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A selection of image analysis algorithms for the processing of diffusion-weighted MR images. Features & Highlights * Tensor and q-ball reconstruction * Glyph visualization * Quantification and partial volume clustering of tensor and q-ball images * Global fiber tractography, visualization, and tract post-processing * Brain network statistics and visualization (connectomics) * Interactive exploration of Tract-based spatial statistics (TBSS) results * Intra-voxel incoherent motion (IVIM) estimation * Synthetic data generation Additional system specific requirements: * Windows: If you have problems running the Windows application, please install the Microsoft Redistributable Packages for VS 2008: 32 bit or 64 bit * Linux: the Qt framework, version 4.6.2 or later Tested systems: Windows 7, Windows Vista; Ubuntu 12.04 and newer; OS X 10.6 (Snow Leopard), OS X 10.8 (Mountain Lion) The OS X 10.6 installer is compatible with OS X 10.7 (Lion) so there is no dedicated disk image build under 10.7. The MITK Diffusion application is based on the MITK research platform and the most of it is open-source. The available code is embedded into the source code of MITK as a module and can be accessed through the public git repository.

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• SciCrunch
• 14 years ago - by Anonymous

Funds innovative research and development in Washington state to promote life sciences competitiveness, enhance economic vitality, and improve health and health care. Its grantmaking opportunities are designed to leverage the state''s investment in research and development by achieving three goals: promoting health; making the life sciences sector more competitive; and strengthening Washington''s economy. LSDF currently offers two different types of granting mechanisms for both for-profit and non-profit organizations in Washington: * Proof of Concept grants to enhance the commercial viability of intellectual property developed by non-profit organizations or enhance the competitiveness of early-stage companies for private equity investment. (This grant mechanism combines the Commercialization and PreCede mechanisms offered in prior years.) * Opportunity grants to fund extraordinary research and development proposals having the ability to significantly leverage LSDF dollars against those from other sources.

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• SciCrunch
• 14 years ago - by Anonymous

Ontology and database that links plant anatomy, morphology and growth and development to plant genomics data.Plant Ontology Consortium develops, curates and shares controlled vocabularies (ontologies) that describe plant structures and growth and developmental stages, providing semantic framework for meaningful cross species queries across databases. PO is under active development to expand to encompass terms and annotations from all plants.

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• SciCrunch
• 16 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. Database of sequence tagged sites (STSs) derived from STS-based maps and other experiments. STSs are defined by PCR primer pairs and are associated with additional information such as genomic position, genes, and sequences. Chromosome maps are labeled by name of the originating organism, the map title, total markers, total UniSTSs and links to view maps as well as research documents available through PubMed, another NCBI database. The search functions within UniSTS allow the user to search by gene marker, chromosome, gene symbol and gene description terms to locate markers on specified genes. A representation of the UniSTS datasets is available by ftp. NOTE: All data from this resource have been moved to the Probe database, http://www.ncbi.nlm.nih.gov/probe. You can retrieve all UniSTS records by searching the probe database using the search term unists(properties). (use brackets insead of parenthesis). Additionally, legacy data remain on the NCBI FTP Site in the UniSTS Repository (ftp://ftp.ncbi.nih.gov/pub/ProbeDB/legacy_unists).

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• SciCrunch
• 17 years ago - by Anonymous

Information dissemination service of the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) established to increase knowledge and understanding about diseases of the kidneys and urologic system among people with these conditions and their families, health care professionals, and the general public: online, in booklets and fact sheets, by email, and over the phone. To carry out this mission, NKUDIC works closely with a coordinating panel of representatives from Federal agencies; voluntary organizations on the national level; professional groups; and State health departments to identify and respond to informational needs about kidney and urologic diseases. NKUDIC provides the following informational products and services: * Response to inquiries about kidney and urologic diseases-ranging from information about available patient and professional education materials to statistical data. By phone (8:30 a.m. to 5 p.m. eastern time, M-F), fax, mail, and email. * Publications about specific kidney and urologic diseases, provided free of copyright, in varying reading levels. Available online or as booklets and brochures. (See our Publications Catalog.) NKUDIC also sends publications to health fairs and community events. Please contact us for more information. * Referrals to health professionals through the National Library of Medicine''''s MEDLINEplus includes a consumer-friendly listing of organizations that will assist you in your search for physicians and other health professionals. * Exhibits at professional meetings specific to kidney and urologic diseases, as well as cross-cutting professional meetings. NKUDIC exhibits at 11 professional meetings, each year, including Society of Urologic Nurses and Associates, American Urologic Association, American Society of Nephrology, National Kidney Foundation, Polycystic Kidney Disease Research Foundation, American Academy of Family Physicians, American Academy of Physician Assistants, American Nurses Association, and the National Conference for Nurse Practitioners.

