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http://biogps.org/dataset/tag/kawasaki%20disease/

Collection of data sets on Kawasaki disease, a rare childhood illness that affects the blood vessels. The data includes biochemical measurements of myocardial strain, oxidative stress, and cardiomyocyte injury as well as protein level analysis.

Proper citation: Kawasaki Disease Dataset (RRID:SCR_001451) Copy   

•   Source: SciCrunch Registry

https://scicrunch.org/resources/Tools/record/nlx_144509-1/6b508d2a-fd5f-56f2-93cf-462fcd52548e/search?q=*&l=&facet%5B%5D=Parent%20Organization:University%20of%20Michigan;%20Michigan;%20USA&sort=added

THIS RESOURCE IS NO LONGER IN SERVICE. Documented September 12, 2017.

Dataset in Bilingual exposure optimizes left-hemisphere dominance for selective attention processes in the developing brain by Arredondo, Su, Satterfield, & Kovelman (XX) Does early bilingual exposure alter the representations of cognitive processes in the developing brain? Theories of bilingual development have suggested that bilingual language switching might improve children''s executive function and foster the maturation of prefrontal brain regions that support higher cognition. To test this hypothesis, we used functional Near Infrared Spectroscopy to measure brain activity in Spanish-English bilingual and English-monolingual children during a visuo-spatial executive function task of attentional control (N=27, ages 7-13). Prior findings suggest that while young children start with bilateral activation for the task, it becomes right-lateralized with age (Konrad et al., 2005). Indeed monolinguals showed bilateral frontal activation, however young bilinguals showed greater activation in left language areas relative to right hemisphere and relative to monolinguals. The findings suggest that bilingual experience optimizes attention mechanisms in the language hemisphere, and highlight the importance of early experiences for neurodevelopmental plasticity of higher cognition. These data are made available from Ioulia Kovelman''s Language and Literacy Lab at University of Michigan and may be exported through the NIF Data Federation. To cite these data please use this text Data were published by Arredondo et al. (XX) and made available via the NIF at XX

Proper citation: Arredondo ANT fNIRS dataset1 (RRID:SCR_002653) Copy   

•   Source: SciCrunch Registry

http://www.humanconnectome.org/documentation/S500/

Behavioral and 3T MR imaging data from over 500 healthy adult participants with 14 subjects also scanned in resting-state MEG (rMEG) and task MEG (tMEG). Highlights: * Behavioral and demographic data on 550 subjects. * MR imaging data preprocessed using updated pipelines (structural pipeline v3.1, functional pipeline v3.1, diffusion pipeline v3.1, task analysis pipeline v3.3). * Updates to pipelines include a new intersubject registration method called MSMSulc. All MR data from Q1-Q3 releases have been reprocessed. HCP strongly advises against mixing data from this release with previously-released data. * Individual task fMRI grayordinate-based analysis results (available at 2mm, 4mm, 8mm, and 12mm smoothing levels) and volume-based analysis results (4mm smoothing) are available for all complete 500 Subjects tfMRI data, using an updated task analysis pipeline v3.3. * New extensively processed 100- and 400+-subject group-average functional MR data. * Updates to MEG data and access in ConnectomeDB. Structural MRI-based MEG anatomical models and MR data for the 14 MEG1 Release subjects. * Improvements to behavioral data organization and data dictionary, including the addition of previously unreleased restricted behavioral and demographic data. * All imaging data soon to be available on the cloud through Amazon S3. (More information to come!)

Proper citation: WU-Minn HCP 500 Subjects MR and MEG Release (RRID:SCR_003922) Copy   

•   Source: SciCrunch Registry

http://www.informatics.jax.org/searches/MP_form.shtml

Community ontology to provide standard terms for annotating mammalian phenotypic data. It has a hierarchical structure that permits a range of detail from high-level, broadly descriptive terms to very low-level, highly specific terms. This range is useful for annotating phenotypic data to the level of detail known and for searching for this information using either broad or specific terms as search criteria. Your input is welcome.

