Tools   Select Another Resource Report Type

http://www.pd-doc.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on December 02, 2011. Notice: This domain name expired on 10/29/11 and is pending renewal or deletion PD-DOC is a portal and a database resource, hosting a database and linking to other databases and data sets of clinical and translational data. PD-DOC functions to organize and facilitate clinical and translational research in Parkinson's disease. The PD-DOC Database contains standardized data collected by user institutions on large numbers of patients with Parkinsons disease and other parkinsonian disorders. In some cases, data is obtained at a single point in time, while in others data is collected repeatedly over time. The PD-DOC Database is composed of the Core Data Set (CDS) which consists of those variables required to be gathered for each subject whose data is entered into the PD-DOC database. In 2005, working groups of Udall Center and invited experts deliberated to establish the components of each CDS section (e.g. General Clinical, Cognitive/Behavioral, Postmortem Brain Neuropathological Findings). The PD-DOC CDS was established and designed to optimize data analyses and data mining for large numbers of subjects participating in a variety of research studies. In most cases corresponding DNA samples are available form the NINDS Human Genetic Repository (at Coriell). Much of the website is publicly available for viewing. To request access to sections of the website dealing with downloading or requesting data, requesting a consultation, or submitting data or other information you will need to register. Before registering, you should read the PD-DOC Policies. Note that PD-DOC data can be used for research purposes only. Once your registration is successfully completed you will be automatically logged into the website.

Proper citation: PD-DOC (RRID:SCR_001596) Copy   

•   Source: SciCrunch Registry

http://drcrnet.jaeb.org/

A collaborative network to facilitate multicenter clinical research of diabetic retinopathy, diabetic macular edema and associated conditions. It supports the identification, design, and implementation of multicenter clinical research initiatives focused on diabetes-induced retinal disorders. Principal emphasis is placed on clinical trials, but epidemiologic outcomes and other research may be supported as well. It currently includes over 109 participating sites (offices) with over 320 physicians throughout the United States. Closed and active studies are listed along with the associated protocols, public datasets, and publications.

Proper citation: Diabetic Retinopathy Clinical Research Network (RRID:SCR_001514) Copy   

•   Source: SciCrunch Registry

http://www.niddklabs.org

Consortium comprised of six clinical centers and a data coordinating center to facilitate coordinated clinical, epidemiological, and behavioral research in the field of bariatric surgery, through the cooperative development of common clinical protocols and a bariatric surgery database that will collect information from participating clinical centers. LABS will help pool the necessary clinical expertise and administrative resources to facilitate the conduct of multiple clinical studies in a timely, efficient manner. Also, the use of standardized definitions, clinical protocols, and data-collection instruments will enhance the investigator's ability to provide meaningful evidence-based recommendations for patient evaluation, selection, and follow-up care. The consortium was funded in September 2003. The investigators have collaboratively developed a core database and clinical protocols, and subject enrollment began in early 2005. A repository of data and biological specimens for future research also will be collected by the centers participating in LABS. These will provide valuable resources for future study of obesity and its complications.

Proper citation: Longitudinal Assessment of Bariatric Surgery (RRID:SCR_001536) Copy   

•   Source: SciCrunch Registry

http://www.va.gov/visn4mirecc/

The mission of the VISN 4 MIRECC is the treatment and prevention of comorbid medical, mental health, and/or substance use disorders, with the aim of improving the health, quality of life, and outcomes of healthcare services for veterans with mental illness. This is accomplished through the integration of basic, clinical, and services research and educational and clinical programs. The objectives of this MIRECC are: * Develop new empirical knowledge that can be directly applied to improve the clinical care of veterans * Provide education to providers and trainees to enhance the delivery of high quality healthcare to veterans * Impact public health in terms of veterans' mental health and quality of life * Serve as a national resource in education, research, and treatment of patients with comorbidity, and as a replicable model of excellence in clinical and educational programs Examine causal factors in the development of comorbid conditions. Assess impact of comorbidity on: * the identification and classification of disorders * the development and implementation of treatments * access to treatment and the impact of treatments on outcomes Sponsors: This work is supported by the US Department of Veterans Affairs

Proper citation: VISN 4 MIRECC (RRID:SCR_001970) Copy   

•   Source: SciCrunch Registry

http://qnl.bu.edu/obart

Tool that provides an interactive method to examine quantitative relationships between brain regions defined by different digital atlases or parcellation methods. Its current focus is for human brain imaging, though the techniques generalize to other domains. The method offers a quantitative answer to the nomenclature problem in neuroscience by comparing brain parts on the basis of their geometrical definitions rather than on the basis of name alone. Thus far these tools have been used to quantitatively compare eight distinct parcellations of the International Consortium for Brain Mapping (ICBM) single-subject template brain, each created using existing atlasing methods. This resources provides measures of global and regional similarity, and offers visualization techniques that allow users to quickly identify the correspondences (or lack of correspondences) between regions defined by different atlases.

