer as well as on a high end graphics workstation, the user can interactively explore terabyte sized data sets. Finally, the open source nature as well as the strict component-by-component design allow developers not only to extend ImageVis3D itself but also reuse parts of it, such as the rendering core. This rendering core, for instance, is planned to replace the volume rendering subsystems in many applications at the SCI Institute and with their collaborators.

Proper citation: ImageVis3D (RRID:SCR_009566) Copy   

•   Source: SciCrunch Registry

http://www.bsl.ece.vt.edu/index.php?page=ara-dataset

Dataset of structural MR images of 70 subjects collected during 2008-2010 across a wide range of ages. The dataset also contains resting state fMRI for most subjects. The structural images are T1 weighted, T2 weighted-FLAIR, 25 direction DTI, and the T1 mapping DESPOT [1] sequence. Reconstructed T1 maps for each subject are also available. The aquisition protocol was designed to study structural differences between young and older adults including both shape and intensity changes. Anonymized DICOM image sessions and processed images for each subject are available. The data is licensed under the Creative Commons Attribution License. It may be used freely for commercial, academic, or other use, as long as the original source is properly cited. http://www.bsl.ece.vt.edu/index.php?page=ara-dataset

Proper citation: Age Related Atrophy Dataset (RRID:SCR_009528) Copy   

•   Source: SciCrunch Registry

https://flowcore.hsc.wvu.edu/

Facility provides instrumentation and scientific support for single cell analysis and sorting. Routinely performs analysis of both eukaryotic and prokaryotic cells for expression of intracellular and extracellular proteins, cell cycle, cell proliferation, cytokine production, and cell sorting based on expression of cell surface antigen(s) and/or expression of genetically engineered intercellular fluorescent proteins.

Proper citation: West Virginia University Flow Cytometry and Single Cell Core Facility (RRID:SCR_017738) Copy   

•   Source: SciCrunch Registry

https://dna-analysis.yale.edu/

Core supports DNA Sequencing of PCR, Plasmid, BAC and Fosmid templates, Fragment Analysis of Microsatellites, AFLP, t-RFLP, SHAPE Experiments and Human Cell Line Authentication.

Proper citation: Yale University DNA Analysis on Science Hill Core Facility (RRID:SCR_017689) Copy   

•   Source: SciCrunch Registry

http://facs.stanford.edu/

Provides flow cytometry instrumentation and expertise. Provides operator assisted analyzer and sorter use, as well as training and support for user instrument operation.

Proper citation: Stanford University Shared FACS Core Facility (RRID:SCR_017788) Copy   

•   Source: SciCrunch Registry

http://massspec.chem.wisc.edu

Core provides mass spectrometers including Thermo Q Exactive Plus,Bruker impact II ,Bruker microflex LRF,Bruker ULTRAFLEX III,Shimadzu GCMS-QP2010S,Waters Acquity LCMS.

Proper citation: University of Wisconsin-Madison Chemistry Instrumentation Center - Mass Spectrometry Core Facility (RRID:SCR_017931) Copy   

•   Source: SciCrunch Registry

https://www.brown.edu/research/facilities/proteomics/

Core provides instrumentation and proteomics expertise to Brown University and Rhode Island-EPSCoR scientific communities and training in emerging proteomic techniques. Mass Spectrometry proteomics resources and services are provided by COBRE Center for Cancer Research Development (CCRD) at Rhode Island Hospital: Proteomics Core.

Proper citation: Brown University Division of Biology and Medicine Proteomics Shared Resource Core Facility (RRID:SCR_017910) Copy   

•   Source: SciCrunch Registry

https://med.nyu.edu/research/scientific-cores-shared-resources/microscopy-laboratory

Core offers comprehensive light and electron microscopy technologies. Our scientists use light microscopes and electron microscopes at resolutions ranging from centimeters to angstroms, providing clear and detailed images.We assist at every stage of your experiment, offering research-design consultation and instrument training, as well as guidance in study execution, analysis, and presentation for publication.

Proper citation: New York University School of Medicine Langone Health Microscopy Laboratory Core Facility (RRID:SCR_017934) Copy   

•   Source: SciCrunch Registry

https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FIRST

Software model based segmentation and registration tool. Used for segmentation of sub-cortical structures. Introduces basic segmentation and vertex analysis for detecting group differences.

Proper citation: FMRIB’s Integrated Registration and Segmentation Tool (RRID:SCR_024921) Copy   

•   Source: SciCrunch Registry