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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.

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On page 4 showing 61 ~ 80 out of 176 results
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  • RRID:SCR_013152

    This resource has 10+ mentions.

http://surfer.nmr.mgh.harvard.edu/fswiki/Tracula

Software tool developed for automatically reconstructing a set of major white matter pathways in the brain from diffusion weighted images using probabilistic tractography. This method utilizes prior information on the anatomy of the pathways from a set of training subjects. By incorporating this prior knowledge in the reconstruction procedure, our method obviates the need for manual intervention with the tract solutions at a later stage and thus facilitates the application of tractography to large studies. The trac-all script is used to preprocess raw diffusion data (correcting for eddy current distortion and B0 field inhomogenities), register them to common spaces, model and reconstruct major white matter pathways (included in the atlas) without any manual intervention. trac-all may be used to execute all the above steps or parts of it depending on the dataset and user''''s preference for analyzing diffusion data. Alternatively, scripts exist to execute chunks of each processing pipeline, and individual commands may be run to execute a single processing step. To explore all the options in running trac-all please refer to the trac-all wiki. In order to use this script to reconstruct tracts in Diffusion images, all the subjects in the dataset must have Freesurfer Recons.

Proper citation: TRACULA (RRID:SCR_013152) Copy   


  • RRID:SCR_017446

    This resource has 10+ mentions.

https://github.com/flatironinstitute/mountainsort

Neurophysiological spike sorting software.

Proper citation: MountainSort (RRID:SCR_017446) Copy   


  • RRID:SCR_006760

    This resource has 1+ mentions.

http://www.ninds.nih.gov/news_and_events/proceedings/20101217-NEXT.htm

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on June 26,2022. A unique clinical trial network open to studies of more than 400 neurological diseases, allowing investigators to more efficiently pursue new therapies based on scientific opportunity. The network has a centralized IRB serving 25 sites, which will allow trials to move faster, without the need to coordinate IRBs at each individual site. It is not necessary to be part of the NeuroNEXT infrastructure to propose and conduct a study within the network. The Network for Excellence in Neuroscience Clinical Trials, or NeuroNEXT, was created to conduct studies of treatments for neurological diseases through partnerships with academia, private foundations, and industry. The network is designed to expand the National Institute of Neurological Disorders and Stroke''s (NINDS) capability to test promising new therapies, increase the efficiency of clinical trials before embarking on larger studies, and respond quickly as new opportunities arise to test promising treatments for people with neurological disorders. The NeuroNEXT program aims to: * Provide a robust, standardized, and accessible infrastructure to facilitate rapid development and implementation of protocols in neurological disorders affecting adult and/or pediatric populations. The network includes multiple Clinical Sites, one Clinical Coordinating Center (CCC) and one Data Coordinating Center (DCC). * Support scientifically sound, possibly biomarker-informed, Phase II clinical trials that provide data for clear go/no-go decisions. * Energize and mobilize federal, industry, foundations and patient advocacy partners by leveraging existing relationships between NINDS and NeuroNEXT to organize high impact Phase II clinical trials for neurological disorders. * Expand the pool of experienced clinical investigators and research staff who are prepared to be leaders of multicenter clinical research trials. * Working with NeuroNEXT is a cooperative venture between NINDS, the NeuroNEXT network and the applicant.

Proper citation: NeuroNEXT (RRID:SCR_006760) Copy   


http://pdbml.pdb.org/

Markup Language that provides a representation of PDB data in XML format. The description of this format is provided in XML schema of the PDB Exchange Data Dictionary. This schema is produced by direct translation of the mmCIF format PDB Exchange Data Dictionary Other data dictionaries used by the PDB have been electronically translated into XML/XSD schemas and these are also presented in the list below. * PDBML data files are provided in three forms: ** fully marked-up files, ** files without atom records ** files with a more space efficient encoding of atom records * Data files in PDBML format can be downloaded from the RCSB PDB website or by ftp. * Software tools for manipulating PDB data in XML format are available.

Proper citation: Protein Data Bank Markup Language (RRID:SCR_005085) Copy   


  • RRID:SCR_005657

    This resource has 1+ mentions.

http://headit.ucsd.edu

Platform for sharing, download, and re-analysis or meta-analysis of sophisticated, fully annotated, human electrophysiological data sets. It uses EEG Study Schema (ESS) files to provide task, data collection, and subject metadata, including Hierarchical Event Descriptor (HED) tag descriptions of all identified experimental events. Visospatial task data also available from, http://sccn.ucsd.edu/eeglab/data/headit.html: A 238-channel, single-subject EEG data set recorded at the Swartz Center, UCSD, by Arnaud Delorme, Julie Onton, and Scott Makeig is al.

Proper citation: HeadIT (RRID:SCR_005657) Copy   


http://cerebrovascularportal.org

Portal enables browsing, searching, and analysis of human genetic information linked to cerebrovascular disease and related traits, while protecting the integrity and confidentiality of the underlying data.

