Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.
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.
http://sccn.ucsd.edu/fmrlab/index.html
A Matlab toolbox for fMRI data analysis using Independent Component Analysis (ICA). It provides an integrated environment to manage, process and analyze fMRI data in a single framework so that users can complete the analysis without switching between software. In addition, it provides an interactive Matlab graphic user interface (GUI). All the necessary processes to apply ICA to fMRI data and review its results can be run from the graphic interface. The FMRLAB processing flow is straightforward. Custom analyses can be performed with Matlab scripts using the FMRLAB functions and data structure. Since fMRI data analysis is a complex enterprise, including digital image processing, statistical analysis and data visualization, an integrated framework combining processing elements is desired eagerly by users in the neuroimaging community. Recently, large number of software tools for data analysis and visualization have been developed for this purpose. However, most of these tools use model-based statistical methods which assume that the users know the hemodynamic response (HR) for their paradigm in advance and can specify a reasonable HR model. Often, however, accurate or reasonable response HR models are unavailable. An alternative data-driven method, infomax ICA (McKeown et al., 1998), does not require that an a priori HR model, instead deriving HRs of spatially independent components of the entire data set from the higher-order statistics of the data themselves. FMRLAB is a toolbox running under Matlab containing necessary components for data-driven fMRI data analysis using the highly reliable infomax ICA algorithm (Bell & Sejnowski, 1995), normalized (Amari, 1999), extended (Lee, Girolami and Sejnowski, 1999) and automated by Makeig et al. FMRLAB has been developed under Matlab 6.1 running on Red Hat Linux. FMRLAB Features * Graphic user interface * Flexible data importing * Interactive data plotting * Computationally efficient * Defined FMRI data structure * Independent component browser * Smooth, transparent component exporting and spatial normalization process * Interface with other software for further analysis or visualization. * SPM-style component plots (MIP, 2-D slice overlay and 3-D)
Proper citation: FMRLAB (RRID:SCR_005164) Copy
Platform for large-scale, automated synthesis of functional magnetic resonance imaging (fMRI) data extracted from published articles. It''s a website wrapped around a set of open-source Python and JavaScript packages. Neurosynth lets you run crude but useful analyses of fMRI data on a very large scale. You can: * Interactively visualize the results of over 3,000 term-based meta-analyses * Select specific locations in the human brain and view associated terms * Browse through the nearly 10,000 studies in the database Their ultimate goal is to enable dynamic real-time analysis, so that you''ll be able to select foci, tables, or entire studies for analysis and run a full-blown meta-analysis without leaving your browser. You''ll also be able to do things like upload entirely new images and obtain probabilistic estimates of the cognitive states most likely to be associated with the image.
Proper citation: NeuroSynth (RRID:SCR_006798) Copy
http://code.google.com/p/lapdftext/
Software that facilitates accurate extraction of text from PDF files of research articles for use in text mining applications. It is intended for both scientists and natural language processing (NLP) engineers interested in getting access to text within specific sections of research articles. The system extracts text blocks from PDF-formatted full-text research articles and classifies them into logical units based on rules that characterize specific sections. The LA-PDFText system focuses only on the textual content of the research articles. The current version of LA-PDFText is a baseline system that extracts text using a three-stage process: * identification of blocks of contiguous text * classification of these blocks into rhetorical categories * extraction of the text from blocks grouped section-wise.
Proper citation: lapdftext (RRID:SCR_006167) Copy
http://www.mbl.org/mbl_main/atlas.html
High-resolution electronic atlases for mouse strains c57bl/6j, a/j, and dba/2j in either coronal or horizontal section. About this Atlas: The anterior-posterior coordinates are taken from an excellent print atlas of a C57BL/6J brain by K. Franklin and G. Paxinos (The Mouse Brain in Stereotaxic Coordinates, Academic Press, San Diego, 1997, ISBN Number 0-12-26607-6; Library of Congress: QL937.F72). The abbreviations we have used to label the sections conform to those in the Franklin-Paxinos atlas. A C57BL/6J mouse brain may contain as many as 75 million neurons, 23 million glial cells, 7 million endothelial cells associated with blood vessels, and 3 to 4 million miscellaneous pial, ependymal, and choroid plexus cells (see data analysis in Williams, 2000). We have not yet counted total cell number in DBA/2J mice, but the counts are probably appreciably lower.The brain and sections were all processed as described in our methods section. The enlarged images have a pixel count of 1865 x 1400 and the resolution is 4.5 microns/pixel for the processed sections.Plans: In the next several years we hope to add several additional atlases of the same sort for other strains of mice. A horizontal C57BL/6J atlas and a DBA/2J coronal atlas were completed by Tony Capra, summer 2000, and additional atlases may be made over the next several years. As describe in the MBL Procedures Section is not hard to make your own strain-specific atlas from the high resolution images in the MBL.
