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.
Collection of revertible protein trap gene-breaking transposon (GBT) insertional mutants in zebrafish with active or cryopreserved lines from initially identified lines. Open to community-wide contributions including expression and functional annotation and represents world-wide central hub for information on how to obtain these lines from diverse members of International Zebrafish Protein Trap Consortium (IZPTC) and integration within other zebrafish community databases including Zebrafish Information Network (ZFIN), Ensembl and National Center for Biotechnology Information. Registration allows users to save their favorite lines for easy access, request lines from Mayo Clinic catalog, contribute to line annotation with appropriate credit, and puts them on optional mailing list for future zfishbook newletters and updates.
Proper citation: zfishbook (RRID:SCR_006896) Copy
A Python package intended to ease statistical learning analyses of large datasets. It offers an extensible framework with a high-level interface to a broad range of algorithms for classification, regression, feature selection, data import and export. While it is not limited to the neuroimaging domain, it is eminently suited for such datasets. PyMVPA is truly free software (in every respect) and additionally requires nothing but free-software to run. Decoding patterns of neural activity onto cognitive states is one of the central goals of functional brain imaging. Standard univariate fMRI analysis methods, which correlate cognitive and perceptual function with the blood oxygenation-level dependent (BOLD) signal, have proven successful in identifying anatomical regions based on signal increases during cognitive and perceptual tasks. Recently, researchers have begun to explore new multivariate techniques that have proven to be more flexible, more reliable, and more sensitive than standard univariate analysis. Drawing on the field of statistical learning theory, these new classifier-based analysis techniques possess explanatory power that could provide new insights into the functional properties of the brain. However, unlike the wealth of software packages for univariate analyses, there are few packages that facilitate multivariate pattern classification analyses of fMRI data. This Python-based, cross-platform, open-source software toolbox software toolbox for the application of classifier-based analysis techniques to fMRI datasets makes use of Python's ability to access libraries written in a large variety of programming languages and computing environments to interface with the wealth of existing machine learning packages.
Proper citation: PyMVPA (RRID:SCR_006099) Copy
http://www.rad.upenn.edu/sbia/
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on June 2, 2023. A section of the Penn department of radiology, it is devoted to the development of computer-based image analysis methods and their application to clinical research studies. Image analysis methodologies include image registration, segmentation, population-based statistical analysis, biophysical modeling of anatomical deformations, and high-dimensional pattern classification. Clinical research studies spans a variety of clinical areas and organs, and they include brain diseases such as Alzheimer's disease and schizophrenia, evaluation of treatment effects in large clinical trials, diagnosis of cardiac diseases, and diagnosis prostate, breast and brain cancer. SBIA also performs small animal imaging research aiming to understand brain development in mouse models. It has multiple resources which can be accessed by researcher.
Proper citation: SBIA (RRID:SCR_013628) Copy
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 31, 2022. Center focused on the development of computational biological atlases of different populations, subjects, modalities, and spatio-temporal scales with 3 types of resources: (1) Stand-alone computational software tools (image and volume processing, analysis, visualization, graphical workflow environments). (2) Infrastructure Resources (Databases, computational Grid, services). (3) Web-services (web-accessible resources for processing, validation and exploration of multimodal/multichannel data including clinical data, imaging data, genetics data and phenotypic data). The CCB develops novel mathematical, computational, and engineering approaches to map biological form and function in health and disease. CCB computational tools integrate neuroimaging, genetic, clinical, and other relevant data to enable the detailed exploration of distinct spatial and temporal biological characteristics. Generalizable mathematical approaches are developed and deployed using Grid computing to create practical biological atlases that describe spatiotemporal change in biological systems. The efforts of CCB make possible discovery-oriented science and the accumulation of new biological knowledge. The Center has been divided into cores organized as follows: - Core 1 is focused on mathematical and computational research. Core 2 is involved in the development of tools to be used by Core 3. Core 3 is composed of the driving biological projects; Mapping Genomic Function, Mapping Biological Structure, and Mapping Brain Phenotype. - Cores 4 - 7 provide the infrastructure for joint structure within the Center as well as the development of new approaches and procedures to augment the research and development of Cores 1-3. These cores are: (4)Infrastructure and Resources, (5) Education and Training, (6) Dissemination, and (7) Administration and Management. The main focus of the CCB is on the brain, and specifically on neuroimaging. This area has a long tradition of sophisticated mathematical and computational techniques. Nevertheless, new developments in related areas of mathematics and computational science have emerged in recent years, some from related application areas such as Computer Graphics, Computer Vision, and Image Processing, as well as from Computational Mathematics and the Computational Sciences. We are confident that many of these ideas can be applied beneficially to neuroimaging.