Proper citation: OBART (RRID:SCR_001903) Copy   

•   Source: SciCrunch Registry

https://www.mdcalc.com/calc/715/nih-stroke-scale-score-nihss

The National Institutes of Health Stroke Scale (NIHSS) is a systematic assessment tool that provides a quantitative measure of stroke-related neurological deficit. The NIHSS was originally designed as a research tool to measure baseline data on patients in acute stroke clinical trials. Now, the scale is also widely used as a clinical assessment tool to evaluate acuity of stroke patients, determine appropriate treatment, and predict patient outcome. The NIHSS can be used as a clinical stroke assessment tool to evaluate and document neurological status in acute stroke patients. The stroke scale is valid for predicting lesion size and can serve as a measure of stroke severity. The NIHSS has been shown to be a predictor of both short and long term outcome of stroke patients. Additionally, the stroke scale serves as a data collection tool for planning patient care and provides a common language for information exchanges among healthcare providers. Performing the scale takes between 5-8 minutes. Emergency physicians and nurses, neurologists, neuroscience nurses and other stroke team members are typical examples of who should be certified to perform the NIHSS. The NINDS/NIH training and testing DVD can be obtained from the National Institute of Neurological Disorders and Stroke. Sponsors: NIHSS is supported by the National Institute of Neurological Disorders and Stroke (NINDS).

Proper citation: National Institutes of Health Stroke Scale (RRID:SCR_001804) Copy   

•   Source: SciCrunch Registry

http://www.aspergillus-genomes.org.uk/

A resource for viewing annotated genes arising from various Aspergillus sequencing and annotation projects, resulting from the merging of Central Aspergillus Data REpository (CADRE) and The Aspergillus Website, which took place in June 2008. The principal role of CADRE is to aid the Aspergillus research community by managing Aspergillus genome data and by providing visualization tools, ranging from relatively simple annotation displays to more complex data integration displays. In contrast, The Aspergillus Website provides a range of information to the medical community (i.e., clinicians, patients and scientists) regarding the genus Aspergillus and the diseases, such as Aspergillosis, that it can cause. CADRE has been implemented using the Ensembl v22 suite. This suite comprises: * a database schema, which has been devised for storing annotated eukaryotic genomes. The schema is implemented with the MySQL relational database management system. * several specialized programming modules for building interfaces (i.e., BioPerl and Ensembl API modules). * a series of programs (i.e., Perl CGI scripts using the API modules) for viewing genomic data within a web browser., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Aspergillus Genomes (RRID:SCR_001880) Copy   

•   Source: SciCrunch Registry

https://meded.ucsd.edu/index.cfm/asa/dcp/goddp/

The UCSD School of Medicine are dedicated to producing future leaders in all areas of medicine. As such, the School promotes the pursuit of dual degrees, either in the Medical School's own graduate degree programs or programs offered in other disciplines in the institution. In addition to the study of medicine, the School of Medicine actively encourages its student body to explore broadly in various scholarly areas related to the biomedical sciences. The goal of this additional training is to produce graduates who will bring fresh, innovative ideas to the research laboratory, the public health sector, the humanities and the social sciences, and the business environment. Students may elect to obtain advanced degrees in the following areas: * Biomedical Sciences * Masters in Bioengineering * Masters in Public Health * Masters in Leadership of Health Care Organizations * Masters of Advanced Studies in Clinical Research * Ph.D. Program in the Humanities and Social Sciences * Independent Ph.D. programs Opportunities for enrollment in research or degree programs outside of UCSD are also available, and students are encouraged to investigate these, if interested. Sponsors: This program is supported by the University of California at San Diego.

Proper citation: University of California at San Diego, School of Medicine: Graduate Opportunities & Dual Degree Programs (RRID:SCR_001942) Copy   

•   Source: SciCrunch Registry

http://library.med.utah.edu/WebPath/webpath.html#MENU

This popular web resource includes over 1900 images along with text, tutorials, laboratory exercises, and examination items for self-assessment that demonstrate gross and microscopic pathologic findings associated with human disease conditions. Content includes pathology cases (surgical pathology, autopsy, cytopathology, forensic pathology, clinical pathology) at the University of Utah Health Sciences Center and affiliated hospitals and laboratories, and from contributors at other institutions worldwide. The content at this web site will assist a medical student in achievement of an important goal: passing step 1 of the USMLE examination required to become licensed as a physician. This site was conceived from the necessity to create useful multimedia teaching resources for medical students at the University of Utah for use in the pathology courses given in the second year of the curriculum.