Proper citation: MPO (RRID:SCR_004855) Copy   

•   Source: SciCrunch Registry

http://senselab.med.yale.edu/modeldb/

Curated database of published models so that they can be openly accessed, downloaded, and tested to support computational neuroscience. Provides accessible location for storing and efficiently retrieving computational neuroscience models.Coupled with NeuronDB. Models can be coded in any language for any environment. Model code can be viewed before downloading and browsers can be set to auto-launch the models. The model source code has to be available from publicly accessible online repository or WWW site. Original source code is used to generate simulation results from which authors derived their published insights and conclusions.

Proper citation: ModelDB (RRID:SCR_007271) Copy   

•   Source: SciCrunch Registry

https://cgc.umn.edu

Center that acquires, maintains, and distributes genetic stocks and information about stocks of the small free-living nematode Caenorhabditis elegans for use by investigators initiating or continuing research on this genetic model organism. A searchable strain database, general information about C. elegans, and links to key Web sites of use to scientists, including WormBase, WormAtlas, and WormBook are available.

Proper citation: Caenorhabditis Genetics Center (RRID:SCR_007341) Copy   

•   Source: SciCrunch Registry

http://senselab.med.yale.edu/ordb/

Database of vertebrate olfactory receptors genes and proteins. It supports sequencing and analysis of these receptors by providing a comprehensive archive with search tools for this expanding family. The database also incorporates a broad range of chemosensory genes and proteins, including the taste papilla receptors (TPRs), vomeronasal organ receptors (VNRs), insect olfaction receptors (IORs), Caenorhabditis elegans chemosensory receptors (CeCRs), and fungal pheromone receptors (FPRs). ORDB currently houses chemosensory receptors for more than 50 organisms. ORDB contains public and private sections which provide tools for investigators to analyze the functions of these very large gene families of G protein-coupled receptors. It also provides links to a local cluster of databases of related information in SenseLab, and to other relevant databases worldwide. The database aims to house all of the known olfactory receptor and chemoreceptor sequences in both nucleotide and amino acid form and serves four main purposes: * It is a repository of olfactory receptor sequences. * It provides tools for sequence analysis. * It supports similarity searches (screens) which reduces duplicate work. * It provides links to other types of receptor information, e.g. 3D models. The database is accessible to two classes of users: * General public www users have full access to all the public sequences, models and resources in the database. * Source laboratories are the laboratories that clone olfactory receptors and submit sequences in the private or public database. They can search any sequence they deposited to the database against any private or public sequence in the database. This user level is suited for laboratories that are actively cloning olfactory receptors.

Proper citation: Olfactory Receptor DataBase (RRID:SCR_007830) Copy   

•   Source: SciCrunch Registry

http://www.cellml.org/models

Repository of biological models created using CellML, a free, open-source, eXtensible markup language based standard for defining mathematical models of cellular function. Models may be browsed by category, which include: Calcium Dynamics, Cardiovascular Circulation, Cell Cycle, Cell Migration, Circadian Rhythms, Electrophysiology, Endocrine, Excitation-Contraction Coupling, Gene Regulation, Hepatology, Immunology, Ion Transport, Mechanical Constitutive Laws, Metabolism, Myofilament Mechanics, Neurobiology, pH Regulation, PKPD, Signal Transduction, Synthetic Biology. The community can contribute their models to this resource.

Proper citation: CellML Model Repository (RRID:SCR_008113) Copy   

•   Source: SciCrunch Registry

http://roadmapepigenomics.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 11, 2022. Project for human epigenomic data from experimental pipelines built around next-generation sequencing technologies to map DNA methylation, histone modifications, chromatin accessibility and small RNA transcripts in stem cells and primary ex vivo tissues selected to represent normal counterparts of tissues and organ systems frequently involved in human disease. Consortium expects to deliver collection of normal epigenomes that will provide framework or reference for comparison and integration within broad array of future studies. Consortium is also committed to development, standardization and dissemination of protocols, reagents and analytical tools to enable research community to utilize, integrate and expand upon this body of data.