Proper citation: Center for Computational Biology at UCLA (RRID:SCR_000334) Copy
A central organization that develops, supports, co-ordinates and promotes scientific research in all fields concerning the brain; promotes international collaboration and interchange of scientific information on brain research throughout the world; and provides for and to assist in education and the dissemination of information relating to brain research by all available means. IBRO represents the interests of more than 50,000 neuroscientists around the globe. Over the years, IBRO has set up a number of program to stimulate international contacts in brain research. Symposia and workshops are sponsored on the basis of competitive applications. Under its Publications Programme, IBRO publishes the journal Neuroscience and the annual newsletter IBRO News. IBRO offers post-doctoral fellowships and travel grants to students from less-developed countries. It has run a Neuroscience Schools Programme, organized by the committees of IBROs six Regions, aimed at forming interactive networks among students and teachers during training courses in Africa, Asia, Central and Eastern Europe, Latin America, Western Europe, and the US and Canada. With just three schools in 1999, expansion has been rapid - in 2007 there were 22 schools around the world.
Proper citation: International Brain Research Organization (RRID:SCR_007406) Copy
http://www.neuroanatomy.wisc.edu/
Training materials including Web edition modules of the neuroanatomy coursebooks used by first-year medical students at the University of Wisconsin Medical School (UWMS), videos, and images. Topics include spinal cord, brain stem, Cerebellum, Thalamus, Cranial Nerves and National Board Review practice questions.
Proper citation: UW-Madison Neuroscience Resources (RRID:SCR_001649) Copy
A 4D adult brain extraction and analysis toolbox with graphical user interfaces to consistently analyze 4D adult brain MR images. Single-time-point images can also be analyzed. Main functions of the software include image preprocessing, 4D brain extraction, 4D tissue segmentation, 4D brain labeling, ROI analysis. Linux operating system (64 bit) is required. A computer with 8G memory (or more) is recommended for processing many images simultaneously. The graphical user interfaces and overall framework of the software are implemented in MATLAB. The image processing functions are implemented with the combination of C/C++, MATLAB, Perl and Shell languages. Parallelization technologies are used in the software to speed up image processing.
Proper citation: aBEAT (RRID:SCR_002238) Copy
Open-source software package for the analysis of neural data. Chronux routines may be employed in the analysis of both point process and continuous data, ranging from preprocessing, exploratory and confirmatory analysis. The current release is implemented as a MATLAB library. Chronux offers several routines for computing spectra and coherences for both point and continuous processes. In addition, it also offers several general purpose routines that were found useful such as a routine for extracting specified segments from data, or binning spike time data with bins of a specified size. Since the data can be continuous valued, point process times, or point processes that are binned, methods that apply to all these data types are given in routines whose names end with ''''c'''' for continuous, ''''pb'''' for binned point processes, and ''''pt'''' for point process times. Thus, mtspectrumc computes the spectrum of continuous data, mtspectrumpb computes a spectrum for binned point processes, and mtspectrumpt compute spectra for data consisting of point process times. Hybrid routines are also available and similarly named - for instance coherencycpb computes the coherency between continuous and binned point process data.
Proper citation: Chronux (RRID:SCR_005547) Copy
http://www.research.va.gov/programs/tissue_banking/als/
A human tissue bank that collects, processes, stores and gives out research specimens for future scientific studies. Presently, the VABBB is obtaining neurologic tissue specimens from Veterans who suffer from amyotrophic lateral sclerosis (ALS) and other illnesses that affect Veterans, along with relevant clinical data, essential for research. Currently, neither the cause nor prevention of ALS is known. Medical researchers are currently examining environmental, toxic, genetic, traumatic, medical, and occupational influences as possible contributors to the development and progression of ALS. Veterans have a higher risk of developing ALS compared with non-Veterans; however, the reasons for this higher risk are currently unknown. Any Veteran with ALS in the U.S. may enroll in the VABBB.
Proper citation: VA Biorepository Brain Bank (RRID:SCR_006546) Copy
Mission of the School of Behavioral and Brain Sciences is to understand the intersection of mind, brain and behavior; enhance the health, education, and quality of life of children and families; and create and implement technologies and therapies that repair and strengthen human abilities. The School is housed in Green Hall on the main UT Dallas campus in Richardson. It also has satellite research centers and facilities in downtown Dallas.
Proper citation: University of Texas at Dallas School of Behavioral and Brain Sciences (RRID:SCR_004645) Copy
Website for brain experimental data and other resources such as stimuli and analysis tools. Provides marketplace and discussion forum for sharing tools and data in neuroscience. Data repository and collaborative tool that supports integration of theoretical and experimental neuroscience through collaborative research projects. CRCNS offers funding for new class of proposals focused on data sharing and other resources.
Proper citation: CRCNS (RRID:SCR_005608) Copy
https://www.bminds.brain.riken.jp/
Web-accessible digital brain atlas of the common marmoset (Callithrix jacchus), prepared from histological sections of the marmoset brain using various staining techniques.