Proper citation: Cerebrovascular Disease Knowledge Portal (RRID:SCR_015628) Copy   


https://www.icpsr.umich.edu/icpsrweb/content/addep/index.html

Provides access to data including wide range of topics related to disability. ADDEP data can be used to better understand and inform the implementation of Americans with Disabilities Act and other disability policies.

Proper citation: Archive of Data on Disability to Enable Policy (ADDEP) (RRID:SCR_016315) Copy   


  • RRID:SCR_006577

    This resource has 10+ mentions.

http://www.commondataelements.ninds.nih.gov

The purpose of the NINDS Common Data Elements (CDEs) Project is to standardize the collection of investigational data in order to facilitate comparison of results across studies and more effectively aggregate information into significant metadata results. The goal of the National Institute of Neurological Disorders and Stroke (NINDS) CDE Project specifically is to develop data standards for clinical research within the neurological community. Central to this Project is the creation of common definitions and data sets so that information (data) is consistently captured and recorded across studies. To harmonize data collected from clinical studies, the NINDS Office of Clinical Research is spearheading the effort to develop CDEs in neuroscience. This Web site outlines these data standards and provides accompanying tools to help investigators and research teams collect and record standardized clinical data. The Institute still encourages creativity and uniqueness by allowing investigators to independently identify and add their own critical variables. The CDEs have been identified through review of the documentation of numerous studies funded by NINDS, review of the literature and regulatory requirements, and review of other Institute''s common data efforts. Other data standards such as those of the Clinical Data Interchange Standards Consortium (CDISC), the Clinical Data Acquisition Standards Harmonization (CDASH) Initiative, ClinicalTrials.gov, the NINDS Genetics Repository, and the NIH Roadmap efforts have also been followed to ensure that the NINDS CDEs are comprehensive and as compatible as possible with those standards. CDEs now available: * General (CDEs that cross diseases) Updated Feb. 2011! * Congenital Muscular Dystrophy * Epilepsy (Updated Sept 2011) * Friedreich''s Ataxia * Parkinson''s Disease * Spinal Cord Injury * Stroke * Traumatic Brain Injury CDEs in development: * Amyotrophic Lateral Sclerosis (Public review Sept 15 through Nov 15) * Frontotemporal Dementia * Headache * Huntington''s Disease * Multiple Sclerosis * Neuromuscular Diseases ** Adult and pediatric working groups are being finalized and these groups will focus on: Duchenne Muscular Dystrophy, Facioscapulohumeral Muscular Dystrophy, Myasthenia Gravis, Myotonic Dystrophy, and Spinal Muscular Atrophy The following tools are available through this portal: * CDE Catalog - includes the universe of all CDEs. Users are able to search the full universe to isolate a subset of the CDEs (e.g., all stroke-specific CDEs, all pediatric epilepsy CDEs, etc.) and download details about those CDEs. * CRF Library - (a.k.a., Library of Case Report Form Modules and Guidelines) contains all the CRF Modules that have been created through the NINDS CDE Project as well as various guideline documents. Users are able to search the library to find CRF Modules and Guidelines of interest. * Form Builder - enables users to start the process of assembling a CRF or form by allowing them to choose the CDEs they would like to include on the form. This tool is intended to assist data managers and database developers to create data dictionaries for their study forms.

Proper citation: NINDS Common Data Elements (RRID:SCR_006577) Copy   


  • RRID:SCR_017330

    This resource has 100+ mentions.

https://syngoportal.org/

Evidence based, expert curated knowledge base for synapse. Universal reference for synapse research and online analysis platform for interpretation of omics data. Interactive knowledge base that accumulates available research about synapse biology using Gene Ontology annotations to novel ontology terms.

Proper citation: SynGO (RRID:SCR_017330) Copy   


  • RRID:SCR_014762

    This resource has 1+ mentions.

http://www.jadesantiago.com/Electrophysiology/IonChannelLab/

Software for kinetic modeling of ion channels which operates on Windows XP or Windows Vista.

Proper citation: IonChannelLab (RRID:SCR_014762) Copy   


http://www.cise.ufl.edu/~abarmpou/lab/fanDTasia/

A Java applet tool for DT-MRI processing. It opens Diffusion-Weighted MRI datasets from user's computer and performs very efficient tensor field estimation using parallel threaded processing on user's browser. No installation is required. It runs on any operating system that supports Java (Windows, Mac, Linux,...). The estimated tensor field is guaranteed to be positive definite second order or higher order and is saved in user's local disc. MATLAB functions are also provided to open the tensor fields for your convenience in case you need to perform further processing. The fanDTasia Java applet provides also vector field visualization for 2nd and 4th-order tensors, as well as calculation of various anisotropic maps. Another useful feature is 3D fiber tracking (DTI-based) which is also shown using 3d graphics on the user's browser.

