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Database and central repository for genetic, genomic, molecular and cellular phenotype data and clinical information about people who have participated in pharmacogenomics research studies. The data includes, but is not limited to, clinical and basic pharmacokinetic and pharmacogenomic research in the cardiovascular, pulmonary, cancer, pathways, metabolic and transporter domains. PharmGKB welcomes submissions of primary data from all research into genes and genetic variation and their effects on drug and disease phenotypes. PharmGKB collects, encodes, and disseminates knowledge about the impact of human genetic variations on drug response. They curate primary genotype and phenotype data, annotate gene variants and gene-drug-disease relationships via literature review, and summarize important PGx genes and drug pathways. PharmGKB is part of the NIH Pharmacogenomics Research Network (PGRN), a nationwide collaborative research consortium. Its aim is to aid researchers in understanding how genetic variation among individuals contributes to differences in reactions to drugs. A selected subset of data from PharmGKB is accessible via a SOAP interface. Downloaded data is available for individual research purposes only. Drugs with pharmacogenomic information in the context of FDA-approved drug labels are cataloged and drugs with mounting pharmacogenomic evidence are listed.
Proper citation: PharmGKB (RRID:SCR_002689) Copy
Non-profit organization focused on imaging technology that is dedicated to advancing the diagnosis and treatment of mental illness and brain injury. MRN consists of an interdisciplinary association of scientists located at universities, national laboratories and research centers around the world and is focused on imaging technology and its emergence as an integral element of neuroscience investigation. The MRNs initial plan called for the building of state-of-the-art magnetic resonance imaging (MRI) and magnetoencephalogram (MEG) neuroimaging systems to be applied to studies of mental illness. This important task was carried out by Minds initial collaborators: Massachusetts General Hospitals Martinos Biomedical Imaging Center (Harvard and MIT), the University of Minnesota, the University of New Mexico, and Los Alamos National Laboratory. Since both the Network and the mission have expanded beyond building neuroimaging tools, a comprehensive understanding of mental illness and more fundamental and systematic understanding of the brain, is possible. The MRN Mobile Imaging system is a custom designed one-of-a-kind facility.
Proper citation: Mind Research Network (RRID:SCR_002925) Copy
An American global biotechnology company that manufactures drug therapies for cancer and inflammatory disorders. The company's major products are Thalomid (thalidomide), which is approved for the acute treatment of the cutaneous manifestations of moderate to severe erythema nodosum leprosum (ENL), as well as in combination with dexamethasone for patients with newly diagnosed multiple myeloma, and Revlimid (lenalidomide), for which the company has received FDA and EMA approval in combination with dexamethasone for the treatment of multiple myeloma patients who have received at least one prior therapy. Revlimid is also approved in the United States for the treatment of patients with transfusion-dependent anemia due to Low- or Intermediate-1-risk Myelodysplastic syndromes (MDS) associated with a deletion 5q cytogenetic abnormality with or without additional cytogenetic abnormalities. Both Thalomid and Revlimid are sold through proprietary risk-management distribution programs to ensure safe and appropriate use of these pharmaceuticals. Vidaza is approved for the treatment of patients with MDS. Celgene also receives royalties from Novartis Pharma AG on sales of the entire Ritalin family of drugs, which are widely used to treat Attention Deficit Hyperactivity Disorder (ADHD). (Adapted from Wikipedia) There are numerous clinical trials at major medical centers using compounds from Celgene. Investigational compounds are being studied for patients with incurable hematological and solid tumor cancers, including multiple myeloma, myelodysplastic syndromes, chronic lymphocyte leukemia (CLL), non-Hodgkin's lymphoma (NHL), glioblastoma, and ovarian, pancreatic and prostate cancer.
Proper citation: Celgene (RRID:SCR_002955) Copy
This center provides routine behavioral/cognitive testing of mice with phenotypes that are expressed as a consequence of alterations at the level of gene function, and that are relevant to basic neuroscience and to animal models of neurological and psychiatric disorders. Current Research Behavioral testing within the center involves a collaborative component in which mice provided by users are assessed for behavioral/cognitive functions. All research includes behavioral assessment of a variety of genetically altered mice provided by users. Services Provided The objective of the center is to provide a link between genetic and molecular analysis of neural function and the study of integrative systems and clinical conditions through behavioral assessment of animal models, and mouse behavioral phenotypes generated by genetic modification. Sponsors: This resource is supported by the National Center of Research Resources (Grant Number: P40 RR017688).