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• dkNET
• 14 years ago - by Anonymous

Database and biorepository from a multi-site, multi-disciplinary study characterizing the familial transmission of alcoholism and related phenotypes and identifying susceptibility genes using genetic linkage. Investigators have assembled a collection of over 300 extended families densely affected by alcoholism (more than 3000 individuals), including clinical, neuropsychological, electrophysiological, biochemical, and genetic data, and established a repository of immortalized cell lines from these individuals, to serve as a permanent source of DNA for genetic studies. NIAAA has funded the Collaborative Studies on Genetics of Alcoholism (COGA) since 1989, with the goal of identifying the specific genes underlying this vulnerability. Data and biomaterials are available to qualified investigators in the broader scientific community. Recipients of data and biomaterials will be responsible for defraying the cost of their distribution. Pedigrees densely affected with alcoholism (DSM-III-R) have been ascertained at six sites (SUNY Downstate Health Sciences Center, University of Connecticut, Indiana University, Washington University, University of Iowa, and The University of California at San Diego). Diagnoses of alcohol dependence according to several diagnostic systems (e.g., DSM-III-R, Feighner, ICD-10) are made based on examination of medical records and direct assessment using the Semi-Structured Assessment for Genetics of Alcoholism (SSAGA). Nuclear and extended pedigrees containing at least two alcohol-dependent first-degree relatives in addition to an alcohol dependent proband (with all affected individuals meeting both DSM-IIIR and Feighner criteria) have been ascertained. Clinical data comprises anonymous data on family structure, age, sex, vital status, psychopathology, diagnosis, other clinically relevant information, are stored, maintained, and distributed by Washington University. Research data, consist of data on blood biochemistry and psychological test performance, which are stored, maintained, and distributed by Washington University, and brain electrophysiological data, which are stored, maintained, and distributed by SUNY. Genetic analysis data, consisting of marker genotypes, along with results of previous genetic analyses of COGA data, are stored, maintained, and distributed by Washington University. Biomaterials, consisting of lymphoblastoid cell lines and DNA from participating subjects are stored, maintained, and distributed by Rutgers University. Researchers may gain access to clinical data, research data, genetic analysis data, and biomaterials, subject to NIAAA approval, by completing an application details available from the website. After access certification, the principal investigator will be given access to electronic data files and other documentation.

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• SciCrunch
• 17 years ago - by Anonymous

The Epilepsy Genetic Association Database (epiGAD) is an online repository of data relating to genetic association studies in the field of epilepsy. It summarizes the results of both published and unpublished studies, and is intended as a tool for researchers in the field to keep abreast of recent studies, providing a bird''s eye view of this research area. The goal of epiGAD is to collate all association studies in epilepsy in order to help researchers in this area identify all the available gene-disease associations. Finally, by including unpublished studies, it hopes to reduce the problem of publication bias and provide more accurate data for future meta-analyses. It is also hoped that epiGAD will foster collaboration between the different epilepsy genetics groups around the world, and faciliate formation of a network of investigators in epilepsy genetics. There are 4 databases within epiGAD: - the susceptibility genes database - the epilepsy pharmacogenetics database - the meta-analysis database - the genome-wide association studies (GWAS) database The susceptibility genes database compiles all studies related to putative epilepsy susceptibility genes (eg. interleukin-1-beta in TLE), while the pharmacogenetics studies in epilepsy (eg. ABCB1 studies) are stored in ''phamacogenetics''. The meta-analysis database compiles all existing published epilepsy genetic meta-analyses, whether for susceptibility genes, or pharmacogenetics. The GWAS database is currently empty, but will be filled once GWAS are published. Sponsors: The epiGAD website is supported by the ILAE Genetics Commission.

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• SciCrunch
• 17 years ago - by Anonymous

A Graphical User Interface for NEURON simulator environment with 3D capabilities. Neuronvisio makes easy to select and investigate sections'''' properties and it offers easy integration with matplotlib for plotting the results. The geometry can be saved using NeuroML and the computational results in a customized and extensible HDF5 format; the results can then be reload in the software and analyzed in a later stage, without re-running the simulation. Featuring 3D visualization of the model with the possibility to change it runtime; creation of vectors to record any variables present in the section; pylab integration to plot directly the result of the simulation; exploration of the timecourse of any variable among time using a color coded scale; saving the results simulation for later analysis; automatic download and running of models in ModelDB.

