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http://compbio.charite.de/phenexplorer/

The PhenExplorer allows you to browse the Human Phenotype Ontology (HPO) in different ways, using the tabs ''''by features'''', ''''by disease'''', ''''by ontology'''' or ''''by genes''''. Clicking on a particular phenotypic feature (HPO-term) you can get a list of disease entries that are linked to it (i.e. diseases that are annotated with this HPO-term). You can also visualize this term in the context of the ontological structure. Finally, a lists of genes can be displayed, that are known to cause (when mutated) the linked diseases mentioned above. For each disease you can get the list of linked HPO-terms and genes. You can also search for specific genes and explore to which HPO-terms and diseases they are linked.

Proper citation: Phenexplorer (RRID:SCR_006156) Copy   

•   Source: SciCrunch Registry

http://www.jsmf.org/

Supports research and scholarship to improve the quality of life by providing funding for grants in three program areas: studying complex systems, understanding human cognition, and mathematical and complex systems approaches for brain cancer. Types of awards include Fellowship Awards, Scholar Awards, and Collaborative Awards. * Studying Complex Systems: This program supports scholarship and research directed toward the development of theoretical and mathematical tools that can be applied to the study of complex, adaptive, nonlinear systems. It is anticipated that research funded in this program will address issues in fields such as biology, biodiversity, climate, demography, epidemiology, technological change, economic development, governance, or computation. * Understanding Human Cognition: This program supports research studying how neural systems are linked to and support cognitive functions and how cognitive systems are related to an organism's (preferably human) observable behavior. Studies with model organisms should justify why such models were selected and how data obtained from models advances our understanding of human cognition. * Mathematical & Complex Systems Approaches for Brain Cancer: (Collaborative Activity Awards grant type only.) Despite some recent cause for optimism for advancing the clinical treatment of brain cancers, for many patients brain tumor remains a devastating diagnosis. Progress against this disease has been stymied by limited understandings of the molecular, metabolic, and physiological characteristics of human brain cancers across multiple temporal and spatial scales and by the failure of many preclinical models to predict patient responses.

Proper citation: James S. McDonnell Foundation (RRID:SCR_006341) Copy   

•   Source: SciCrunch Registry

http://intramural.nimh.nih.gov/gcap/index.htm

Schizophrenia related portal that aims to solve the mystery of genetic predisposition to psychosis, develop new methods for early diagnosis and prevention, and discover new treatments that will cure people suffering from it. Our objectives are to fully characterize: # neurobiological mechanisms related to susceptibility genes for schizophrenia and related clinical disorders; # genetic variation in aspects of cognition and emotionality associated with schizophrenia; and # small molecular targets for novel therapies. A unique feature of this Program is that its diverse scientific resources will be focused on a highly specific scientific agenda, that is to acquire the critical biological information about the susceptibility genes associated with schizophrenia and related illnesses. Our mission and goal, to understand the basic mechanisms of serious mental illness, has again guided us into new areas of research and to new insights. We have found evidence of new genes implicated in the cause of schizophrenia and involved in brain functions related to cognition and emotion and we have begun to explore how genes interact with each other and with the environment to individualize risk for these conditions. We are working now with over 20 genes related to schizophrenia. One of the key developments in our research over the past year has been the emergence of some targets for the development of novel therapeutics. We have discovered a new schizophrenia susceptibility gene, KCNH2, which represents the first clear target for the development of novel treatments. Just in this past year, for example, we published the first extensive statistical analysis of how schizophrenia genes may vary in their risk effects based on different genetic background (Nicodemus et al Hum Gen 2006), the first studies of schizophrenia genes interacting in effecting gene expression in brain (Lipska et al Hum Mol Genetics 2006a, Lipska et al Hum Mol Gen 2006 b); the first evidence that the mechanism of genetic association of NRG1 with schizophrenia involves a novel isoform of the gene in human brain (Law et al PNAS 2006), and the first evidence that MAOA may be linked to mood and impulse control because it effects critical mood regulatory neural networks (Meyer-Lindenberg et al PNAS 2006).

