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https://www.immport.org/home

Data sharing repository of clinical trials, associated mechanistic studies, and other basic and applied immunology research programs. Platform to store, analyze, and exchange datasets for immune mediated diseases. Data supplied by NIAID/DAIT funded investigators and genomic, proteomic, and other data relevant to research of these programs extracted from public databases. Provides data analysis tools and immunology focused ontology to advance research in basic and clinical immunology.

Proper citation: The Immunology Database and Analysis Portal (ImmPort) (RRID:SCR_012804) Copy   

•   Source: SciCrunch Registry

http://i2b2.cchmc.org/

A data warehouse that integrates information on patients from multiple sources and consists of patient information from all the visits to Cincinnati Children''''s between 2003 and 2007. This information includes demographics (age, gender, race), diagnoses (ICD-9), procedures, medications and lab results. They have included extracts from Epic, DocSite, and the new Cerner laboratory system and will eventually load public data sources, data from the different divisions or research cores (such as images or genetic data), as well as the research databases from individual groups or investigators. This information is aggregated, cleaned and de-identified. Once this process is complete, it is presented to the user, who will then be able to query the data. The warehouse is best suited for tasks like cohort identification, hypothesis generation and retrospective data analysis. Automated software tools will facilitate some of these functions, while others will require more of a manual process. The initial software tools will be focused around cohort identification. They have developed a set of web-based tools that allow the user to query the warehouse after logging in. The only people able to see your data are those to whom you grant authorization. If the information can be provided to the general research community, they will add it to the warehouse. If it cannot, they will mark it so that only you (or others in your group with proper approval) can access it.

Proper citation: i2b2 Research Data Warehouse (RRID:SCR_013276) Copy   

•   Source: SciCrunch Registry

http://www.geworkbench.org

geWorkbench (genomics Workbench) is a Java-based open-source platform for integrated genomics. Using a component architecture it allows individually developed plug-ins to be configured into complex bioinformatic applications. At present there are more than 70 available plug-ins supporting the visualization and analysis of gene expression and sequence data. Example use cases include: * loading data from local or remote data sources. * visualizing gene expression, molecular interaction networks, protein sequence and protein structure data in a variety of ways. * providing access to client- and server-side computational analysis tools such as t-test analysis, hierarchical clustering, self organizing maps, regulatory networks reconstruction, BLAST searches, pattern/motif discovery, etc. * validating computational hypothesis through the integration of gene and pathway annotation information from curated sources as well as through Gene Ontology enrichment analysis. geWorkbench is the Bioinformatics platform of MAGNet, the National Center for the Multi-scale Analysis of Genomic and Cellular Networks (one of the 7 National Centers for Biomedial Computing funded through the NIH Roadmap). Additionally, geWorkbench is supported by caBIG, NCI''s cancer Biomedical Informatics Grid initiative.

Proper citation: genomics Workbench (RRID:SCR_013599) Copy   

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http://www.metabolomicsworkbench.org

Repository for metabolomics data and metadata which provides analysis tools and access to various resources. NIH grantees may upload data and general users can search metabolomics database. Provides protocols for sample preparation and analysis, information about NIH Metabolomics Program, data sharing guidelines, funding opportunities, services offered by its Regional Comprehensive Metabolomics Resource Cores (RCMRC)s, and training workshops.

Proper citation: Metabolomics Workbench (RRID:SCR_013794) Copy   

•   Source: SciCrunch Registry

http://www.ohsu.edu/xd/health/services/brain/

A clinical care and research center for neurological conditions such as Alzheimer's, dementia and seizure disorders. It provides a dynamic setting for training healthcare professionals and neuroscience researchers to develop and implement evidence-based treatment.

Proper citation: OHSU Brain Institute (RRID:SCR_008932) Copy   

•   Source: SciCrunch Registry

http://cbfbirn.ucsd.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented August 23, 2017.

A web based central repository for individual and group analysis of Arterial Spin Labeling (ASL) data sets and ASL pulse sequences developed at CMFRI UCSD for MRI researchers. This resource currently hosts more 1300 ASL data sets from 22 projects and consists of mainly two main tools 1) The Cerebral Blood Flow Database and Analysis Pipeline (CBFDAP) is a web enabled data and workflow management system extended from the HID codebase on NITRC specialized for Arterial Spin Labeling data management and analysis (including group analysis) in a centralized manner. 2) Pulse Sequence Distribution System (PSDS) for managing dissamination of ASL pulse sequences developed at the UCSD CFMRI. This resource also includes web and video tutorials for end users.

