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http://www.transformproject.eu/portfolio-item/d6-2-clinical-research-information-model/

A clinical research information model for the integration of clinical research covering randomized clinical trials (RCT), case-control studies and database searches into the TRANSFoRm application development. TRANSFoRm clinical research is based on primary care data, clinical data and genetic data stored in databases and electronic health records and employs the principle of reusing primary care data, adapting data collection by patient reported outcomes (PRO) and eSource based Case Report Forms. CRIM was developed using the TRANSFoRm clinical use cases of GORD and Diabetes. Their use case driven approach consisted of three levels of modelling drawing heavily on the clinical research workflow of the use cases. Different available information models were evaluated for their usefulness to represent TRANSFoRm clinical research, including for example CTOM of caBIG, Primary Care Research Object Model (PRCOM) of ePCRN and BRIDG of CDISC. The PCROM model turned out to be the most suitable and it was possible to extend and modify this model with only 12 new information objects, 3 episode of care related objects and 2 areas to satisfy all requirements of the TRANSFoRm research use cases. Now the information model covers Good Clinical Practice (GCP) compliant research, as well as case control studies and database search studies, including the interaction between patient and GP (family doctor) during patient consultation, appointment, screening, patient recruitment and adverse event reporting.

Proper citation: TRANSFoRm Clinical Research Information Model (RRID:SCR_003889) Copy   

•   Source: SciCrunch Registry

http://www.transformproject.eu/

Project to develop a ''rapid learning healthcare system'' driven by advanced computational infrastructure that can improve both patient safety and the conduct and volume of clinical research in Europe. Three carefully chosen clinical ''use cases'' will drive, evaluate and validate the approach to the ICT (information and communications technology) challenges. The project will build on existing work at international level in clinical trial information models (BRIDG and PCROM), service-based approaches to semantic interoperability and data standards (ISO11179 and controlled vocabulary), data discovery, machine learning and electronic health records based on open standards (openEHR). TRANSFoRm will extend this work to interact with individual eHR systems as well as operate within the consultation itself providing both diagnostic support and support for the identification and follow up of subjects for research. The approach to system design will be modular and standards-based, providing services via a distributed architecture, and will be tightly linked with the user community. Four years of development and testing will end with a fifth year that will be dedicated to summative validation of the project deliverables in the Primary Care setting. In order to support patient safety in both clinical and research settings, significant ICT challenges need to be overcome in the areas of interoperability, common standards for data integration, data presentation, recording, scalability, and security., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: TRANSFoRm (RRID:SCR_003888) Copy   

•   Source: SciCrunch Registry

http://www.alzheimer-europe.org/Research/PharmaCog

Project aiming to tackle bottlenecks in Alzheimer''''s disease research and drug discovery by developing and validating new tools to test candidate drugs for the treatment of symptoms and disease in a faster and more sensitive way. They will provide the tools needed to define more precisely the potential of a drug candidate, reduce the development time of new medicines and thus accelerate the approvals of promising new medicines. By bringing together databases of previously conducted clinical trials and combining the results from blood tests, brain scans and behavioral tests, the scientists will develop a ''''signature'''' that gives more accurate information on the progression of the disease and the effect of candidate drugs than current methods do. The scientists will conduct parallel studies in laboratory models, healthy volunteers and patients in order to better predict good new drugs as early as possible. This will enable them, for instance, to find out how memory loss in Alzheimer''''s disease can be simulated in healthy volunteers, for example with sleep deprivation or drugs that temporarily affect the memory, in order to test the effect of candidate-medicines early in the drug development process.