Proper citation: Roadmap Epigenomics Project (RRID:SCR_008924) Copy   

•   Source: SciCrunch Registry

http://bmi.neuroinf.jp/

Databases of accumulating BMI (Brain Machine Interfaces)-related experimental data, mathematical models, and tools generated in neuroscience, computational theory, and robotics. Databases include: # Database of BMI (Brain Machine Interfaces)-related papers: More than 3500 BMI-related papers are registered. Each paper has original tags, for example, recording method and subject, for easy searching. # Database of original contents: BMI-related materials (Movie, Picture, Data, Program) provided by scientists. # Database of BMI-related research sites: 185 BMI-related research sites in the world (university, institute and company) are registered. The research site can be searched either by the location using clickable map or by the field of interest. # Database of BMI-related materials: Links to BMI-related materials (Movie, Picture, Document, Data, Program) are listed. You can easily find materials of your interest since each material is classified into research field. # BMI-related column: The columns are written by researchers specialized in BMI. Original contents include: * Neuronal activity during performance of a memory-guided movement * Reconstructed visual images from human fMRI activity * fMRI data and program for visual image reconstruction * Brain sections of monkeys, stained for several gene markers * Cortical Box Method: The Cortical box method is an analytical method that standardizes the serial coronal sections of rodent cortex for quantitative analysis. * Multineuron activity in monkey prefrontal cortex * Monkey Atlas: **Brain sections of monkeys, stained for AChE, ER81 mRNA and Sema3E mRNA - These pictures are low-resolution photos of serial brain sections of monkeys, stained for AChE as well as for ER81 and Sema3E mRNAs. The compressed file contains JPEG photos and html files for web browser navigation. Other materials are available at our website BraInSitu dedicated for in situ hybridization resources for brains. BraInSitu http://www.nibb.ac.jp/brish/indexE.html ** MRI Brain Atlas of Japanese Snow Monkey (Macaca Fuscata) at different ages - MRI Brain Atlas of Japanese Snow Monkey (Macaca Fuscata) at different ages ** The Stereotaxic MRI Brain Atlas of Japanese Snow Monkey - The Stereotaxic MRI Brain Atlas of Japanese Snow Monkey * Monkey M1 BMI ** m-file for checking the results of wrist angle estimation- This program is m-file to train the relationship between joint angles and EMG signals using artificial neural network. The input signals are four EMG signals and the output signals are joint angles of wrist, such as flexion/extension, radial deviation/uln ** m-file for training of wrist angle estimation -This program is m-file to train the relationship between joint angles and EMG signals using artificial neural network. The input signals are four EMG signals and the output signals are joint angles of wrist, such as flexion/extension, radial deviation/ulnar deviation.ar deviation. ** M1 Neuronal Activity during monkey performing a motor task - video/x-ms-wmv ** Muscle tension - To estimate muscle tension from raw emg signal ** raw EMG signal - Raw EMG signal for 5 seconds ** training data of wrist angle and emg signal - This program is m-file to train the relationship between joint angles and EMG signals using artificial neural network. The input signals are four EMG signals and the output signals are joint angles of wrist, such as flexion/extension, radial deviation/ulnar deviation. ** Weight file of neural network - This program is m-file to train the relationship between joint angles and EMG signals using artificial neural network. The input signals are four EMG signals and the output signals are joint angles of wrist, such as flexion/extension, radial deviation/ulnar deviation. * Multineuron activity in monkey prefrontal cortex: Multineuron activity in monkey prefrontal cortex recorded by 3 tetrodes. Vertical 4 lines indicate one tetrode. Adjacent tetrodes are around 500 micron apart to each other.

