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https://www.nugene.org/

Collects and stores genetic (DNA) samples along with associated healthcare information from patients of Northwestern-affiliated hospitals and clinics. This resource is available to scientists to conduct groundbreaking genetic research. The information and blood samples provided will be used by researchers to examine the role genes play in the development and treatment of common diseases. The NUgene Project seeks to increase the understanding of genetic mechanisms underlying common diseases, assist in the development of DNA-based technology for diagnosis and treatment of disease, and aid physicians and other healthcare providers in the application of genetics to the practice of medicine. NUgene participants are recruited throughout the Northwestern-affiliated healthcare community in order to create an ethnically and medically diverse population for research. Participants must be 18 years of age or older and receive their medical care from a Northwestern-affiliated provider, regardless of health status. Consenting individuals complete all aspects of enrollment in a single meeting with a research coordinator. The enrollment process includes the donation of a single sample of blood and the completion of a self-administered questionnaire. Participants also sign a consent form during this encounter. The NUgene Project is an interdisciplinary project that relies on the expertise of individuals working in a variety of fields, including science, medicine, clinical research, statistics, epidemiology, and computational biology. NUgene''s multidisciplinary approach has spurred collaborations within Northwestern-affiliated institutions and with other outside institutions. This collaboration of ideas is the future of genetics and genomic research., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: NUgene Project (RRID:SCR_007426) Copy   

•   Source: SciCrunch Registry

http://www.niaid.nih.gov/about/organization/dait/pages/csgadp.aspx

Collaborative network of investigators with a focus on prevention of autoimmune disease, defined as halting the development of autoimmune disease prior to clinical onset by means other than global immunosuppression, and an emphasis on Type 1 diabetes. Its mission is to engage in scientific discovery that significantly advances knowledge for the prevention and regulation of autoimmune disease. The specific goals enunciated in pursuit of this mission are: * To create improved models of disease pathogenesis and therapy to better understand immune mechanisms that will provide opportunities for prevention strategies * To use these models as validation platforms with which to test new tools applicable to human studies * To encourage core expertise and collaborative projects designed for rapid translation from animal to human studies, emphasizing the development of surrogate markers for disease progression and/or regulation which can be utilized in the context of clinical trials

Proper citation: Cooperative Study Group for Autoimmune Disease Prevention (RRID:SCR_006803) Copy   

•   Source: SciCrunch Registry

http://www.niaaa.nih.gov/research/major-initiatives/collaborative-studies-genetics-alcoholism-coga-study

Database and biorepository from a multi-site, multi-disciplinary study characterizing the familial transmission of alcoholism and related phenotypes and identifying susceptibility genes using genetic linkage. Investigators have assembled a collection of over 300 extended families densely affected by alcoholism (more than 3000 individuals), including clinical, neuropsychological, electrophysiological, biochemical, and genetic data, and established a repository of immortalized cell lines from these individuals, to serve as a permanent source of DNA for genetic studies. NIAAA has funded the Collaborative Studies on Genetics of Alcoholism (COGA) since 1989, with the goal of identifying the specific genes underlying this vulnerability. Data and biomaterials are available to qualified investigators in the broader scientific community. Recipients of data and biomaterials will be responsible for defraying the cost of their distribution. Pedigrees densely affected with alcoholism (DSM-III-R) have been ascertained at six sites (SUNY Downstate Health Sciences Center, University of Connecticut, Indiana University, Washington University, University of Iowa, and The University of California at San Diego). Diagnoses of alcohol dependence according to several diagnostic systems (e.g., DSM-III-R, Feighner, ICD-10) are made based on examination of medical records and direct assessment using the Semi-Structured Assessment for Genetics of Alcoholism (SSAGA). Nuclear and extended pedigrees containing at least two alcohol-dependent first-degree relatives in addition to an alcohol dependent proband (with all affected individuals meeting both DSM-IIIR and Feighner criteria) have been ascertained. Clinical data comprises anonymous data on family structure, age, sex, vital status, psychopathology, diagnosis, other clinically relevant information, are stored, maintained, and distributed by Washington University. Research data, consist of data on blood biochemistry and psychological test performance, which are stored, maintained, and distributed by Washington University, and brain electrophysiological data, which are stored, maintained, and distributed by SUNY. Genetic analysis data, consisting of marker genotypes, along with results of previous genetic analyses of COGA data, are stored, maintained, and distributed by Washington University. Biomaterials, consisting of lymphoblastoid cell lines and DNA from participating subjects are stored, maintained, and distributed by Rutgers University. Researchers may gain access to clinical data, research data, genetic analysis data, and biomaterials, subject to NIAAA approval, by completing an application details available from the website. After access certification, the principal investigator will be given access to electronic data files and other documentation.