Proper citation: PharmaCog (RRID:SCR_003878) Copy   

•   Source: SciCrunch Registry

https://sites.google.com/site/p2tconsortium/

A three-member pharmaceutical industry consortium that aims to provide a new platform to improve access to information about clinical trials for patients and providers. The platform aims to enhance the existing clinicaltrials.gov by providing more detailed and patient-friendly information about available trials and embedding a machine-readable target health profile to improve the ability of healthcare software to match individual health profiles with applicable clinical trials. Using clinicaltrials.gov as its foundation and Eli Lilly''''s Application Programming Interface (API), the consortium is focused on creating an open platform to make this data more amenable to patients and providers, as well as creating an opportunity to integrate a patient''''s electronic health record into the clinical trial matching service. This feature will allow patients to search for trials using their own Blue Button data. The following features are planned add-ons to clinicaltrials.gov: * Target Profile is a machine readable query, that can be executed against an electronic file (or record) with patient health data such as an Electronic Health Record (EHR), an Electronic Medical Record (EMR) or Personally Controlled Health Record (PCHR) * Augmented Content is public, IRB approved information about the study that has not been published on clinicaltrials.gov, and that is shared with / targeted for patients with a matching Target Profile. The following are the incremental goals of the consortium: * Advancement of the Lilly API platform to support read/write interaction and additional data objects and information. * The initial 3 sponsor organizations - Lilly, Pfizer and Novartis - will upload Target Profiles for a select set of clinical trials. A Target Profile is a machine interpretable description of the characteristics of patients who may qualify for that trial i.e. a query that can be executed against a patient''''s electronic health record or personal health record. Additionally, sponsors of clinical research studies will also be able to upload Augmented Content to the Lilly Platform to supplement information on clinicaltrials.gov with additional, patient-focused information about the study, e.g., a study brochure and practical information on how to contact investigational sites. * A matching service, developed by Corengi, will compare Target Profiles to a de-dentified personally controlled health record (PCHR), represented by patient''''s Blue Button Plus CCDA XML document. * Integration into a patient community platform from Avado for providing the patient PCHR and presenting the results of the match service. The patient will be able to explore the respective matching studies for additional information and next steps such as contacting a nearby investigator clinic or hospital. The first demo of the prototype was made available on June 2014, built on a database of anonymized patient health records from different clinical research studies sponsored by Lilly, Novartis, and Pfizer. Other website: http://portal.lillycoi.com/

Proper citation: Patients to Trials Consortium (RRID:SCR_003877) Copy   

•   Source: SciCrunch Registry

https://www.bigtencrc.org/

A consortium that aims to transform cancer research through collaborative oncology trials that leverage the scientific and clinical expertise of the Big Ten universities. The goal is to align the conduct of cancer research through collaborative, hypothesis-driven, highly translational oncology trials that leverage the scientific and clinical expertise. The clinical trials that will be developed will be linked to molecular diagnostics, enabling researchers to understand what drives the cancers to grow and what might be done to stop them from growing. The consortium also leverages geographical locations and existing relationships among the cancer centers. One of the consortium's goals is to harmonize contracts and scientific review processes to expedite clinical trials. The consortium will only focus on phase 0 to II trials because larger trials - even a randomized phase II trial - are difficult to conduct at a single cancer center.

Proper citation: Big Ten Cancer Research Consortium (RRID:SCR_004025) Copy   

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http://www.euadr-project.org/

Consortium that created the capability to detect Adverse Drug Response (ADR) signals by creating the infrastructure for large-scale monitoring of drug safety using electronic health records (EHR). The platform leverages EHR''''s comprising demographics, drug use and clinical data of over 30 million patients from several European countries. Special attention was given to patient groups that are not routinely involved in clinical trials, for ethical or practical reasons (e.g. pregnant women, elderly people, people using many drugs simultaneously, and children). This project also studies and compares a number of different techniques that all aim to detect unexpected or disproportional rates of events. The algorithms that they studied originate not only from the field of (pharmaco)epidemiology, but also from fields such as bio-terrorism, machine learning, and classical signal detection. EU-ADR specific objectives are: To detect events, To relate these events to drugs, To develop hypothesis that explain adverse events, To detect adverse events earlier, and To avoid false positives. The web-based platform is available at https://bioinformatics.ua.pt/euadr/ EU-ADR has contributed to the ability to conduct better drug safety studies based on the re-use of healthcare data. By facilitating the early detection of adverse drug reactions, but also providing key information on populations at risk, potential drug interactions, potential underlying mechanisms and intervening pathways in adverse events, etc., the project will allow for improved and more complete information to be available for drug and healthcare delivery, leading to increased patient safety and its associated cost savings. The EU-ADR system can be considered as a complementary tool to already existing pharamcovigilance systems. Should the system be widespread in the long term, it has the potential to contribute to the development of future electronic health record systems, insofar as the expected benefits of these IT tools are only fully attainable when EHRs develop themselves in consistency, richness and formats that allow them to be subject of such tools. In anticipation, EU-ADR has been designed to be modular and scalable, so that different EHR databases (other than those participating in the Consortium) can be progressively enlisted in the future, adopt the software for data extraction and therefore become susceptible of exploitation by the system, for maximum global effect.