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• SciCrunch
• 13 years ago - by Anonymous

Provides NIH clinical investigators with access to identifiable data for the subjects on their own active protocols, while providing all NIH investigators with access to de-identified data across all protocols. BTRIS provides users with advanced search, filtering, and aggregation methods to create data sets to support ongoing studies and stimulate ideas for new research. BTRIS is two distinct but interrelated applications, BTRIS Data Access and BTRIS Preferences. * BTRIS Data Access is the data repository where principal investigators or their designee create reports on their active protocols with identified subject data. Reports include the IRB Inclusion Enrollment Report, demographics, patient lists, laboratory and microbiology results, vital signs, medication orders and administration, diagnoses, and radiology reports (with links to images in the CC PACS system). * BTRIS Preferences is a Web based application that allows principal investigators or their designees to verify subject enrollment in their protocol(s). This ensures that reports created in BTRIS Data Access include all subjects. It also allows the principal investigator to designate an alternate investigator from the protocol to manage subject enrollment and create reports in BTRIS Data Access. BTRIS contains subject data from CRIS/MIS (the Clinical Center Medical Information Systems) and research data from NIAID (Crimson), NIAAA, and NCI. Data are available from 1976 to the present.

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• SciCrunch
• 17 years ago - by Anonymous

A program developed by the NIMH Laboratory of Neuropsychology for data acquisition and experimental control of neurophysiological experiments. The purpose of this website is to make it easier to access new versions of NIMH CORTEX and its supporting documents. Ultimately, it is also hoped that these pages will make it easier for users to report bugs, request enhancements, and obtain help. Download the latest version and unzip it into a new sub-directory. Then read the on-line documentation. For the new user, the User''s Manuals are invaluable in specifying system requirements and giving an overview of the features and necessary hardware. The Function reference goes into more detail about how to write experiments using NIMH CORTEX. The Demos reference is a good place for new and experienced users to start to get an idea of what NIMH CORTEX can do these days.

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• SciCrunch
• 17 years ago - by Anonymous

Action Potential is a forum operated by neuroscience editors at Nature for the entire neuroscience community. We''ll discuss what''s new and exciting in science, be it in our journals or elsewhere, as well as science policy and publishing and provide updates from major meetings. Although we provide the opportunity to comment as a service to the community, we do not endorse all viewpoints represented here. To contact the contributors directly with confidential questions or suggestions for future entries, please e-mail n.gray (at) us.nature.com.

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• SciCrunch
• 15 years ago - by Anonymous

A structured controlled vocabulary of the anatomy of Caenorhabditis elegans.

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• SciCrunch
• 13 years ago - by Anonymous

This web server makes predictions of family, superfamily and fold level classifications of proteins based on the Structural Classification of Proteins (SCOP) hierarchy using the Support Vector Machine (SVM) learning algorithm. SVM-FOLD detects subtle protein sequence similarities by learning from all available annotated proteins, as well as utilizing potential hits as identified by PSI-BLAST. Predictions of classes of proteins that do not have any known example with a significant pairwise PSI-BLAST E-value can still be found using SVMs.

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• SciCrunch
• 16 years ago - by Anonymous

NCI''s comprehensive cancer database that contains summaries on a wide range of cancer topics; a registry of 8,000+ open and 19,000+ closed cancer clinical trials from around the world; a directory of professionals who provide genetics services; the NCI Dictionary of Cancer Terms, with definitions for 6,800+ cancer and medical terms; and the NCI Drug Dictionary, which has information on 2,300+ agents used in the treatment of cancer or cancer-related conditions. The PDQ cancer information summaries are peer reviewed and updated monthly by six editorial boards comprised of specialists in adult treatment, pediatric treatment, supportive care, screening and prevention, genetics, and complementary and alternative medicine. The Boards review current literature from more than 70 biomedical journals, evaluate its relevance, and synthesize it into clear summaries. Many of the summaries are also available in Spanish.

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• SciCrunch
• 17 years ago - by Anonymous

Software package that implements a model of per-position sequencing bias in high-throughput sequencing data using a simple Bayesian network, the structure and parameters of which are trained on a set of aligned reads and a reference genome sequence.

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• SciCrunch
• 13 years ago - by Anonymous

A specialized version of autoPack designed to pack biological components together. The current version is optimized to pack molecules into cells with biologically relevant interactions to populate massive cell models with atomic or near-atomic details. Components of the algorithm pack transmembrane proteins and lipids into bilayers, globular molecules into compartments defined by the bilayers (or as exteriors), and fibrous components like microtubules, actin, and DNA.