Proper citation: Neurogenetics and Behavior Center (RRID:SCR_002851) Copy
Computational biology research at Memorial Sloan-Kettering Cancer Center (MSKCC) pursues computational biology research projects and the development of bioinformatics resources in the areas of: sequence-structure analysis; gene regulation; molecular pathways and networks, and diagnostic and prognostic indicators. The mission of cBio is to move the theoretical methods and genome-scale data resources of computational biology into everyday laboratory practice and use, and is reflected in the organization of cBio into research and service components ~ the intention being that new computational methods created through the process of scientific inquiry should be generalized and supported as open-source and shared community resources. Faculty from cBio participate in graduate training provided through the following graduate programs: * Gerstner Sloan-Kettering Graduate School of Biomedical Sciences * Graduate Training Program in Computational Biology and Medicine Integral to much of the research and service work performed by cBio is the creation and use of software tools and data resources. The tools that we have created and utilize provide evidence of our involvement in the following areas: * Cancer Genomics * Data Repositories * iPhone & iPod Touch * microRNAs * Pathways * Protein Function * Text Analysis * Transcription Profiling
Proper citation: Computational Biology Center (RRID:SCR_002877) Copy
ISCoS promotes the highest standard of care in the practice of spinal cord injury for men, women and children throughout the world. Through its medical and multi disciplinary team of Professionals ISCoS endeavours to foster education, research and clinical excellence. ISCoS has a membership of over 1,000 Clinicians and Scientists from 87 countries. They regularly update their knowledge at the Annual Scientific Meeting held in a different country each year. Goals of ISCoS: :- Serve as an international impartial, non-political and non-profit making association whose purpose is to study all problems relating to traumatic and non-traumatic lesions of the spinal cord. This includes causes, prevention, basic and clinical research, medical and surgical management, clinical practice, education, rehabilitation and social reintegration. This society will function in close collaboration with other national and international bodies, thereby encouraging the most efficient use of available resources. :- Provide a scientific exchange among its members and others by collecting and disseminating information through publications, correspondence, exhibits, regional and international seminars, symposia, conferences and otherwise. :- Advise, encourage, promote and when requested, assist in efforts to co-ordinate or guide research, development and evaluation activities related to spinal cord lesions throughout the world. :- Advise, encourage, guide and support the efforts of those responsible for the care of patients involved and when requested, correlate these activities throughout the world. :- Advise, encourage, guide and support the efforts of those responsible for the education and training of medical professionals and professionals allied to medicine and when requested, correlate these activities throughout the world.
Proper citation: International Spinal Cord Society (RRID:SCR_002908) Copy
http://www.crdamc.amedd.army.mil/behav-health/strong-star.aspx
A multidisciplinary and multi-institutional research consortium to develop and evaluate the most effective early interventions possible for the detection, prevention, and treatment of combatrelated posttraumatic stress disorder (PTSD) in activeduty military personnel and recently discharged veterans. Complementary investigations are focused on the root causes of PTSD, including biological factors that influence PTSD susceptibility and recovery; the influence of comorbid physical and psychological ailments; and the interaction of cognitive-behavioral therapies and pharmacologic treatments. The full cohort of STRONG STAR trials include: Treatment Studies, Biological Studies, Epidemiological Studies, and Preclinical Studies. STRONG STAR is currently conducting three clinical treatment trials at Carl R. Darnall Army Medical Center (CRDAMC). The studies are examining the effectiveness of Cognitive Processing Therapy (CPT), Prolonged Exposure Therapy (PE) and Cognitive Behavioral Therapy for Insomnia (CBTi) with active duty service members. Treatments are offered in individual, group, and online formats, and last from two to eight weeks. Study participants must be active duty service members who will remain in the Ft Hood area for at least 34 months to complete initial assessments and treatment programs. Referrals to the treatment studies can be made through a behavioral health provider or through selfreferral., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: Strong Star (RRID:SCR_003132) Copy
http://purl.bioontology.org/ontology/MMO
An ontology designed to represent the variety of methods used to make qualitative and quantitative clinical and phenotype measurements both in the clinic and with model organisms.
Proper citation: Measurement Method Ontology (RRID:SCR_003373) Copy
https://cabig.nci.nih.gov/tools/caTRIP
THIS RESOURCE IS NO LONGER IN SERVICE documented June 4, 2013. Allows users to query across a number of caBIG data services, join on common data elements (CDEs), and view results in a user-friendly interface. With an initial focus on enabling outcomes analysis, caTRIP allows clinicians to query across data from existing patients with similar characteristics to find treatments that were administered with success. In doing so, caTRIP can help inform treatment and improve patient care, as well as enable the searching of available tumor tissue, enable locating patients for clinical trials, and enable investigating the association between multiple predictors and their corresponding outcomes such as survival caTRIP relies on the vast array of open source caBIG applications, including: * Tumor Registry, a clinical system that is used to collect endpoint data * cancer Text Information Extraction System (caTIES), a locator of tissue resources that works via the extraction of clinical information from free text surgical pathology reports. while using controlled terminologies to populate caBIG-compliant data structures * caTissue CORE, a tissue bank repository tool for biospecimen inventory, tracking, and basic annotation * Cancer Annotation Engine (CAE), a system for storing and searching pathology annotations * caIntegrator, a tool for storing, querying, and analyzing translational data, including SNP data Requires Java installation and network connectivity.
Proper citation: caTRIP (RRID:SCR_003409) Copy
http://purl.bioontology.org/ontology/IDOMAL
An application ontology to cover all aspects of malaria (clinical, epidemiological, biological, etc) as well as the intervention attempts to control it, extending the infectious disease ontology (IDO).
