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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.
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://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
http://dx.doi.org/10.5281/zenodo.21157
A graphical source code file used for an automated motion detection and reward system for animal training (see comment for full paper title). It was designed on the LabVIEW programming system. Running the program requires the appropriate LabVIEW runtime software from National Instruments Corporation.
Proper citation: Monkey Motion (RRID:SCR_014285) Copy
http://www.nitrc.org/projects/ibsr
Data set of manually-guided expert segmentation results along with magnetic resonance brain image data. Its purpose is to encourage the development and evaluation of segmentation methods by providing raw test and image data, human expert segmentation results, and methods for comparing segmentation results. Please see the MediaWiki for more information. This repository is meant to contain standard test image data sets which will permit a standardized mechanism for evaluation of the sensitivity of a given analysis method to signal to noise ratio, contrast to noise ratio, shape complexity, degree of partial volume effect, etc. This capability is felt to be essential to further development in the field since many published algorithms tend to only operate successfully under a narrow range of conditions which may not extend to those experienced under the typical clinical imaging setting. This repository is also meant to describe and discuss methods for the comparison of results.
Proper citation: Internet Brain Segmentation Repository (RRID:SCR_001994) Copy
http://krasnow1.gmu.edu/cn3/L-Neuron/database/
A database of virtually generated anatomically plausible neurons for several morphological classes, including cerebellar Purkinje cells, hippocampal pyramidal and granule cells, and spinal cord motoneurons. It presently contains 542 cells. In the trade neurons collection the database contains an amaral cell archive, neuron morpho reconstructions, and mouse alpha motoneurons. Their collection of generated neurons include motoneurons, Purkinje cells, and hippocampal pyramidal cells.
Proper citation: Virtual NeuroMorphology Electronic Database (RRID:SCR_007118) Copy
http://www.stanford.edu/group/exonarray/cgi-bin/plot_selector.pl
Transcriptome database of acutely isolated purified astrocytes, neurons, and oligodendrocytes. Provides improved cell-type-specific markers for better understanding of neural development, function, and disease.
Proper citation: Exon Array Browser (RRID:SCR_008712) Copy
http://senselab.med.yale.edu/odordb
OdorDb is a database of odorant molecules, which can be searched in a few different ways. One can see odorant molecules in the OdorDB, and the olfactory receptors in ORDB that they experimentally shown to bind. You can search for odorant molecules based on their attributes or identities: Molecular Formula, Chemical Abstracts Service (CAS) Number and Chemical Class. Functional studies of olfactory receptors involve their interactions with odor molecules. OdorDB contains a list of odors that have been identified as binding to olfactory receptors.
Proper citation: Odor Molecules DataBase (RRID:SCR_007286) Copy
http://senselab.med.yale.edu/odormapdb
OdorMapDB is designed to be a database to support the experimental analysis of the molecular and functional organization of the olfactory bulb and its basis for the perception of smell. It is primarily concerned with archiving, searching and analyzing maps of the olfactory bulb generated by different methods. The first aim is to facilitate comparison of activity patterns elicited by odor stimulation in the glomerular layer obtained by different methods in different species. It is further aimed at facilitating comparison of these maps with molecular maps of the projections of olfactory receptor neuron subsets to different glomeruli, especially for gene targeted animals and for antibody staining. The main maps archived here are based on original studies using 2-deoxyglucose and on current studies using high resolution fMRI in mouse and rat. Links are also provided to sites containing maps by other laboratories. OdorMapDB thus serves as a nodal point in a multilaboratory effort to construct consensus maps integrating data from different methodological approaches. OdorMapDB is integrated with two other databases in SenseLab: ORDB, a database of olfactory receptor genes and proteins, and OdorDB, a database of odor molecules that serve as ligands for the olfactory receptor proteins. The combined use of the three integrated databases allows the user to identify odor ligands that activate olfactory receptors that project to specific glomeruli that are involved in generating the odor activity maps.
Proper citation: Olfactory Bulb Odor Map DataBase (OdorMapDB) (RRID:SCR_007287) Copy
https://neurophysics.ucsd.edu/software.php
Matlab-based routines for the detection and clustering of putative single units from a multi-unit time series, along with quality metrics. This sofwtare was developed by the David Kleinfeld Laboratory at UC San Diego.
Proper citation: UltraMegaSort 2000 (RRID:SCR_015857) Copy
https://github.com/lambdaloop/anipose
Software package for 3D pose estimation. Uses DeepLabCut for 2D tracking and uses triangulation methods to project pose estimations into three dimensions.Toolkit for robust markerless 3D pose estimation.
Proper citation: Anipose (RRID:SCR_023041) Copy
https://www.ohsu.edu/custom/library/digital-collections/projectionmap
Data set of thalamo-centric mesoscopic projection maps to the cortex and striatum. The maps are established through two-color, viral (rAAV)-based tracing images and high throughout imaging.
Proper citation: Mouse Thalamic Projectome Dataset (RRID:SCR_015702) 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://medinform.jmir.org/2015/4/e35
Algorithm for generating unique study identifiers in distributed and validatable fashion, in multicenter research. Light-weight, block chain style resource identifier generation for tracking resource linkage, provenance, utilization, and visualization. NHash has unique set of properties: (1) it is a pseudonym serving the purpose of linking research data about study participant for research purposes; (2) it can be generated automatically in completely distributed fashion with virtually no risk for identifier collision; (3) it incorporates set of cryptographic hash functions based on N-grams, with combination of additional encryption techniques such as shift cipher; (d) it is validatable (error tolerant) in the sense that inadvertent edit errors will mostly result in invalid identifiers.
Proper citation: NHash Identifier (RRID:SCR_025313) 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
https://kimlab.io/brain-map/DevATLAS/
Whole brain developmental map of neuronal circuit maturation. Generated by whole brain spatiotemporal mapping of circuit maturation during early postnatal development. Standard reference for normative developmental trajectory of neuronal circuit maturation, as well as high throughput platform to pinpoint when and where circuit maturation is disrupted in mouse models of neurodevelopmental disorders, such as fragile X syndrome.
Proper citation: DevATLAS (RRID:SCR_025718) Copy
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
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
https://github.com/tomcatsmith19/ArucoDetection
Automated rodent behavioral scoring system, complete with 3D design files and code/software. System monitors behavioral engagement using open-source software. 3D design files and necessary software has been made available, as well as code that can be used for data analysis.
Proper citation: ArUco (RRID:SCR_026572) Copy
https://github.com/Washington-University/HCPpipelines
Software package as set of tools, primarily shell scripts, for processing multi-modal, high-quality MRI images for the Human Connectome Project. Minimal preprocessing pipelines for structural, functional, and diffusion MRI that were developed by the HCP to accomplish many low level tasks, including spatial artifact/distortion removal, surface generation, cross-modal registration, and alignment to standard space.
Proper citation: HCP Pipelines (RRID:SCR_026575) Copy
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