Proper citation: CBFBIRN (RRID:SCR_009543) Copy   

•   Source: SciCrunch Registry

http://www.usidnet.org/

Research consortium to advance scientific research in the primary immune deficiency diseases (PIDD) and: * Assemble and maintain a registry of patients with primary immunodeficiency diseases to provide a minimum estimate of the prevalence of each disorder in the United States. Provide a comprehensive clinical picture of each disorder and act as a resource for clinical and laboratory research. * Establish a multifaceted mentoring program to introduce new investigators into the field and stimulate interest and research in primary immune deficiency diseases. * Establish an advisory/review committee to maintain a cell/DNA Repository of biologic material from well-characterized PIDD patients for the advancement of scientific research USIDNET operates a large database of patient information for your use. The purpose and scope of this project is to assemble and maintain a registry of residents with primary immunodeficiency diseases. The project was started with the Registry of U.S. Residents with Chronic Granulomatous Disease. Since then, the registry has been expanded and now collects data on all primary immunodeficiency disorders. The following are just a few of the diseases housed in the registry: Chronic Granulomatous Disease, Common Variable Immunodeficiency Disease, DiGeorge Anomaly, Hyper IgM Syndrome, Leukocyte Adhesion Defect, Severe Combined Immunodeficiency Disease, Wiskott-Aldrich Syndrome, X-Linked Agammaglobulinemia Physicians who would like to register their patients or access the registry are encouraged to contact Onika Davis or Lamar Hamilton, USIDNET team, at odavis (at) primaryimmune.org, or lhamilton (at) primaryimmune.org

Proper citation: USIDNET: US Immunodeficiency Network (RRID:SCR_004672) Copy   

•   Source: SciCrunch Registry

http://em.emory.edu/protect/index.cfm

Recently, our team completed an NINDS-funded, Phase IIa double-blinded, placebo-controlled pilot clinical trial that examined the pharmacokinetics, safety, and activity of progesterone, a steroid found to have powerful neuroprotective effects in multiple animal models of brain injury. Our pilot study demonstrated a 50% reduction in death among severe TBI patients and less disability among moderate TBI patients treated with progesterone. Based on these promising results and supportive preclinical data, we are conducting a large, phase III clinical trial (ProTECT III) to definitively assess the safety and efficacy of this treatment for adults with moderate to severe acute TBI. The study is slated to begin August 2008. WHY Progesterone: Although progresterone is widely considered a sex steroid, it is also a potent neurosteroid. Progesterone is naturally synthesized in the CNS. A large and growing body of animal studies indicate that early administration of progesterone after TBI reduces cerebral edema, neuronal loss, and behavioral deficits in laboratory animals. Certain properties of progesterone make it an ideal therapeutic candidate. First, in contrast to most drugs tested to date, progesterone rapidly enters the brain and reaches equilibrium with the plasma within an hour of administration. Second, unlike other experimental agents, progesterone has a long history of safe use in humans. Finally, the findings of our pilot clinical trial (presented in the Preliminary Data Section, below) indicate that progesterone has consistent and predictable pharmacokinetic properties, is unlikely to produce harm, and may be efficacious for treating acute TBI in humans.