Proper citation: EU-ADR (RRID:SCR_004028) Copy   

•   Source: SciCrunch Registry

http://www.commondataelements.ninds.nih.gov

The purpose of the NINDS Common Data Elements (CDEs) Project is to standardize the collection of investigational data in order to facilitate comparison of results across studies and more effectively aggregate information into significant metadata results. The goal of the National Institute of Neurological Disorders and Stroke (NINDS) CDE Project specifically is to develop data standards for clinical research within the neurological community. Central to this Project is the creation of common definitions and data sets so that information (data) is consistently captured and recorded across studies. To harmonize data collected from clinical studies, the NINDS Office of Clinical Research is spearheading the effort to develop CDEs in neuroscience. This Web site outlines these data standards and provides accompanying tools to help investigators and research teams collect and record standardized clinical data. The Institute still encourages creativity and uniqueness by allowing investigators to independently identify and add their own critical variables. The CDEs have been identified through review of the documentation of numerous studies funded by NINDS, review of the literature and regulatory requirements, and review of other Institute''s common data efforts. Other data standards such as those of the Clinical Data Interchange Standards Consortium (CDISC), the Clinical Data Acquisition Standards Harmonization (CDASH) Initiative, ClinicalTrials.gov, the NINDS Genetics Repository, and the NIH Roadmap efforts have also been followed to ensure that the NINDS CDEs are comprehensive and as compatible as possible with those standards. CDEs now available: * General (CDEs that cross diseases) Updated Feb. 2011! * Congenital Muscular Dystrophy * Epilepsy (Updated Sept 2011) * Friedreich''s Ataxia * Parkinson''s Disease * Spinal Cord Injury * Stroke * Traumatic Brain Injury CDEs in development: * Amyotrophic Lateral Sclerosis (Public review Sept 15 through Nov 15) * Frontotemporal Dementia * Headache * Huntington''s Disease * Multiple Sclerosis * Neuromuscular Diseases ** Adult and pediatric working groups are being finalized and these groups will focus on: Duchenne Muscular Dystrophy, Facioscapulohumeral Muscular Dystrophy, Myasthenia Gravis, Myotonic Dystrophy, and Spinal Muscular Atrophy The following tools are available through this portal: * CDE Catalog - includes the universe of all CDEs. Users are able to search the full universe to isolate a subset of the CDEs (e.g., all stroke-specific CDEs, all pediatric epilepsy CDEs, etc.) and download details about those CDEs. * CRF Library - (a.k.a., Library of Case Report Form Modules and Guidelines) contains all the CRF Modules that have been created through the NINDS CDE Project as well as various guideline documents. Users are able to search the library to find CRF Modules and Guidelines of interest. * Form Builder - enables users to start the process of assembling a CRF or form by allowing them to choose the CDEs they would like to include on the form. This tool is intended to assist data managers and database developers to create data dictionaries for their study forms.

Proper citation: NINDS Common Data Elements (RRID:SCR_006577) Copy   

•   Source: SciCrunch Registry

http://www.nlm.nih.gov/research/umls/rxnorm/

Ontology that provides a normalized naming system for generic and branded drugs and a tool for supporting semantic interoperation between drug terminologies and pharmacy knowledge base systems. It contains the names of prescription and many over-the-counter drugs available in the United States and links its names to many of the drug vocabularies commonly used in pharmacy management and drug interaction software. It can mediate messages between systems not using the same software and vocabulary. * RxNorm Download Files - contain data consistent with the 2013AB UMLS Metathesaurus Release Files. * RxNorm API - web service for accessing the current RxNorm data set. * RxNorm Browser (RxNav) - a browser for several drug information sources, including RxNorm, RxTerms and National Drug File - Reference Terminology (NDF-RT) . * Current Prescribable Content - subset of currently prescribable drugs found in RxNorm. * RxTerms Drug Interface Terminology - a drug interface terminology derived from RxNorm for prescription writing or medication history recording

Proper citation: RxNorm (RRID:SCR_006645) Copy   

•   Source: SciCrunch Registry

https://www.fludb.org/brc/home.spg?decorator=influenza

The Influenza Research Database (IRD) serves as a public repository and analysis platform for flu sequence, experiment, surveillance and related data.