Proper citation: WebPath - The Internet Pathology Laboratory for Medical Education (RRID:SCR_002033) Copy   

•   Source: SciCrunch Registry

http://www.bioon.com/bioline/neurosci/course/index.htm

An illustrated guide to the essential basics of clinical neuroscience created in conjunction with the first-year course for medical students.
Topics covered:
* Coronal and horizontal sections
* Basic visual pathway
* Basic somatosensory pathway
* Basic motor pathway
* Eye and retina
* Central visual pathways
* Auditory and vestibular systems
* Somatosensory pathways from the body
* Somatosensory pathways from the face
* Spinal motor structures
* Brainstem nuclei of cranial nerves
* Basal ganglia and cerebellum
* Hypothalamus and autonomic nervous system
* Medial temporal lobe and memory
* Sleep and language
* Where is...?

Proper citation: Washington University School of Medicine Neuroscience Tutorial (RRID:SCR_002271) Copy   

•   Source: SciCrunch Registry

http://www.humgen.rwth-aachen.de/

Catalog of all changes detected in PKHD1 (Polycystic Kidney and Hepatic Disease 1) in a locus specific database. Investigators are invited to submit their novel data to this database. These data should be meaningful for clinical practice as well as of relevance for the reader interested in molecular aspects of polycystic kidney disease (PKD). There are also some links and information for ARPKD patients and their parents. Autosomal recessive polycystic kidney disease (ARPKD/PKHD1) is an important cause of renal-related and liver-related morbidity and mortality in childhood. This study reports mutation screening in 90 ARPKD patients and identifies mutations in 110 alleles making up a detection rate of 61%. Thirty-four of the detected mutations have not been reported previously. Two underlying mutations in 40 patients and one mutation in 30 cases are disclosed, and no mutation was detected on the remaining chromosomes. Mutations were found to be scattered throughout the gene without evidence of clustering at specific sites. PKHD1 mutation analysis is a powerful tool to establish the molecular cause of ARPKD in a given family. Direct identification of mutations allows an unequivocal diagnosis and accurate genetic counseling even in families displaying diagnostic challenges.

Proper citation: Autosomal Recessive Polycystic Kidney Disease Mutation Database (RRID:SCR_002290) Copy   

•   Source: SciCrunch Registry

https://datashare.nida.nih.gov

Website which allows data from completed clinical trials to be distributed to investigators and public. Researchers can download de-identified data from completed NIDA clinical trial studies to conduct analyses that improve quality of drug abuse treatment. Incorporates data from Division of Therapeutics and Medical Consequences and Center for Clinical Trials Network.

Proper citation: NIDA Data Share (RRID:SCR_002002) Copy   

•   Source: SciCrunch Registry

http://www.biomarkersconsortium.org/

Consortium serving to develop and qualify promising biomarkers in order to help accelerate the delivery of successful new technologies, medicines and therapies for prevention, early detection, diagnosis and treatment of disease. Current core disease areas of focus include Cancer, Inflammation and Immunity, Metabolic Disorders, and Neuroscience. One of the most difficult tasks facing biomarker assessment and evaluation is harmonizing the approaches of various stakeholders--government, industry, non-profits and foundations, providers, and academic institutions. Consortium founding members and other partners recognize the critical need for a coordinated cross-sector partnership effort. The Biomarkers Consortium brings together the expertise and resources of various partners to rapidly identify, develop, and qualify potential high-impact biomarkers. Biomarkers Consortium Goals: * Facilitate the development and qualification of biomarkers using new and existing technologies; * Help qualify biomarkers for specific applications in diagnosing disease, predicting therapeutic response or improving clinical practice; * Generate information useful to inform regulatory decision making; * Make consortium project results broadly available to the entire scientific community.

Proper citation: Biomarkers Consortium (RRID:SCR_003121) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/XCO

An ontology designed to represent the conditions under which physiological and morphological measurements are made both in the clinic and in studies involving humans or model organisms.

