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http://www.pedigree-draw.com/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 12,2024. Software application for pedigree drawing (entry from Genetic Analysis Software)

Proper citation: Pedigree-Draw (RRID:SCR_008302) Copy   

•   Source: SciCrunch Registry

http://research-acumen.eu/

European research collaboration aimed at understanding the ways in which researchers are evaluated by their peers and by institutions, and at assessing how the science system can be improved and enhanced. This FP7 project is a cooperation among nine European research institutes with Professor Paul Wouters (CWTS ����?? Leiden University) as principal investigator.

Proper citation: Acumen Consortium (RRID:SCR_006599) Copy   

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http://wiki.c2b2.columbia.edu/califanolab/index.php/BCellInteractome.htm

A network of protein-protein, protein-DNA and modulatory interactions in human B cells. The network contains known interactions (reported in public databases) and predicted interactions by a Bayesian evidence integration framework which integrates a variety of generic and context specific experimental clues about protein-protein and protein-DNA interactions with inferences from different reverse engineering algorithms, such as GeneWays and ARACNE. Modulatory interactions are predicted by the MINDY, an algorithm for the prediction of modulators of transcriptional interactions (please refer to the publication section for more information). The BCI can be downloaded as one tab delimited file containing the complete network (BCI.txt) with each type of interaction explicitly defined.

Proper citation: B Cell Interactome (RRID:SCR_008655) Copy   

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http://www.nmr.mgh.harvard.edu/DOT/resources/homer2/home.htm

Software matlab scripts used for analyzing fNIRS data to obtain estimates and maps of brain activation. Graphical user interface (GUI) for visualization and analysis of functional near-infrared spectroscopy (fNIRS) data.

Proper citation: Homer2 (RRID:SCR_009586) Copy   

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http://hermes.ctb.upm.es/

A toolbox for the Matlab environment designed to study functional and effective brain connectivity from neurophysiological data such as multivariate EEG and/or MEG records. It includes also visualization tools and statistical methods to address the problem of multiple comparisons. This toolbox may be very helpful to all the researchers working in the emerging field of brain connectivity analysis.

Proper citation: HERMES (RRID:SCR_009584) Copy   

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http://www.emqn.org

Welcome to the EMQN website. EMQN is a not-for-profit organisation promoting quality in molecular genetic testing through the provision of external quality assessment (proficiency testing schemes) and the organisation of best practice meetings and publication of guidelines. The European Molecular Genetics Quality Network (EMQN) started in October 1998 after a successful pilot trial. From January 1999 to March 2002, the network was supported by a grant from the European Commission under the Standards Measurement and Testing Programme (contract number SMT4-CT98-7515). From April 2002, the network is supported by subscriptions from it users. External Quality Assessment (EQA): There are 26 EQA schemes being offered in 2010. To participate you must be a registered member of the network. For more information on EQA schemes, click the link here. Best Practice: EMQN is actively promoting ''best practice'' meetings on individual diseases. To assist in this process, EMQN will be organising best practice meetings. To participate you must be a registered member of the network. Following the meeting, draft best practice guidelines are produced and publised on this and other related websites, for example, the web site of the UK Clinical Molecular Genetics Society (CMGS). To find out more about best practice click here. Administration: The EMQN is based at the National Genetics Reference Laboratory (Manchester), St Mary''s Hospital, Manchester, The United Kingdom. The Network is co-ordinated and administered by Dr''s Rob Elles and Simon Patton. A management group is responsible for the activities and direction of the network. National partners in different countries help to disseminate information about the network. Quality Policy The EMQN provides a comprehensive range of quality assurance programs for molecular genetics to laboratories and industry worldwide. The European Molecular Genetics Quality Network (EMQN) is committed to helping ensure diagnostic molecular genetic laboratory test results are accurate, reliable and comparable wherever they are produced. The EMQN will provide a high quality and timely service which takes into account the needs and requirements of its users. Objectives To help to raise and maintain the standards of diagnostic clinical molecular genetic testing. To undertake and promote educational activities. To be a leading authority in quality assurance . To design and provide the best possible materials and data management. To design and provide quality reports that are timely and valid. To provide professional support and consultation. To develop new programs as required. To participate in peer review. To strive for continual improvement of the quality system. Sponsor. the network was supported by a grant from the European Commission under the Standards Measurement and Testing Programme (contract number SMT4-CT98-7515

Proper citation: European Molecular Quality Network (RRID:SCR_008494) Copy   

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http://www.nitrc.org/projects/dti_tract_stat/

This is a command line tool which allows the user to study the behavior of water diffusion (using DTI data) along the length of the white matter fiber-tracts. Various tract-oriented scalar diffusion measures obtained from DTI brain images, are treated as a continuous function of white matter fibers'' arc-length. To analyze the trend along a given fiber tract, a command line tool performs kernel regression on this data. The idea is to try out different noise models and maximum likelihood estimates within kernel windows (along the tract), such that they best represent the data and are robust to noise and Partial Volume effect. The package contains several command line based modules and an GUI based tool called DTIAtlasFiberAnalyzer to access most functions. The features available in the tool currently, its use and input / output formats and other relevant details are provided in the first draft of the documentation. (http://www.na-mic.org/Wiki/index.php/Projects:dtistatisticsfibers).