Proper citation: fanDTasia Java Applet: DT-MRI Processing (RRID:SCR_009624) Copy   


  • RRID:SCR_009651

    This resource has 1+ mentions.

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

A Diffusion Tensor fiber tracking software suite that includes streamline tracking tools. The fiber tracking includes a guided tracking tool that integrates apriori information into a streamlines algorithm. This suite of programs is built using the NA-MIC toolkit and uses the Slicer3 execution model framework to define the command line arguments. These tools can be fully integrated with Slicer3 using the module discovery capabilities of Slicer3. NOTE: All new development is being managed in a github repository. Please visit, https://github.com/BRAINSia/BRAINSTools

Proper citation: GTRACT (RRID:SCR_009651) Copy   


  • RRID:SCR_010000

    This resource has 50+ mentions.

https://www.ieeg.org/

Repository for EEG data. The International Epilepsy Electrophysiology Portal is a collaborative initiative funded by the National Institutes of Neurological Disease and Stroke. This initiative seeks to advance research towards the understanding of epilepsy by providing a platform for sharing data, tools and expertise between researchers. The portal includes a large database of scientific data and tools to analyze these datasets.

Proper citation: ieeg.org (RRID:SCR_010000) Copy   


  • RRID:SCR_023031

https://www.gaitor.org

Software suite to analyse gait trials collected with Experimental Dynamic Gait Arena for Rodents. Used for rodent gait analysis.

Proper citation: GAITOR Suite (RRID:SCR_023031) Copy   


  • RRID:SCR_004520

    This resource has 1+ mentions.

http://ccr.coriell.org/Sections/Collections/NINDS/?SsId=10

Open resource of biological samples (DNA, cell lines, and other biospecimens) and corresponding phenotypic data to promote neurological research. Samples from more than 34,000 unique individuals with cerebrovascular disease, dystonia, epilepsy, Huntington's Disease, motor neuron disease, Parkinsonism, and Tourette Syndrome, as well as controls (population control and unaffected relatives) have been collected. The mission of the NINDS Repository is to provide 1) genetics support for scientists investigating pathogenesis in the central and peripheral nervous systems through submissions and distribution; 2) information support for patients, families, and advocates concerned with the living-side of neurological disease and stroke.

Proper citation: NINDS Repository (RRID:SCR_004520) Copy   


https://kimlab.io/brain-map/epDevAtlas/

Suite of open access resources including 3D atlases of early postnatally developing mouse brain and mapped cell type density growth charts, which can be used as standalone resources or to implement data integration. Web platform can be utilized to analyze and visualize the spatiotemporal growth of GABAergic, microglial, and cortical layer-specific cell type densities in 3D. Morphologically averaged symmetric template brains serve as the basis reference space and coordinate system with an isotropic resolution of 20 μm (XYZ in coronal plane). Average transformations were conducted at 20 μm voxel resolution by interpolating high resolution serial two photon tomography images from primarily Vip-IRES-Cre;Ai14 mice at postnatal (P) ages P4, P6, P8, P10, P12, and P14. For all ages, anatomical labels from the P56 Allen Mouse Brain Common Coordinate Framework (Allen CCFv3) were iteratively down registered to each early postnatal time point in a non-linear manner, aided by manual parcellations of landmarks in 3D, consistent with the Allen Mouse Reference Atlas Ontology.

Proper citation: Early Postnatal Developmental Mouse Brain Atlas (RRID:SCR_024725) Copy   


https://github.com/mcelotto/Feature_Info_Transfer

Software application as MATLAB scripts to compute measures of Feature-specific Information Transfer (FIT) and conditional FIT (cFIT). FIT quantifies direction and magnitude of information flow about specific feature S (such as feature of sensory stimulus) between simultaneously recorded brain regions X and Y. cFIT quantifies amount of directed feature information transmitted between regions X and Y that cannot be potentially routed through region Z.

Proper citation: Feature-specific Information Transfer scripts (RRID:SCR_024772) Copy   


https://painseq.shinyapps.io/harmonized_painseq_v1/

Harmonized cell atlases using sc/snRNA-seq data obtained from dorsal root ganglia and trigeminal ganglio mammalian datasets.

Proper citation: Harmonized DRG and TG Reference Atlas (RRID:SCR_025720) Copy   


  • RRID:SCR_025729

    This resource has 10+ mentions.

https://cran.r-project.org/web/packages/MetaCycle/vignettes/implementation.html

Software R package for detecting rhythmic signals from large scale time-series data. Used to evaluate periodicity in large scale data.

Proper citation: MetaCycle (RRID:SCR_025729) Copy   


https://www.c4r-nih.org

Portal provides information about nationwide study of more than 50,000 individuals to determine factors that predict disease severity and long-term health impacts of COVID-19.

Proper citation: Collaborative Cohort of Cohorts for COVID-19 Research (RRID:SCR_026322) Copy   



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