Proper citation: Experimental Conditions Ontology (RRID:SCR_003306) Copy   

•   Source: SciCrunch Registry

http://www.humanvariomeproject.org/

Project facilitating the establishment and maintenance of standards systems and infrastructure for the worldwide collection and sharing of all genetic variations effecting human disease. The Human Variome Project produces two categories of recommendations: HVP Standards and HVP Guidelines. HVP Standards are those systems, procedures and technologies that the Human Variome Project Consortium has determined should be used by the community. These carry more weight than the less prescriptive HVP Guidelines, which cover those systems, procedures and technologies that the Human Variome Project Consortium has determined would be beneficial for the community to adopt. HVP Standards and Guidelines are central to supporting the work of the Human Variome Project Consortium and cover a wide range of fields and disciplines, from ethics to nomenclature, data transfer protocols to collection protocols from clinics. They can be thought of as both technical manuals and scientific documents, and while the impact of HVP Standards and Guidelines differ, they are both generated in a similar fashion. A document has been generated both as a guide for those collecting and distributing data and for those developing policy. Items should include those generated by HGVS/HVP collaborators as well as those generated by groups of individual Societies and Standards bodies in all relevant fields worldwide.

Proper citation: Human Variome Project (RRID:SCR_003492) Copy   

•   Source: SciCrunch Registry

http://www.i2b2cictr.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on February 08, 2013. A two year Clinical and Translational Science Award (CTSA) supplement that set up a SHRINE (Shared Health Research Informatics NEtwork) network to create an information exchange environment that successfully shared 4.2M deidentified patient records. The network successfully linked i2b2 sites at UW, UCSF, UC Davis and Harvard Catalyst. Recombinant Data Corporation was actively involved in this implementation. This is a collaborative information exchange pilot project to adapt and extend data discovery tools and processes to enhance research design and retrospective data study capabilities for clinical translational investigators. The novel approach of this project will be to incrementally build a common technical, semantic and appropriately secure and governed distributed system in close partnership with active researchers at three large and geographically distributed academic medical centers. This collaboration will extend the Informatics for Integrating Biology and the Bedside (i2b2) software architecture developed by the Harvard based National Center for Biomedical Computing (NCBC) to support multi-institution data query capabilities. The anticipated outcome of this two-year project is to make high-level anonymized descriptive characteristics of population-level data discoverable for research design, hypothesis generation and retrospective data studies.

Proper citation: i2b2 Cross-Institutional Clinical Translational Research project (RRID:SCR_003367) Copy   

•   Source: SciCrunch Registry

http://www.pediatricmri.nih.gov/

Data sets of clinical / behavioral and image data are available for download by qualified researchers from a seven year, multi-site, longitudinal study using magnetic resonance technologies to study brain maturation in healthy, typically-developing infants, children, and adolescents and to correlate brain development with cognitive and behavioral development. The information obtained in this study is expected to provide essential data for understanding the course of normal brain development as a basis for understanding atypical brain development associated with a variety of developmental, neurological, and neuropsychiatric disorders affecting children and adults. This study enrolled over 500 children, ranging from infancy to young adulthood. The goal was to study each participant at least three times over the course of the project at one of six Pediatric Centers across the United States. Brain MR and clinical/behavioral data have been compiled and analyzed at a Data Coordinating Center and Clinical Coordinating Center. Additionally, MR spectroscopy and DTI data are being analyzed. The study was organized around two objectives corresponding to two age ranges at the time of enrollment, each with its own protocols. * Objective 1 enrolled children ages 4 years, 6 months through 18 years (total N = 433). This sample was recruited across the six Pediatric Study Centers using community based sampling to reflect the demographics of the United States in terms of income, race, and ethnicity. The subjects were studied with both imaging and clinical/behavioral measures at two year intervals for three time points. * Objective 2 enrolled newborns, infants, toddlers, and preschoolers from birth through 4 years, 5 months, who were studied three or more times at two Pediatric Study Centers at intervals ranging from three months for the youngest subjects to one year as the children approach the Objective 1 age range. Both imaging and clinical/behavioral measures were collected at each time point. Participant recruitment used community based sampling that included hospital venues (e.g., maternity wards and nurseries, satellite physician offices, and well-child clinics), community organizations (e.g., day-care centers, schools, and churches), and siblings of children participating in other research at the Pediatric Study Centers. At timepoint 1, of those enrolled, 114 children had T1 scans that passed quality control checks. Staged data release plan: The first data release included structural MR images and clinical/behavioral data from the first assessments, Visit 1, for Objective 1. A second data release included structural MRI and clinical/behavioral data from the second visit for Objective 1. A third data release included structural MRI data for both Objective 1 and 2 and all time points, as well as preliminary spectroscopy data. A fourth data release added cortical thickness, gyrification and cortical surface data. Yet to be released are longitudinally registered anatomic MRI data and diffusion tensor data. A collaborative effort among the participating centers and NIH resulted in age-appropriate MR protocols and clinical/behavioral batteries of instruments. A summary of this protocol is available as a Protocol release document. Details of the project, such as study design, rationale, recruitment, instrument battery, MRI acquisition details, and quality controls can be found in the study protocol. Also available are the MRI procedure manual and Clinical/Behavioral procedure manuals for Objective 1 and Objective 2.

