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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.

(last updated: Oct 12, 2019)

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Resource NameResource TypeDescriptionKeywordsResource IDProper CitationParent OrganizationRelated ConditionFunding AgencyRelationReferenceWebsite StatusAlternate IDsAlternate URLsOld URLs
WormBaseResource, database, catalog, service resource, storage service resource, data repository, data or information resourceData concerning genetics, genomics and biology of C. elegans and related nematodes. Central data repository for nematode biology including complete genomic sequence, gene predictions and orthology assignments from range of related nematodes. Derived from initial ACeDB database of C. elegans genetic and sequence information, WormBase includes genomic, anatomical and functional information of C. elegans, other Caenorhabditis species and other nematodes. Maintains public FTP site where researchers can find many commonly requested files and datasets, WormBase software and prepackaged databases.catalog, database, blast, genomic sequence, gene prediction, orthology assignment, gene function, ortholog, roundworm, geneotype, phenotype, gene mapping, genomics, gene expression, transposon family, c elegans, wormmartSCR_003098(WormBase, RRID:SCR_003098) Washington University in St. Louis; Missouri; USA , Cold Spring Harbor Laboratory , Wellcome Trust Sanger Institute; Hinxton; United Kingdom BBSRC, MRC, NHGRI, NIH Blueprint for Neuroscience Research, NIHGRIrelated to: AmiGO, GBrowse, Textpresso, Expression Patterns for C. elegans promoter GFP fusions, C. elegans Gene Knockout Consortium, NIH Data Sharing Repositories, UniParc at the EBI, UniParc, Integrated Manually Extracted Annotation, PhenoGO, used by: NIF Data Federation, Monarch Initiative, Resource Identification Portal, PhenoGO, Integrated Animals, uses: InterMOD, listed by: OMICtools, re3data.org, InterMOD, affiliated with: InterMODReferences (4)Last checked upnif-0000-00053, OMICS_01664http://www.wormbase.org/#01-23-6
NeuronDBResource, data analysis service, production service resource, analysis service resource, database, service resource, data or information resourceDatabase of three types of neuronal properties: voltage gated conductances, neurotransmitter receptors, and neurotransmitter substances. It contains tools that provide for integration of these properties in a given type of neuron and compartment, and for comparison of properties across different types of neurons and compartments.NMDA, LTP, brain, cellular, cerebellum, cortex, dendrite, human, invertebrate, ion channel, molecular, mouse, neuroinformatics, neuron, neuronal property, neurotransmitter receptor, neurotransmitter substance, olfactory, physiology, rat, receptor, retina, voltage gated conductance, rodent, rat, non-human animalSCR_003105(NeuronDB, RRID:SCR_003105)Yale University; Connecticut; USA Human Brain Project, Multidisciplinary University Research Initiative (MURI), NIDCDrelated to: ModelDB, Integrated Manually Extracted Annotation, used by: NIF Data Federation, listed by: Biositemaps, works_with: MicrocircuitDBReferences (2)Last checked upnif-0000-00054
Cell Properties DatabaseResource, data or information resource, databaseA repository for data regarding membrane channels, receptor and neurotransmitters that are expressed in specific types of cells. The database is presently focused on neurons but will eventually include other cell types, such as glia, muscle, and gland cells. This resource is intended to: * Serve as a repository for data on gene products expressed in different brain regions * Support research on cellular properties in the nervous system * Provide a gateway for entering data into the cannonical neuron forms in NeuronDB * Identify receptors across neuron types to aid in drug development * Serve as a first step toward a functional genomics of nerve cells * Serve as a teaching aidgenetics, cellular, molecular, cerebellum, cortex, human, ion channel, mouse, olfactory, invertebrate, mammalian, physiology, rat, receptor, cat, molecular neuroanatomy resourceSCR_007285(Cell Properties Database, RRID:SCR_007285)Yale University; Connecticut; USA AgingMultidisciplinary University Research Initiative, NIA, NICD, NIDCD, NIMH, NINDSLast checked upnif-0000-00055http://senselab.med.yale.edu/senselab/cellpropdb
Odor Molecules DataBaseResource, data or information resource, databaseOdorDb 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.genetics, cellular, molecular, olfactory, receptor, training materialSCR_007286(Odor Molecules DataBase, RRID:SCR_007286)Yale University; Connecticut; USA AgingHuman Brain Project, Multidisciplinary University Research Initiative, NIA, NICD, NIDCD, NIMH, NINDSrelated to: Olfactory Receptor DataBase, works_with: ORModelDBLast checked upnif-0000-00056