Proper citation: Genes Cognition and Psychosis Program (RRID:SCR_006292) Copy   

•   Source: SciCrunch Registry

http://embryoimaging.org/

Collection of high resolution images and movies of mouse and human embryos produced using high resolution episcopic microscopy (HREM). Each data set is a series of block-face images generated during sectioning through an entire embryo, typically cut at 2-3 micrometers. Datasets are organized by approximate developmental stage and each embryo has been assigned a specimen ID (SID) for identification. This is an ongoing project funded by the Wellcome Trust to provide comprehensive imaging of normal and mutant mouse embryos that will complement the standard anatomical texts and form the basis for systematic phenotyping. * Movies: A 3D reconstruction shows each embryo, and lower resolution movies created through each orthogonal plane enable you to quickly review the data set. * Image Stacks: In the stack viewer, you can step through the images in sequence, zoom in to see fine details and adjust the image contrast. * NEW: Embryo Comparison: Two image stacks can now be compared in the stack viewer.

Proper citation: Embryo Imaging (RRID:SCR_006329) Copy   

•   Source: SciCrunch Registry

http://www.areds2.org

Study designed to assess the effects of oral supplementation of high doses of macular xanthophylls (lutein and zeaxanthin) and/or omega -3 LCPUFAs (DHA and EPA) for the treatment of AMD and cataract.

Proper citation: AREDS2: The Age-Related Eye Disease Study 2 (RRID:SCR_006306) Copy   

•   Source: SciCrunch Registry

https://www.researchmatch.org/

Free and secure registry to bring together two groups of people who are looking for one another: (1) people who are trying to find research studies, and (2) researchers who are looking for people to participate in their studies. It has been developed by major academic institutions across the country who want to involve you in the mission of helping today''''s studies make a real difference for everyone''''s health in the future. Anyone can join ResearchMatch. Many studies are looking for healthy people of all ages, while some are looking for people with specific health conditions. ResearchMatch can help ''''match'''' you with any type of research study, ranging from surveys to clinical trials, always giving you the choice to decide what studies may interest you.

Proper citation: ResearchMatch (RRID:SCR_006387) Copy   

•   Source: SciCrunch Registry

http://www-personal.umich.edu/~brdsmith/Research.html

Data set of image collections and movies including Magnetic Resonance Imaging of Embryos, Human Embryo Imaging, MRI of Cardiovascular Development, and Live Embryo Imaging. Individual MRI slice images, three-dimensional images, animations, stereo-pair animations, animations of organ systems, and photo-micrographs are included.

Proper citation: Brad Smith Magnetic Resonance Imaging of Embryos (RRID:SCR_006300) Copy   

•   Source: SciCrunch Registry

http://www.callisto-science.org/NSI/Neuroscience_Image_Database/Images%20of%20the%20Human%20Nervous%20System%20-%20Neuroanatomy.html

Data set of images of the human nervous system focusing on neuroanatomy.

Proper citation: Human Nervous System Neuroanatomy (RRID:SCR_006371) Copy   

•   Source: SciCrunch Registry

http://vinovia.ncl.ac.uk/emagewebapp/pages/eadhb_home.jsf

Database of a set of standard 3D virtual models at different stages of development from Carnegie Stages (CS) 12-23 (approximately 26-56 days post conception) in which various anatomical regions have been defined with a set of anatomical terms at various stages of development (known as an ontology). Experimental data is captured and converted to digital format and then mapped to the appropriate 3D model. The ontology is used to define sites of gene expression using a set of standard descriptions and to link the expression data to an ''''anatomical tree''''. Human data from stages CS12 to CS23 can be submitted to the HUDSEN Gene Expression Database. The anatomy ontology currently being used is based on the Edinburgh Human Developmental Anatomy Database which encompasses all developing structures from CS1 to CS20 but is not detailed for developing brain structures. The ontology is being extended and refined (by Prof Luis Puelles, University of Murcia, Spain) and will be incorporated into the HUDSEN database as it is developed. Expression data is annotated using two methods to denote sites of expression in the embryo: spatial annotation and text annotation. Additionally, many aspects of the detection reagent and specimen are also annotated during this process (assignment of IDs, nucleotide sequences for probes etc). There are currently two main ways to search HUDSEN - using a gene/protein name or a named anatomical structure as the query term. The entire contents of the database can be browsed using the data browser. Results may be saved. The data in HUDSEN is generated from both from researchers within the HUDSEN project, and from the wider scientific community. The HUDSEN human gene expression spatial database is a collaboration between the Institute of Human Genetics in Newcastle, UK, and the MRC Human Genetics Unit in Edinburgh, UK, and was developed as part of the Electronic Atlas of the Developing Human Brain (EADHB) project (funded by the NIH Human Brain Project). The database is based on the Edinburgh Mouse Atlas gene expression database (EMAGE), and is designed to be an openly available resource to the research community holding gene expression patterns during early human development.