Proper citation: NIH MRI Study of Normal Brain Development (RRID:SCR_003394) Copy   

•   Source: SciCrunch Registry

http://www.eyemoviepedia.com/

Archive and access films from the field of Ophthalmology for free on highly secure servers for permanent access and citeability. A citeable identification number (specific addressing using DOI), allows for citation of individual films in journal publications. Films may be commented by the author either in speech, or in text. Key wording provided by the authors at the time of submission, make each film recognizable to internet search machines.

Proper citation: eyeMoviePedia (RRID:SCR_003541) Copy   

•   Source: SciCrunch Registry

http://clinicalinformatics.stanford.edu/projects/cdw.html

Research and development project at Stanford University to create a standards-based informatics platform supporting clinical and translational research. STRIDE consists of three integrated components: a clinical data warehouse, based on the HL7 Reference Information Model (RIM), containing clinical information on over 1.6 million pediatric and adult patients cared for at Stanford University Medical Center since 1995; an application development framework for building research data management applications on the STRIDE platform and a biospecimen data management system. STRIDE's semantic model uses standardized terminologies, such as SNOMED, RxNorm, ICD and CPT, to represent important biomedical concepts and their relationships. STRIDE receives clinical data for research use via HL7 feeds from both SUMC hospitals: Lucile Packard Children's Hospital and Stanford Hospital and Clinics. This clinical data is used to support a wide variety of translational research services including: * Anonymized Patient Research Cohort Discovery * Electronic Chart Review for Research * IRB-Approved Clinical Data Extraction * Biospecimen Data Management * Multimedia Research * Data Management and Research Registries STRIDE is a highly secure environment utilizing encryption, fine-grained access control, robust auditing and detailed data segregation. Additionally, STRIDE has a robust access control framework with well-defined access granting authorities and access control groups. Consequently STRIDE meets or exceeds the requirements of the HIPAA Privacy and Security regulations. Privacy protection is further enhanced by requiring IRB approval for all research projects using STRIDE clinical data. From a technology and standards perspective, STRIDE is hosted on the Oracle 11g database platform. STRIDE application software provides access to the web services of a three-tier infrastructures using SSL encryption with strong authentication. These programs are cross-platform, self-updating thick-client applications that provides a rich user interface for data entry, retrieval and review as well as image manipulation and annotation. STRIDE makes extensive use of XML technologies for representation of structured meta data, distributed systems technologies using JSON for secure remote communication between client and server, and Swing graphical interface components providing a rich widget-set as well as advanced imaging and graphing capabilities. Users of the STRIDE Research Desktop Client can perform rapid data entry into structured fields, compose complex queries, and interact securely with clinical, research and imaging data.

Proper citation: Stanford Translational Research Integrated Database Environment and Clinical Data Warehouse (RRID:SCR_003453) Copy   

•   Source: SciCrunch Registry

http://www.nih.gov/science/amp/alzheimers.htm

The Alzheimer's disease arm of the Accelerating Medicines Partnership (AMP) that will identify biomarkers that can predict clinical outcomes, conduct a large scale analysis of human AD patient brain tissue samples to validate biological targets, and to increase the understanding of molecular pathways involved in the disease to identify new potential therapeutic targets. The initiative will deposit all data in a repository that will be accessible for use by the biomedical community. The five year endeavor, beginning in 2014, will result in several sets of project outcomes. For the biomarkers project, tau imaging and EEG data will be released in year two, as baseline data becomes available. Completed data from the randomized, blinded trials will be added after the end of the five year studies. This will include both imaging data and data from blood and spinal fluid biomarker studies. For the network analysis project, each project will general several network models of late onset AD (LOAD) and identify key drivers of disease pathogensis by the end of year three. Years four and five will be dedicated to validating the novel targets and refining the network models of LOAD, including screening novel compounds or drugs already in use for other conditions that may have the ability to modulate the likely targets.

Proper citation: Accelerating Medicines Partnership - Alzheimers (RRID:SCR_003742) Copy   

•   Source: SciCrunch Registry