Proper citation: Influenza Research Database (IRD) (RRID:SCR_006641) Copy   

•   Source: SciCrunch Registry

http://www.autoimmunitycenters.org/

Nine centers that conduct clinical trials and basic research on new immune-based therapies for autoimmune diseases. This program enhances interactions between scientists and clinicians in order to accelerate the translation of research findings into medical applications. By promoting better coordination and communication, and enabling limited resources to be pooled, ACEs is one of NIAID''''s primary vehicles for both expanding our knowledge and improving our ability to effectively prevent and treat autoimmune diseases. This coordinated approach incorporates key recommendations of the NIH Autoimmune Diseases Research Plan and will ensure progress in identifying new and highly effective therapies for autoimmune diseases. ACEs is advancing the search for effective treatments through: * Diverse Autoimmunity Expertise Medical researchers at ACEs include rheumatologists, neurologists, gastroenterologists, and endocrinologists who are among the elite in their respective fields. * Strong Mechanistic Foundation ACEs augment each clinical trial with extensive basic studies designed to enhance understanding of the mechanisms responsible for tolerance initiation, maintenance, or loss, including the role of cytokines, regulatory T cells, and accessory cells, to name a few. * Streamlined Patient Recruitment The cooperative nature of ACEs helps scientists recruit patients from distinct geographical areas. The rigorous clinical and basic science approach of ACEs helps maintain a high level of treatment and analysis, enabling informative comparisons between patient groups.

Proper citation: Autoimmunity Centers of Excellence (RRID:SCR_006510) Copy   

•   Source: SciCrunch Registry

https://repository.niddk.nih.gov/home/

NIDDK Central Repositories are two separate contract funded components that work together to store data and samples from significant, NIDDK funded studies. First component is Biorepository that gathers, stores, and distributes biological samples from studies. Biorepository works with investigators in new and ongoing studies as realtime storage facility for archival samples.Second component is Data Repository that gathers, stores and distributes incremental or finished datasets from NIDDK funded studies Data Repository helps active data coordinating centers prepare databases and incremental datasets for archiving and for carrying out restricted queries of stored databases. Data Repository serves as Data Coordinating Center and website manager for NIDDK Central Repositories website.

Proper citation: NIDDK Central Repository (RRID:SCR_006542) Copy   

•   Source: SciCrunch Registry

http://projectreporter.nih.gov/project_info_description.cfm?aid=8661937&icde=19363283&ddparam=&ddvalue=&ddsub=&cr=1&csb=default&cs=ASC

Initiative to assemble a multicenter team of expert neuroscientists to evaluate the late effects of Traumatic brain injury (TBI), including single and repetitive TBI of varying severity, and Chronic Traumatic Encephalopathy (CTE), using histological examination of postmortem bio specimens and neuroimaging tools as a foundation to develop in vivo diagnostics. As a first aim, this proposal will bring together a team of 5 accomplished neuropathologists in neurodegenerative disease to establish consensus criteria for the post-mortem diagnosis of CTE. This team will also define the stages of CTE pathology, the features that differentiate CTE from other neurodegenerations and the effects of substance abuse, and the characteristics of posttraumatic neurodegeneration after single TBI. As a second aim, this proposal will establish a national bio specimen and data bank for TBI (Understanding Neurological Injury and Traumatic Encephalopathy (UNITE) bio bank) by developing a nationwide brain donor registry and hotline to acquire high quality bio specimens and data. The UNITE bank will use strictly standardized protocols and a web-based interface to ensure that tissue and data are readily available to qualified investigators. Comprehensive retrospective clinical data including clinical symptoms, brain trauma and substance abuse history, and medical records (including common data elements) will be entered into a secure database. Behavioral/ mood dysfunction, cognitive changes, substance abuse and traumatic exposure will be correlated with quantitative assessment of the multifocal tauopathy, Ass deposition and axonal injury. As a third aim, neuroimaging signatures of the neuropathology will be determined in post-mortem tissue using high spatial resolution diffusion tensor imaging (DTI) and autoradiography using a highly selective PET ligand for tau. Quantitative assessment of axonal injury, tau, and Ass will be correlated with ex vivo DTI abnormalities and tau ligand autoradiography. Pilot neuroimaging studies of individuals at high risk for the development of CTE will also be conducted in the final 2 years of the proposal. This proposal will determine the clinical and neuroimaging correlates of CTE and posttraumatic neurodegeneration and create the groundwork for establishing their incidence and prevalence. This study will have a tremendous impact on public health of millions of Americans and greatly increase our understanding of the latent effects of brain trauma.