Olfactory Bulb Odor Map DataBase (OdorMapDB)Resource, atlas, database, data or information resourceOdorMapDB 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.odor, male, urine, mouse, methyl anisole, patchone, indole, helional, butyrophenone, fenchone, olfactory bulb, fmri, rat, odor ligand, olfactory receptor, smellSCR_007287(Olfactory Bulb Odor Map DataBase (OdorMapDB), RRID:SCR_007287)Yale University; Connecticut; USA AgingMultidisciplinary University Research Initiative, NIA, NICD, NIDCD, NIMH, NINDS, The Human Brain Projectused by: NIF Data FederationPMID:15067166Last checked upnif-0000-00057
Protein-Protein Interaction DatabaseResource, data or information resource, databaseMammalian protein-protein interaction database focusing on synaptic proteins. The Protein-Protein Interaction Database was originally a single-person's attempt to integrate a gamut of biological/bibliographical/molecular data and build a framework which might help understanding how cells orchestrate their protein content in order to become what they are: machines with a purpose. This is based on the simple paradigm that functionality like signal cascades are held together in a close space, thereby allowing specific events to occur without the necessity of passive diffusion and random events. The PPID database arose from the need to interpret Proteomic datasets, which were generated analysing the NMDA-receptor complex (see H. Husi, M. A. Ward, J. S. Choudhary, W. P. Blackstock and S. G. Grant (2000). Proteomic analysis of NMDA receptor-adhesion protein signaling complexes. Nat Neurosci 3, 661-669.). To study these clusters of proteins requires unavoidably the handling of large datasets, which PPID is generally aimed and tailored for. This database is unifying molecular entries across three species, namely human, rat and mouse and is is footed on sequence databases such as SwissProt, EMBL, TrEMBL (translated EMBL sequences) and Unigene and the literature database PubMed. A typical entry in PPID holds up to three general entries for the three species, all protein and gene accession numbers associated with them (assembled from Blast2 searches of the databases) and the OMIM entry as maintained by Johns Hopkins University. Furthermore protein sequence information is also included, together with known and novel splice-variants of each molecule as found by ClustalW sequence alignments. Entry points also include protein-binding information together with the literature reference. The whole database is curated manually to insure accuracy and quality. Querying the database will be possible by online browsing and batch-submission for large datasets holding accession number information, as can be generated using software like Mascot for mass-spectrometry. Cluster-analysis of the submitted datasets in the form of a graphical output will be developed as well as an easy-to-use web-interface. An interface is currently being built in collaboration with the Department of Informatics (T. Theodosiou and D. Armstrong) and will be deployed soon The current team of people collating and deploying the database are H. Husi (database mining and information gathering) and T. Theodosiou (web-interface and deployment). Please note that this database is not funded financially, and cannot survive without sponsorship.synapse, synapses, synapticSCR_007288(Protein-Protein Interaction Database, RRID:SCR_007288)University of Edinburgh; Scotland; United Kingdom Last checked upnif-0000-00058
Michigan State University Brain Biodiversity BankResource, atlas, narrative resource, data or information resource, training material, databaseThe Brain Biodiversity Bank refers to the repository of images of and information about brain specimens contained in the collections associated with the National Museum of Health and Medicine at the Armed Forces Institute of Pathology in Washington, DC. Atlases and brain sections are available for a variety of mammals, and we are also developing a series of labeled atlases of stained sections for educators, students, and researchers. These collections include, besides the Michigan State University Collection, the Welker Collection from the University of Wisconsin, the Yakovlev-Haleem Collection from Harvard University, the Meyer Collection from the Johns Hopkins University, and the Huber-Crosby and Crosby-Lauer Collections from the University of Michigan. What we are doing currently at Michigan State is a series of demonstration projects for publicizing the contents of the collections and ways in which they can be used. For example, the images from the collection can be used for comparative brain study. We have prepared databases of the contents of the collections for presentation and use on this site, as well as for downloading by users in several formats. We are also developing a series of labeled atlases of stained sections for educators, students, and researchers. This internet site is associated with the Comparative Mammalian Brain Collections site. All of the images are in JPEG or GIF format.echidna, anatomy, axolotl, brain, brainstem, cat, cerebellum, chimpanzee, cortex, cow, dolphin, histology, human, hyena, hypothalamus, images, imaging, lion, llama, loris, manatee, mandrill, mongoose, morphology, movies, mri, nissl, owl monkey, pig, polar bear, red kangaroo, rhesus monkey, sea lion, sheep, subcortical, tasmanian devil, weasel, white matter, zebraSCR_003289(Michigan State University Brain Biodiversity Bank, RRID:SCR_003289)Michigan State University; Michigan; USA Last checked upnif-0000-00059