Proper citation: Brain Machine Interface Platform (RRID:SCR_001813) Copy   

•   Source: SciCrunch Registry

http://neuromorpho.org/index.jsp

Centrally curated inventory of digitally reconstructed neurons associated with peer-reviewed publications that contains some of the most complete axonal arborizations digitally available in the community. Each neuron is represented by a unique identifier, general information (metadata), the original and standardized ASCII files of the digital morphological reconstruction, and a set of morphometric features. It contains contributions from over 100 laboratories worldwide and is continuously updated as new morphological reconstructions are collected, published, and shared. Users may browse by species, brain region, cell type or lab name. Users can also download morphological reconstructions for research and analysis. Deposition and distribution of reconstruction files ultimately prevents data loss. Centralized curation and annotation aims at minimizing the effort required by data owners while ensuring a unified format. It also provides a one-stop entry point for all available reconstructions, thus maximizing data visibility and impact.

Proper citation: NeuroMorpho.Org (RRID:SCR_002145) Copy   

•   Source: SciCrunch Registry

http://ccdb.ucsd.edu

THIS RESOURCE IS NO LONGER IN SERVICE, documented June 5, 2017. It has been merged with Cell Image Library. Database for sharing and mining cellular and subcellular high resolution 2D, 3D and 4D data from light and electron microscopy, including correlated imaging that makes unique and valuable datasets available to the scientific community for visualization, reuse and reanalysis. Techniques range from wide field mosaics taken with multiphoton microscopy to 3D reconstructions of cellular ultrastructure using electron tomography. Contributions from the community are welcome. The CCDB was designed around the process of reconstruction from 2D micrographs, capturing key steps in the process from experiment to analysis. The CCDB refers to the set of images taken from microscope the as the Microscopy Product. The microscopy product refers to a set of related 2D images taken by light (epifluorescence, transmitted light, confocal or multiphoton) or electron microscopy (conventional or high voltage transmission electron microscopy). These image sets may comprise a tilt series, optical section series, through focus series, serial sections, mosaics, time series or a set of survey sections taken in a single microscopy session that are not related in any systematic way. A given set of data may be more than one product, for example, it is possible for a set of images to be both a mosaic and a tilt series. The Microscopy Product ID serves as the accession number for the CCDB. All microscopy products must belong to a project and be stored along with key specimen preparation details. Each project receives a unique Project ID that groups together related microscopy products. Many of the datasets come from published literature, but publication is not a prerequisite for inclusion in the CCDB. Any datasets that are of high quality and interest to the scientific community can be included in the CCDB.

Proper citation: Cell Centered Database (RRID:SCR_002168) Copy   

•   Source: SciCrunch Registry

http://www.addgene.org

Non-profit plasmid repository dedicated to helping scientists around the world share high-quality plasmids. Facilitates archiving and distributing DNA-based research reagents and associated data to scientists worldwide. Repository contains over 65,000 plasmids, including special collections on CRISPR, fluorescent proteins, and ready-to-use viral preparations. There is no cost for scientists to deposit plasmids, which saves time and money associated with shipping plasmids themselves. All plasmids are fully sequenced for validation and sequencing data is openly available. We handle the appropriate Material Transfer Agreements (MTA) with institutions, facilitating open exchange and offering intellectual property and liability protection for depositing scientists. Furthermore, we curate free educational resources for the scientific community including a blog, eBooks, video protocols, and detailed molecular biology resources.

Proper citation: Addgene (RRID:SCR_002037) Copy   

•   Source: SciCrunch Registry

http://www.candidagenome.org/

Database of genetic and molecular biological information about Candida albicans. Contains information about genes and proteins, descriptions and classifications of their biological roles, molecular functions, and subcellular localizations, gene, protein, and chromosome sequence information, tools for analysis and comparison of sequences and links to literature information. Each CGD gene or open reading frame has an individual Locus Page. Genetic loci that are not tied to DNA sequence also have Locus Pages. Provides Gene Ontology, GO, to all its users. Three ontologies that comprise GO (Molecular Function, Cellular Component, and Biological Process) are used by multiple databases to annotate gene products, so that this common vocabulary can be used to compare gene products across species. Development of ontologies is ongoing in order to incorporate new information. Data submissions are welcome.

