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https://database.riken.jp/sw/en/The_RIKEN_integrated_database_of_mammals/ria254i/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 16, 2019.
A database that integrates not only RIKEN''''s original large-scale mammalian databases, such as FANTOM, the ENU mutagenesis program, the RIKEN Cerebellar Development Transcriptome Database and the Bioresource Database, but also imported data from public databases, such as Ensembl, MGI and biomedical ontologies. Our integrated database has been implemented on the infrastructure of publication medium for databases, termed SciNetS/SciNeS, or the Scientists'''' Networking System, where the data and metadata are structured as a semantic web and are downloadable in various standardized formats. The top-level ontology-based implementation of mammal-related data directly integrates the representative knowledge and individual data records in existing databases to ensure advanced cross-database searches and reduced unevenness of the data management operations. Through the development of this database, we propose a novel methodology for the development of standardized comprehensive management of heterogeneous data sets in multiple databases to improve the sustainability, accessibility, utility and publicity of the data of biomedical information.

Proper citation: RIKEN integrated database of mammals (RRID:SCR_006890) Copy   

•   Source: SciCrunch Registry

http://www.nih.gov/science/brain/

Project aimed at revolutionizing understanding of human brain, to show how individual cells and complex neural circuits interact, enable rapid progress in development of new technologies and data analysis tools to treat and prevent brain disorders. BRAIN Initiative encourages collaborations between neurobiologists and scientists from disciplines such as statistics, physics, mathematics, engineering, and computer and information sciences. Institutes and centers contributing to NIH BRAIN Initiative support those research efforts.

Proper citation: BRAIN Initiative (RRID:SCR_006770) Copy   

•   Source: SciCrunch Registry

http://www.bic.mni.mcgill.ca/ServicesAtlases/NIHPD-obj1

An unbiased standard magnetic resonance imaging template brain volume for pediatric data from the 4.5 to 18.5y age range. These volumes were created using data from 324 children enrolled in the NIH-funded MRI study of normal brain development (Almli et al., 2007, Evans and Group 2006). Tools for using these atlases can be found in the Software section. To view the atlases online, click on the appropriate JIV2 link in the Download section. You can download templates constructed for different age ranges. For each age range you will get an average T1w, T2w, PDw maps normalized between 0 and 100 and tissue probability maps, with values between 0 and 1. Also each age range includes a binary brain mask.

Proper citation: NIHPD Objective 1 atlases (4.5 - 18.5y) (RRID:SCR_008794) Copy   

•   Source: SciCrunch Registry

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

A novel C++ based application developped at UNC-Chapel Hill that performs automatic brain tissue classification and structural segmentation. AutoSeg is designed for use with human and non-human primate pediatric, adolescent and adult data. AutoSeg uses a BatchMake pipeline script that includes the main steps of the framework entailing N4 bias field correction, rigid registration to a common coordinate image, tissue segmentation, skull-stripping, intensity rescaling, atlas-based registration, subcortical segmentation and lobar parcellation, regional cortical thickness and intensity statistics. AutoSeg allows efficient batch processing and grid computing to process large datasets and provides quality control visualizations via Slicer3 MRML scenes.

Proper citation: AutoSeg (RRID:SCR_009438) Copy   

•   Source: SciCrunch Registry

http://www.genboree.org/epigenomeatlas/index.rhtml

Collection of human reference epigenomes and results of their integrative and comparative analyses. Successive releases of the Atlas will provide progressively more detailed insights into locus-specific epigenomic states, including histone marks and DNA methylation marks across specific tissues and cell types, developmental stages, physiological conditions, genotypes, and disease states. The Human Epigenome Atlas is produced by the NIH Epigenomics Roadmap Consortium.

Proper citation: Human Epigenome Atlas (RRID:SCR_006153) Copy   

•   Source: SciCrunch Registry

http://www.mayo.edu/research/centers-programs/alzheimers-disease-research-center

A clinical research department that specializes in the study of Alzheimer's disease. The Mayo Clinic Alzheimer's Disease Research Center conducts many types of research studies related to dementia, as well as normal or successful aging. The purpose of the center is to provide care for dementia patients and promote research and education on Alzheimer's Disease and related dementias.

