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http://www.ncbi.nlm.nih.gov/gtr/

Central location for voluntary submission of genetic test information by providers including the test''s purpose, methodology, validity, evidence of the test''s usefulness, and laboratory contacts and credentials. GTR aims to advance the public health and research into the genetic basis of health and disease. GTR is accepting registration of clinical tests for Mendelian disorders, complex tests and arrays, and pharmacogenetic tests. These tests may include multiple methods and may include multiple major method categories such as biochemical, cytogenetic, and molecular tests. GTR is not currently accepting registration of tests for somatic disorders, research tests or direct-to-consumer tests.

Proper citation: Genetic Testing Registry (RRID:SCR_005565) Copy   

•   Source: SciCrunch Registry

http://www.matrics.ucla.edu/index.html

Cognitive deficits -- including impairments in areas such as memory, attention, and executive function -- are a major determinant and predictor of long-term disability in schizophrenia. Unfortunately, available antipsychotic medications are relatively ineffective in improving cognition. Scientific discoveries during the past decade suggest that there may be opportunities for developing medications that will be effective for improving cognition in schizophrenia. The NIMH has identified obstacles that are likely to interfere with the development of pharmacological agents for treating cognition in schizophrenia. These include: (1) a lack of a consensus as to how cognition in schizophrenia should be measured; (2) differing opinions as to the pharmacological approaches that are most promising; (3) challenges in clinical trial design; (4) concerns in the pharmaceutical industry regarding the US Food and Drug Administration''s (FDA) approaches to drug approval for this indication; and (5) issues in developing a research infrastructure that can carry out clinical trials of promising drugs. The MATRICS program will bring together representatives of academia, industry, and government in a consensus process for addressing all of these obstacles. Specific goals of the NIMH MATRICS are: * To catalyze regulatory acceptance of cognition in schizophrenia as a target for drug registration. * To promote development of novel compounds to enhance cognition in schizophrenia. * Leverage economic research power of industry to focus on important but neglected clinical targets. * Identify lead compounds and if deemed feasible, support human proof of concept trials for cognition in schizophrenia.

Proper citation: MATRICS - Measurement And Treatment Research to Improve Cognition in Schizophrenia (RRID:SCR_005644) Copy   

•   Source: SciCrunch Registry

https://neurobot.incf.org

Software tool for data management in clinical studies to improve care for patients with Traumatic Brain Injury (TBI). Used to search and find study variables with the associated information and export study data for further analysis.

Proper citation: INCF-Neurobot (RRID:SCR_017004) Copy   

•   Source: SciCrunch Registry

https://prismclinical.com/

Provides Prism softwares and services that integrate advanced imaging into the clinical workflow for brain mapping from acquisition through processing, visualization, and export to PACS. Prism integrates functional MRI, diffusion MRI, perfusion, MR spectroscopy, and PET/CT into a unified workflow for diagnosis and treatment planning in brain disorders. Processing is also available as a cloud deployed service, Prism Serve. Research support includes import/export for imaging and derived quantitative data in both DICOM and research formats such as AFNI and Trackviz.

Proper citation: Prism Clinical Imaging (RRID:SCR_016977) Copy   

•   Source: SciCrunch Registry

https://t1dexchange.org/research/biobank/

Collection of biological samples linked to participant medical data from individuals living with type 1 diabetes. Unifies samples and data from eight different clinical studies related to type 1 diabetes.

Proper citation: T1D Exchange Biobank (RRID:SCR_017195) Copy   

•   Source: SciCrunch Registry

https://glomcon.org

Consortium to bring together clinicians, pathologists, researchers, and biotech innovators to create scalable network of stakeholders interested in helping patients with glomerular kidney disease. Makes collective expertise of its members available for discussion of individual cases, provides infrastructure for biomarker studies, enables genomic research, and facilitates clinical trials.

Proper citation: Glomerular Disease Study & Trial Consortium (RRID:SCR_017264) Copy   

•   Source: SciCrunch Registry

https://www.daqcord.org/

Software tool for practical self assessment and reporting method for clinical research studies, to capture key information about data acquisition and quality control measures. Linked to dataset so that potential research collaborators can determine if data meets their needs and expectations.

Proper citation: DAQCORD (RRID:SCR_017395) Copy   

•   Source: SciCrunch Registry

https://bioconductor.org/packages/TCGAbiolinks/

Software R Bioconductor package for integrative analysis with TCGA data.TCGAbiolinks is able to access National Cancer Institute Genomic Data Commons thorough its GDC Application Programming Interface to search, download and prepare relevant data for analysis in R.