Proper citation: Candida Genome Database (RRID:SCR_002036) Copy   

•   Source: SciCrunch Registry

http://www.csardock.org

Experimental datasets of crystal structures and binding affinities for diverse protein-ligand complexes. Some datasets are generated in house while others are collected from the literature or deposited by academic labs, national centers, and the pharmaceutical industry. For the community to improve their approaches, they need exceptional datasets to train scoring functions and develop new docking algorithms. They aim to provide the highest quality data for a diverse collection of proteins and small molecule ligands. They need input from the community in developing target priorities. Ideal targets will have many high-quality crystal structures (apo and 10-20 bound to diverse ligands) and affinity data for 25 compounds that range in size, scaffold, and logP. It is best if the ligand set has several congeneric series that span a broad range of affinity, with low nanomolar to mid-micromolar being most desirable. They prefer Kd data over Ki data over IC50 data (no % activity data). They will determine solubility, pKa, logP/logD data for the ligands whenever possible. They have augmented some donated IC50 data by determining Kon/Koff and ITC data.

Proper citation: Community Structure-Activity Resource (RRID:SCR_002206) Copy   

•   Source: SciCrunch Registry

https://datashare.nida.nih.gov

Website which allows data from completed clinical trials to be distributed to investigators and public. Researchers can download de-identified data from completed NIDA clinical trial studies to conduct analyses that improve quality of drug abuse treatment. Incorporates data from Division of Therapeutics and Medical Consequences and Center for Clinical Trials Network.

Proper citation: NIDA Data Share (RRID:SCR_002002) Copy   

•   Source: SciCrunch Registry

http://clinicaltrials.gov/

Registry and results database of federally and privately supported clinical trials conducted in United States and around world. Provides information about purpose of trial, who may participate, locations, and phone numbers for more details. This information should be used in conjunction with advice from health care professionals.Offers information for locating federally and privately supported clinical trials for wide range of diseases and conditions. Research study in human volunteers to answer specific health questions. Interventional trials determine whether experimental treatments or new ways of using known therapies are safe and effective under controlled environments. Observational trials address health issues in large groups of people or populations in natural settings. ClinicalTrials.gov contains trials sponsored by National Institutes of Health, other federal agencies, and private industry. Studies listed in database are conducted in all 50 States and in 178 countries.

Proper citation: ClinicalTrials.gov (RRID:SCR_002309) Copy   

•   Source: SciCrunch Registry

http://www.ensembl.org/

Collection of genome databases for vertebrates and other eukaryotic species with DNA and protein sequence search capabilities. Used to automatically annotate genome, integrate this annotation with other available biological data and make data publicly available via web. Ensembl tools include BLAST, BLAT, BioMart and the Variant Effect Predictor (VEP) for all supported species.

Proper citation: Ensembl (RRID:SCR_002344) Copy   

•   Source: SciCrunch Registry

http://www.behav.org/abcd/abcd.php

THIS RESOURCE IS NO LONGER IN SERVICE. Documented August 21, 2017.

Database developed for storing, retrieving and cross-referencing neuroscience information about the connectivity of the avian brain. It contains entries about the new and old terminology of the areas and their hierarchy and data on connections between brain regions, as well as a functional keyword system linked to brain regions and connections.

Proper citation: Avian Brain Circuitry Database (RRID:SCR_002401) Copy   

•   Source: SciCrunch Registry

https://simtk.org

A National NIH Center for Biomedical Computing that focuses on physics-based simulation of biological structures and provides open access to high quality simulation tools, accurate models and the people behind them. It serves as a repository for models that are published (as well as the associated code) to create a living archive of simulation scholarship. Simtk.org is organized into projects. A project represents a research endeavor, a software package or a collection of documents and publications. Includes sharing of image files, media, references to publications and manuscripts, as well as executables and applications for download and source code. Simulation tools are free to download and space is available for developers to manage, share and disseminate code.

Proper citation: Simtk.org (RRID:SCR_002680) Copy   

•   Source: SciCrunch Registry