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http://openfurther.org/

Data and knowledge management infrastructure for the new Center for Clinical and Translational Science (CCTS) at the University of Utah. This clinical cohort search tool is used to search across the University of Utah clinical data warehouse and the Utah Population Database for people who satisfy various criteria of the researchers. It uses the i2b2 front end but has a set of terminology servers, metadata servers and federated query tool as the back end systems. FURTHeR does on-the-fly translation of search terms and data models across the source systems and returns a count of results by unique individuals. They are extending the set of databases that can be queried.

Proper citation: FURTHeR (RRID:SCR_006383) Copy   

•   Source: SciCrunch Registry

http://www.h-outcomes.com/

Software application that supports the execution of multivariable prediction models with patient-specific characteristics so that personalized estimates of outcomes, often as a function of alternative treatments, can be generated within the routine flow of patient care. This can support evidence-based, shared medical decision-making to improve the safety, outcomes and cost-effectiveness of care. The current application is in the setting of generating individualized informed consent documents for PCI. However, the tool can support that translation of novel biomarkers, genetics and pharmacogenomic interactions into clinical care. The platform gives healthcare providers instantaneous access to the latest clinical prediction models coupled with rich visualization tools. These models may come from national organizations, outcomes researchers or a specific institution. In addition to decision support applications, it can be used to rapidly create personalized educational materials, patient letters, informed consent documents and a broad array of other items that can help elevate the quality of healthcare delivery.

Proper citation: ePRISM (RRID:SCR_006386) Copy   

•   Source: SciCrunch Registry

http://ctakes.apache.org

An open-source natural language processing system for information extraction from electronic medical record clinical free-text. This is a system through which one creates one or more pipelines to process clinical notes and to identify clinical named entities. It processes clinical notes, identifying types of clinical named entities, drugs, diseases/disorders, signs/symptoms, anatomical sites and procedures. Each named entity that is found is given attributes for the text span, the ontology mapping code, the context (family history of, current, unrelated to patient), and negated/not negated. cTAKES is built on the UIMA framework. cTAKES 2.5 does not provide a GUI of its own for installation or processing. The cTAKES documentation shows how to use the GUIs provided by the UIMA framework, and how to run cTAKES from a command line. Before using cTAKES you need to know that cTAKES does not provide any mechanisms of its own to handle patient data securely. It is assumed that cTAKES is installed on a system that can process patient data, or that any data being processed by cTAKES has already been through a deidentification step in order to comply with any applicable laws. The tool has been developed and deployed at Mayo Clinic since early 2000.

Proper citation: cTAKES (RRID:SCR_006379) Copy   

•   Source: SciCrunch Registry

http://www.hopkinsguides.com/

Authoritative, need-to-know information from Johns Hopkins available for mobile devices and the web. Guides provide up to date information and break down details of diagnosis, drug indications, dosing, pharmacokinetics, side effects and interactions, pathogens, management, and vaccines into frequently-updated, quick-read entries. Available for infectious disease (ABX), diabetes, and HIV.

Proper citation: Johns Hopkins Point of Care Guides (RRID:SCR_006314) Copy   

•   Source: SciCrunch Registry

http://www.patientcrossroads.com/

A trusted third-party gatekeeper of patient data from participants in a rare disease ecosystem, collecting and managing the information in a scalable, cost-effective manner. Each patient registry provides critical disease knowledge which makes that disease easier to study, increasing the probability a treatment can be developed. PatientCrossroads takes a network approach to patient registry programs. Unlike companies that merely sell registry software, we offer a full range of administration, management, and genetic curation services. What does this consolidated, patient-centric approach to patient registries mean? * Patients can more easily find registries and provide their valuable data (including locations of blood and tissue samples as well as reports of diagnoses, disease symptoms, treatment usage, and lifestyle activities) * Patients can be confident in the privacy of their de-identified data and the knowledge that PatientCrossroads does not sell patient data * Researchers and pharmaceutical companies have a larger, more easily accessible pool of potential patients for research studies and clinical trials targeting specific rare diseases * Pharmaceutical companies can collect post-market surveillance data in a more scalable and cost-effective manner * Rare disease advocacy and research foundations can more easily organize their global patient populations for inclusion in trials and studies

Proper citation: PatientCrossroads (RRID:SCR_006279) Copy   

•   Source: SciCrunch Registry

http://univ.cns.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 19,2021.Designed with the neurosurgeon in mind, this portal contains everything you need to acquire new skills and techniques, including courses, an image database, and the world''s largest neurosurgical wiki reference - NeuroWiki. The new University of Neurosurgery includes: * More than 40 new online courses - in all neurosurgical subspecialties. * Archived webinars. * Lectures from the CNS Annual Meetings. * Neurosurgical image database. We are continuing to add new content - check back often.

