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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
Public research university in Edmonton, Alberta, Canada that offers degree programs in a variety of fields including business, arts, education, engineering, nursing, and medicine.
Proper citation: University of Alberta; Alberta; Canada (RRID:SCR_001853) Copy
http://www.bioconductor.org/packages/release/bioc/html/SamSPECTRAL.html
Software that identifies cell population in flow cytometry data. It demonstrates significant advantages in proper identification of populations with non-elliptical shapes, low density populations close to dense ones, minor subpopulations of a major population and rare populations. It samples large data such that spectral clustering is possible while preserving density information in edge weights. More specifically, given a matrix of coordinates as input, SamSPECTRAL first builds the communities to sample the data points. Then, it builds a graph and after weighting the edges by conductance computation, the graph is passed to a classic spectral clustering algorithm to find the spectral clusters. The last stage of SamSPECTRAL is to combine the spectral clusters. The resulting connected components estimate biological cell populations in the data sample.
Proper citation: SamSPECTRAL (RRID:SCR_001858) Copy
The SeattleSNPs PGA is focused on identifying, genotyping, and modeling the associations between single nucleotide polymorphisms (SNPs) in candidate genes and pathways that underlie inflammatory responses in humans. SeattleSNPs is focused on variation analysis in genes related to the inflammatory response. These gene targets are found in specific pathways and from interacting molecules contributing to this response. Available Resources: - Baseline assembled and complete genomic sequence and chromosomal location for candidate gene targets - Mapping of exon and repeat structure for candidate genes - Amplification primers and conditions - SNPs mapped by location in gene structure - SNPs with immediate surrounding sequence for genotype assay design - Genotypes and relative allele frequencies of the SNPs - Special features of SNPs - location (5', coding, etc.), amino acid substitutions, recurrent variation - Manuals on all protocols, data analysis procedures, and use of software tools - Workshop on genetic variation analysis and a gene submission program for variation analysis Sponsors: SeattleSNPs is funded as part of the National Heart Lung and Blood Institute's (NHLBI) Programs for Genomic Applications (PGA).
Proper citation: SeattleSNPs - Variation Discovery Resource (RRID:SCR_001859) Copy
Founded in 1985, the San Diego Supercomputer Center (SDSC) enables international science and engineering discoveries through advances in computational science and data-intensive, high-performance computing. SDSC is considered a leader in data-intensive computing, providing resources, services and expertise to the national research community including industry and academia. The mission of SDSC is to extend the reach of scientific accomplishments by providing tools such as high-performance hardware technologies, integrative software technologies, and deep interdisciplinary expertise to these communities. From 1997 to 2004, SDSC extended its leadership in computational science and engineering to form the National Partnership for Advanced Computational Infrastructure (NPACI), teaming with approximately 40 university partners around the country. Today, SDSC is an Organized Research Unit of the University of California, San Diego with a staff of talented scientists, software developers, and support personnel. A broad community of scientists, engineers, students, commercial partners, museums, and other facilities work with SDSC to develop cyberinfrastructure-enabled applications to help manage their extreme data needs. Projects run the gamut from creating astrophysics visualization for the American Museum of Natural History, to supporting more than 20,000 users per day to the Protein Data Bank, to performing large-scale, award-winning simulations of the origin of the universe or how a major earthquake would affect densely populated areas such as southern California. Along with these data cyberinfrastructure tools, SDSC also offers users full-time support including code optimization, training, 24-hour help desk services, portal development and a variety of other services. As one of the NSF's first national supercomputer centers, SDSC served as the data-intensive site lead in the agency's TeraGrid program, a multiyear effort to build and deploy the world's first large-scale infrastructure for open scientific research. SDSC currently provides advanced user support and expertise for XSEDE (Extreme Science and Engineering Discovery Environment) the five-year NSF-funded program that succeeded TeraGrid in mid-2011.
Proper citation: San Diego Supercomputer Center (RRID:SCR_001856) Copy
http://www.dkfz.de/en/mol_embryology/axeldb.html
THIS RESOURCE IS NO LONGER IN SERVICE, documented on June 21, 2011. Database focusing on gene expression in the frog Xenopus laevis, it is the web companion to the research papers describing a large-scale in situ hybridization screening in Xenopus embryos. The goals of this large-scale in situ screen project are to identify genes by the characterization of their expression pattern, to partially sequence the corresponding cDNAs and to maintain a database collecting the results.