Proper citation: Digital Brain Atlas of the Common Marmoset (RRID:SCR_005069) Copy
http://penglab.janelia.org/proj/v3d/V3D/About_V3D.html
V3D is a handy, fast, and versatile 3D/4D/5D Image Visualization & Analysis System for Bioimages & Surface Objects. It also provides many unique functions, is Open Source, supports a very simple and powerful plugin interface and thus can be extended & enhanced easily. V3D-Neuron is a powerful 3D neuron reconstruction, visualization, and editing software built on top of V3D. Both V3D and V3D-Neuron have recently been published in Nature Biotechnology (April, 2010), and Highlighted in Nature Methods (May, 2010), and Science News (April, 2010), etc. V3D is a cross-platform (Mac, Linux, and Windows) tool for visualizing large-scale (gigabytes, and 64-bit data) 3D image stacks and various surface data. It is also a container of powerful modules for 3D image analysis (cell segmentation, neuron tracing, brain registration, annotation, quantitative measurement and statistics, etc) and data management. This makes V3D suitable for various bioimage informatics applications, and a nice platform to develop new 3D image analysis algorithms for high-throughput processing. In short, V3D streamlines the workflow of visualization-assisted analysis. In the latest V3D development, it can render 5D (spatial-temporal) data directly in 3D volume-rendering mode; it supports convenient and interactive local and global 3D views at different scales. It even has a Matlab file IO toolbox. A user can now write his/her own plugins to take advantage of the V3D platform very easily.
Proper citation: V3D (RRID:SCR_008646) Copy
http://www.nimh.nih.gov/labs-at-nimh/research-areas/research-support-services/hbcc/index.shtml
A collection of brain tissue from individuals suffering from schizophrenia, bipolar disorder, depression, anxiety disorders, and substance abuse, as well as healthy individuals. The research mission of the NIMH Brain Bank is to better understand the underlying biological mechanisms and pathways that contribute to schizophrenia and other neuropsychiatric disorders, as well as to study normal human brain development.
Proper citation: NIMH Brain Tissue Collection (RRID:SCR_008726) Copy
Brain tissue donation program at the UT Southwestern Memory Clinic that aims to utilize these contributions for research on Alzheimer's. Diagnosis of Alzheimer's disease or other dementias are made through autopsy, the results of which are available to family members.
Proper citation: UT Southwestern ADC Brain Tissue Donation Program (RRID:SCR_008837) Copy
Open source software package of Python modules for neuroscience, primarily focused on functional Magnetic Resonance Imaging (fMRI) analysis. Used for analyzing neuroimaging data.
Proper citation: Brain Imaging Analysis Kit (RRID:SCR_014824) Copy
Strategy guide for HED Annotation. Framework for systematically describing laboratory and real world events.HED tags are comma separated path strings. Organized in forest of groups with roots Event, Item, Sensory presentation, Attribute, Action, Participant, Experiment context, and Paradigm. Used for preparing brain imaging data for automated analysis and meta analysis. Applied to brain imaging EEG, MEG, fNIRS, multimodal mobile brain or body imaging, ECG, EMG, GSR, or behavioral data. Part of Brain Imaging Data Structure standard for brain imaging.
Proper citation: HED Tags (RRID:SCR_014074) Copy
http://www.sci.utah.edu/software/fluorender.html
Interactive rendering tool for confocal microscopy data visualization. Combines rendering of multi-channel volume data and polygon mesh data, where properties of each dataset can be adjusted independently and quickly. Designed for neurobiologists, allowing them to better visualize confocal data from fluorescently-stained brains, but it is also useful for other biological samples. Features include feature tracking, 3D measurement tools, multiple render modes for multi-channel confocal data, and volume paint selection and segmentation.
Proper citation: FluoRender (RRID:SCR_014303) Copy
A community encyclopaedia that links brain research concepts with data, models and literature from around the world. It is an open project where users can participate and contribute to the global research community.
Proper citation: KnowledgeSpace (RRID:SCR_014539) Copy
https://www.mbfbioscience.com/brainmaker
Software tool to automatically align sections to visualize brains in 3D. Assists with cell mapping, cytoarchitectonics and other areas requiring characterization of neuronal circuitry to create comprehensive anatomical reference. Automatically creates full resolution, 3D reconstructions of entire brain or any organ from serial sections of whole slide images. Allows to view cells, structures, and lesions, locate neurons expressing particular gene or visualize axonal projections of specific neurons with full anatomical context.
Proper citation: BrainMaker (RRID:SCR_017666) 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 NIF Resources search. From here you can search through a compilation of resources used by NIF and see how data is organized within our community.
You are currently on the Community Resources tab looking through categories and sources that NIF 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 NIF then you can log in from here to get additional features in NIF 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 NIF 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 NIF 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.