Proper citation: Congress of Neurological Surgeons University of Neurosurgery (RRID:SCR_006309) 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

http://radiology.arizona.edu/CGRI/

Biomedical technology resource center that develops new gamma-ray imaging instruments and techniques that yield substantially improved spatial and temporal resolutions. The Center makes its imagers and expertise available to a wide community of biomedical and clinical researchers through collaborative and service-oriented interactions. The collaborative research applies these new imaging tools to basic research in functional genomics, proteomics, cancer, cardiovascular disease and cognitive neuroscience, and to clinical research in tumor detection and other selected topics. There are five core research projects: * Detector technology research and development * Reconstruction algorithms and system modeling * Data acquisition, signal processing, and system development * Image-quality assessment and system optimization * Techniques for molecular imaging

Proper citation: Center for Gamma Ray Imaging (RRID:SCR_001384) Copy   

•   Source: SciCrunch Registry

http://c-path.org/programs/camd/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 8, 2022. Consortium developing new technologies and methods to accelerate the development and review of medical products for neurodegenerative diseases. It is focused on accelerating drug development for patients with chronic neurodegenerative disease, namely, Alzheimer's disease (AD) and Parkinson's disease (PD), by advancing drug development tools for evaluating drug efficacy, conducting clinical trials, and streamlining the process of regulatory review. The consortium focuses on sharing precompetitive patient-level data from the control arms of legacy clinical trials, developing new tools to be submitted to the regulatory agencies, and developing consensus data standards. CAMD has the following areas of focus: (1) qualification of biomarkers, (2) development of common data standards, (3) creation of integrated databases for clinical trials data, and (4) development of quantitative model-based tools for drug development. Regulatory milestones include a qualification opinion with EMA for the use of low baseline hippocampal volume for patient enrichment in pre-dementia trials, and most recently, positive regulatory decisions from the FDA and EMA for the use of a clinical trial simulation tool to aid in trials for mild to moderate stages of AD., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: CAMD (RRID:SCR_001389) Copy   

•   Source: SciCrunch Registry

http://www.brain-dynamics.net/

The Brain Dynamics Centre (BDC) is a network of centers and units. It achieves a unique exploration of the healthy brain and disorders of brain function. It translates these insights into new ways to tailor treatments to the individual. There approach is: "integrative neuroscience" - bringing together clinical observations, theory, and modern imaging technologies. And it's theoretical framework derives from linking physiology, psychology and evolution. Additionally, BDC also actively researches ADHD and conduct disorder, stress and trauma-related problems, depression and anxiety, anorexia nervosa, psychosis (including early onset) and conversion disorders. The research facilities DBC include assessment, rooms, two cognition-brain function laboratories, genotyping and an MRI Suite with 1.5 and 3T GE systems. BDC is the coordinating site for an international network - BRAINnet. It has over 180 members, and coordinates access to the first standardized database on the human brain for scientific purposes: Brain Resource International Database.