Datasharing.netResource, topical portal, portal, data or information resourceThe U.S. National Institutes of Health Final NIH Statement on Sharing Research Data (NIH-OD-03-032) is now in effect. It specifies that all high-direct-cost NIH grant applications include plans for sharing of research data. To support and encourage collegial, enabling, and rewarding data sharing for neuroscience and beyond, the Laboratory of Neuroinformatics at Weill Medical College of Cornell University has established this site. A source of, and portal to, tools and proposals supporting the informed exchange of neuroscience data.data management, neuroinformatics, data sharingSCR_003312(Datasharing.net, RRID:SCR_003312)Weill Cornell Medical College; New York; USA Human Brain Project, NIMH, NINDS, NSFLast checked downnif-0000-00061
Model Organisms for Biomedical ResearchResource, topical portal, portal, data or information resourceInformation about national and international activities and major resources that are being developed to facilitate biomedical research using animal models Mammalian Models: * Mouse * Rat Non-Mammalian Models * S. cerevisiae (budding yeast) * S.pombe (Fission Yeast) * Neurospora (filamentous fungus) * D. discoideum (social amoebae) * C. elegans (round worm) * Daphnia * D. melanogaster (fruit fly) * D. rerio (zebrafish) * Xenopus (frog) * Gallus (chicken) Other Model Organisms: * Arabidopsismammal, model organism, mouse, rat, saccharomyces cerevisiae, saccharomyces pombe, neurospora, dictyostelium discoideum, caenorhabditis elegans, daphnia, drosophila melanogaster, zebrafish, xenopus, gallus, arabidopsis, organism supplierSCR_007282(Model Organisms for Biomedical Research, RRID:SCR_007282)National Institutes of Health Last checked downnif-0000-00062
LONI SoftwareResource, software resource, software application, software repository, data analysis software, data processing softwareA portal of software resources offered by UCLA's Laboratory of Neuro Imaging. LONI Webapps allow users to analyze, visualize and interact with neuroscience data directly from their web browser. LONI aims to encourage communication between users and LONI software engineers in order to improve the effectiveness of our software and to promote its use by researchers worldwide. We have expanded our software website to include more tools, training and support. Be sure to visit LONI Forums and discuss our tools with other end-users as well as our dedicated LONI staff.visualization, shape analysis, registration, statistical analysis, data management, image processing, pre=processing, segmentation, surface modeling, modelSCR_003323(LONI Software, RRID:SCR_003323)University of California at Los Angeles; California; USA DOE, NCRR, NIBIB, NIGMS, NIH, NIMH, NINDSrelated to: Mouse Atlas Project, listed by: 3DVC, BiositemapsLast checked downnif-0000-00063http://www.loni.ucla.edu/Software/
Brede DatabaseResource, data or information resource, databaseA database of human data from functional neuroimaging scientific articles containing Talairach coordinates that provides data for novel information retrieval techniques and automated meta-analyses. Each article in this database is identified by a unique number: A WOBIB. Some of the structure of the Brede database is similar to the structure of the BrainMap database (Research Imaging Center, San Antonio). The database is inspired by the hierarchical structure of BrainMap with scientific articles (bib structures) on the highest level containing one or more experiments (exp structure, corresponding to a contrast in general linear model analyses), these in turn comprising one or more locations (loc structures). The information on the bib level (author, title, ...) is setup automatically from PubMed while the rest of the information is entered manually in a Matlab graphical user interface. On the loc level this includes the 3D stereotactic coordinates in either Talairach or MNI space, the brain area (functional, anatomical or cytoarchitectonic area) and magnitude values such as Z-score and P-value. On the exp level information such as modality, scanner and behavioral domain are recorded with external components (such as face recognition or kinetic boundaries) organized in a directed graph and marked up with Medical Subject Headings (MeSH) where possible. The database is distributed as part of the Brede neuroinformatics toolbox (hendrix.imm.dtu.dk/software/brede/) which also provides the functions to manipulate and analyze the data. The Brede Toolbox is a program package primarily written in Matlab. As of 2006/11, 186 papers with 586 experiments.neuroinformatics, functional neuroimaging, talairach, mni, brain, fmri, neuroimaging, matlab, pet, positron emission tomography, functional magnetic resonance imaging, multichannel electroencephalography, eeg, magnetoencephalography, near infrared spectroscopic imaging, single photon emission computed tomography, mri, coordinate, brain function, brain region, ontologySCR_003327(Brede Database, RRID:SCR_003327)Technical University of Denmark; Lyngby; Denmark European Union, Project MAPAWAMOrelated to: Brede Wiki, Brede Toolbox, Brede Toolbox, Brede Wiki, brainmap.org, Integrated Manually Extracted Annotation, used by: NIF Data FederationReferences (2)Last checked upnif-0000-00064
