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https://resource.loni.usc.edu/resources/atlases/

Probabilistic reference system for human brain, including tools to establish this reference system for structural and functional anatomy on both macroscopic (in vivo) and microscopic (post mortem) levels. Project has expanded neuroinformatics tools for data sharing and created Conforming Site System that allows laboratories worldwide to contribute data to evolving atlas. Through implementation of ICBM data sharing policy space, they are fostering data exchange while still providing for scientific credit assignment and subject confidentiality.ICBM atlas collection consists of ICBM Template, tool developed to provide reference that includes both set of coordinates and associated anatomical labels; the ICBM 452 T1 atlas, average of T1-weighted MRIs of normal young adult brains, ICBM probabilistic atlases, and Cytoarchitectonic Atlas. ICBM Subject Database is web-based database infrastructure that simplifies image dataset collection, organization and dissemination. Authorized users may view representations of data and form collections of datasets that can be downloaded or fed directly into Pipeline environment for distributed processing and analysis.

Proper citation: International Consortium for Brain Mapping (RRID:SCR_000445) Copy   

•   Source: SciCrunch Registry

http://www.talairach.org/

Software automated coordinate based system to retrieve brain labels from the 1988 Talairach Atlas. Talairach Daemon database contains anatomical names for brain areas using x-y-z coordinates defined by the 1988 Talairach Atlas.

Proper citation: Talairach Daemon (RRID:SCR_000448) Copy   

•   Source: SciCrunch Registry

https://github.com/PacificBiosciences/stsPlots

Software to plot primary analysis quality control metrics to assess potential SMRTcell loading problems.

Proper citation: stsPlots (RRID:SCR_000449) Copy   

•   Source: SciCrunch Registry

http://highwire.stanford.edu/

A division of the Stanford University Libraries, which produces the online versions of journals and other scholarly content.

Proper citation: HighWire Press (RRID:SCR_000761) Copy   

•   Source: SciCrunch Registry

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

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 6,2023. A series of of webinars offered directly to users' computers. The webinars are offered in a variety of subjects, including neurotrauma, spine, tumor and vascular. Each webinars costs $35 US and offers CME credit.

Proper citation: University of Neurosurgery Webinar Series (RRID:SCR_000639) Copy   

•   Source: SciCrunch Registry

http://neuralensemble.org/neo/

A Python package for representing electrophysiology data, together with support for reading a wide range of neurophysiology file formats, including Spike2, NeuroExplorer, AlphaOmega, Axon, Blackrock, Plexon, Tdt, and support for writing to a subset of these formats plus non-proprietary formats including HDF5. The goal of Neo is to improve interoperability between Python tools for analyzing, visualizing and generating electrophysiology data (such as OpenElectrophy, NeuroTools, G-node, Helmholtz, PyNN) by providing a common, shared object model. In order to be as lightweight a dependency as possible, Neo is deliberately limited to represention of data, with no functions for data analysis or visualization. Neo implements a hierarchical data model well adapted to intracellular and extracellular electrophysiology and EEG data with support for multi-electrodes (for example tetrodes). Neo's data objects build on the quantities package, which in turn builds on NumPy by adding support for physical dimensions. Thus Neo objects behave just like normal NumPy arrays, but with additional metadata, checks for dimensional consistency and automatic unit conversion.

Proper citation: Neo (RRID:SCR_000634) Copy   

•   Source: SciCrunch Registry

http://www.icpsr.umich.edu/icpsrweb/NAHDAP/

Archive that acquires, preserves and disseminates data relevant to drug addiction and HIV research. Collection of data on drug addiction and HIV infection in United States. Most of datasets are raw data from surveys, interviews, and administrative records. They were originally gathered in research projects and for administrative purposes. Some datasets have been used in published studies. Bibliographies of these studies are available . Provides access to research data and technical assistance for data depositors. Provides e-workshops on data preparation and data systems.

Proper citation: National Addiction and HIV Data Archive Program (NAHDAP) (RRID:SCR_000636) Copy   

•   Source: SciCrunch Registry

http://athina.biol.uoa.gr/CAST/

A novel algorithm for low-complexity region detection and selective masking. The algorithm is based on multiple-pass Smith-Waterman comparison of the query sequence against twenty homopolymers with infinite gap penalties. The output of the algorithm is both the masked query sequence for further analysis, e.g. database searches, as well as the regions of low complexity.

Proper citation: CAST (RRID:SCR_000628) Copy   

•   Source: SciCrunch Registry

https://team.inria.fr/empenn/research/

Research team focused on research and development of new algorithms in medical imaging, information processing and computer assisted intervention in the context of the pathologies of the central nervous system. Research team jointly affiliated to INSERM (National Institute of Health and Scientific Research), Inria (National Institute of Research in Computer Sciences and Automation) and IRISA / UMR CNRS 6074, University of Rennes I. Multidisciplinary team merging researchers in image processing and medical doctors.

Proper citation: VISAGES Research (RRID:SCR_000749) Copy   

•   Source: SciCrunch Registry

http://www.helsinki.fi/bsg/software/BEBaC/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Software for Bayesian estimation of bacterial communities.