Proper citation: Axel Database (RRID:SCR_001890) Copy
http://hopkinsneuro.org/research/jhu_nimh/
The Johns Hopkins NIMH Center is comprised of an interdisciplinary research team who has pooled their talents to study the nature of HIV-associated neurocognitive disorders (HAND). Their aim is to translate discoveries of the pathophysiological mechanisms into novel therapeutics for HAND. Objectives * To integrate aspects of ongoing research in HAND and SIV encephalitis * Develop high-throughput and screening assays for identifying novel therapeutic compounds * Use proteomics and lipidomics approaches to indentifying surrogate markers of disease activity * Disseminate information and education about HAND through existing and new educational systems, including the JHU AIDS Education Training Center and the JHU Center for Global Clinical Education * Facilitate the entry of new investigators into Neuro-AIDS research, and to catalyze new areas of research, particularly where relevant for drug discovery or the development of validated surrogate markers
Proper citation: Johns Hopkins NIMH Research Center Novel Therapeutics of HIV-associated Cognitive Disorders (RRID:SCR_001891) Copy
http://lad.icmb.utexas.edu/index_smd.shtml
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. The Longhorn Array Database (LAD) is a MIAME compliant microarray database that operates on PostgreSQL and Linux. It is a fully open source version of the Stanford Microarray Database (SMD), one of the largest microarray databases. LAD provides a simple, free, open, reliable and proven solution for storage and analysis of two-color microarray data. It stores raw and normalized data from microarray experiments, as well as their corresponding image files. In addition, LAD provides interfaces for data retrieval, analysis, and visualization.
Proper citation: Longhorn Array Database (RRID:SCR_001895) Copy
http://www.nesys.uio.no/Atlas3D/
A multi-platform visualization tool which allows import and visualization of 3-D atlas structures in combination with tomographic and histological image data. The tool allows visualization and analysis of the reconstructed atlas framework, surface modeling and rotation of selected structures, user-defined slicing at any chosen angle, and import of data produced by the user for merging with the atlas framework. Tomographic image data in NIfTI (Neuroimaging Informatics Technology Initiative) file format, VRML and PNG files can be imported and visualized within the atlas framework. XYZ coordinate lists are also supported. Atlases that are available with the tool include mouse brain structures (3-D reconstructed from The Mouse Brain in Stereotaxic Coordinates by Paxinos and Franklin (2001)) and rat brain structures (3-D reconstructed from The Rat Brain in Stereotaxic Coordinates by Paxinos and Watson (2005)). Experimental data can be imported in Atlas3D and warped to atlas space, using manual linear registration, with the possibility to scale, rotate, and position the imported data. This facilitates assignment of location and comparative analysis of signal location in tomographic images.
Proper citation: Atlas3D (RRID:SCR_001808) Copy
http://opencourse.org/Collaboratories/harveyproject/
THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. It is an international collaboration of educators, researchers, physicians, students, programmers, instructional designers and graphic artists working together to build interactive, dynamic human physiology course materials on the Web. Sponsors: This work has received funding from the US National Science Foundation.
Proper citation: Harvey Project: Open Course Collaboratories (RRID:SCR_001887) Copy
Professional society of genetic counselors that promotes networking, continuing education opportunities, advocacy, and discussion of relevant issues in the field of genetics.
Proper citation: National Society of Genetic Counselors (RRID:SCR_001803) Copy
http://www.bioconductor.org/packages/release/bioc/html/RchyOptimyx.html
Software that constructs a hierarchy of cells using flow cytometry for maximization of an external variable (e.g., a clinical outcome or a cytokine response).
Proper citation: RchyOptimyx (RRID:SCR_001889) Copy
https://code.google.com/p/tbrowse/
Software providing a HTML5/javascript based browser for visualizing RNA-seq results in the familiar track layout of common genome browser. But given the quantitative nature of RNA-seq data, in addition to visualizing sequence coverage, the browser quantitates transcript abundance across regions of interest. The HTML5 functionality is made of use to render all the tracks using the canvas drawing element. This greatly reduces the load on servers and allows for rich interactive graphics without the need for third-party plugins. Furthermore, this framework completely segregates data from visualization, making development much easier. The browser is designed to run on all modern browsers: Firefox, Safari, Chrome, Opera and Internet Explorer (though not recommended).
Proper citation: tbrowse (RRID:SCR_001918) Copy
http://www-genome.stanford.edu/
This resource hyperlinks to systematic analysis projects, resources, laboratories, and departments at Stanford University.