Language Map Experiment Management SystemResource, data or information resource, databaseAn experiment management system for researchers studying language organization in the brain. Data from thirteen patients are available as a public demo. Language Map EMSfmri, 3d models, anatomy, cortex, data managementas of 2006/11 data from 110 patients in repository., imaging, mri, segmentation, volumeSCR_004562(Language Map Experiment Management System, RRID:SCR_004562)University of Washington; Seattle; USA AgingNIA, NIDCD, NIMHLast checked upnif-0000-00065
FMAResource, data analysis software, data processing software, database, software application, software resource, ontology, controlled vocabulary, data or information resourceA domain ontology that represents a coherent body of explicit declarative knowledge about human anatomy. It is concerned with the representation of classes or types and relationships necessary for the symbolic representation of the phenotypic structure of the human body in a form that is understandable to humans and is also navigable, parseable and interpretable by machine-based systems. Its ontological framework can be applied and extended to all other species. The description of how the OWL version was generated is in Pushing the Envelope: Challenges in a Frame-Based Representation of Human Anatomy by N. F. Noy, J. L. Mejino, C. Rosse, M. A. Musen: http://bmir.stanford.edu/publications/view.php/pushing_the_envelope_challenges_in_a_frame_based_representation_of_human_anatomy The Foundational Model of Anatomy ontology has four interrelated components: # Anatomy taxonomy (At), # Anatomical Structural Abstraction (ASA), # Anatomical Transformation Abstraction (ATA), # Metaknowledge (Mk), The ontology contains approximately 75,000 classes and over 120,000 terms; over 2.1 million relationship instances from over 168 relationship types link the FMA's classes into a coherent symbolic model.anatomy, informatics, model, neuroanatomy, protg, reference, standard, structural, taxonomy, owl, phenotypeSCR_003379(FMA, RRID:SCR_003379)University of Washington; Seattle; USA Intel Corporation, Microsoft, Murdock Charitable Trust, NHLBI, NLM, RSNA-NIBIB, University of Washington; Washington; USArelated to: T3DB, HIV Brain Sequence Database, CELDA Ontology, listed by: BioPortalReferences (3)Last checked upnif-0000-00066http://bioportal.bioontology.org/ontologies/FMA
NeuroScholarResource, software resourceNeuroscholar is a framework for knowledge management of the neuroscientific literature. It is not a single database but a methodology for creating knowledge models that answer specific questions with direct links to the literature. The NeuroScholar Project is the flagship project for the Biomedical Knowledge Engineering Research Group at the Information Sciences Institute in Marina Del Rey. We are a group specializing in computational approaches (based on Natural Language Processing and Knowledge Engineering) to computing with information drawn from the scientific literature. The literature is the natural repository for scientific knowledge, our mission is therefore to find ways to make that information readily available to non-computational biomedical scientists and help them organize their understanding of their systems of interest. We have generated two downloadable working systems at present: 1. The NeuroScholar System 2. The NeuARt II System. We are developing NLP architecture for Information Extraction of data from large bodies of text. We will also soon be moving websites. The subject of neuroscience is complex, broad and deep. It uses data from many disciplines: anatomy, physiology, chemistry, physics, molecular biology, cognitive science and ethology to name a few. It traverses many temporal and spatial scales; from milliseconds to generations, and angstroms to meters. The brain itself has been called "the most complex object in the known universe" (by Nobel-Prize winner James Watson) and the number of individual cells, and connections between cells is (literally) astronomical. The biggest challenge to understanding the large-scale organization of the brain across systems, modalities and scales is therefore complexity of our own data. We contend that knowledge management systems could be built that address this challenge. The NeuroScholar project provides knowledge engineering software for use by the neuroscience community. The basic framework of our approach is illustrated in the Figure shown below. Shown here is a typical scenario facing neuroscientists: the information required is scattered throughout a number of knowledge sources (in the literature, on the web, in local data files in the lab). NeuroScholar permits users to capture "fragments" from the knowledge sources, which then can be used to define knowledge representation items within the primary system.The NeuroScholar system permits users to isolate fragments of data from those sources and then bring them together to form facts which may then be incorporated with interpretations and relations to build representations of knowledge within NeuroScholar that may then be used. Supporting Agencies: nlmdata storage, metadata, neuroinformaticsSCR_000114(NeuroScholar, RRID:SCR_000114)University of Southern California; Los Angeles; USA Last checked upnif-0000-00067