Proper citation: Brain Dynamics Centre (RRID:SCR_001685) Copy   

•   Source: SciCrunch Registry

http://dial.mc.duke.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. The Duke Image Analysis Laboratory (DIAL) is committed to providing comprehensive imaging support in research studies and clinical trials to various agencies. The capabilities of the lab include protocol development, site training and certification, and image archival and analysis for a variety of modalities including magnetic resonance imaging, magnetic resonance spectroscopy, computed tomography and nuclear medicine. DIAL uses the latest technologies to analyze Magnetic Resonance Imaging (MRI) data sets of the brain. Currently the lab is engaged in measurement of the hippocampus, amygdala, caudate, ventricular system, and other brain regional volumes. Each of these techniques have undergone a rigorous validation process. The measurements of brain structures provide a useful means of non-invasively testing for changes in the brain of the patient. Changes over time in the brain can be detected, and evaluated with respect to the treatment that the patient is receiving. Magnetic Resonance Spectroscopy (MRS) allows DIAL to obtain an accurate profile of the chemical content of the brain. This sensitive technique can detect small changes in the metabolic state of the brain; changes that vary in response to administration of therapeutic agents. The ability to detect these subtle shifts in brain chemistry allows DIAL to identify changes in the brain with more sensitivity than allowed by image analysis. In this respect, NMR spectroscopy can provide early detection of changes in the brain, and serves to compliment the data obtained from image analysis. Additionally, DIAL also contains SQUID (Scalable Query Utility and Image Database). It is an image management system developed to facilitate image management in research and clinical trials: SQUID offers secure, redundant image storage and organizational functions for sorting and searching digital images for a variety of modalities including MRI, MRS, CAT Scan, X-Ray and Nuclear Medicine. SQUID can access images directly from DUMC scanners. Data can also be loaded via DICOM CDs, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Duke University Medical Center: Duke Image Analysis Laboratory (RRID:SCR_001716) Copy   

•   Source: SciCrunch Registry

http://hopkinsneuro.org/research/jhu_nimh/

The Johns Hopkins NIMH Center is comprised of an interdisciplinary research team who has pooled their talents to study the nature of HIV-associated neurocognitive disorders (HAND). Their aim is to translate discoveries of the pathophysiological mechanisms into novel therapeutics for HAND. Objectives * To integrate aspects of ongoing research in HAND and SIV encephalitis * Develop high-throughput and screening assays for identifying novel therapeutic compounds * Use proteomics and lipidomics approaches to indentifying surrogate markers of disease activity * Disseminate information and education about HAND through existing and new educational systems, including the JHU AIDS Education Training Center and the JHU Center for Global Clinical Education * Facilitate the entry of new investigators into Neuro-AIDS research, and to catalyze new areas of research, particularly where relevant for drug discovery or the development of validated surrogate markers

Proper citation: Johns Hopkins NIMH Research Center Novel Therapeutics of HIV-associated Cognitive Disorders (RRID:SCR_001891) Copy   

•   Source: SciCrunch Registry

https://ftp.ncbi.nlm.nih.gov/pub/mhc/mhc/Final%20Archive/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 23, 2019 Database was open, publicly accessible platform for DNA and clinical data related to human Major Histocompatibility Complex (MHC). Data from IHWG workshops were provided as well., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: dbMHC (RRID:SCR_002302) Copy   

•   Source: SciCrunch Registry

http://www.clsi.org/

A not-for-profit membership organization that brings together the global laboratory community to foster excellence in laboratory medicine by facilitating the development of clinical laboratory testing standards based on input from and consensus among industry, government, and health care professionals. CLSI is setting the standard for quality in clinical laboratory testing around the world.

Proper citation: Clinical and Laboratory Standards Institute (RRID:SCR_002382) Copy   

•   Source: SciCrunch Registry

http://bioinf.uta.fi/base_root/

IDbases are locus-specific databases for immunodeficiency-causing mutations. Our aim is to establish database for every immunodeficiency or provide links to those maintained elsewhere. IDbases contain in addition to gene mutation, also information about clinical presentation. Information has been collected from literature as well as received directly from researchers. It would be most glad if those analyzing mutations would send their information by using the interactive web submission available in each database. A number of articles have been published related to IDbases. IDbases are curated and distributed with proprietary MUTbase software suite.

Proper citation: IDbases (RRID:SCR_002378) Copy   

•   Source: SciCrunch Registry

https://pdbp.ninds.nih.gov

Common data management resource and web portal to promote discovery of Parkinson's Disease diagnostic and progression biomarker candidates for early detection and measurement of disease progression. PDBP will serve as multi-faceted platform for integrating existing biomarker efforts, standardizing data collection and management across these efforts, accelerating discovery of new biomarkers, and fostering and expanding collaborative opportunities for all stakeholders.