Proper citation: Stanford Genomic Resourses (RRID:SCR_001874) Copy
This site is provided as a service to scientists, educators, students and others simply interested in the Biological subjects. While many of the resources listed on these pages are designed for scientific professionals, those that require little or no background are labeled as Beginner's Level. Topics include: Angiogenesis, Apoptosis, Carbohydrates, Cell Adhesion & ECM, Cell Cycle, Cell Senescence, Chemical Biology, Cytoskeleton & Motility, Development, Enzymes, Genes, Lipids & Membranes, Metabolism, Microscopy, Organelles, Proteins, Signaling, Structural Biology, Systems Biology Other available categories include: General Resources & Tutorials, Scientific Research Groups, Databases & Tools, Methods, Software, Vendors, Books, Journals, Literature Search, Career & Funding, Organizations & Meetings
Proper citation: BioChemWeb.org - The Virtual Library of Biochemistry Molecular Biology and Cell Biology (RRID:SCR_001912) Copy
THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. Obesity e-Lab is a unique, secure environment for producing, sharing, communicating and finding obesity research between epidemiologists, public health researchers and social scientists. Features of e-Lab: - Tools to share: it enables social and biomedical researchers to share data, information and analytical tools for obesity research. First, it will create a portal to provide access to the platform and facilitate social networking. - Navigation tools: Second, it will generate search and navigation tools for researchers in academic, NHS or local government organizations to find data from administrative and secure data services, via social science views of health datasets, and health science views of social datasets. Within the NHS, e-Lab links records from a variety of administrative and health (and social) care sources for broadly-specified obesity research, and make pseudonymised extracts of NHS-linked datasets available via the portal. - Analytical tools: Third, it will develop analytical tools, focused on: i) easy, reliable and privacy-protecting transformation of geo-codes in health records to other geographies and area-based social and economic measures; ii) epidemiological extensions to geographical information systems; iii) growth-standardization of child obesity measures. The tool-building will employ as much existing software as possible, focusing on the provision of simple, intuitive interfaces to proven software to make it easy for social or biomedical researchers to use collaboratively.
Proper citation: National Center for e-Social Science: Obesity e-Lab (RRID:SCR_001796) Copy
Portal for researchers to locate information relevant to interpretation and follow-up of human genetic epidemiological discoveries, including: a range of population and case and family genetic epidemiological studies, relevant gene and sequence databases, genetic variation databases, trait measurement, resource labs, journals, software, general information, disease genes and genetic diversity.
Proper citation: Online Encyclopedia for Genetic Epidemiology studies (RRID:SCR_001825) Copy
https://www.bioconductor.org/packages//2.10/bioc/html/spade.html
An analysis and visualization software tool for high dimensional flow cytometry data that organizes cells into hierarchies of related phenotypes.
Proper citation: SPADE (RRID:SCR_001810) Copy
http://www.nesys.uio.no/Micro3D/
The Micro3D 2004 is a software for 3-D reconstruction, visualization, and analysis of neuronal populations and brain regions. Micro3D generates geometric models from line and point coded data sets, representing labeled objects such as cell bodies or axonal plexuses, and boundaries of brain regions in serial sections. Data are typically imported from image-combining computerized microscopy systems, such as Neurolucida (MicroBrightField, Colchester, VT). The models may be rotated and zoomed in real-time. Surfaces are re-synthesized on the basis of stacks of contour lines. Clipping is used for defining section-independent subdivisions of the model. Flattening of sheets of points in curved layers (e.g., neurons in a cortical lamina) facilitates inspection of complicated distribution patterns. Micro3D computes color-coded density maps, and allows production of mpeg videos. Micro3D 2004 runs on LINUX PCs equipped with Open Inventor. It performs operations similar to the Silicon Graphics based version that has been used in more than 25 investigations and in various species, ranging from insects to monkeys, at the LM- and EM-level. Sponsors:Micro 3D was developed with support from The Research Council of Norway and The Oslo Research Park / FORNY.
Proper citation: Neural Systems and Graphics Computing Laboratory: Micro3D Software (RRID:SCR_001811) Copy
http://www.kindai.ac.jp/english/
Private non-sectarian and coeducational university based in Higashiosaka, Osaka, Japan.
Proper citation: Kindai University; Osaka; Japan (RRID:SCR_001814) Copy
http://sammeth.net/confluence/display/ASTA/2+-+Download
Tool that extracts and displays alternative splicing (AS) events from a given genomic annotation of exon-intron gene coordinates. By comparing all given transcripts, it detects the variations in their splicing structure and identifies all AS events (like exon skipping, alternate donor, etc) by assigning to each of them an AS code. It provides a visual summary of the AS landscape in the analyzed dataset, the possibility to browse the results on the UCSC website or to download them in GTF or ASTA format. You can use AStalavista for any genome by providing your own annotation set, the identifier of your gene(s) of interest, or analyze the AS landscape of reference annotation datasets like Gencode, RefSeq, Ensembl, FlyBase, etc.
Proper citation: AStalavista (RRID:SCR_001815) Copy
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