Proper citation: CTE and Post-traumatic Neurodegeneration: Neuropathology and Ex Vivo Imaging (RRID:SCR_006543) Copy   

•   Source: SciCrunch Registry

http://www.LOVD.nl/

Freely available tool for Gene-centered collection and display of DNA variations. It also provides patient-centered data storage and storage of Next Generation Sequencing (NGS) data, even of variants outside of genes. Please note that LOVD provides a system for storage of information on genes and allelic variants. To obtain information about any genes or variants, do not download the LOVD package. This information should be obtained from the respective databases, http://www.lovd.nl/2.0/index_list.php In total: 2,507,027 variants (2,208,937 unique) in 170,935 individuals in 62619 genes in 88 LOVD installations. (Aug. 2013) LOVD 3.0 shared installation, http://databases.lovd.nl/shared/genes To maintain a high quality of the data stored, LOVD connects with various resources, like HGNC, NCBI, EBI and Mutalyzer. You can download LOVD in ZIP and GZIPped TARball formats.

Proper citation: Leiden Open Variation Database (RRID:SCR_006566) Copy   

•   Source: SciCrunch Registry

https://fitbir.nih.gov/

Platform for Traumatic Brain Injury relevant data. System was developed to share data across entire TBI research field and to facilitate collaboration between laboratories and interconnectivity between informatics platforms. FITBIR implements interagency Common Data Elements for TBI research and provides tools and resources to extend data dictionary. Established submission strategy to ensure high quality and to provide maximum benefit to investigators. Qualified researchers can request access to data stored in FITBIR and/or data stored at federated repositories.

Proper citation: Federal Interagency Traumatic Brain Injury Research Informatics System (RRID:SCR_006856) Copy   

•   Source: SciCrunch Registry

http://www.niaid.nih.gov/topics/transplant/research/Pages/fundedBasics.aspx#NHPTCSP

Cooperative program for research on nonhuman primate models of kidney, islet, heart, and lung transplantation evaluating the safety and efficacy of existing and new treatment regimens that promote the immune system''''s acceptance of a transplant and to understand why the immune system either rejects or does not reject a transplant. This program bridges the critical gap between small-animal research and human clinical trials. The program supports research into the immunological mechanisms of tolerance induction and development of surrogate markers for the induction, maintenance, and loss of tolerance.

Proper citation: Nonhuman Primate Transplantation Tolerance Cooperative Study Group (RRID:SCR_006847) Copy   

•   Source: SciCrunch Registry

http://diabetes.niddk.nih.gov/dm/pubs/america/

A compilation and assessment of epidemiologic, public health, and clinical data on diabetes and its complications in the United States. Published by the National Diabetes Data Group of the National Institute of Diabetes and Digestive and Kidney Diseases, the book contains 36 chapters organized in five areas: * the descriptive epidemiology of diabetes in the United States based on national surveys and community-based studies, including prevalence, incidence, sociodemographic and metabolic characteristics, risk factors for developing diabetes, and mortality * the myriad complications that affect patients with diabetes * characteristics of therapy and medical care for diabetes * economic aspects, including health insurance and health care costs * diabetes in special populations, including African Americans, Hispanics, Asian and Pacific Islanders, Native Americans, and pregnant women. Diabetes in America, 2nd Edition, has been designed to serve as a reliable scientific resource for assessing the scope and impact of diabetes and its complications, determining health policy and priorities in diabetes, and identifying areas of need in research. The intended audience includes health policy makers at the local and Federal levels who need a sound quantitative base of knowledge to use in decision making; clinicians who need to know the probability that their patients will develop diabetes and the prognosis of the disease for complications and premature mortality; persons with diabetes and their families who need sound information on which to make decisions about their life with diabetes; and the research community which needs to identify areas where important scientific knowledge is lacking.

Proper citation: Diabetes in America (RRID:SCR_006754) Copy   

•   Source: SciCrunch Registry

http://cebs.niehs.nih.gov

Repository for toxicogenomics data, including study design and timeline, clinical chemistry and histopathology findings and microarray and proteomics data. Data derived from studies of chemicals and of genetic alterations, and is compatible with clinical and environmental studies. Data relating to environmental health, pharmacology, and toxicology. It is not necessary to have microarray data, but study design and phenotypic anchoring data are required.CEBS contains raw microarray data collected in accordance with MIAME guidelines and provides tools for data selection, pre-processing and analysis resulting in annotated lists of genes of interest. Biomedical Investigation Database is another component of CEBS system. used to load and curate study data prior to export to CEBS, in addition to capturing and displaying novel data types such as PCR data, or additional fields of interest, including those defined by the HESI Toxicogenomics Committee. BID has been shared with Health Canada and the US Environmental Protection Agency.