Proper citation: DTI Fiber Tract Statistics (RRID:SCR_009460) Copy   

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http://tripod.nih.gov/npc/

The NCGC Pharmaceutical Collection (NPC) is a comprehensive, publically-accessible collection of approved and investigational drugs for high-throughput screening that provides a valuable resource for both validating new models of disease and better understanding the molecular basis of disease pathology and intervention. The NPC has already generated several useful probes for studying a diverse cross section of biology, including novel targets and pathways. NCGC provides access to its set of approved drugs and bioactives through the Therapeutics for Rare and Neglected Diseases (TRND) program and as part of the compound collection for the Tox21 initiative, a collaborative effort for toxicity screening among several government agencies including the US Environmental Protection Agency (EPA), the National Toxicology Program (NTP), the US Food and Drugs Administration (FDA), and the NCGC. Of the nearly 2750 small molecular entities (MEs) that have been approved for clinical use by US (FDA), EU (EMA), Japanese (NHI), and Canadian (HC) authorities and that are amenable to HTS screening, we currently possess 2,400 as part of our screening collection. The NPC resource currently consists of (i) the physical collection suitable for high throughput screening (HTS) and (ii) the informatics browser and database. Putting together the physical collection has been surprisingly challenging in terms of the time and effort required in the informatics, compound management and synthetic chemistry related activities required for this endeavor. We provide access to the NPC screening library through collaboration. Please contact our Scientific Director Dr. Chris Austin for additional information. The other half of the NPC resource is the NPC browser. This is a self-contained software that is actively developed and maintained by the informatics group to provide electronic access to the NPC content. The latest version of the NPC browser for various platforms can be downloaded.

Proper citation: NCGC Pharmaceutical Collection (RRID:SCR_006909) Copy   

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http://www.ngfn.de/en/start.html

The program of medical genome research is a large-scale biomedical research project which extends the national genome research net (NGFN) and will be funded by the federal ministry of education and research (BMBF) from 2008-2013. Currently the program includes two fields: * Research ** NGFN-Plus: With the aim on combating diseases that are central to health policy, several hundred researchers are systematically investigating the complex molecular interactions of the human body. They are organized in 26 Integrated Genome Research Networks. * Application ** NGFN-Transfer: The rapid transfer of results from medical genome research into medical and industrial application is the aim of the scientists from research institutes and biomedical enterprises that cooperate in eight Innovation Alliances. AREAS OF DISEASE * Cardiovascular disease * Cancer * Neuronal diseases * Infections and Inflammations * Environmental factors

Proper citation: National Genome Research Network (RRID:SCR_006626) Copy   

•   Source: SciCrunch Registry

https://www.guidetopharmacology.org/nciuphar.jsp

Issues guidelines for nomenclature and classification of human biological targets, including targets of current and future prescription medicines. Works to facilitate interface between discovery of new sequences from Human Genome Project and designation of derived entities as functional biological targets and potential drug targets. Developes database which provides access to data on all known biological targets.

Proper citation: NC-IUPHAR (RRID:SCR_006901) Copy   

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http://www.zymogenetics.com.

Founded in 1981, ZymoGenetics is a biopharmaceutical company focused on the development and commercialization of therapeutic proteins. ZymoGenetics is publicly traded (NASDAQ: ZGEN) and headquartered in Seattle, Washington in the historic Seattle City Light Steam Plant building. Our mission is to create novel protein drugs that will significantly help patients fight their diseases. We have contributed to the discovery or development of six recombinant protein products now marketed by other companies. Current programs target viral infection, cancer, inflammatory diseases and bleeding. Our first internally developed product, RECOTHROM Thrombin, topical (Recombinant), was approved by the U.S. Food and Drug Administration (FDA) on January 17, 2008 for use as a topical hemostat to control moderate bleeding during surgical procedures and is now marketed in the United States. We have a promising pipeline of novel therapeutics, which we are developing on our own or in collaboration with partners.