Proper citation: Mouse Brain Atlases (RRID:SCR_007127) Copy
http://www.cpc.unc.edu/projects/addhealth
Longitudinal study of a nationally representative sample of adolescents in grades 7-12 in the United States during the 1994-95 school year. Public data on about 21,000 people first surveyed in 1994 are available on the first phases of the study, as well as study design specifications. It also includes some parent and biomarker data. The Add Health cohort has been followed into young adulthood with four in-home interviews, the most recent in 2008, when the sample was aged 24-32. Add Health combines longitudinal survey data on respondents social, economic, psychological and physical well-being with contextual data on the family, neighborhood, community, school, friendships, peer groups, and romantic relationships, providing unique opportunities to study how social environments and behaviors in adolescence are linked to health and achievement outcomes in young adulthood. The fourth wave of interviews expanded the collection of biological data in Add Health to understand the social, behavioral, and biological linkages in health trajectories as the Add Health cohort ages through adulthood. The restricted-use contract includes four hours of free consultation with appropriate staff; after that, there''s a fee for help. Researchers can also share information through a listserv devoted to the database.
Proper citation: Add Health (National Longitudinal Study of Adolescent Health) (RRID:SCR_007434) Copy
http://senselab.med.yale.edu/cellpropdb
A 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 aid
Proper citation: Cell Properties Database (RRID:SCR_007285) Copy
http://www.oreganno.org/oregano/
Open source, open access database and literature curation system for community based annotation of experimentally identified DNA regulatory regions, transcription factor binding sites and regulatory variants. Automatically cross referenced against PubMED, Entrez Gene, EnsEMBL, dbSNP, eVOC: Cell type ontology, and Taxonomy database. Community driven resource for curated regulatory annotation.
Proper citation: Open Regulatory Annotation Database (RRID:SCR_007835) Copy
http://fcon_1000.projects.nitrc.org/indi/pro/eNKI_RS_TRT/FrontPage.html
A test-retest dataset to assess the reliability of multiband resting state fMRI (R-fMRI) and diffusion tensor imaging (DTI) scans prior to launch of the Enhanced Nathan Kline Institute - Rockland Sample (NKI-RS). The dataset is primarily composed of individuals from the initial NKI-RS - for these individuals psychiatric assessment information is available and included (participants were not excluded due to history of illness. In addition to R-fMRI and DTI, they included: 1) simple visual checkerboard stimulation fMRI scans to allow for assessment of traditional fMRI data quality metrics (e.g., contrast-to-noise ratio), 2) breath holding data to enable assessment of regional differences in vascular responsiveness, and 3) eye movement calibration scans to enable the assessment of eye-movement related artifacts which may be particularly troublesome for multiband sequences since several slices are acquired simultaneously.
Proper citation: NKI-RS Multiband Imaging Test-Retest Pilot Dataset (RRID:SCR_010460) Copy
http://fcon_1000.projects.nitrc.org/indi/enhanced/
Dataset of 1000 characterized community-ascertained participants using state-of-the-art multiband imaging-based resting state fMRI (R-fMRI) and diffusion tensor imaging (DTI), genetics, and a deep phenotyping protocol from a large cross-sectional sample of brain development, maturation and aging (ages 6 - 85 yrs). The Center for Magnetic Resonance Research (CMRR), University of Minnesota, provided the NKI-RS effort with the latest version of the Multiband EPI sequence (Xu et al. 2012) and associated image reconstruction algorithms, enabling the acquisition of state-of-the-art imaging datasets for this large-scale imaging effort. The enhanced NKI-RS expands upon the phenotypic protocol of the original NKI-RS and captures a broad range of behavioral and cognitive phenomenology relevant to psychiatric health and illness. The validity and value of assessments were evaluated by consulting leaders in the field of psychiatric phenotyping.
Proper citation: NKI-RS Enhanced Sample (RRID:SCR_010461) Copy
https://github.com/fsotoc/FaReT
Software toolkit of three dimensional models and software to study face perception. Collection of plugins used with MakeHuman to create face stimuli for experiments.
Proper citation: Face Research Toolkit (RRID:SCR_023322) Copy
https://github.com/parklab/NGSCheckMate
Software package for validating sample identity in next generation sequencing studies within and across data types. Used for identifying next generation sequencing data files from the same individual. Used for checking sample matching for NGS data.