Proper citation: TCGAbiolinks (RRID:SCR_017683) Copy   

•   Source: SciCrunch Registry

https://intbir.nih.gov/

Project whose goal is to improve health care and lessen the global burden of TBI through the discovery of causal relationships between treatments and clinically meaningful outcomes. InTBIR seeks to encourage well-designed, hypothesis-driven studies that include the collection of high quality data followed by rigorous statistical analysis.

Proper citation: International Initiative for Traumatic Brain Injury Research (RRID:SCR_016237) Copy   

•   Source: SciCrunch Registry

http://amp.pharm.mssm.edu/l1000fwd/

Web application that provides interactive visualization of drug and small-molecule induced gene expression signatures. L1000FWD enables coloring of signatures by different attributes such as cell type, time point, concentration, as well as drug attributes such as MOA and clinical phase.

Proper citation: L1000 Fireworks Display (RRID:SCR_016175) Copy   

•   Source: SciCrunch Registry

https://www.nimhgenetics.org/

Stores biosamples, genetic, pedigree and clinical data collected in designated NIMH-funded human subject studies. RGR database likewise links to other repositories holding data from same subjects, including dbGAP, GEO and NDAR. Allows to access these data and biospecimens (e.g., lymphoblastoid cell lines, induced pluripotent cell lines, fibroblasts) and further expand genetic and molecular characterization of patient populations with severe mental illness.

Proper citation: NIMH Repository and Genomics Resources (NRGR) (RRID:SCR_016318) Copy   

•   Source: SciCrunch Registry

http://conp.ca/

Web interface that facilitates open science for neuroscience community by simplifying global access to and sharing of datasets and tools. Portal internalizes typical data cycle of research project, beginning with data acquisition, followed by data processing with published tools, and ultimately publication of results with link to original dataset. Platform to form interactive network of collaborations in brain research, interdisciplinary student training, international partnerships, clinical translation and open publishing. Provides unified interface to Canadian neuroscience research community. Open neuroscience research with sharing of both data and methods, to create large-scale databases, development of standards for sharing, facilitation of advanced analytic strategies, open dissemination to global community of neuroscience data and methods, and establishment of training programs for next generation of computational neuroscience researchers.

Proper citation: Canadian Open Neuroscience Platform (RRID:SCR_016433) Copy   

•   Source: SciCrunch Registry

https://www.denovosoftware.com/?gclid=EAIaIQobChMI36rn3-Dd3AIV2ud3Ch27lw2oEAAYASAAEgLbRvD_BwE

Software tool for flow and image cytometry data analysis by De Novo Software company.

Proper citation: FCS Express (RRID:SCR_016431) Copy   

•   Source: SciCrunch Registry

https://www.gvkbio.com/

Collection of databases with standalone databases, which gives opportunity for customers to integrate the data into their internal tools and databases, as well as online databases, that are available to the customers from a dedicated website where an individual can query and export the data in the selected format. The standalone database topics include medicinal chemistry, drugs and target class based compounds. The online databases are comprised of three major compilations: GVK BIO Online Structure Activity Relation Database (GOSTAR), GVK BIO Biomarker Database (GOBIOM), and Clinical Trial Outcome Database (CTOD).

Proper citation: GVKBIO databases (RRID:SCR_014893) 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

http://www.imi-getreal.eu/

Consortium that aims to improve the efficiency of the medicine development process by better incorporating estimates of relative effectiveness into drug development and to enrich decision-making by regulatory authorities and health technology assessment (HTA) bodies through: * Bringing together regulators, HTA bodies, academics, companies, patients and other societal stakeholders; * Assessing existing processes, methodologies, and key research issues; * Proposing innovative (and more pragmatic) trial designs and assessing the value of information; * Proposing and testing innovative analytical and predictive modelling approaches; * Assessing operational, ethical, regulatory issues and proposing and testing solutions; * Creating new decision making frameworks, and building open tools to allow for the evaluation of development programs and use in the assessment of the value of new medicines; * Sharing and discussing deliverables with, among others, Pharmaceutical companies, regulatory authorities, HTA / reimbursement agencies, clinicians and patient organizations; * Developing training activities for researchers, decision makers and societal stakeholders in the public and private sector in order to increase knowledge about various aspects of relative effectiveness. The expected impact is that it will contribute to the knowledge base, particularly to inform clinical decision making and improve the efficiency of the R&D process. GETREAL will help to generate a consensus on best practice in the timing, performance and use of real life clinical studies in regulatory and reimbursement decision-making. It will also help to create a strong platform for the communication of results and for future discussions in this important area.