Proper citation: Zymo Genetics (RRID:SCR_008602) Copy   

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https://cnprc.ucdavis.edu/

Center for investigators studying human health and disease, offering the opportunity to assess the causes of disease, and new treatment methods in nonhuman primate models that closely recapitulate humans. Its mission is to provide interdisciplinary programs in biomedical research on significant human health-related problems in which nonhuman primates are the models of choice.

Proper citation: California National Primate Research Center (RRID:SCR_006426) Copy   

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http://repeatmasker.genome.washington.edu

Welcome to the Department of Genome Sciences, which began in September 2001 by the fusion of the Departments of Genetics and Molecular Biotechnology. Our goal is to address leading edge questions in biology and medicine by developing and applying genetic, genomic and computational approaches that take advantage of genomic information now available for humans, model organisms and a host of other species. Our faculty study a broad range of topics, including the genetics of E. coli, yeast, C. elegans, Drosophila, and mouse; human and medical genetics; mathematical, statistical and computer methods for analyzing genomes, and theoretical and evolutionary genetics; and genome-wide studies by such approaches as sequencing, transcriptional and translational analysis, polymorphism detection and identification of protein interactions. Our chair, Dr. Robert Waterston, joined the department in January 2003. Our department includes both faculty with primary appointments in Genome Sciences, as well as adjuncts in other departments and Seattle institutions. Nine faculty are members of the National Academy of Sciences, including 2001 Nobel Prize winner Dr. Lee Hartwell, who conducted much of his groundbreaking work in the Department of Genetics. Five training faculty are Howard Hughes Medical Institute Investigators. Graduate research in the Department leads to a Ph.D. in Genome Sciences and students may also choose to participate in the Computational Molecular Biology or Molecular Medicine programs. Our department has around 55 - 60 graduate students at any given time and has moved into the new William H. Foege Building.

Proper citation: UW Genome Sciences (RRID:SCR_008562) Copy   

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http://www.uv.es/vista/vistavalencia/

The general goal is to achieve a deeper understanding of natural image statistics because from this knowledge it should be possible to explain the behavior of the visual cortex and propose new alternatives in a number of applications in image processing and computer vision in which the basic problem is the choice of an appropriate signal representation. The range of basic and applied topics in which we are currently working include: * Mathematical models of human vision * Statistical image models * Image distortion metrics * Image coding * Motion estimation * Video coding * Image restoration * Color representation

Proper citation: Visual Statistics Group (RRID:SCR_008317) Copy   

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http://www.ini.uzh.ch/~acardona/trakem2.html

An ImageJ plugin for morphological data mining, three-dimensional modeling and image stitching, registration, editing and annotation. Two independent modalities exist: either XML-based projects, working directly with the file system, or database-based projects, working on top of a local or remote PostgreSQL database. What can you do with it? * Semantic segmentation editor: order segmentations in tree hierarchies, whose template is exportable for reuse in other, comparable projects. * Model, visualize and export 3D. * Work from your laptop on your huge, remote image storage. * Work with an endless number of images, limited only by the hard drive capacity. Dozens of formats supported thanks to LOCI Bioformats and ImageJ. * Import stacks and even entire grids (montages) of images, automatically stitch them together and homogenize their histograms for best montaging quality. * Add layers conveniently. A layer represents, for example, one 50 nm section (for TEM) or a confocal section. Each layer has its own Z coordinate and thickness, and contains images, labels, areas, nodes of 3d skeletons, profiles... * Insert layer sets into layers: so your electron microscopy serial sections can live inside your optical microscopy sections. * Run any ImageJ plugin on any image. * Measure everything: areas, volumes, pixel intensities, etc. using both built-in data structures and segmentation types, and standard ImageJ ROIs. And with double dissectors! * Visualize RGB color channels changing the opacity of each on the fly, non-destructively. * Annotate images non-destructively with floating text labels, which you can rotate/scale on the fly and display in any color. * Montage/register/stitch/blend images manually with transparencies, semiautomatically, or fully automatically within and across sections, with translation, rigid, similarity and affine models with automatically extracted SIFT features. * Correct the lens distortion present in the images, like those generated in transmission electron microscopy. * Add alpha masks to images using ROIs, for example to split images in two or more parts, or to remove the borders of an image or collection of images. * Model neuronal arbors with 3D skeletons (with areas or radiuses), and synapses with connectors. * Undo all steps. And much more...

