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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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  • RRID:SCR_002518

    This resource has 100+ mentions.

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

A free software tool for Copy Number Variation (CNV) detection from SNP genotyping arrays. Currently it can handle signal intensity data from Illumina and Affymetrix arrays. With appropriate preparation of file format, it can also handle other types of SNP arrays and oligonucleotide arrays. PennCNV implements a hidden Markov model (HMM) that integrates multiple sources of information to infer CNV calls for individual genotyped samples. It differs form segmentation-based algorithm in that it considered SNP allelic ratio distribution as well as other factors, in addition to signal intensity alone. In addition, PennCNV can optionally utilize family information to generate family-based CNV calls by several different algorithms. Furthermore, PennCNV can generate CNV calls given a specific set of candidate CNV regions, through a validation-calling algorithm.

Proper citation: PennCNV (RRID:SCR_002518) Copy   


http://www.matrics.ucla.edu/index.html

Cognitive deficits -- including impairments in areas such as memory, attention, and executive function -- are a major determinant and predictor of long-term disability in schizophrenia. Unfortunately, available antipsychotic medications are relatively ineffective in improving cognition. Scientific discoveries during the past decade suggest that there may be opportunities for developing medications that will be effective for improving cognition in schizophrenia. The NIMH has identified obstacles that are likely to interfere with the development of pharmacological agents for treating cognition in schizophrenia. These include: (1) a lack of a consensus as to how cognition in schizophrenia should be measured; (2) differing opinions as to the pharmacological approaches that are most promising; (3) challenges in clinical trial design; (4) concerns in the pharmaceutical industry regarding the US Food and Drug Administration''s (FDA) approaches to drug approval for this indication; and (5) issues in developing a research infrastructure that can carry out clinical trials of promising drugs. The MATRICS program will bring together representatives of academia, industry, and government in a consensus process for addressing all of these obstacles. Specific goals of the NIMH MATRICS are: * To catalyze regulatory acceptance of cognition in schizophrenia as a target for drug registration. * To promote development of novel compounds to enhance cognition in schizophrenia. * Leverage economic research power of industry to focus on important but neglected clinical targets. * Identify lead compounds and if deemed feasible, support human proof of concept trials for cognition in schizophrenia.

Proper citation: MATRICS - Measurement And Treatment Research to Improve Cognition in Schizophrenia (RRID:SCR_005644) Copy   


http://www.patternlabforproteomics.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented July 5, 2018. Gene Ontology Explorer (GOEx) combines data from protein fold changes with GO over-representation statistics to help draw conclusions in proteomic experiments. It is tightly integrated within the PatternLab for Proteomics project and, thus, lies within a complete computational environment that provides parsers and pattern recognition tools designed for spectral counting. GOEx offers three independent methods to query data: an interactive directed acyclic graph, a specialist mode where key words can be searched, and an automatic search. A recent hack included in GOEx is to load the sparse matrix index file directly into GOEx, instead of going through the report generation using the AC/T-fold methods. This makes it easy for GOEx to analyze any list of proteins as long as the list follows the index file format (described in manuscript) . Please note that if using this alternative strategy, there will be no protein fold information. Platform: Windows compatible

Proper citation: GOEx - Gene Ontology Explorer (RRID:SCR_005779) Copy   


  • RRID:SCR_017203

    This resource has 1+ mentions.

http://www.open-ephys.org/pulsepal

Open source pulse train generator that allows users to create and trigger software defined trains of voltage pulses with high temporal precision. Generates precisely timed pulse sequences for use in research involving electrophysiology or psychophysics.

Proper citation: Pulse Pal (RRID:SCR_017203) Copy   


https://clinicaltrials.gov/ct2/show/NCT00014001

The NIMH-funded Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) Study was a nationwide public health-focused clinical trial that compared the effectiveness of older (first available in the 1950s) and newer (available since the 1990s) antipsychotic medications used to treat schizophrenia. These newer medications, known as atypical antipsychotics, cost roughly 10 times as much as the older medications. CATIE is the largest, longest, and most comprehensive independent trial ever done to examine existing therapies for this disease. Schizophrenia is a brain disorder characterized by hallucinations, delusions, and disordered thinking. The course of schizophrenia is variable, but usually is recurrent and chronic, often causing severe disability. Previous studies have shown that taking antipsychotic medications consistently is far more effective than taking no medicine and that the drugs are necessary to manage the disease. The aim of the CATIE study was to determine which medications provide the best treatment for schizophrenia. Additional information may be found by following the links, http://www.nimh.nih.gov/trials/practical/catie/index.shtml, http://www.clinicaltrials.gov/ct/show/NCT00014001?order=1

Proper citation: CATIE - Clinical Antipsychotic Trials in Intervention Effectiveness (RRID:SCR_005615) Copy   


https://beadl.org

Universal framework for describing behavioral tasks. Language to abstract and standardize behavioral task descriptions on two layers. Graphical layer specifies elements to describe behavioral tasks as state machine in formal flow diagram and how task controlling system interacts with subject. This graphical layer has been designed to be easy to understand while retaining all aspects of behavioral task. The second layer is corresponding, XML-based description of task. This layer forms rigid, yet extensible foundation of BEADL and hides hardware implementation related details form graphical representation.BEADL-specific extension for Neurodata Without Borders data standard defines how behavioral outcomes of task are stored in NWB including corresponding BEADL task description.

