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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

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://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

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://talkbank.org/

Databases of transcript and media data collected from conversations with adults and older children to foster fundamental research in the study of human and animal communication. Conversations with children are available from CHILDES. All of the data is transcribed in CHAT and CA/CHAT formats. Databases of the following types are included in the collection: Aphasia patient speech, Child speech, Study of Phonological Development, Conversation Analysis, and Bilingualism and Second Language Acquisition. TalkBank will use these databases to advance the development of standards and tools for creating, sharing, searching, and commenting upon primary materials via networked computers.

Proper citation: TalkBank (RRID:SCR_003242) 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.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

http://www.cimit.org/

A non-profit consortium of Boston academic medical centers and universities (and growing) to accelerate the healthcare innovation cycle by fostering interdisciplinary, inter-institutional collaboration among experts in translational research, medicine, science, engineering, healthcare implementation and entrepreneurship in concert with industry, foundations and government to rapidly improve patient care. It concentrates on early stage, high-risk ideas, projects and supports them through to a commercial exit from academia. It provides innovators with resources to explore, develop and implement novel technological solutions for today's most urgent healthcare problems. CIMIT is dedicated to helping develop medical technology that will help both military and civilian patients.

Proper citation: Center for Integration of Medicine and Innovative Technology (RRID:SCR_003710) Copy   

•   Source: SciCrunch Registry

http://www.atheroremo.org/

Project targeting vulnerable plaques causing unexpected acute myocardial infarcts and sudden cardiac deaths by identifying and validating novel drug targets as well as devising and validating diagnostic tests. It has been designed to advance the present knowledge on the role of inflammatory remodeling in the different stages of atherosclerosis. It will also provide important knowledge for the development of strategies for prevention and clinical management of vascular diseases.

Proper citation: AtheroRemo (RRID:SCR_003831) Copy   

•   Source: SciCrunch Registry

http://c3nproject.org/

Project designing, prototyping, optimizing, and evaluating a learning health system to improve clinical practice, patient self-management, and disease outcomes of patients with chronic illness. This open, peer production system combines the collective input of patients, clinicians and researchers. It combines large clinical data registries with patient entered data and makes them accessible and interactive. A platform allows researchers to design, test and implement new knowledge and innovations in patient care. To test their platform approach, C3N is working on a model of treating children with Inflammatory Bowel Disease using the ImproveCareNow Network of pediatric clinics. Following this demonstration phase, the goal is to apply the social, scientific and technical platform to transform the care of a variety of chronic illnesses. The C3N effort has the following goals: # Deploy and optimize an integrated set of engagement tools to make it easier for patients and care providers to collect and use the right information during the clinical encounter and in between visits. # Prototype novel interventions to re-design care delivery by promoting the development of tools for real-time and dynamic population management, "just-in time" scheduling of visits, virtual clinic visits, and measuring the impact of these interventions on health, care, and cost. # Pilot and deploy patient-focused technology to improve the flow of data between patients, clinicians and scientists to enable faster learning and improvement.

Proper citation: Collaborative Chronic Care Network (RRID:SCR_003708) Copy   

•   Source: SciCrunch Registry

http://www.innomed-addneuromed.com/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 9,2023. Project portal for a cross European study designed to find biomarkers, or tests, for Alzheimer's disease. Its objectives are to produce and improve experimental models of Alzheimer's for biomarker discovery and to identify a biomarker for Alzheimer's disease suitable for diagnosis, prediction, and monitoring disease progression for use in clinical trials and in clinical practice. The baseline dataset database was scheduled to be completed and locked in 2008 and become available to researchers by 2009. Requests to access the data will be reviewed by the scientific projects committee.

Proper citation: AddNeuroMed (RRID:SCR_003819) Copy   

•   Source: SciCrunch Registry

http://www.mrc-cbu.cam.ac.uk/

Unit studying human cognition and the brain with about 90 researchers and postgraduate students investigating topics such as attention, emotion, language and memory. They are developing new treatments for depression, improving hearing through cochlear implants, and helping children to overcome memory problems. With a large collection of scientists engaged in both basic and translational research on the mind and brain, the Unit provides an exceptional training and academic environment that benefits postgraduate students and researchers at all levels. A significant part of their research makes use of brain imaging and they have excellent on-site facilities for magnetic resonance imaging (MRI) magnetoencephalography (MEG) and electroencephalography (EEG). They also have clinical facilities at Addenbrooke's Hospital. The Unit has close links both with the hospital and with Cambridge University.