Proper citation: Collaborative Studies on Genetics of Alcoholism (RRID:SCR_006841) Copy   

•   Source: SciCrunch Registry

http://www.ppmi-info.org/

An observational longitudinal clinical study partnership to identify and validate biomarkers of Parkinson disease (PD) progression and provide easy and open web-based access to the comprehensive set of correlated clinical data and biospecimens, information, and biosamples acquired from PD and age and gender matched healthy control subjects to the research community. The data and specimens have been collected in a standardized manner under strict protocols and includes clinical (demographic, motor and non-motor, cognitive and neurobehavioral), imaging (raw and processed MRI, SPECT and DAT), and blood chemistry and hematology subject assessments and biospecimen inventories (serum, plasma, whole blood, CSF, DNA, RNA and urine). All data are de-identified to protect patient privacy. PPMI will be carried out over five years at 21 clinical sites in the United States and Europe and requires the participation of 400 Parkinson's patients and 200 control participants. The PPMI database provides researchers with access to correlated clinical and imaging data, along with annotated biospecimens, all available within an open access system that encourages data sharing (http://www.ppmi-info.org/access-data-specimens/). The website hosts an Ongoing Analysis section to keep the scientific community apprised of analyses being completed, in hopes of stimulating collaborations between researchers who are using PPMI data and specimens.

Proper citation: Parkinson's Progression Markers Initiative (RRID:SCR_006431) Copy   

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https://cmp.missouri.edu/

Program provides advanced graduate training to veterinarians who wish to pursue careers in comparative medicine. Trainees may combine one year of residency training in clinical, administrative and diagnostic laboratory animal medicine with two or more years of research training. Alternatively, trainees with experience in laboratory animal medicine, comparative pathology or related disciplines may begin research training at the time of admission. Training is designed to prepare individuals for a variety of careers including comparative medicine research, clinical and administrative laboratory animal medicine and comparative and diagnostic laboratory animal pathology. Students may either pursue an MS or PhD. Research opportunities are available in several areas including infectious disease, pathology, molecular biology, mouse biology and cardiovascular physiology. Resources available include the University of Missouri Office of Animal Resources (OAR) and Research Animal Diagnostic Laboratory (RADIL) and Mutant Mouse and Rat Resource and Research Centers. The University of Missouri Comparative Medicine Program (CMP) is post Doctor of Veterinary Medicine training that combines graduate residency training, course work and research. Trainees with relevant experience in laboratory animal medicine or comparative pathology may pursue research training without residency training. In the residency year of training, two rotations are performed: diagnostic laboratory animal pathology in the Research Animal Diagnostic Laboratory (RADIL); clinical medicine and animal resource management in the Office of Animal Resources (OAR). The remaining two to four years focus on research training under an established investigator. After three years, trainees successfully fulfilling program requirements receive a certificate of residency training. MS students complete their program while PhD students continue to pursue research training. Sponsors: CMP is supported by the University of Missouri comparative, medicine, veterinarian, residency, training, clinical, administrative, diagnostic, laboratory, animal, pathology, cardiovascular, molecular, biology, mouse, physiology

Proper citation: University of Missouri Comparative Medicine Program (RRID:SCR_008298) Copy   

•   Source: SciCrunch Registry

http://www.ohsu.edu/xd/research/centers-institutes/neurology/alzheimers/research/data-tissue/biomarkers-genetics.cfm

A center that works with the Oregon Alzheimer's Disease Center's Data Core, and collects and stores tissue samples, family history and genotype data of various populations. These include samples and data from subjects from the following sources: OADC clinical studies, the Oregon Brain Aging Study, the Community Brain Donor Program, the Preventing Cognitive Decline with Alternative Therapies program (informally called the Dementia Prevention Study or DPS), the African American Dementia and Aging Project, and the Klamath Exceptional Aging Project. The collected data samples include genomic DNA, lymphoblast cell lines, genome-wide and candidate region SNP marker data, APOE, AD candidate gene markers.