Proper citation: BEADL:BEhavioral tAsk Description Language (RRID:SCR_025464) Copy   


  • RRID:SCR_001551

    This resource has 10+ mentions.

http://proteomics.ucsd.edu/Software/NeuroPedia/index.html

A neuropeptide encyclopedia of peptide sequences (including genomic and taxonomic information) and spectral libraries of identified MS/MS spectra of homolog neuropeptides from multiple species.

Proper citation: NeuroPedia (RRID:SCR_001551) Copy   


  • RRID:SCR_002380

    This resource has 10000+ mentions.

http://www.uniprot.org/

Collection of data of protein sequence and functional information. Resource for protein sequence and annotation data. Consortium for preservation of the UniProt databases: UniProt Knowledgebase (UniProtKB), UniProt Reference Clusters (UniRef), and UniProt Archive (UniParc), UniProt Proteomes. Collaboration between European Bioinformatics Institute (EMBL-EBI), SIB Swiss Institute of Bioinformatics and Protein Information Resource. Swiss-Prot is a curated subset of UniProtKB.

Proper citation: UniProt (RRID:SCR_002380) Copy   


http://www.oasis-brains.org/

Project aimed at making neuroimaging data sets of brain freely available to scientific community. By compiling and freely distributing neuroimaging data sets, future discoveries in basic and clinical neuroscience are facilitated.

Proper citation: Open Access Series of Imaging Studies (RRID:SCR_007385) Copy   


  • RRID:SCR_003612

    This resource has 100+ mentions.

http://fcon_1000.projects.nitrc.org/indi/abide/

Resting state functional magnetic resonance imaging (R-fMRI) datasets from 539 individuals with autism spectrum disorder (ASD) and 573 typical controls. This initiative involved 16 international sites, sharing 20 samples yielding 1112 datasets composed of both MRI data and an extensive array of phenotypic information common across nearly all sites. This effort is expected to facilitate discovery science and comparisons across samples. All datasets are anonymous, with no protected health information included.

Proper citation: ABIDE (RRID:SCR_003612) Copy   


http://www.nimh.nih.gov/funding/clinical-trials-for-researchers/datasets/nimh-procedures-for-requesting-data-sets.shtml

A listing of data sets from NIMH-supported clinical trials. Limited Access Datasets are available from numerous NIMH studies. NIMH requires all investigators seeking access to data from NIMH-supported trials held by NIMH to execute and submit as their request the appropriate Data Use Certification pertaining to the trial. The datasets distributed by NIMH are referred to as limited access datasets because access is limited to qualified researchers who complete Data Use Certifications.

Proper citation: Limited Access Datasets From NIMH Clinical Trials (RRID:SCR_005614) Copy   


  • RRID:SCR_008914

    This resource has 10+ mentions.

http://mialab.mrn.org/data/index.html

An MRI data set that demonstrates the utility of a mega-analytic approach by identifying the effects of age and gender on the resting-state networks (RSNs) of 603 healthy adolescents and adults (mean age: 23.4 years, range: 12-71 years). Data were collected on the same scanner, preprocessed using an automated analysis pipeline based in SPM, and studied using group independent component analysis. RSNs were identified and evaluated in terms of three primary outcome measures: time course spectral power, spatial map intensity, and functional network connectivity. Results revealed robust effects of age on all three outcome measures, largely indicating decreases in network coherence and connectivity with increasing age. Gender effects were of smaller magnitude but suggested stronger intra-network connectivity in females and more inter-network connectivity in males, particularly with regard to sensorimotor networks. These findings, along with the analysis approach and statistical framework described, provide a useful baseline for future investigations of brain networks in health and disease.

Proper citation: MIALAB - Resting State Data (RRID:SCR_008914) Copy   


  • RRID:SCR_013742

    This resource has 50+ mentions.

http://hbatlas.org

A data repository containing transcriptome and associated metadata for the developing and adult human brain. It provides genome-wide, exon-level transcriptome data from both sexes and multiple ethnicities.

Proper citation: Human Brain Transcriptome (RRID:SCR_013742) Copy   


http://fcon_1000.projects.nitrc.org/indi/pro/nyu.html

Datasets including a collection of scans from 49 psychiatrically evaluated neurotypical adults, ranging in age from 6 to 55 years old, with age, gender and intelligence quotient (IQ) information provided. Future releases will include more comprehensive phenotypic information, and child and adolescent datasets, as well as individuals from clinical populations. The following data are released for every participant: * At least one 6-minute resting state fMRI scan (R-fMRI) * * One high-resolution T1-weighted mprage, defaced to protect patient confidentiality * Two 64-direction diffusion tensor imaging scans * Demographic information (age, gender) and IQ-measures (Verbal, Performance, and Composite; Weschler Abbreviated Scale of Intelligence - WASI) * Most participants have 2 R-fMRI scans, collected less than 1 hour apart in the same scanning session. Rest_1 is always collected first.