Proper citation: HUDSEN Human Gene Expression Spatial Database (RRID:SCR_006325) Copy   

•   Source: SciCrunch Registry

http://www.hudsen.org/

Forum for researchers in human developmental biology and related fields to meet and establish links.

Proper citation: HUDSEN (RRID:SCR_006324) Copy   

•   Source: SciCrunch Registry

http://w3.cns.org/university/nsimages/index2.asp

Data set of almost 2,000 neurosurgical images using a variety of search options.

Proper citation: Congress of Neurological Surgeons Online Image Database (RRID:SCR_006310) Copy   

•   Source: SciCrunch Registry

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

MATLAB toolbox for performing functional connectivity analyses includes many of the most commonly-used approaches researchers have utilized to date for the identification of condition-dependent functional interactions between fMRI time-series obtained from two or more brain regions. The approaches are either bivariate or multivariate methods defined in time or frequency domains that emphasize distinct features of relationships among the time-series.

Proper citation: Functional Connectivity Toolbox (RRID:SCR_006394) Copy   

•   Source: SciCrunch Registry

http://lincs.hms.harvard.edu/db/

Database that contains all publicly available HMS LINCS datasets and information for each dataset about experimental reagents and experimental and data analysis protocols. Experimental reagents include small molecule perturbagens, cells, antibodies, and proteins.

Proper citation: HMS LINCS Database (RRID:SCR_006454) Copy   

•   Source: SciCrunch Registry

http://www.cochrane.org/editorial-and-publishing-policy-resource/cochrane-central-register-controlled-trials-central

A bibliographic database that provides a highly concentrated source of reports of randomized controlled trials. Records contain the list of authors, the title of the article, the source, volume, issue, page numbers, and, in many cases, a summary of the article (abstract). They do not contain the full text of the article. Cochrane Groups maintain and update Specialized Registers, which are collections of controlled trials relevant to the groups. CENTRAL is comprised of these Specialized Registers, relevant records retrieved from MEDLINE and EMBASE, and records retrieved through handsearching (planned manual searching of a journal or conference proceedings to identify all reports of randomized controlled trials and controlled clinical trials). The Cochrane Collaboration contracts a technology company, Metaxis, to merge the records from the sources outlined above and provide a data feed to the publisher. New and changed data are delivered to the publisher on a monthly basis.

Proper citation: Cochrane Central Register of Controlled Trials (RRID:SCR_006576) Copy   

•   Source: SciCrunch Registry

http://cdmrp.army.mil/

Fund the best research to eradicate diseases and support the warfighter to benefit the American Public. They promote innovative research, recognizing untapped opportunities, creating partnerships, and guarding the public trust. Research Program topics include: * Amyotrophic Lateral Sclerosis * Autism * Bone Marrow Failure * Breast Cancer * Defense Medical Research and Development Program * Duchenne Muscular Dystrophy * Gulf War Illness * Lung Cancer * Multiple Sclerosis * Neurofibromatosis * Ovarian Cancer * Peer Reviewed Cancer * Peer Reviewed Medical * Peer Reviewed Orthopaedic * Prostate Cancer * Psychological Health / Traumatic Brain Injury * Spinal Cord Injury * Tuberous Sclerosis Complex

Proper citation: Congressionally Directed Medical Research Program (RRID:SCR_006456) Copy   

•   Source: SciCrunch Registry

http://colt.ccbr.utoronto.ca/cancer/

The COLT-Cancer database is a collection of shRNA dropout signatures profiles, covering ~16000 human genes, and derived from more than 70 Pancreatic, Ovarian and Breast human cancer cell-lines using the microarray detection platform developed in the COLT (CCBR-OICR Lentiviral Technology) facility at the Moffat Lab. All shRNA dropout profiles are freely available through download or queries via this website.