BIRN Coordinating CenterResource, organization portal, software application, portal, software resource, systems interoperability software, data or information resourceTHIS RESOURCE IS NO LONGER IN SERVICE, documented on September 06, 2013. It was established to develop, implement and support the information infrastructure necessary to achieve large-scale data sharing among the test bed participants (function, morphometry and mouse birn). The BIRN-CC consists of a unique and well-established partnership between computer scientists, neuroscientists and engineers. This partnership addresses a large array of technical, policy, and architectural issues to fundamentally enable a new suite of information technology supported database and analysis tools that allow scientists to analyze and interpret significantly larger sets of data than is possible in the traditional single-institution study paradigm.fmri, 3d models, anatomy, atlas, data management, data storage, dohhs architecture, imaging, map, model, mri, neuroinformatics, ontology, portal, software, talairach, warpingSCR_007290(BIRN Coordinating Center, RRID:SCR_007290) University of Chicago; Illinois; USA , University of Southern California; Los Angeles; USA , University of California at Irvine; California; USA , University of California at Los Angeles; California; USA NCRRLast checked downnif-0000-00068
Morphometry BIRNResource, data set, data or information resourceCalibration data set of spoiled gradient-recalled echo magnetic resonance imaging data from five healthy volunteers (four males and one female) scanned twice at four sites having 1.5T systems from different vendors (Siemens, GE, Marconi Medical Systems) pooled by the Morphometry Testbed's (MBIRN). Some subjects were also scanned a single time at another site. One subject was only scanned twice at three sites (subject 73213384) and once at another site. For each subject, four Fast Low-Angle Shot (FLASH) scans with flip angles of 3, 5, 20, and 30 degrees were obtained in a single scan session, from which tissue proton density and T1 maps can be derived. These data were acquired to investigate various metrics of within-site and across-site reproducibility. The images have been defaced so that no facial features can be reconstructed from these data. The Morphometry Testbed (MBIRN) of the Biomedical Informatics Research Network (BIRN) focused on pooling and analyzing of neuroimaging data acquired at multiple sites. Specific applications include potential relationships between anatomical differences and specific memory dysfunctions, such as Alzheimer's disease. With the completion of the initial BIRN testbed phase, each of the original BIRN testbeds have now been retired in order to focus on new users in other biomedical domains.morphometry, mri, neuroinformatics, subcortical, dicom, magnetic resonance, nifti, quantification, segmentation, visualization, workflow, image collection, structural mri, male, female, neuroimagingSCR_000155(Morphometry BIRN, RRID:SCR_000155)Biomedical Informatics Research Network related to: XNAT Central, listed by: NeuroImaging Tools and Resources Collaboratory (NITRC), BiositemapsLast checked downnif-0000-00069http://www.nitrc.org/projects/mbirn
Function BIRNResource, topical portal, portal, data or information resourceThe FBIRN Federated Informatics Research Environment (FIRE) includes tools and methods for multi-site functional neuroimaging. This includes resources for data collection, storage, sharing and management, tracking, and analysis of large fMRI datasets. fBIRN is a national initiative to advance biomedical research through data sharing and online collaboration. BIRN provides data-sharing infrastructure, software tools, strategies and advisory services - all from a single source.fmri, 3d model, data storage, imaging, map, morphology, mri, neuroinformatics, segmentation, software, talairach, volume, warping, analyze, application, c++, csh/tcsh, data, database, database application, data resource, dicom, javascript, linux, magnetic resonance, nifti, ontology, pl/sql, posix/unix-like, python, quality metrics, spatial transformation, statistical operation, tcl/tk, unix shell, visualization, web resource, web service, workflowSCR_007291(Function BIRN, RRID:SCR_007291)Biomedical Informatics Research Network NCRR, NIGMSlisted by: NeuroImaging Tools and Resources Collaboratory (NITRC)Last checked upnif-0000-00070http://www.nitrc.org/projects/fbirnhttp://nbirn.net/tools/browse_tools.shtm