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• SciCrunch
• 14 years ago - by Anonymous

An open-source general packing algorithm that packs 3D objects onto surfaces, into volumes, and around volumes. It provides a general architecture to allow various packing algorithms to interoperate efficiently in the same model. autoPack can incorporate any packing solution into its modular python program architecture, but is currently optimized to provide a novel solution to the loose packing problem which places objects of discrete size into place (compared to advancing front, popcorn, or other fast tight-packing solutions that allow objects to scale to arbitrary masses.) Most popular 3D software programs now contain robust physics engines based on Bullet that can separate small collections of overlapping objects or allow volumes to be filled by pouring shapes from generators, but these approaches fails for large complex systems and result in either overlapping geometry, crashed software, or non-random gradients. Most packing algorithms are designed to position objects as efficiently as possible, but autoPack allows the user to select from random loose packing to highly organized packing methods����??even to choose both methods at the same time. autoPack positions 3D geometries into, onto, and around volumes with minimal to zero overlap. autoPack mixes several packing approaches and procedural growth algorithms. autoPack can thus place objects with forces and constraints to allow a high degree of control ranging from completely random distributions to highly ordered structures. * zero to minimal overlaps depending on the method used * accuracy vs speed parameters selected by the user * zero edge effects * complete control, from fully random to fully ordered distributions * agent-based interaction, weighting, and collision control

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• SciCrunch
• 14 years ago - by Anonymous

A database and interactive web site for manipulating and displaying annotations on genomes. Features include: detailed views of the genome; use of a variety of premade or personally made glyphs ; customizable order and appearance of tracks by administrators and end-users; search by annotation ID, name, or comment; support of third party annotation using GFF formats; DNA and GFF dumps; connectivity to different databases, including BioSQL and Chado; and a customizable plug-in architecture (e.g. run BLAST, find oligonucleotides, design primers, etc.). GBrowse is distributed as source code for Macintosh OS X, UNIX and Linux platforms, and as pre-packaged binaries for Windows machines. It can be installed using the standard Perl module build procedure, or automated using a network-based install script. In order to use the net installer, you will need to have Perl 5.8.6 or higher and the Apache web server installed. The wiki portion accepts data submissions.

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• SciCrunch
• 17 years ago - by Anonymous

International collaboration producing an extensive public catalog of human genetic variation, including SNPs and structural variants, and their haplotype contexts, in an effort to provide a foundation for investigating the relationship between genotype and phenotype. The genomes of about 2500 unidentified people from about 25 populations around the world were sequenced using next-generation sequencing technologies. Redundant sequencing on various platforms and by different groups of scientists of the same samples can be compared. The results of the study are freely and publicly accessible to researchers worldwide. The consortium identified the following populations whose DNA will be sequenced: Yoruba in Ibadan, Nigeria; Japanese in Tokyo; Chinese in Beijing; Utah residents with ancestry from northern and western Europe; Luhya in Webuye, Kenya; Maasai in Kinyawa, Kenya; Toscani in Italy; Gujarati Indians in Houston; Chinese in metropolitan Denver; people of Mexican ancestry in Los Angeles; and people of African ancestry in the southwestern United States. The goal Project is to find most genetic variants that have frequencies of at least 1% in the populations studied. Sequencing is still too expensive to deeply sequence the many samples being studied for this project. However, any particular region of the genome generally contains a limited number of haplotypes. Data can be combined across many samples to allow efficient detection of most of the variants in a region. The Project currently plans to sequence each sample to about 4X coverage; at this depth sequencing cannot provide the complete genotype of each sample, but should allow the detection of most variants with frequencies as low as 1%. Combining the data from 2500 samples should allow highly accurate estimation (imputation) of the variants and genotypes for each sample that were not seen directly by the light sequencing. All samples from the 1000 genomes are available as lymphoblastoid cell lines (LCLs) and LCL derived DNA from the Coriell Cell Repository as part of the NHGRI Catalog. The sequence and alignment data generated by the 1000genomes project is made available as quickly as possible via their mirrored ftp sites. ftp://ftp.1000genomes.ebi.ac.uk ftp://ftp-trace.ncbi.nlm.nih.gov/1000genomes

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• SciCrunch
• 16 years ago - by Anonymous

An Antibody supplier

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• SciCrunch
• 14 years ago - by Anonymous