Proper citation: ProTECT (RRID:SCR_004531) Copy   

•   Source: SciCrunch Registry

http://krasnow1.gmu.edu/cn3/hippocampus3d/

Data files for a high resolution three dimensional (3D) structure of the rat hippocampus reconstructed from histological sections. The data files (supplementary data for Ropireddy et al., Neurosci., 2012 Mar 15;205:91-111) are being shared on the Windows Live cloud space provided by Microsoft. Downloadable data files include the Nissl histological images, the hippocampus layer tracings that can be visualized alone or superimposed to the corresponding Nissl images, the voxel database coordinates, and the surface rendering VRML files. * Hippocampus Nissl Images: The high resolution histological Nissl images obtained at 16 micrometer inter-slice distance for the Long-Evans rat hippocampus can be downloaded or directly viewed in a browser. This dataset consists of 230 jpeg images that cover the hippocampus from rostral to caudal poles. This image dataset is uploaded in seven parts as rar files. * Hippocampus Layer Tracings: The seven hippocampus layers ''ML, ''GC'', ''HILUS'' in DG and ''LM'', ''RAD'', ''PC'', ''OR'' in CA were segmented (traced) using the Reconstruct tool which can be downloaded from Synapse web. This tool outputs all the tracings for each image in XML format. The XML tracing files for all these seven layers for each of the above Nissl images are zipped into one file and can be downloaded. * Hippocampus VoxelDB: The 3D hippocampus reconstructed is volumetrically transformed into 16 micrometer sized voxels for all the seven layers. Each voxel is reported according to multiple coordinate systems, namely in Cartesian, along the natural hippocampal dimensions, and in reference to the canonical brain planes. The voxel database file is created in ascii format. The single voxel database file was split into three rar archive files. Please note that the three rar archive files should be downloaded and decompressed in a single directory in order to obtain the single voxel data file (Hippocampus-VoxelDB.txt). * 3D Surface Renderings: This is a rar archive file with a single VRML file containing the surface rendering of DG and CA layers. This VRML file can be opened and visualized in any VRML viewer, e.g. the open source software view3dscene. * 3D Hippocampus Movie: This movie contains visualization of the 3D surface renderings of CA (blue) and DG (red) inner and outer boundaries; neuronal embeddings of DG granule and CA pyramidal dendritic arbors; potential synapses between CA3b interneuron axon and pyramidal dendrite, and between CA2 pyramidal axon and CA pyramidal dendrites.

Proper citation: Hippocampus 3D Model (RRID:SCR_005083) Copy   

•   Source: SciCrunch Registry

http://www.stanford.edu/group/brainsinsilicon/neurogrid.html

A specialized hardware platform that will perform cortex-scale emulations while offering software-like flexibility. With sixteen 12x14 sq-mm chips (Neurocores) assembled on a 6.5x7.5 sq-in circuit board that can model a slab of cortex with up to 16x256x256 neurons - over a million! The chips are interconnected in a binary tree by 80M spike/sec links. An on-chip RAM (in each Neurocore) and an off-chip RAM (on a daughterboard, not shown) softwire vertical and horizontcal cortical connections, respectively. It provides an affordable option for brain simulations that uses analog computation to emulate ion-channel activity and uses digital communication to softwire synaptic connections. These technologies impose different constraints, because they operate in parallel and in serial, respectively. Analog computation constrains the number of distinct ion-channel populations that can be simulatedunlike digital computation, which simply takes longer to run bigger simulations. Digital communication constrains the number of synaptic connections that can be activated per secondunlike analog communication, which simply sums additional inputs onto the same wire. Working within these constraints, Neurogrid achieves its goal of simulating multiple cortical areas in real-time by making judicious choices.

Proper citation: Neurogrid (RRID:SCR_005024) 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://elementsofmorphology.nih.gov/

Data set of standardized terms used to describe human morphology including definitions of terms for the craniofacies in general, the major components of the face, and the hands and feet. This provides a uniform and internationally accepted terms to describe the human phenotype.

Proper citation: elements of morphology (RRID:SCR_003707) Copy   

•   Source: SciCrunch Registry

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

The autoimmune disease arm of the Accelerating Medicine Partnership (AMP), which aims to identify and validate the most promising biological targets of disease for new diagnostic and drug development, that is focused on rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). They seek to identify shared common flaws in inflammation, particularly those that are shared with a larger number of autoimmune disorders which can cause severe disability, greatly affect quality of life, and are associated with an increased risk of death. This project aims to reveal biomarkers and biological targets for drug development, matching existing drugs to patients with specific molecular profiles who are most likely to benefit. The research plan proposes a 5 year process. Year one will include startup activities such as validation of tissue acquisition processes and analytic technologies, and the development of operating procedures. The second year will focus on identification of disease specific pathways by comparing data from patients and healthy individuals. Years 3-5 will expand the scale to include comparisons of different subsets of patients with RA or lupus to allow molecularly based patient stratification for precise treatment. The final 12 months (2019) will also include preliminary target validation. The data will be made publicly available through an internet-based information portal.