Proper citation: Layton Center Biomarkers and Genetics (RRID:SCR_008824) Copy   

•   Source: SciCrunch Registry

http://www.framinghamheartstudy.org/

A longitudinal, epidemiologic study to identify the common risk factors or characteristics that contribute to cardiovascular disease by following its development over a long period of time in a large group of participants who had not yet developed overt symptoms or suffered a heart attack or stroke. Since that time the FHS has studied three generations of participants resulting in biological specimens and data from nearly 15,000 participants. Since 1994, two groups from minority populations, including related individuals have been added to the FHS. FHS welcomes proposals from outside investigators for data and biospecimens. The researchers recruited 5,209 men and women between the ages of 30 and 62 from the town of Framingham, Massachusetts, and began the first round of extensive physical examinations and lifestyle interviews that they would later analyze for common patterns related to CVD development. Since 1948, the subjects have continued to return to the study every two years for a detailed medical history, physical examination, and laboratory tests, and in 1971, the Study enrolled a second generation - 5,124 of the original participants'''' adult children and their spouses - to participate in similar examinations. In 1994, the need to establish a new study reflecting a more diverse community of Framingham was recognized, and the first Omni cohort of the Framingham Heart Study was enrolled. In April 2002 the Study entered a new phase, the enrollment of a third generation of participants, the grandchildren of the Original Cohort. In 2003, a second group of Omni participants was enrolled. Over the years, careful monitoring of the Framingham Study population has led to the identification of major CVD risk factors, as well as valuable information on the effects of these factors such as blood pressure, blood triglyceride and cholesterol levels, age, gender, and psychosocial issues. Risk factors for other physiological conditions such as dementia have been and continue to be investigated. In addition, the relationships between physical traits and genetic patterns are being studied. FHS clinical and research data is stored in the dbGaP and NHLBI Repository repositories and may be accessed by application. Please check the following repositories before applying for data through FHS. Investigators seeking data that is not available through dbGaP or BioLINCC or seeking biological specimens may submit a proposal through the FHS web-based research application. The FHS data repository may be accessed through this FHS website, under the For Researchers link, then Description of Data, in order to determine if and how the desired data is stored. Proposals may involve the use of existing data, the collection of new data, either directly from participants or from previously collected samples, images, or other materials (e.g., medical records). The FHS Repository also has biological specimens available for genetic and non-genetic research proposals. Specimens include urine, blood and blood products, as well as DNA.

Proper citation: Framingham Heart Study (RRID:SCR_008963) Copy   

•   Source: SciCrunch Registry

http://psychiatry.stanford.edu/alzheimer/files/gpkt.pdf

50 question test devised by Javaid Sheikh, M.D., and Jerome A. Yesavage, M.D., of the Department of Psychiatry and Behavioral Sciences at Stanford University School of Medicine, to test one''s knowledge of certain aspects of geriatric psychiatry, including five broad areas: psychodynamics and psychotherapy, cognitive assessment, psychosocial and developmental aspects, psychopharmacology, and clinical syndromes.

Proper citation: Geriatric Psychiatry Knowledge Test (RRID:SCR_009029) Copy   

•   Source: SciCrunch Registry

http://ccb.loni.usc.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 31, 2022. Center focused on the development of computational biological atlases of different populations, subjects, modalities, and spatio-temporal scales with 3 types of resources: (1) Stand-alone computational software tools (image and volume processing, analysis, visualization, graphical workflow environments). (2) Infrastructure Resources (Databases, computational Grid, services). (3) Web-services (web-accessible resources for processing, validation and exploration of multimodal/multichannel data including clinical data, imaging data, genetics data and phenotypic data). The CCB develops novel mathematical, computational, and engineering approaches to map biological form and function in health and disease. CCB computational tools integrate neuroimaging, genetic, clinical, and other relevant data to enable the detailed exploration of distinct spatial and temporal biological characteristics. Generalizable mathematical approaches are developed and deployed using Grid computing to create practical biological atlases that describe spatiotemporal change in biological systems. The efforts of CCB make possible discovery-oriented science and the accumulation of new biological knowledge. The Center has been divided into cores organized as follows: - Core 1 is focused on mathematical and computational research. Core 2 is involved in the development of tools to be used by Core 3. Core 3 is composed of the driving biological projects; Mapping Genomic Function, Mapping Biological Structure, and Mapping Brain Phenotype. - Cores 4 - 7 provide the infrastructure for joint structure within the Center as well as the development of new approaches and procedures to augment the research and development of Cores 1-3. These cores are: (4)Infrastructure and Resources, (5) Education and Training, (6) Dissemination, and (7) Administration and Management. The main focus of the CCB is on the brain, and specifically on neuroimaging. This area has a long tradition of sophisticated mathematical and computational techniques. Nevertheless, new developments in related areas of mathematics and computational science have emerged in recent years, some from related application areas such as Computer Graphics, Computer Vision, and Image Processing, as well as from Computational Mathematics and the Computational Sciences. We are confident that many of these ideas can be applied beneficially to neuroimaging.

