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http://www.celllineauthentication.com/

A material analysis service of the commercial organization Genetica DNA Laboratories which provides authentication of human cancer cell lines, stem cell lines and xenografts utilizing STR DNA technology.

Proper citation: Cell Line Authentication Testing (RRID:SCR_014504) Copy   

•   Source: SciCrunch Registry

http://www.brainsimagebank.ac.uk

A searchable collection of anonymised images and associated clinical data. It includes normal individuals at all ages (from prenatal to old age). The image bank contains integrated data sets already collected as part of research studies which include control subjects. New data is added as they become available.

Proper citation: BRAINS Imagebank (RRID:SCR_014576) Copy   

•   Source: SciCrunch Registry

http://ibrain.nuaa.edu.cn/

Brain research group affiliated with the Nanjing University of Aeronautics and Astronautics (NUAA) in China. The main research interests of iBRAIN include developing methods in machine learning, data mining, neural computation, and related areas for decoding brain functions or recognizing brain disease. Research related code and datasets can be found on the main site.

Proper citation: iBRAIN (RRID:SCR_014691) Copy   

•   Source: SciCrunch Registry

https://sites.google.com/ucsd.edu/drc/home

Research center across five institutions for clinical research in diabetes. Collaborators include UC San Diego's School of Medicine, Salk Institute, Cedars-Sinai Medical Center, UC Los Angeles' School of Medicine, and LA Biomedical Research Center.

Proper citation: University of California San Diego - University of California Los Angeles Diabetes Research Center (RRID:SCR_015100) Copy   

•   Source: SciCrunch Registry

http://www.uab.edu/shp/drc/

Research center which operates in collaboration with the University of Alabama Birmingham Comprehensive Diabetes Center to promote excellence in diabetes research and patient care. The DRC supports the areas of animal physiology, human biology and intervention and translational research. It focuses on developing new methods to treat, prevent, and ultimately cure diabetes and its complications.

Proper citation: University of Alabama at Birmingham Diabetes Research Center (RRID:SCR_015107) Copy   

•   Source: SciCrunch Registry

https://diabetes.med.umich.edu/partners/michigan-diabetes-research-center-mdrc

Multidisciplinary unit of the University of Michigan funded by the National Institute of Diabetes and Digestive and Kidney Diseases/National Institute of Health. Promotes new discoveries and enhance scientific progress through the support of basic and clinical research related to diabetes, its complications, and related disorders. Creates environment that supports innovative research; attracts and retains early stage investigators and investigators new to diabetes research; provides core services that leverage funding and unique expertise; fosters interdisciplinary collaborations; raises awareness and interest in fundamental and clinical diabetes research at their institutions, as well as locally, regionally, and nationally.

Proper citation: Michigan Diabetes Research Center (RRID:SCR_015112) Copy   

•   Source: SciCrunch Registry

http://www.baderc.org

Consortium of laboratory-based and clinical investigators who research etiology, pathogenesis, treatment and cure of type 1 and type 2 diabetes, and their associated microvascular and atherosclerotic complications.

Proper citation: Boston Area Diabetes Endocrinology Research Center (RRID:SCR_015072) Copy   

•   Source: SciCrunch Registry

http://www.einstein.yu.edu/centers/diabetes-research/

Research center that facilitates the research of diabetes and related studies in obesity, metabolism and endocrinology

Proper citation: Einstein-Mount Sinai Diabetes Research Center (RRID:SCR_015070) Copy   

•   Source: SciCrunch Registry

http://derc.yale.edu

University-affiliated center that promotes research in diabetes and related metabolic and endocrine disorders at Yale University.

Proper citation: Yale Diabetes Research Center (RRID:SCR_015142) Copy   

•   Source: SciCrunch Registry

http://aldconnect.org

Group whose goal is to improve health outcomes for individuals with X-linked adrenoleukodystrophy by raising disease awareness, improving education, providing support for and information to patients, and performing clinical ALD research.

Proper citation: ALD Connect (RRID:SCR_015035) Copy   

•   Source: SciCrunch Registry

http://www.oif.org

Foundation for improving the quality of life for people affected by OI through treatment and cure research, education, awareness, and mutual support. OIF lists personal resources for individuals affected by osteogenesis imperfecta as well as professional and clinical resources for researchers.

Proper citation: Osteogenesis Imperfecta Foundation (RRID:SCR_015034) Copy   

•   Source: SciCrunch Registry

http://pituitary.org

International non-profit organization for patients, relatives, and physicians with pituitary tumors and disorders.

Proper citation: Pituitary Network Association (RRID:SCR_015006) Copy   

•   Source: SciCrunch Registry

http://depts.washington.edu/diabetes/

University-affiliated center to support both basic and clinical research in diabetes and related metabolic disorders with the ultimate purpose of translating findings into opportunities to prevent these diseases and to improve clinical care and outcomes.

Proper citation: University of Washington Diabetes Research Center (RRID:SCR_015126) Copy   

•   Source: SciCrunch Registry

http://toppcluster.cchmc.org/

A tool for performing multi-cluster gene functional enrichment analyses on large scale data (microarray experiments with many time-points, cell-types, tissue-types, etc.). It facilitates co-analysis of multiple gene lists and yields as output a rich functional map showing the shared and list-specific functional features. The output can be visualized in tabular, heatmap or network formats using built-in options as well as third-party software. It uses the hypergeometric test to obtain functional enrichment achieved via the gene list enrichment analysis option available in ToppGene.