Proper citation: Chemical Effects in Biological Systems (CEBS) (RRID:SCR_006778) Copy   

•   Source: SciCrunch Registry

http://www.chr7.org

Database containing the DNA sequence and annotation of the entire human chromosome 7, encompassing nearly 158 million nucleotides of DNA and 1917 gene structures, are presented; the most up to date collation of sequence, gene, and other annotations from all databases (eg. Celera published, NCBI, Ensembl, RIKEN, UCSC) as well as unpublished data. To generate a higher order description, additional structural features such as imprinted genes, fragile sites, and segmental duplications were integrated at the level of the DNA sequence with medical genetic data, including 440 chromosome rearrangement breakpoints associated with disease. The objective of this project is to generate a comprehensive description of human chromosome 7 to facilitate biological discovery, disease gene research and medical genetic applications. There are over 360 disease-associated genes or loci on chromosome 7. A major challenge ahead will be to represent chromosome alterations, variants, and polymorphisms and their related phenotypes (or lack thereof), in an accessible way. In addition to being a primary data source, this site serves as a weighing station for testing community ideas and information to produce highly curated data to be submitted to other databases such as NCBI, Ensembl, and UCSC. Therefore, any useful data submitted will be curated and shown in this database. All Chromosome 7 genomic clones (cosmids, BACs, YACs) listed in GBrowser and in other data tables are freely distributed.

Proper citation: Chromosome 7 Annotation Project (RRID:SCR_007134) Copy   

•   Source: SciCrunch Registry

http://www.idars.org/

IDARS is an international scientific organization that promotes and fosters the research and collaboration of scientists around the world in the area of substances of abuse and addiction. Our focus is to foster research in molecular, cellular and systems biology and includes neuropharmacological, neurobehavioral, neurochemical and neuroanatomical themes. The purposes of IDARS are scientific, educational and charitable. We strive to promote excellence in: advancing the understanding of drug abuse, substance abuse and addictions, including the part they play in behaviors of humans and in animal models bringing together scientists of varying backgrounds and disciplines within the field of drug abuse research integrating drug abuse research directed at all levels of biological organization and its translation to improvement in clinical prevention and treatment efforts promoting education in the addiction sciences informing the general public on the results and implications of current research in the addiction sciences promoting other activities that will contribute to the development of addiction sciences IDARS is a 501c3 nonprofit organization.

Proper citation: International Drug Abuse Research Society (RRID:SCR_007411) Copy   

•   Source: SciCrunch Registry

http://cardiogenomica.altervista.org/CARDIOGENOMICS/CardioGenomics%20Homepage.htm

The primary goal of the CardioGenomics PGA is to begin to link genes to structure, function, dysfunction and structural abnormalities of the cardiovascular system caused by clinically relevant genetic and environmental stimuli. The principal biological theme to be pursued is how the transcriptional network of the cardiovascular system responds to genetic and environmental stresses to maintain normal function and structure, and how this network is altered in disease. This PGA will generate a high quality, comprehensive data set for the functional genomics of structural and functional adaptation of the cardiovascular system by integrating expression data from animal models and human tissue samples, mutation screening of candidate genes in patients, and DNA polymorphisms in a well characterized general population. Such a data set will serve as a benchmark for future basic, clinical, and pharmacogenomic studies. Training and education are also a key focus of the CardioGenomics PGA. In addition to ongoing journal clubs and seminars, the PGA will be sponsoring symposia at major conferences, and developing workshops related to the areas of focus of this PGA. Information regarding upcoming events can be found in the Events section of this site, and information about training and education opportunities sponsored by CardioGenomics can be found on the Teaching and Education page. The CardioGenomics project came to a close in 2005. This server, cardiogenomics.med.harvard.edu, remains online in order to continue to distribute data that was generated by investigators under the auspices of the CardioGenomics Program for Genomic Applications (PGA). :Sponsors: This resource is supported by The National Heart, Lung and Blood Institute (NHLBI) of the NIH., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: CardioGenomics (RRID:SCR_007248) Copy   

•   Source: SciCrunch Registry