Proper citation: TrakEM2 (RRID:SCR_008954) Copy   

•   Source: SciCrunch Registry

http://www.cdc.gov/nccdphp/dnpa/

Our vision a world where regular physical activity, good nutrition, and healthy weight are part of everyone''s life. Our mission to lead strategic public health efforts to prevent and control obesity, chronic disease, and other health conditions though regular physical activity and good nutrition. Our goals: * Increase health-related physical activity through population-based approaches. * Improve those aspects of dietary quality most related to the population burden of chronic disease and unhealthy child development. * Decrease prevalence of obesity through preventing excess weight gain and maintenance of healthy weight loss. Our Work With fiscal year (FY) 2008 funding of 38 million, CDC''s DNPAO is working to reduce obesity and obesity-related diseases. This is done through state programs, research, surveillance, training, intervention development and evaluation, leadership, policy and environmental change, communication and social marketing, and partnership development. See At A Glance 2009 for more. Supporting State Programs The Nutrition, Physical Activity and Obesity Program (NPAO) is a cooperative agreement between the Centers for Disease Control and Prevention''s Division of Nutrition, Physical Activity and Obesity (DNPAO) and 23 state health departments. The program goal is to prevent and control obesity and other chronic diseases through healthful eating and physical activity. The state program will develop strategies to leverage resources and coordinate statewide efforts with multiple partners to address all of the following DNPAO principal target areas: 1. Increase physical activity. 2. Increase the consumption of fruits and vegetables. 3. Decrease the consumption of sugar sweetened beverages. 4. Increase breastfeeding initiation, duration and exclusivity. 5. Reduce the consumption of high energy dense foods. 6. Decrease television viewing. Our Research DNPAO supports research to enhance the effectiveness of physical activity and nutrition programs. Topics of these research activities include: * the effectiveness of parent-focused strategies to reduce the time children spend watching television * the influences of the home environment on sugar-sweetened beverage consumption * the use of policy interventions to promote physical activity * the effectiveness of breastfeeding interventions in various settings. Publications: http://www.cdc.gov/nccdphp/DNPAO/aboutus/manuscripts/index.html

Proper citation: Division of Nutrition, Physical Activity and Obesity (RRID:SCR_008557) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/gcva_pca/

A platform for any Principal Component Analysis (PCA)-based analysis on functional neuroimaging data (PET and fMRI). Includes: * Ordinal Trend Canonical Variance Analysis for parametric designs (C. Habeck et al. A New Approach to Spatial Covariance Modeling of Functional Brain Imaging Data: Ordinal Trend Analysis. Neural Computation 2005; 17: 1602-1645) * Partial Least Squares for any design matrix * Subprofile Scaling Model for cross-sectional designs (JR. Moeller, Strother SC. A regional covariance approach to the analysis of functional patterns in positron emission tomographic data.J Cereb Blood Flow Metab. 1991 Mar;11(2):A121-35.)

Proper citation: Generalized Covariance Analysis (RRID:SCR_009488) Copy   

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http://www.nih.gov/science/brain/

Project aimed at revolutionizing understanding of human brain, to show how individual cells and complex neural circuits interact, enable rapid progress in development of new technologies and data analysis tools to treat and prevent brain disorders. BRAIN Initiative encourages collaborations between neurobiologists and scientists from disciplines such as statistics, physics, mathematics, engineering, and computer and information sciences. Institutes and centers contributing to NIH BRAIN Initiative support those research efforts.

Proper citation: BRAIN Initiative (RRID:SCR_006770) Copy   

•   Source: SciCrunch Registry

http://tulane.edu/som/regenmed/services/index.cfm

The Stem Cell Research and Regenerative Medicine''s Tissue Culture Core provides cells for research use within the department, as well as for distribution to other facilities. The core obtains hMSCs from bone marrow donor samples and expands these cells for research use. The hMSC''s are also characterized for bone, fat and cartilage differentiation, and are stored on site for use. The Tissue Culture Core also handles the expansion and characterization of mouse and rat MSC''s. The animal cells are cultured in a separate area, and never interact with human derived cells. We also have a supply of hMSC''s marked with GFP+, Mito Red and Mito Blue available.

Proper citation: Tulane Stem Cell Research and Regenerative Medicine Tissue Culture Core (RRID:SCR_007342) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/gamma_suite/

GAMMA suite is an open-source cross-platform data mining software package designed to analyze neuroimaging data. A neuroimaging study often focuses on biomarker detection and classification. We designed and implemented a Bayesian, multivariate, nonparametric suite of algorithms for analyzing neuroimaging data. The GAMMA suite can be used for brain morphometric analysis, lesion-deficit analysis, and functional MR data analysis.

Proper citation: GAMMA (RRID:SCR_009484) Copy   

•   Source: SciCrunch Registry