Proper citation: ToppCluster (RRID:SCR_001503) Copy   

•   Source: SciCrunch Registry

https://sourceforge.net/projects/viste/

Open source, platform-independent application for the visualization and analysis of complex, high-dimensional imaging data such as Diffusion Tensor Imaging (DTI) and High Angular Resolution Diffusion Imaging (HARDI). It has a plugin-based architecture which allows third parties to develop new plugins to extend the tool. Overview of the many features: * vIST/e is programmed in C++. It uses the Visualization Toolkit for visualization and pipelined data processing, as well as the cross-platform toolkit Qt Framework for an easy-to-use Graphical User Interface. * vIST/e introduces a powerful new plugin system, which allows for modular development with increased extensibility and stability. * Powerful GPU-based visualization techniques allow for smooth, real-time visualization of large data sets. Using custom ray tracing algorithms created with OpenGL, vIST/e can render DTI ellipsoids and HARDI spherical harmonics glyphs up to 4th order. The high frame rates offered by modern GPU technology allows for interactive exploration of this complex data. * Diffusion Tensor Imaging data can be visualized and interactively explored in a number of ways, including multiple cross-sections, volume rendering, and tensor glyphs. Derived scalar volumes, including various different anisotropy measures, can be computed and visualized. Data from other modalities, such as structural MRI, can be shown alongside the DTI data. * Various fiber tracking methods allow for fast and accurate reconstruction of fiber pathways. Interactively defined Regions of Interest (ROIs) can be used for seeding and filtering of fibers. Fibers are visualized either as lines, optionally using a powerful, GPU-based lighting engine, or as 3D structures such as tubes. * Scalar volumes, glyphs, and fibers can be colored using a wide array of coloring option. Customizable color loop-up tables allow for highly flexible visualization of scalar data. * Visualization and processing of various different HARDI formats is supported. HARDI data is interactively visualized using highly detailed glyphs rendered on the GPU. HARDI glyphs can be visualized in combination with DTI glyphs, for a better overview of complex diffusion data. * vIST/e includes support for NVIDIA's Compute Unified Device Architecture (CUDA), which enables highly parallel, GPU-based data processing, allowing for significant speed-up of computationally expensive algorithms.

Proper citation: vIST/e (RRID:SCR_001627) 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

https://www.synapse.org/#!Synapse:syn22345748/wiki/605339

Reference dataset of multiplexed immunofluorescence microscopy images collected at HMS Laboratory of Systems Pharmacology. Includes set of images of different types for development and benchmarking of computational methods for image processing. As of 4/2/2021, EMIT comprises tissue microarray containing cores from 34 cancer, non-neoplastic diseases, and normal tissue collected from clinical discards under IRB supervised protocol. TMA was imaged using cyclic immunofluorescence method. Additional extensions of EMIT are currently in the planning stages. Long term goal is to compose ImageNet like resource for highly multiplexed images of tissues and tumors by consolidating high quality curated datasets.

Proper citation: Exemplar Microscopy Images of Tissues (RRID:SCR_021052) Copy   

•   Source: SciCrunch Registry

http://knightadrc.wustl.edu/

The Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC) supports researchers and our surrounding community in their pursuit of answers that will lead to improved diagnosis and care for persons with Alzheimer disease (AD). The Center is committed to the long-term goal of finding a way to effectively treat and prevent AD. The Knight ADRC facilitates advanced research on the clinical, genetic, neuropathological, neuroanatomical, biomedical, psychosocial, and neuropsychological aspects of Alzheimer disease, as well as other related brain disorders.

Proper citation: Washington University School of Medicine Knight Alzheimers Disease Research Center (RRID:SCR_000210) Copy   

•   Source: SciCrunch Registry

http://teddy.epi.usf.edu/

International consortium of six centers assembled to participate in the development and implementation of studies to identify infectious agents, dietary factors, or other environmental agents, including psychosocial factors, that trigger type 1 diabetes in genetically susceptible people. The coordinating centers recruit and enroll subjects, obtaining informed consent from parents prior to or shortly after birth, genetic and other types of samples from neonates and parents, and prospectively following selected neonates throughout childhood or until development of islet autoimmunity or T1DM. The study tracks child diet, illnesses, allergies and other life experiences. A blood sample is taken from children every 3 months for 4 years. After 4 years, children will be seen every 6 months until the age of 15 years. Children are tested for 3 different autoantibodies. The study will compare the life experiences and blood and stool tests of the children who get autoantibodies and diabetes with some of those children who do not get autoantibodies or diabetes. In this way the study hopes to find the triggers of T1DM in children with higher risk genes.

Proper citation: TEDDY (RRID:SCR_000383) Copy   

•   Source: SciCrunch Registry

http://www.opencolleges.edu.au/

A resource for online accredited courses in a wide variety of areas, including accounting, animal care, beauty, building and construction, business, education, design and writing. This resource is based in Australia.

Proper citation: Open Colleges (RRID:SCR_000418) Copy   

•   Source: SciCrunch Registry