Proper citation: BEBaC (RRID:SCR_000621) Copy   

•   Source: SciCrunch Registry

http://genboree.org

A software application and database viewing system for genomic research, more specifically formulti-genome comparison and pattern discovery via genome self-comparison. Data are available for a range of species including Human Chr3, Human Chr12, Sea Urchin, Tribolium, and cow. The Genboree Discovery System is the largest software system developed at the bioinformatics laboratory at Baylor in close collaboration with the Human Genome Sequencing Center. Genboree is a turnkey software system for genomic research. Genboree is hosted on the Internet and, as of early 2007, the number of registered users exceeds 600. While it can be configured to support almost any genome-centric discovery process, a number of configurations already exist for specific applications. Current focus is on enabling studies of genome variation, including array CGH studies, PCR-based resequencing, genome resequencing using comparative sequence assembly, genome remapping using paired-end tags and sequences, genome analysis and annotation, multi-genome comparison and pattern discovery via genome self-comparison. Genboree database and visualization settings, tools, and user roles are configurable to fit the needs of specific discovery processes. Private permanent project-specific databases can be accessed in a controlled way by collaborators via the Internet. Project-specific data is integrated with relevant data from public sources such as genome browsers and genomic databases. Data processing tools are integrated using a plug-in model. Genboree is extensible via flexible data-exchange formats to accommodate project specific tools and processing steps. Our Positional Hashing method, implemented in the Pash program, enables extremely fast and accurate sequence comparison and pattern discovery by employing low-level parallelism. Pash enables fast and sensitive detection of orthologous regions across mammalian genomes, and fast anchoring of hundreds of millions of short sequences produced by next-generation sequencing technologies. We are further developing the Pash program and employing it in the context of various discovery pipelines. Our laboratory participates in the pilot stage of the TCGA (The Cancer Genome Atlas) project. We aim to develop comprehensive, rapid, and economical methods for detecting recurrent chromosomal aberrations in cancer using next-generation sequencing technologies. The methods will allow detection of recurrent chromosomal aberrations in hundreds of small (

Proper citation: Genboree Discovery System (RRID:SCR_000747) Copy   

•   Source: SciCrunch Registry

http://bioconductor.org/packages/release/bioc/html/flipflop.html

Software that discovers which isoforms of a gene are expressed in a given sample together with their abundances, based on RNA-Seq read data.

Proper citation: FlipFlop (RRID:SCR_000625) Copy   

•   Source: SciCrunch Registry

http://cryptogenome.ucsf.edu

THIS RESOURCE IS NO LONGER IN SERVICE, documented July 19, 2016. This site is built and maintained by the Madhani Lab, Dept. of Biochemistry and Biophysics at the University of California, San Francisco

Proper citation: CryptoBase (RRID:SCR_000780) Copy   

•   Source: SciCrunch Registry

http://www.stanford.edu/group/nusselab/cgi-bin/wnt/

A resource for members of the Wnt community, providing information on progress in the field, maps on signaling pathways, and methods. The page on reagents lists many resources generously made available to and by the Wnt community. Wnt signaling is discussed in many reviews and in a recent book. There are usually several Wnt meetings per year.

Proper citation: Wnt homepage (RRID:SCR_000662) Copy   

•   Source: SciCrunch Registry

http://www.filemaker.com

A database software for managing, analyzing and sharing information across multiple devices and people, both online and offline.

Proper citation: FileMaker (RRID:SCR_000783) Copy   

•   Source: SciCrunch Registry

https://code.google.com/p/glycoworkbench/

A suite of software tools designed for the rapid drawing of glycan structures and for assisting the process of structure determination from mass spectrometry data.

Proper citation: GlycoWorkbench (RRID:SCR_000782) Copy   

•   Source: SciCrunch Registry

http://www.drugs.com

The Drugs.com mission is to be the Internets most trusted resource for drug and related health information. We will achieve this aim by presenting independent, objective, comprehensive and up-to-date information in a clear and concise format for both consumers and healthcare professionals. Their goal is to provide clear information about drugs sold in the USA, at a level everyone can comprehend. For consumers, we provide product information in non-technical language. Health professionals will find what they need in the FDA Product Label Professional Information database. The Care Guide provides information about the treatment of common illnesses and injuries. The Drug Interactions checker details drug-drug interaction mechanisms, severity and management, and also outlines drug-food interactions. Drugs.com is NOT an online pharmacy and does not condone the sale of prescription medicines over the Internet without a prescription. Drugs.com simply provides a free drug-information service to help you better understand how medicines work: their uses, side effects and potential to interact with other medicines. For information on purchasing prescription medicines online please visit the FDAs Buying Prescription Medicine Online: A Consumer Safety Guide. Drugs.com medical dictionary is powered by Stedmans. Since 1911, Stedmans Medical Dictionary has been the medical professions most trusted source for medical definitions. A complete medical terms dictionary, Steadmans Electronic Medical Dictionary contains over 107,000 medical terms taken directly from Stedmans Medical Dictionary, 28th Edition. Most search engines cover the entire Internet, and searches on these engines may produce many results that are not specific to your drug question. On Drugs.com, you can search by medical condition or by drug, and get the answer you need right away. Searches by drug can be made using the brand name or the generic name of the drug. Searches by medical condition will return a list of medications used to treat that condition. Sponsors: The Drugs.com drug information service is supported by donations and revenue from site advertisers. The Drugs.com staff endeavor to source ads that are medically or community-service oriented. All ads must be appropriate for all-age family viewing, and we screen banner ads for family-appropriate content before the ads go live.