Proper citation: MRC Cognition and Brain Sciences Unit (RRID:SCR_003818) Copy   

•   Source: SciCrunch Registry

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

A public-private partnership to identify new and improved translational safety testing methods for use in nonclinical and clinical studies and submit them for formal regulatory qualification by the FDA (Food and Drug Administration), EMA (European Medicines Agency), and PMDA (Japanese Pharmaceutical and Medical Devices Agency). The current 19 corporate members of the consortium share internal experience with nonclinical and clinical safety biomarkers in six working groups: cardiac hypertrophy, nephrotoxicity, hepatotoxicity, skeletal myopathy, testicular toxicity, and vascular injury. The ultimate goal of the consortium is to improve the current approach to drug safety testing and offer assurance to the drug developers that these approaches will be accepted by the regulatory authorities in their drug development programs. Through PSTC, members are able to share their expertise, resources, data, and internally developed approaches in a neutral, precompetitive, confidential environment. There are more than 250 participating scientists and C-Path serves as the trusted third party, leading the collaborative process by collecting and summarizing the data, and leading the interactions with global health authorities.

Proper citation: Predictive Safety Testing Consortium (RRID:SCR_003727) Copy   

•   Source: SciCrunch Registry

http://ispy2.org/

A collaboration to test an adaptive clinical trial model that would assess the efficacy of a candidate therapeutic earlier than traditional clinical trials, potentially enabling drugs to be developed and approved using fewer patients, less time and fewer resources. This trial focuses on women with newly diagnosed locally advanced breast cancer to test whether adding investigational drugs to standard chemotherapy is better than standard chemotherapy alone. It uses genetic and biological markers from individual patients' tumors to screen several promising new treatments simultaneously and allows doctors to quickly measure the effectiveness of the treatment prior to removing the tumor. The experimental adaptive trial design uses patient outcomes to immediately inform treatment options for subsequent trial participants. The trial has 5 components that differentiate it from conventional clinical trial models. # I-SPY2 uses tissue and imaging biomarkers from individual cancer patients' tumors to determine eligibility, guide/screen promising new treatments and identify which treatments are most effective in specific tumor subtypes. # The trial's adaptive design allows the Team to learn as they go, enabling researchers to use data from patients early in the trial to guide decisions about which treatments might be more useful for patients who enter the trial earlier. I-SPY2 provides a scientific basis for researchers to eliminate ineffective treatments and graduate effective treatments more quickly. # The neoadjuvant treatment approach - in which chemotherapy is given to patients prior to surgery - allow the team to evaluate tumor response with MRI before removal. This approach is safe as treating after surgery, allowing tumors to shrink, and more importantly, it enables critical learning early on about how well treatments work. # The ability for the team to screen multiple drug candidates developed by multiple companies. New agents will be selected and added as those used initially and either graduate to Phase III, or are dropped, based on their efficacy in targeted patients. # The trials informatics system allows data to be collected, verified, and shared in real-time. This allows data to be assessed early and in an integrated fashion - with an aim to enhance and encourage collaboration

Proper citation: I-SPY 2 TRIAL (RRID:SCR_003713) Copy   

•   Source: SciCrunch Registry

http://dc-research.eu/

An open knowledge resource for the dendritic cell research community, this index of research assets and expertise is designed to support translational research by providing annotations and interrelations on materials, datasets, tools, techniques, persons and organizations. The content of DC-RESEARCH.EU can be accessed by researchers through its website and can be accessed programmatically: the information in DC-RESEARCH.EU is represented through machine processable languages, proper of the Semantic Web (RDF and RDFa). To submit to the dc-thera directory please contact: dc-research_at_leafbioscience.com

Proper citation: DC-Research.eu - Dendritic Cell Research Knowledge Portal (RRID:SCR_004200) Copy   

•   Source: SciCrunch Registry

http://www.transformproject.eu/portfolio-item/d6-3-data-integration-models/

A set of three models, which in conjunction with the semantic mediator enables the execution of queries formulated through the eligibility representation of the Clinical research information model (WT6.4). An ontology-driven mechanism was developed to enable linkage and integration of phenotypic and genotypic data from multiple distributed data sources. It makes use of the Clinical Data Integration Model (CDIM, WT6.5), the Data Source Model (DSM, WT6.6) and the CDIM-DSM mapping model (WT6.6). Queries formulated through the CDIM and vocabulary service (WT7.2) are translated to local queries by the mediator using the individual source instances of the DSM and CDIM-DSM models.

Proper citation: TRANSFoRm Data Integration Models (RRID:SCR_003892) Copy   

•   Source: SciCrunch Registry