Proper citation: Accelerating Medicines Partnership Autoimmune Diseases of Rheumatoid Arthritis and Lupus (RRID:SCR_003731) Copy   

•   Source: SciCrunch Registry

http://www.med.uc.edu/cardio_bio/

Our 24 faculty members approach the Research and Training in Cardiovascular Biology program from different subspecialties that include genetics, metabolism, development, cellular biology, systems biology, structural biology, biophysics, pharmacology, molecular biology, bioinformatics and biochemistry. While these subspecialties are clearly diverse, our faculty collaboratively leverages these areas toward the common goal of understanding cardiovascular disease from the gene all the way up to integrated organism function (systems biology). This diverse array of subspecialties provides a truly unique training environment that few centers can match. Another critical aspect of our training program is our steadfast commitment to a superior and nurturing training environment for our predoctoral trainees, postdoctoral trainees and clinician-scientists. Our training faculty are uniformly committed to monitoring our personnel for success in every way possible, to not only ensure their future placement in the academic ranks but to also build a stronger cardiovascular community around the country. The current National Institutes of Health-sponsored Research and Training in Cardiovascular Biology was instituted in 1978 by Arnold Schwartz, MD, PhD. This program has trained more than 120 scientists, who have pursued independent research careers and are holding prominent scientific positions worldwide. Our trainees have been distinguished as chairs of basic science departments, directors of centers or pharmaceutical companies, clinical directors and tenured faculty members in academic research. The overall emphasis continues to focus on integrative training and well-rounded knowledge of the fundamentals in biochemical, molecular, physiological and pharmacological underpinnings of cardiovascular disease. Dr. Schwartz has been a constant guiding force since the program was established. The University of Cincinnati, with Cincinnati Children's, has also developed a reputation as a leading center for the generation and analysis of genetically modified mouse models for interrogation of gene-disease relationships in the heart. This theme has been expanded to incorporate molecular genomics, proteomics and bioinformatics, as we continue to be among the leaders in the nation in molecular pathway analysis associated with single gene manipulations in the hearts of mice. Most faculty and trainees are using these approaches, but they are also well-versed in many other aspects of cardiovascular science, including excellence in basic physiology, pharmacology, biochemistry, structural biology and molecular biology. Thus, we are a rare conglomeration of faculty in which all aspects of cardiovascular biology are practiced, starting with cutting-edge molecular and genetic approaches, spanning more traditional cellular and whole animal approaches to build an integrated network of functional and disease-relevant data and extending to translational research incorporating cell therapy.

Proper citation: University of Cincinnati Research and Training in Cardiovascular Biology (RRID:SCR_003860) Copy   

•   Source: SciCrunch Registry

https://neurowiki.case.edu/

Curriculum materials for an Introduction to Neurobiology course for undergraduate and graduate students.

The course focuses on the analysis of neurons and neural circuits for behavior using the fundamental principles of neuroscience. From the online course syllabus, the 24 units that make up the course may be directly accessed. Each unit contains a reading, links to at least one simulation, and a problem set.

A list of all available simulations can be found here: https://neurowiki.case.edu/wiki/Simulations. * 25 simulations are written in JavaScript and will run in any browser.
Source code: https://github.com/CWRUChielLab/JSNeuroSim * Pre-compiled executables (Windows, Mac, Linux) are available for 1 desktop simulation, the Nernst Potential Simulator.
Source code: https://github.com/CWRUChielLab/Nernst Structure of the Course * Solving problems based on simulations of neuronal components, neurons, and simple circuits to understand how they work. * For advanced students, writing a neuroscience Wikipedia article, critical review, or grant, in stages.

Proper citation: NeuroWiki (RRID:SCR_004066) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/pmc/

Collection of full text archive of biomedical and life sciences journal literature at U.S. National Institutes of Health National Library of Medicine (NIH/NLM). With PubMed Central, NCBI is taking lead in preserving and maintaining open access to electronic literature. Value of PubMed Central, in addition to its role as an archive, lies in what can be done when data from diverse sources is stored in common format in single repository. All articles in PMC are free (sometimes on a delayed basis). Some journals go beyond free, to Open Access.