Proper citation: Drugs.com (RRID:SCR_000656) Copy   

•   Source: SciCrunch Registry

http://gowiki.tamu.edu/wiki/

A wiki where users of the Gene Ontology can contribute and view notes about how specific GO terms are used. GONUTS can also be used as a GO term browser, or to search for GO annotations of specific genes from included organisms. The rationale for this wiki is based on helping new users of the gene ontology understand and use it. The GONUTS wiki is not an official product of the the Gene Ontology consortium. The GO consortium has a public wiki at their website, http://wiki.geneontology.org/. Maintaining the ontology involves many decisions to carefully choose terms and relationships. These decisions are currently made at GO meetings and via online discussion using the GO mailing lists and the Sourceforge curator request tracker. However, it is difficult for someone starting to use GO to understand these decisions. Some insight can be obtained by mining the tracker, the listservs and the minutes of GO meetings, but this is difficult, as these discussions are often dispersed and sometimes don't contain the GO accessions in the relevant messages. Wikis provide a way to create collaboratively written documentation for each GO term to explain how it should be used, how to satisfy the true path requirement, and whether an annotation should be placed at a different level. In addition, the wiki pages provide a discussion space, where users can post questions and discuss possible changes to the ontology. GONUTS is currently set up so anyone can view or search, but only registered users can edit or add pages. Currently registered users can create new users, and we are working to add at least one registered user for each participating database (So far we have registered users at EcoliHub, EcoCyc, GOA, BeeBase, SGD, dictyBase, FlyBase, WormBase, TAIR, Rat Genome Database, ZFIN, MGI, UCL and AgBase...

Proper citation: GONUTS (RRID:SCR_000653) Copy   

•   Source: SciCrunch Registry

https://www.wool.com/

Company focused on animal welfare and pest prevention in the wool industry.

Proper citation: Australian Wool Innovation Limited (RRID:SCR_000775) Copy   

•   Source: SciCrunch Registry

http://www.pbtc.org/

The PEDIATRIC BRAIN TUMOR CONSORTIUM (PBTC) is a multidisciplinary cooperative research organization devoted to the study of correlative tumor biology and new therapies for primary CNS tumors of childhood. PBTC's mission is to contribute rapidly and effectively to the understanding and cure of these tumors through the conduct of multi-center, multidisciplinary, innovative studies with designs and analyses based on uniformly high quality statistical science. While the primary mission of the PBTC is to identify through laboratory and clinical science superior treatment strategies for children with brain cancers, the PBTC investigators recognize their profound responsibility to meet the special needs of the children and families as they face this enormous challenge. Members are committed to working within their institutions and communities to improve support services and follow up care for these patients and their families. The PBTC's primary objective is to rapidly conduct novel phase I and II clinical evaluations of new therapeutic drugs, new biological therapies, treatment delivery technologies and radiation treatment strategies in children from infancy to 21 years of age with primary central nervous system (CNS) tumors. A second objective is to characterize reliable markers and predictors (direct or surrogate) of brain tumors' responses to new therapies. The Consortium conducts research on brain tumor specimens in the laboratory to further understand the biology of pediatric brain tumors. A third objective is to develop and coordinate innovative neuro-imaging techniques. Through the PBTC's Neuro-Imaging Center, formed in May 2000, research to evaluate new treatment response criteria and neuro-imaging methods to understand regional brain effects is in progress. These imaging techniques can also advance understanding of significant neuro-toxicity in a developing child's central nervous system. The Neuro-Imaging Center is supported in part by private sources - grants from foundations and non-profit organizations - in addition to the NCI. As an NCI funded Consortium, the Pediatric Brain Tumor Consortium (PBTC) is required to make research data available to other investigators for use in research projects. An investigator who wishes to use individual patient data from one or more of the Consortium's completed and published studies must submit in writing a description of the research project, the PBTC studies from which data are requested, the specific data requested, and a list of investigators involved with the project and their affiliated research institutions. A copy of the requesting investigator's CV must also be provided. Participating Institutions: Children's Hospital of Philadelphia, Children's National Medical Center (Washington, DC), Children's Memorial Hospital (Chicago), Duke University, National Cancer Institute, St. Jude Children's Research Hospital, Texas Children's Cancer Center, University of California at San Francisco, and University of Pittsburgh.

Proper citation: Pediatric Brain Tumor Consortium (RRID:SCR_000658) Copy   

•   Source: SciCrunch Registry