Proper citation: NYU Institute for Pediatric Neuroscience Sample (RRID:SCR_010458) Copy   


http://neuromorphometrics.com/?page_id=23

Collection of neuroanatomically labeled MRI brain scans, created by neuroanatomical experts. Regions of interest include the sub-cortical structures (thalamus, caudate, putamen, hippocampus, etc), along with ventricles, brain stem, cerebellum, and gray and white matter and sub-divided cortex into parcellation units that are defined by gyral and sulcal landmarks.

Proper citation: Manually Labeled MRI Brain Scan Database (RRID:SCR_009604) Copy   


  • RRID:SCR_008819

    This resource has 1+ mentions.

http://HIVBrainSeqDB.org

The HIV Brain Sequence Database (HIVBrainSeqDB) is a public database of HIV envelope sequences, directly sequenced from brain and other tissues from the same patients. For inclusion in the database, sequences must: (i) be deposited in Genbank; (ii) include some portion of the HIV env region; (iii) be clonal, amplified directly from tissue; and (iv) be sampled from the brain, or sampled from a patient for which the database already contains brain sequence. Sequences are annotated with clinical data including viral load, CD4 count, antiretroviral status, neurocognitive impairment, and neuropathological diagnosis, all curated from the original publication. Tissue source is coded using an anatomical ontology, the Foundational Model of Anatomy, to capture the maximum level of detail available, while maintaining ontological relationships between tissues and their subparts. 44 tissue types are represented within the database, grouped into 4 categories: (i) brain, brainstem, and spinal cord; (ii) meninges, choroid plexus, and CSF; (iii) blood and lymphoid; and (iv) other (bone marrow, colon, lung, liver, etc). Currently, the database contains 2517 envelope sequences from 90 patients, obtained from 22 published studies. 1272 sequences are from brain; the remaining 1245 are from blood, lymph node, spleen, bone marrow, colon, lung and other non-brain tissues. The database interface utilizes a faceted interface, allowing real-time combination of multiple search parameters to assemble a meta-dataset, which can be downloaded for further analysis. This online resource will greatly facilitate analysis of the genetic aspects of HIV macrophage tropism, HIV compartmentalization and evolution within the brain and other tissue reservoirs, and the relationship of these findings to HIV-associated neurological disorders and other clinical consequences of HIV infection.

Proper citation: HIV Brain Sequence Database (RRID:SCR_008819) Copy   


  • RRID:SCR_007286

    This resource has 1+ mentions.

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   


  • RRID:SCR_006821

    This resource has 1+ mentions.

http://dally.nimh.nih.gov/matoff/matoff.html

An interactive analysis program that searches neurophysiological data and plots the results. MatOFF was developed especially for dealing with the complexities common to behavioral neurophysiological experiments. It runs under Windows 2000 or XP and relies on MATLAB version R11.1 (or above) for all operations. MatOFF searches a data file to locate and plot epochs (trials) of special interest to the investigator. Appropriate input data files have time-stamped event codes, usually including neuron action potential firing events (spikes), and digitized analog data. The user specifies a list of event code numbers that uniquely identify a sequence of events. MatOFF uses this sequence to search the raw data file, select the epochs that meet the criteria, time-shift the trials to align them on a common event, order the epochs based on user-selected criteria, and plot the results based on a collection of page formatting specifications. MatOFF will also save extracted data and some statistics to disk. Features: * Powerful, interactive searching tools for locating relevant experimental events * Compatible with Cortex data acquisition program * Compatible with Plexon data acquisition system * Flexible, publication-quality graphical display and printing * Comprehensive scripting language * Supports learning and other dynamic behavior * Integrated interface to MATLAB functions * Automatic alignment of trial data and generation of histograms * Large variety of options for selecting and ordering trial data * Descriptive and non-parametric statistics * XY analog displays * Data export with flexible format control * Up to 72 plots per page * Display templates can be saved and reloaded * Free for public or private use * Adaptable to almost any data file format

Proper citation: MatOFF (RRID:SCR_006821) Copy   


  • RRID:SCR_006837

    This resource has 10+ mentions.

http://dally.nimh.nih.gov/index.html

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.

Proper citation: NIMH CORTEX (RRID:SCR_006837) Copy   


  • RRID:SCR_007143

    This resource has 1+ mentions.

http://hendrix.imm.dtu.dk/software/lyngby/

Matlab toolbox for the analysis of functional neuroimages (PET, fMRI). The toolbox contains a number of models: FIR-filter, Lange-Zeger, K-means clustering among others, visualizations and reading of neuroimaging files.

Proper citation: Lyngby (RRID:SCR_007143) Copy   



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