Proper citation: Mayo Alzheimer's Disease Research Center (RRID:SCR_008727) Copy   

•   Source: SciCrunch Registry

http://www.tcgls.com/

Leading contract research and manufacturing services company in the area of drug discovery and development.

Proper citation: TCG Life Sciences (RRID:SCR_010571) Copy   

•   Source: SciCrunch Registry

http://www.iit.edu/~mri/

Atlas that contains new anatomical, DTI, HARDI templates and probabilistic gray matter labels of the adult human brain in ICBM-152 space. Artifact-free MRI data from 72 human subjects was used in the development of the atlas. All diffusion MRI data collection was conducted using Turboprop, and spatial normalization was accomplished in a population-based fashion. A description of the contents of the atlas can be found in the Downloads link. NOTE: The files of the older IIT2 DTI Brain Template are still available. However, the new DTI template of the IIT Human Brain Atlas (v.3) is of superior quality and allows more accurate registration across subjects.

Proper citation: IIT Human Brain Atlas (RRID:SCR_009587) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/r-spit/

Group ICA (Independent Component Analysis) was used to generate spatial templates for 12 common resting-state networks in 62 typically-developing children, ages 9-15. They have made these available for those that will find them useful for masking and spatial template matching procedures. Basic demographic data on the sample is provided along with the protocol used to generate the templates.

Proper citation: resting-state pediatric imaging template (RRID:SCR_009647) Copy   

•   Source: SciCrunch Registry

https://dctd.cancer.gov/programs/cdp/organization/bbrb

BBRB supports medical discovery and precision medicine by providing leadership, tools, and resources to the biobanking community. Provides input on policy related to biobanking and supports the availability of biospecimens for research. Develops standardized procedures for biospecimen science and research; conducts and sponsors research on the effects of biospecimen preanalytical factors; leads and supports major scientific initiatives requiring high-quality biospecimens; and supports investigations into the ethical, legal, and social issues concerning biospecimen collection and use.

Proper citation: Biorepositories and Biospecimens Research Branch (RRID:SCR_013979) Copy   

•   Source: SciCrunch Registry

https://www.nihstrokenet.org/#annotations:4TlyYopcEeaUdC-3RQ97KQ

NIH network designed to follow and help conduct clinical trials and research studies investigating acute stroke treatment, stroke prevention, and stroke recovery and rehabilitation. Clinical trials are listed once they are reviewed, approved, and ready for volunteer recruitment.

Proper citation: NIH StrokeNet (RRID:SCR_014648) Copy   

•   Source: SciCrunch Registry

http://www.ucl.ac.uk/ploras#annotations:QXuC2C7REeaxtw-aEPo07Q

A research project investigating the difficulties of recovering language after stroke (aphasia). The overall aim of the study is to give future stroke survivors accurate predictions of their aphasia recovery by creating clinical tools and discerning why some patients recover from aphasia better than others.

Proper citation: Predicting Language Outcome and Recovery After Stroke (PLORAS) (RRID:SCR_014498) Copy   

•   Source: SciCrunch Registry

http://www.med.umich.edu/mgpc/

Center whose goal is to investigate signal transduction mechanisms regulating homeostasis and GI disorders. Their approach includes studies on genetics and gene regulation, cellular signaling pathways, receptors and ion channels.

Proper citation: University of Michigan Center for Gastrointestinal Research (RRID:SCR_015605) Copy   

•   Source: SciCrunch Registry

https://www.med.upenn.edu/cbica/captk/

Software platform for analysis of radiographic cancer images. Used as quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome.

Proper citation: Cancer Imaging Phenomics Toolkit (RRID:SCR_017323) Copy   

•   Source: SciCrunch Registry

http://hmri.info

Software toolbox for quantitative MRI in neuroscience and clinical research. Open source and flexible tool for qMRI data handling and processing. Allows estimation of high quality multi parameter qMRI maps followed by spatial registration in common space for statistical analysis.

Proper citation: hMRI-toolbox (RRID:SCR_017682) Copy   

•   Source: SciCrunch Registry

https://scienceofbehaviorchange.org/about/

Repository for behavioral science measures that have been validated or are in process of being validated in accordance with SOBC Experimental Medicine Approach.