Proper citation: Parkinson’s Disease Biomarkers Program Data Management Resource (PDBP DMR) (RRID:SCR_002517) Copy   

•   Source: SciCrunch Registry

http://www.aetionomy.eu/

Consortium founded to establish mechanism-based taxonomies for Alzheimer's and Parkinson's disease and other neurodegenerative disorders (NDD), with the goal of facilitating development of more effective and targeted treatments. To do this, the consortium collects and analyzes data to: * Create new ways to combine underutilized data currently available in the literature, public databases, and from private companies * Determine how to dynamically organize and structure different types of knowledge about NDD * Determine how to apply this knowledge to construct new patient group classification * Identify correlations between disease features at molecular, tissue or organ-specific, and clinical levels * Identify sub-groups of patients based on the molecular cause of their disease, as opposed to the nature and location of their symptoms * Deliver data, tools, and recommendations for the biomedical community in the treatment of NDD A mechanism-based taxonomy is hoped to advance the: # Description and organization of the indication-specific data # Linking of data to disease models, based on causal and correlative relationships The expected outcome of AETIONOMY is a new NDD taxonomy system that distinguishes mixed pathologies, allowing for new features or classes to be added into the taxonomy, all with the goal of aiding drug and biomarker discovery.

Proper citation: AETIONOMY (RRID:SCR_000232) Copy   

•   Source: SciCrunch Registry

http://toc.lbg.ac.at/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. The projected cluster includes the LBIs for Applied Cancer Research, Clinical Oncology and Photodynamic Therapy, Gynecology and Gynecologic Oncology, Stem Cell Transplantation and Surgical Oncology. The aim of the projected cluster Translational Oncology is the cooperative investigation of genetic and molecular biological characteristics of the tumor cells involved in minimal residual disease (MRD) in vitro and translation of the experimental and diagnostic results into the clinical practice involving therapeutic modalities with the newest generation of antitumoral drugs. Minimal residual disease is the designation for the occurrence of a low number of tumor cells remaining clinically undetected following curative therapy that give rise to tumor relapses. MRD is a central question in cancer therapy, since a major subpopulation of patients which underwent curative resection and therapy ultimately relapse and would have received more aggressive adjuvant therapy, provided that residual disease had been clearly proven. Otherwise low-risk patients would have not been treated aggressively in an adjuvant setting. MRD can be detected by methods in bone marrow or by extremely sensitive PCR (polymerase-chain-reaction)-based methods in peripheral blood. PCR-based methods allow for the characterization of tumor-specific gene expression in circulating tumor cells and thereby provide additional information in regard to malignity of cells and prognosis. The different participating institutions have extensive experience in patient care, organization of clinical studies and laboratory investigation. In particular, expert knowledge in stem cell transplantation and histological detection of MRD, multicentric clinical testing of new anticancer drugs, specialized treatment of various selected tumor entities such as neuroendocrine tumors, gene expression analysis of circulating tumor cells and tumor signatures, and in vitro characterization of chemosensitivity as well as tumor cell biology have been acquired at the individual LBIs in the past and are complementary to each other to be combined in a larger cluster structure. The detection of circulating tumor cells will be supported by ongoing EU (OVCAD OVarian CAncer Diagnosis) and GenAU projects aiming at identification of ovarian cancer cells in the blood. The assessment of methylated DNA sequences (suppressor genes) in peripheral blood as an indicator of MRD can be performed with the help of OncoLab Diagnostics GmbH. Cooperative action in this cluster, using a common tumor bank/clinical data collection and the combined clinical and experimental efforts are the base for the execution of the presented MRD project.

Proper citation: Ludwig Boltzmann Cluster Translationale Onkologie (RRID:SCR_000020) Copy   

•   Source: SciCrunch Registry

http://www.epilepsygenetics.eu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 16,2023. Group of clinical care and epilepsy research centers who are committed to improving the lives of people with epilepsy through an understanding of the genetics of epilepsy. The consoritum was in an effort to speed discovery to epilepsy genetics by pooling the resources of several research centres., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: EPIGEN (RRID:SCR_000093) Copy   

•   Source: SciCrunch Registry

http://www.cdisc.org/

A global, open, multidisciplinary, non-profit organization that has established standards to support the acquisition, exchange, submission and archive of clinical research data and metadata. Its mission is to develop and support global, platform-independent data standards that enable information system interoperability to improve medical research and related areas of healthcare. CDISC standards are vendor-neutral, platform-independent and freely available via the CDISC website.

Proper citation: Clinical Data Interchange Standards Consortium (RRID:SCR_000219) Copy   

•   Source: SciCrunch Registry