Proper citation: COLT-Cancer (RRID:SCR_006485) Copy   

•   Source: SciCrunch Registry

http://www.mitre.org/news/digest/archives/2002/neuroinformatics.html

This resource''s long-term goal is to develop informatics methodologies and tools that will increase the creativity and productivity of neuroscience investigators, as they work together to use shared human brain mapping data to generate and test ideas far beyond those pursued by the data''s originators. This resource currently has four major projects supporting this goal: * Database tools: The goal of the NeuroServ project is to provide neuroscience researchers with automated information management tools that reduce the effort required to manage, analyze, query, view, and share their imaging data. It currently manages both structural magnetic resonance image (MRI) datasets and diffusion tensor image (DTI) datasets. NeuroServ is fully web-enabled: data entry, query, processing, reporting, and administrative functions are performed by qualified users through a web browser. It can be used as a local laboratory repository, to share data on the web, or to support a large distributed consortium. NeuroServ is based on an industrial-quality query middleware engine MRALD. NeuroServ includes a specialized neuroimaging schema and over 40 custom Java Server Pages supporting data entry, query, and reporting to help manage and explore stored images. NeuroServ is written in Java for platform independence; it also utilizes several open source components * Data sharing: DataQuest is a collaborative forum to facilitate the sharing of neuroimaging data within the neuroscience community. By publishing summaries of existing datasets, DataQuest enables researchers to: # Discover what data is available for collaborative research # Advertise your data to other researchers for potential collaborations # Discover which researchers may have the data you need # Discover which researchers are interested in your data. * Image quality: The approach to assessing the inherent quality of an image is to measure how distorted the image is. Using what are referred to as no-reference or blind metrics, one can measure the degree to which an image is distorted. * Content-based image retrieval: NIRV (NeuroImagery Retrieval & Visualization) is a work environment for advanced querying over imagery. NIRV will have a Java-based front-end for users to issue queries, run processing algorithms, review results, visualize imagery and assess image quality. NIRV interacts with an image repository such as NeuroServ. Users can also register images and will soon be able to filter searches based on image quality.

Proper citation: MITRE Neuroinformatics (RRID:SCR_006508) Copy   

•   Source: SciCrunch Registry

http://ctdbase.org/

A public database that enhances understanding of the effects of environmental chemicals on human health. Integrated GO data and a GO browser add functionality to CTD by allowing users to understand biological functions, processes and cellular locations that are the targets of chemical exposures. CTD includes curated data describing cross-species chemical–gene/protein interactions, chemical–disease and gene–disease associations to illuminate molecular mechanisms underlying variable susceptibility and environmentally influenced diseases. These data will also provide insights into complex chemical–gene and protein interaction networks.

Proper citation: Comparative Toxicogenomics Database (CTD) (RRID:SCR_006530) Copy   

•   Source: SciCrunch Registry

http://www.roslin.ed.ac.uk/

World class research center that undertakes top-class basic and translational science to tackle some of the most pressing issues in animal health and welfare, their implications for human health and for the role of animals in the food chain. Roslin provides holistic solutions to global challenges in human and veterinary medicine and the livestock industry. Its mission is to gain fundamental understanding of genetic, cellular, organ and systems bioscience underpinning common mechanisms of animal development and pathology, and to drive this into prevention and treatment of important veterinary diseases and develop sustainable farm animal production systems. The Roslin Institute aims to enhance the lives of animals and humans through world class research in animal biology. The principal objectives are to: * Enhance animal health and welfare through knowledge of genetic factors affecting resistance to disease. * Enhance sustainability and productivity of livestock systems and food supply chains through understanding of reproductive and developmental biology. * Enhance food safety by understanding interactions between disease causing organisms and animals. * Enhance human health through an understanding of basic mechanisms of health and disease and comparative biology of animal species. * Identify of new and emerging zoonoses and understand how pathogens might cross from animals to humans. * Enhance quality of life for animals by studying the mechanisms and behaviors associated with optimizing their environment and life experiences.

Proper citation: Roslin Institute (RRID:SCR_006533) Copy   

•   Source: SciCrunch Registry

http://nkdep.nih.gov/

Educational resource to increase awareness of kidney disease and its risk factors, improve early detection of chronic kidney disease (CKD), reduce the burden of CKD, facilitate identification of patients at greatest risk for progression to kidney failure, stress the importance of testing those at risk, promote evidence-based interventions to slow progression of CKD, and support the coordination of Federal responses to CKD. Target audiences include individuals at risk, particularly those with diabetes, high blood pressure, and a family history of kidney disease, and primary care providers.

Proper citation: National Kidney Disease Education Program (RRID:SCR_006527) Copy   

•   Source: SciCrunch Registry