Proper citation: Science of Behavior Change Research Network (RRID:SCR_017385) Copy   

•   Source: SciCrunch Registry

https://bruskolab.diabetes.ufl.edu/research/handel-i/

HANDEL-1 program to better understand normal human immune development by acquiring stromal and mucosal tissues from infant and pediatric organ donors and to create novel and essential dataset informing immune system development in collaborative research project that leverages shared access to various tissues in conjunction with existing HANDEL-P program that seeks to understand development of pancreas and islet microenvironment in early life.

Proper citation: Human Atlas of Neonatal Development and Early Life Immunity (RRID:SCR_021947) Copy   

•   Source: SciCrunch Registry

http://www.uchicagoddrcc.org

Center whose goals include fostering collaboration among basic and clinical investigators, facilitating the use of new technologies in the study of treatment of digestive diseases, and providing education and training for improved treatment and diagnosis.

Proper citation: University of Chicago Digestive Diseases Research Core Center (RRID:SCR_015601) Copy   

•   Source: SciCrunch Registry

http://www.bsc.gwu.edu/dpp/index.htmlvdoc

Multicenter clinical research study aimed at discovering whether modest weight loss through dietary changes and increased physical activity or treatment with the oral diabetes drug metformin (Glucophage) could prevent or delay the onset of type 2 diabetes in study participants. At the beginning of the DPP, all 3,234 study participants were overweight and had blood glucose levels higher than normal but not high enough for a diagnosis of diabetesa condition called prediabetes. In addition, 45 percent of the participants were from minority groups-African American, Alaska Native, American Indian, Asian American, Hispanic/Latino, or Pacific Islander-at increased risk of developing diabetes. The DPP found that participants who lost a modest amount of weight through dietary changes and increased physical activity sharply reduced their chances of developing diabetes. Taking metformin also reduced risk, although less dramatically. In the DPP, participants from 27 clinical centers around the United States were randomly divided into different treatment groups. The first group, called the lifestyle intervention group, received intensive training in diet, physical activity, and behavior modification. By eating less fat and fewer calories and exercising for a total of 150 minutes a week, they aimed to lose 7 percent of their body weight and maintain that loss. The second group took 850 mg of metformin twice a day. The third group received placebo pills instead of metformin. The metformin and placebo groups also received information about diet and exercise but no intensive motivational counseling. A fourth group was treated with the drug troglitazone (Rezulin), but this part of the study was discontinued after researchers discovered that troglitazone can cause serious liver damage. The participants in this group were followed but not included as one of the intervention groups. In the years since the DPP was completed, further analyses of DPP data continue to yield important insights into the value of lifestyle changes in helping people prevent type 2 diabetes and associated conditions. For example, one analysis confirmed that DPP participants carrying two copies of a gene variant, or mutation, that significantly increased their risk of developing diabetes benefited from lifestyle changes as much as or more than those without the gene variant. Another analysis found that weight loss was the main predictor of reduced risk for developing diabetes in DPP lifestyle intervention group participants. The authors concluded that diabetes risk reduction efforts should focus on weight loss, which is helped by increased exercise.

Proper citation: Diabetes Prevention Program (RRID:SCR_001501) Copy   

•   Source: SciCrunch Registry

http://www.radiology.ucsf.edu/cind

Biomedical technology research center that develops and validates new imaging methods for detecting brain abnormalities in neurodegenerative diseases, including Alzheimer's disease, vascular dementia, frontotemporal dementia, Parkinson's disease, as well as epilepsy, depression, and other conditions associated with nerve loss in the brain. As people around the globe live longer, the impact of neurodegenerative diseases is expected to increase further with dire social and economical consequences for societies if no effective treatments are developed soon. The development at CIND is aimed to improve magnetic resonance imaging (MRI). The ultimate goal of the scientific program is to identify imaging markers that improve accuracy in diagnosing neurodegenerative diseases at early stages, achieve more reliable prognoses of disease progression, and facilitate the discovery of effective treatment interventions. In addition to addressing the general needs for studying neurodegenerative diseases, another focus of CIND concerns brain diseases associated with military service and war combat, such as post traumatic stress disorder (PTSD), brain trauma, gulf war illness and the long-term effects of these conditions on the mental health of veterans. The symbiosis between CIND and the Veterans Administration Medical Center in San Francisco makes this program uniquely suited to serve military veterans.

Proper citation: Center for Imaging of Neurodegenerative Diseases (RRID:SCR_001968) Copy   

•   Source: SciCrunch Registry