Proper citation: NGSCheckMate (RRID:SCR_022994) Copy
https://github.com/namboodirilab/B-CALM
Open source system for behavioral control based on Arduino Mega microcontroller and MATLAB based graphical interface and analysis code. Behavior controller optimized and customized for associative learning and memory tasks. Provided software should be able to control many different types of hardware for different task configurations.
Proper citation: B-CALM (RRID:SCR_023884) Copy
https://github.com/rondolab/MR-PRESSO
Software R package for performing Mendelian randomization pleiotropy residual sum and outlier method.Used to identify horizontal pleiotropic outliers in multi instrument summary level MR testing.
Proper citation: MR-PRESSO (RRID:SCR_023697) Copy
http://mus.well.ox.ac.uk/mouse/INBREDS/
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 19,2025. Data set of genotypes available for 480 strains and 13370 successful SNP assays that are mapped to build34 of the mouse genome, including 107 SNPs that are mapped to random unanchored sequence 13374 SNPs are mapped onto Build 33 of the mouse genome. You can access the data relative to Build 33 or Build 34.
Proper citation: Wellcome-CTC Mouse Strain SNP Genotype Set (RRID:SCR_003216) Copy
Neurophysiology imaging core facility that provides anatomical and functional MRI scanning for researchers in the National Institute of Mental Health (NIMH), the National Eye Institute (NEI), and the National Institute for Neurological Disorders and Stroke (NINDS). The shared intramural resource centers on a cutting-edge 4.7T vertical bore scanner dedicated to imaging of nonhuman primates.
Proper citation: Neurophysiology Imaging Facility (RRID:SCR_004080) Copy
http://fcon_1000.projects.nitrc.org/indi/pro/nki.html
A phenotypically rich neuroimaging sample, consisting of data obtained from individuals between the ages of 4 and 85 years-old. All individuals included in the sample undergo semi-structured diagnostic psychiatric interviews, and complete a battery of psychiatric, cognitive and behavioral assessments in order to provide comprehensive phenotypic information for the purpose of exploring brain / behavior relationships.
Proper citation: NKI/Rockland Sample (RRID:SCR_009435) Copy
https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/MSM
Software tool for registering cortical surfaces. Capable of driving alignment using wide variety of descriptors of brain architecture, function and connectivity.
Proper citation: Multimodal Surface Matching (RRID:SCR_024929) Copy
https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FIRST
Software model based segmentation and registration tool. Used for segmentation of sub-cortical structures. Introduces basic segmentation and vertex analysis for detecting group differences.
Proper citation: FMRIB’s Integrated Registration and Segmentation Tool (RRID:SCR_024921) Copy
https://github.com/bmvdgeijn/WASP/
Software allele-specific pipeline for unbiased read mapping and molecular QTL discovery. Allele-specific software for robust molecular quantitative trait locus discovery.
Proper citation: WASP (RRID:SCR_025497) Copy
http://casestudies.brain-map.org/celltax
Cellular Taxonomy of Mouse Visual Cortex by analyzing gene expression patterns at single cell level. Construction of cellular taxonomy of one cortical region, primary visual cortex, in adult mice done on basis of single cell RNA sequencing.
Proper citation: CellTax vignette (RRID:SCR_017000) Copy
Can't find your Tool?
We recommend that you click next to the search bar to check some helpful tips on searches and refine your search firstly. Alternatively, please register your tool with the SciCrunch Registry by adding a little information to a web form, logging in will enable users to create a provisional RRID, but it not required to submit.
Welcome to the dkNET Resources search. From here you can search through a compilation of resources used by dkNET and see how data is organized within our community.
You are currently on the Community Resources tab looking through categories and sources that dkNET has compiled. You can navigate through those categories from here or change to a different tab to execute your search through. Each tab gives a different perspective on data.
If you have an account on dkNET then you can log in from here to get additional features in dkNET such as Collections, Saved Searches, and managing Resources.
Here is the search term that is being executed, you can type in anything you want to search for. Some tips to help searching:
You can save any searches you perform for quick access to later from here.
We recognized your search term and included synonyms and inferred terms along side your term to help get the data you are looking for.
If you are logged into dkNET you can add data records to your collections to create custom spreadsheets across multiple sources of data.
Here are the sources that were queried against in your search that you can investigate further.
Here are the categories present within dkNET that you can filter your data on
Here are the subcategories present within this category that you can filter your data on
If you have any further questions please check out our FAQs Page to ask questions and see our tutorials. Click this button to view this tutorial again.