National Brain DatabankResource, data set, data or information resource, databaseTHIS RESOURCE IS NO LONGER IN SERVCE, documented September 6, 2016. A publicly accessible data repository to provide neuroscience investigators with secure access to cohort collections. The Databank collects and disseminates gene expression data from microarray experiments on brain tissue samples, along with diagnostic results from postmortem studies of neurological and psychiatric disorders. All of the data that is derived from studies of the HBTRC collection is being incorporated into the National Brain Databank. This data is available to the general public, although strict precautions are undertaken to maintain the confidentiality of the brain donors and their family members. The system is designed to incorporate MIAME and MAGE-ML based microarray data sharing standards. Data from various types of studies conducted on brain tissue in the HBTRC collection will be available from studies using different technologies, such as gene expression profiling, quantitative RT-PCR, situ hybridization, and immunocytochemistry and will have the potential for providing powerful insights into the subregional and cellular distribution of genes and/or proteins in different brain regions and eventually in specific subregions and cellular subtypes.cellular, cortex, sequence data, molecular neuroanatomy resource, gene expression, microarray, brain tissue, post-mortem, neurological disorder, mental disease, human, gene expression profiling, quantitative rt pcr, in situ hybridization, immunocytochemistry, schizophrenia, bipolar disorder, huntington's disease, parkinson's diseaseSCR_003606(National Brain Databank, RRID:SCR_003606)Harvard Brain Tissue Resource Center Schizophrenia, Huntington's disease, Parkinson's disease, bipolar disorderNIMH, NINDSLast checked downnif-0000-00071
Nclamp - data acquisition software for electrophysiologyResource, software resource, data acquisition software, data processing software, software applicationData acquisition software that runs in conjunction with neuromatic. configured to work with Igor Pro on PC or Mac, instrutech or national instrument acquisition devices. Funded by The Medical Research Council (UK) Compatibility with WaveMetrics Igor Pro 5 and 6. Compatibility with Mac or PC. NIDAQ interfacing multifunction DAQ boards from National Instruments. Requires Igor NIDAQ Tools MX. ITC interfacing - data acquisition systems from InstruTech / Heka. Requires Igor ITC XOPs. Episodic acquisition (stim and sample). Continuous acquisition (currently for ITC users only). Online analysis, with ability to create your own analysis functions. Notes and Log Files which can be displayed within a table or notebook. Automatic saving of data and log folders to your hard drive. Flexible stimulus pulse generator with ability to use your own pulse waveforms. Instant accessibility to all of NeuroMatics and Igor Pros pre-existing data analysis functions.SCR_003750(Nclamp - data acquisition software for electrophysiology, RRID:SCR_003750)Last checked upnif-0000-00072
NeuroMaticResource, software resource, software application, data analysis software, data processing softwareNeuroMatic is a collection of Igor Pro functions for analyzing electrophysiological data. By allowing users to organize their data into Sets and Groups, NeuroMatic makes it relatively easy to compute transformations and statistical analyses on their data, including scaling, alignment averaging, baseline subtraction, spike detection, stationarity analysis, rise-time computations, etc. Being open source and modular designed, NeuroMatic also allows users to develop their own analysis functions that can be easily incorporated into NeuroMatic's framework. Note, if you have reached this page in search of a freeware tool for neuronal reconstructions, you are more likely to be interested in Neuromantic, a software package that sounds like NeuroMatic, but is not quite the same. Features of NeuroMatic Include * Sorting, Scaling, Averaging, Interpolation * Max / Min / Mean / Level / Rise Time / FWHM / Slope Measurements * Stability / Stationarity Analysis * Event Detection * Waveform Template Matching * Spike Raster Plots * Interspike-Interval and Peri-Stimulus Time (PST) Histograms * Compact Easy-to-Use Interface * Modular design as a basis for your own procedures * Extra space for your own buttons and controls * Import functions for Axograph and Pclamp data * Automatic macro generation for batch processing Supporting Agencies: MRC, Wellcome Trust Spike, Event, Fit, NClamp, Acquisition, spike train, EPSP, IPSP, IPSC, EPSCepsc, epsp, event, fit, acquisition, data management, ipsc, ipsp, nclamp, software, spike, spike trainSCR_004186(NeuroMatic, RRID:SCR_004186)University College London; London; United Kingdom Last checked upnif-0000-00073
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