Proper citation: Center for Computational Biology at UCLA (RRID:SCR_000334) Copy   

•   Source: SciCrunch Registry

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

Consortium establishing data standards, tools and methods for conducting research in therapeutic areas important to public health including Alzheimer's disease, Parkinson's disease, multiple sclerosis, polycystic kidney disease, and tuberculosis.CDISC and C-Path have agreed to discontinue using separate CFAST brand, but they both remain committed to this mission and continue to partner to develop and publish therapeutic area data standards.

Proper citation: Coalition For Accelerating Standards and Therapies (RRID:SCR_000206) Copy   

•   Source: SciCrunch Registry

http://www.bioeden.com/

International private stem cell storage bank to collect, assess and cryogenically store living tooth cells from deciduous baby teeth. Tooth cell banking is a safe, natural and completely noninvasive method of collecting and preserving valuable stem cells which could hold the key to your child's health. Simply enroll, send us your child's tooth when it falls out, and they'll do the rest. Stem cell treatment to repair or replace damaged tissues or organs is the cornerstone of future medical science. Children's milk teeth, (baby teeth) have been identified as a rich source of these stem cells and have the potential to treat some of the worst illnesses and diseases facing people today. Stem cells from teeth (mesenchymal stem cells) are different from those found in cord blood (hematopoietic stem cells). Cord blood cells can be used to treat blood disorders such as leukemia, but stem cells from teeth are different. Stem cells from teeth can be used to grow a range of tissues including bone, nerve, fat, muscle and cartilage and may one day be used to grow entire organs. It is widely believed that stem cells will be used to treat a wide variety of diseases and injuries within the next decade. Their UK facility is regulated by the Human Tissue Authority (HTA), and they hold a full license. They are also registered with the Food and Drug Administration (FDA) in the US. BioEDEN, Ltd is ISO 9001:2008 accredited by the British Assessment Bureau. When you enroll for the BioEDEN service, you will be offered the opportunity to consent to donate any excess cells. BioEDEN will provide these cells to leading academic and clinical research centers to help further the progression of this technology to useful clinical applications. BioEDEN will only provide cells to researchers that have full ethical approval for their research and will be guided by our Advisory team as to the most appropriate research to support. The cells will be donated in accordance with strict regulatory guidelines and anonymity of the donor will be strictly assured at all times. Donation of cells is an entirely opt in service. If you choose not to give consent to donate, BioEDEN will simply store the cells for your child.

Proper citation: BioEden Tooth Cell Bank (RRID:SCR_000507) Copy   

•   Source: SciCrunch Registry

http://cahub.cancer.gov/about/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented July 5, 2018. A national center for biospecimen science and standards to advance cancer research and treatment. It was created in response to the critical and growing need for high-quality, well-documented biospecimens for cancer research. The initiative builds on resources already developed by the NCI, including the Biospecimen Research Network and the NCI Best Practices for Biospecimen Resources, both of which were developed to address challenges around standardization of the collection and dissemination of quality biospecimens. caHUB will develop the infrastructure for collaborative biospecimen research and the production of evidence-based biospecimen standard operating procedures.

Proper citation: caHUB (RRID:SCR_009657) Copy   

•   Source: SciCrunch Registry

http://code.google.com/p/neurological-disease-ontology/

An ontology for the representation of the range of clinical and basic science aspects of neurological diseases. ND has a broad scope that includes neurological diseases as well as their associated signs, symptoms, diagnoses, pathologies, etiologies, processes, treatments, and any other aspect of a neurological disease that is or can be encountered in the course of clinical practice or medical research. ND is being built in accordance with the OBO Foundry principles. It is an extension of the Ontology for General Medical Science (OGMS) as well as the Basic Formal Ontology (BFO). ND aims to develop classes utilizing both textual and axiomatized definitions to describe and formalize relations between instances of classes both within the ontology itself as well as between ND and external ontologies such as the: Gene Ontology (GO), Cell Ontology (CL), Protein Ontology (PRO), Chemical Entities of Biological Interest (ChEBI), and Ontology for Biomedical Investigations (OBI).

Proper citation: Neurological disease ontology (RRID:SCR_010284) Copy   

•   Source: SciCrunch Registry

http://code.google.com/p/ogms/

An ontology based on the papers Toward an Ontological Treatment of Disease and Diagnosis and On Carcinomas and Other Pathological Entities to address some of the issues raised at the Workshop on Ontology of Diseases (Dallas, TX) and the Signs, Symptoms, and Findings Workshop (Milan, Italy). OGMS was formerly called the clinical phenotype ontology. Terms from OGMS hang from the Basic Formal Ontology.