Proper citation: PubMed Central (RRID:SCR_004166) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/pdbe/

The European resource for the collection, organization and dissemination of data on biological macromolecular structures. In collaboration with the other worldwide Protein Data Bank (wwPDB) partners - the Research Collaboratory for Structural Bioinformatics (RCSB) and BioMagResBank (BMRB) in the USA and the Protein Data Bank of Japan (PDBj) - they work to collate, maintain and provide access to the global repository of macromolecular structure data. The main objectives of the work at PDBe are: * to provide an integrated resource of high-quality macromolecular structures and related data and make it available to the biomedical community via intuitive user interfaces. * to maintain in-house expertise in all the major structure-determination techniques (X-ray, NMR and EM) in order to stay abreast of technical and methodological developments in these fields, and to work with the community on issues of mutual interest (such as data representation, harvesting, formats and standards, or validation of structural data). * to provide high-quality deposition and annotation facilities for structural data as one of the wwPDB deposition sites. Several sophisticated tools are also available for the structural analysis of macromolecules.

Proper citation: PDBe - Protein Data Bank in Europe (RRID:SCR_004312) Copy   

•   Source: SciCrunch Registry

http://www.feinsteininstitute.org/Feinstein/Feinstein+HomePage

The Feinstein Institute for Medical Research is the research branch of the North Shore-Long Island Jewish Health System. Biomedical research has been a vital aspect of its two academic medical centers North Shore University Hospital and Long Island Jewish Medical Center since their establishment in the early 1950''s. Through its connection to the hospital system, the Institute bridges the gap between biomedical research and patient care, accessing hundreds of thousands of patients in the health system''s 15 hospitals, four long-term care facilities, three trauma centers, six home health agencies and dozens of outpatient facilities. Institute scientists collaborate with clinicians throughout the system to shed light on basic biological processes underlying disease. This knowledge is used to develop new therapies and diagnostics. Currently, more than 800 scientists and investigators are conducting research in oncology, immunology and inflammation, genetics, psychiatry, neurology, pediatrics, surgery, urology, obstetrics/gynecology and many other specialties. In 2008, the Feinstein received funding from the National Institutes of Health in excess of $28 million, and an additional $10 million from other federal sources. Total annual research funding from all sources exceeded $44 million in 2008. We stand at the threshold of an extraordinary time in medicine. Over the last 100 years, biomedical science has progressed very rapidly. Advances coming from the integration of genomics, proteomics and bioinformatics into the biomedical toolkit hold the promise that this transformation will continue well into the 21st century. The Feinstein Institute for Medical Research is a growing force in research innovation, education and progress.

Proper citation: Feinstein Institute for Medical Research (RRID:SCR_004470) Copy   

•   Source: SciCrunch Registry

http://www.mprc.umaryland.edu/mbc.asp

The Maryland Brain Collection (MBC), a resource of the Maryland Psychiatric Research Center (MPRC), is dedicated to promoting research with brain tissue obtained post-mortem from individuals with schizophrenia or related disorders. The primary goal of the MBC is to provide high-quality tissue, along with comprehensive clinical information, for hypothesis-driven research. The MBC is not conceptualized as a Brain Bank with open access but is maintained and funded through collaborative research. The Maryland Brain Collection is managed by researchers at the Maryland Psychiatric Research Center (MPRC). MPRC scientists are dedicated to understanding the causes and improving the treatment of mental illness. The Maryland Brain Collection is associated with the Office of the Chief Medical Examiner for the State of Maryland and other donor sources. MPRC scientists collaborate with scientists from around the world to understand how abnormalities in brain tissue relate to mental illness. The purpose of the MBC is to study the following: Schizophrenia, Bipolar Disorder, Depression, Suicide/Teen suicide, Substance Abuse.

Proper citation: Maryland Brain Collection (RRID:SCR_004384) Copy   

•   Source: SciCrunch Registry

http://rarediseasesnetwork.epi.usf.edu/index.htm

The Rare Diseases Clinical Research Network (RDCRN) was created to facilitate collaboration among experts in many different types of rare diseases. Our goal is to contribute to the research and treatment of rare diseases by working together to identify biomarkers for disease risk, disease severity and activity, and clinical outcome, while also encouraging development of new approaches to diagnosis, prevention, and treatment. The Rare Diseases Clinical Research Network (RDCRN) is made up of 19 distinctive consortia that are working in concert to improve availability of rare disease information, treatment, clinical studies, and general awareness for both patients and the medical community. The RDCRN also aims to provide up-to-date information for patients and to assist in connecting patients with advocacy groups, expert doctors, and clinical research opportunities.

Proper citation: Rare Diseases Clinical Research Network (RRID:SCR_004372) Copy   

•   Source: SciCrunch Registry