Proper citation: GetReal (RRID:SCR_003862) Copy   

•   Source: SciCrunch Registry

http://www.asiancancerresearchgroup.org/

An independent, not-for-profit consortium to accelerate research, and improve treatment for patients affected with the most commonly-diagnosed cancers in Asia by generating a genomic data resource for the most prevalent cancers in Asia. ACRG is focusing its initial efforts on Asian liver, gastric and lung cancers. Goals * Generate comprehensive genomics data sets for Asia-prevalent cancers * Conduct all research under good clinical practices and in accordance with local laws * Uncover key mutations and pathways for developing targeted therapies * Discover molecular tumor classifiers for patient stratification * Discover prognostic markers to identify high-risk patients * Freely share resulting raw data with scientific community to empower researchers globally and enable development of new diagnostics and medicines * Publish data analysis results jointly in prominent scientific journals Over the next two years, Lilly, Merck and Pfizer have committed to create an extensive pharmacogenomic cancer database that will be composed of data from approximately 2,000 tissue samples from patients with lung and gastric cancer that will be made publicly available to researchers and, over time, further populated with clinical data from a longitudinal analysis of patients. Comparison of the contrasting genomic signatures of these cancers could inform new approaches to treatment. Lilly has assumed responsibility for ultimately providing the data to the research public through an open-source concept managed by Lilly''''s Singapore research site. Moreover, Lilly, Merck and Pfizer will each provide technical and intellectual expertise. One dataset can be found at http://gigadb.org/dataset/100034

Proper citation: Asian Cancer Research Group (RRID:SCR_004001) Copy   

•   Source: SciCrunch Registry

http://humanconnectome.org/connectome/connectomeDB.html

Data management platform that houses all data generated by the Human Connectome Project - image data, clinical evaluations, behavioral data and more. ConnectomeDB stores raw image data, as well as results of analysis and processing pipelines. Using the ConnectomeDB infrastructure, research centers will be also able to manage Connectome-like projects, including data upload and entry, quality control, processing pipelines, and data distribution. ConnectomeDB is designed to be a data-mining tool, that allows users to generate and test hypotheses based on groups of subjects. Using the ConnectomeDB interface, users can easily search, browse and filter large amounts of subject data, and download necessary files for many kinds of analysis. ConnectomeDB is designed to work seamlessly with Connectome Workbench, an interactive, multidimensional visualization platform designed specifically for handling connectivity data. De-identified data within ConnectomeDB is publicly accessible. Access to additional data may be available to qualified research investigators. ConnectomeDB is being hosted on a BlueArc storage platform housed at Washington University through the year 2020. This data platform is based on XNAT, an open-source image informatics software toolkit developed by the NRG at Washington University. ConnectomeDB itself is fully open source.

Proper citation: ConnectomeDB (RRID:SCR_004830) Copy   

•   Source: SciCrunch Registry

http://alzheimers.med.umich.edu/

An Alzheimer's disease center which aims to conduct and promote research on Alzheimer's disease and enhance public and professional understanding of dementia through education and outreach efforts. The MADC promotes clinical research on memory and aging which involves the direct use of research volunteers, biomarkers, and other clinical data collected through the University of Michigan Memory and Aging Project.

Proper citation: Michigan Alzheimer's Disease Center (RRID:SCR_008773) Copy   

•   Source: SciCrunch Registry

http://clinicaltrials.gov/ct2/show/study/NCT00248638

Multi-center, double-blind, placebo-controlled, intent-to-treat Phase III trial, designed to determine the effect of parenteral glutamine (GLN) dipeptide on important clinical outcomes in patients requiring surgical intensive care unit (SICU) care and parenteral nutrition (PN) after cardiac, vascular, or intestinal surgery. Patients who required PN and SICU care will receive either standard glutamine (GLN)-free PN (STD-PN) or isocaloric, isonitrogenous alanyl-glutamine dipeptide (AG)-PN until enteral feedings are established. The study will determine whether AG-PN decreases hospital mortality, nosocomial infection and other important indices of morbidity and will obtain mechanistically relevant observational data in the subjects on whether AG-PN a) increases serial blood concentrations of glutathione (GSH), heat shock proteins (HSP)-70 and -27, and glutamine; b) decreases the serum presence of the bacterial products flagellin and lipopolysaccharide (LPS) and the adaptive immune response to these mediators; and c) improves key indices of innate and adaptive immunity.

Proper citation: Efficacy and Mechanisms of Glutamine Dipeptide in the Surgical Intensive Care Unit (RRID:SCR_006806) Copy   

•   Source: SciCrunch Registry