Proper citation: Ontology for General Medical Science (RRID:SCR_010384) Copy   

•   Source: SciCrunch Registry

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

Web application that allows users to build and manage online surveys and databases. Using REDCap's stream-lined process for rapidly developing projects, you may create and design projects using 1) the online method from your web browser using the Online Designer; and/or 2) the offline method by constructing a "data dictionary" template file in Microsoft Excel, which can be later uploaded into REDCap. Both surveys and databases (or a mixture of the two) can be built using these methods. REDCap provides audit trails for tracking data manipulation and user activity, as well as automated export procedures for seamless data downloads to Excel, PDF, and common statistical packages (SPSS, SAS, Stata, R). Also included are a built-in project calendar, a scheduling module, ad hoc reporting tools, and advanced features, such as branching logic, file uploading, and calculated fields. REDCap has a quick and easy software installation process, so that you can get REDCap running and fully functional in a matter of minutes. Several language translations have already been compiled for REDCap (e.g. Chinese, French, German, Portuguese), and it is anticipated that other languages will be available in full versions of REDCap soon. The REDCap Shared Library is a repository for REDCap data collection instruments and forms that can be downloaded and used by researchers at REDCap partner institutions.

Proper citation: REDCap (RRID:SCR_003445) Copy   

•   Source: SciCrunch Registry

http://www.cvm.ncsu.edu/ccmtr/

The mission of the CCMTR is to promote scientific discovery and facilitate its clinical application to achieve the goal of improving the health of animals and humans. The needs of the patients direct the emphasis of basic research, patient samples provide the critical resource to investigate the basis of disease, and patient participation in clinical studies is required to generate the evidence needed to apply new drugs, vaccines and technology to the broader patient population. Initiatives at the Center are designed to develop the multidisciplinary teams necessary to bring an idea from the lab to the patient. The Center is home to service cores that provide advanced technology, collect and store clinical patient samples, and perform clinical trials to validate new medical interventions. North Carolina State University''s College of Veterinary Medicine (CVM) is a dynamic community whose members are dedicated to preparing veterinarians and veterinarian scientists while advancing animal and human health from the cellular level through entire ecosystems.

Proper citation: Center for Comparative Medicine and Translational Research (RRID:SCR_008299) Copy   

•   Source: SciCrunch Registry

http://www.rad.upenn.edu/sbia/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on June 2, 2023. A section of the Penn department of radiology, it is devoted to the development of computer-based image analysis methods and their application to clinical research studies. Image analysis methodologies include image registration, segmentation, population-based statistical analysis, biophysical modeling of anatomical deformations, and high-dimensional pattern classification. Clinical research studies spans a variety of clinical areas and organs, and they include brain diseases such as Alzheimer's disease and schizophrenia, evaluation of treatment effects in large clinical trials, diagnosis of cardiac diseases, and diagnosis prostate, breast and brain cancer. SBIA also performs small animal imaging research aiming to understand brain development in mouse models. It has multiple resources which can be accessed by researcher.

Proper citation: SBIA (RRID:SCR_013628) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/cnv-webstore

Integrated platform to analyse, store, visualise and interpret CopyNumber Variation data. Analysis is supported for Illumina data, all CNV-reports and raw data can be imported after third-party analysis. Platform to streamline processing and downstream interpretation of microarray data in clinical context. Analysis tools include CNV analysis, parent of origin and uniparental disomy detection. Interpretation tools include data visualisation, gene prioritisation, automated PubMed searching, linking data to several genome browsers and annotation of CNVs based on several public databases.

Proper citation: CNV webstore (RRID:SCR_018007) Copy   

•   Source: SciCrunch Registry

https://github.com/qiicr/dcmqi

Software library to help with the conversion between imaging research formats and the standard DICOM representation for image analysis results. Used to implement conversion of the data stored in commonly used research formats into the standard DICOM representation. Available as a precompiled binary package for every major operating system, as a Docker image, and as an extension to 3D Slicer.

Proper citation: dcmqi (RRID:SCR_016933) Copy   

•   Source: SciCrunch Registry

https://proteomics.cancer.gov/programs/cptac

Clinical proteomic tumor analysis consortium to systematically identify proteins that derive from alterations in cancer genomes and related biological processes, in order to understand molecular basis of cancer that is not possible through genomics and to accelerate translation of molecular findings into clinic. Operates through Proteome Characterization Centers, Proteogenomic Translational Research Centers, and Proteogenomic Data Analysis Centers. CPTAC investigators collaborate, share data and expertise across consortium, and participate in consortium activities like developing standardized workflows for reproducible studies.

Proper citation: CPTAC (RRID:SCR_017135) Copy   

•   Source: SciCrunch Registry