Proper citation: Malaria Ontology (RRID:SCR_003369) Copy
http://edoctoring.ncl.ac.uk/Public_site/
Online educational tool that brings challenging clinical practice to your computer, providing medical education that is engaging, challenging and interactive. While there is no substitute for real-life direct contact with patients or colleagues, research has shown that interactive online education can be a highly effective and enjoyable method of learning many components of clinical medicine, including ethics, clinical management, epidemiology and communication skills. eDoctoring offers 25 simulated clinical cases, 15 interactive tutorials and a virtual library containing numerous articles, fast facts and video clips. Their learning material is arranged in the following content areas: * Ethical, Legal and Social Implications of Genetic Testing * Palliative and End-of-Life Care * Prostate Cancer Screening and Shared Decision-Making
Proper citation: eDoctoring (RRID:SCR_003336) Copy
http://purl.bioontology.org/ontology/CMO
An ontology designed to be used to standardize morphological and physiological measurement records generated from clinical and model organism research and health programs.
Proper citation: Clinical Measurement Ontology (RRID:SCR_003291) Copy
miniTUBA is a web-based modeling system that allows clinical and biomedical researchers to perform complex medical/clinical inference and prediction using dynamic Bayesian network analysis with temporal datasets. The software allows users to choose different analysis parameters (e.g. Markov lags and prior topology), and continuously update their data and refine their results. miniTUBA can make temporal predictions to suggest interventions based on an automated learning process pipeline using all data provided. Preliminary tests using synthetic data and laboratory research data indicate that miniTUBA accurately identifies regulatory network structures from temporal data. miniTUBA represents in a network view possible influences that occur between time varying variables in your dataset. For these networks of influence, miniTUBA predicts time courses of disease progression or response to therapies. minTUBA offers a probabilistic framework that is suitable for medical inference in datasets that are noisy. It conducts simulations and learning processes for predictive outcomes. The DBN analysis conducted by miniTUBA describes from variables that you specify how multiple measures at different time points in various variables influence each other. The DBN analysis then finds the probability of the model that best fits the data. A DBN analysis runs every combination of all the data; it examines a large space of possible relationships between variables, including linear, non-linear, and multi-state relationships; and it creates chains of causation, suggesting a sequence of events required to produce a particular outcome. Such chains of causation networks - are difficult to extract using other machine learning techniques. DBN then scores the resulting networks and ranks them in terms of how much structured information they contain compared to all possible models of the data. Models that fit well have higher scores. Output of a miniTUBA analysis provides the ten top-scoring networks of interacting influences that may be predictive of both disease progression and the impact of clinical interventions and probability tables for interpreting results. The DBN analysis that miniTUBA provides is especially good for biomedical experiments or clinical studies in which you collect data different time intervals. Applications of miniTUBA to biomedical problems include analyses of biomarkers and clinical datasets and other cases described on the miniTUBA website. To run a DBN with miniTUBA, you can set a number of parameters and constrain results by modifying structural priors (i.e. forcing or forbidding certain connections so that direction of influence reflects actual biological relationships). You can specify how to group variables into bins for analysis (called discretizing) and set the DBN execution time. You can also set and re-set the time lag to use in the analysis between the start of an event and the observation of its effect, and you can select to analyze only particular subsets of variables.
Proper citation: miniTUBA (RRID:SCR_003447) Copy
A reference terminology and core biomedical ontology for NCI that covers approximately 100,000 key biomedical concepts with terms, codes, definitions, and more than 200,000 inter-concept relationships. It is the reference terminology for NCI, NCI Metathesaurus and NCI informatics infrastructure covering vocabulary for clinical care, translational and basic research, and public information and administrative activities. It includes broad coverage of the cancer domain, including cancer related diseases, findings and abnormalities; anatomy; agents, drugs and chemicals; genes and gene products and so on. In certain areas, like cancer diseases and combination chemotherapies, it provides the most granular and consistent terminology available. It combines terminology from numerous cancer research related domains, and provides a way to integrate or link these kinds of information together through semantic relationships. NCIt features: * Stable, unique codes for biomedical concepts; * Preferred terms, synonyms, definitions, research codes, external source codes, and other information; * Links to NCI Metathesaurus and other information sources; * Over 200,000 cross-links between concepts, providing formal logic-based definition of many concepts; * Extensive content integrated from NCI and other partners, much available as separate NCIt subsets * Updated frequently by a team of subject matter experts. NCIt is a widely recognized standard for biomedical coding and reference, used by a broad variety of public and private partners both nationally and internationally including the Clinical Data Interchange Standards Consortium Terminology (CDISC), the U.S. Food and Drug Administration (FDA), the Federal Medication Terminologies (FMT), and the National Council for Prescription Drug Programs (NCPDP).
Proper citation: NCI Thesaurus (RRID:SCR_003563) Copy
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
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
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
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
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
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
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