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://www.cmrr.umn.edu/stimulate
An fMRI analysis software package with a GUI (Graphical User Interface) front end. Stimulate offers a comprehensive set of fMRI analysis tools integrated into a single package for convenient and flexible data processing. Users can point and click with the mouse to modify analysis or display variables. Activation maps can be calculated from the fMRI data and overlaid onto structural MRI image displays.
Proper citation: Stimulate (RRID:SCR_007375) Copy
A database which supports high-throughput NMR and MS approaches to the identification and quantification of metabolites present in biological samples. MMCD serves as a hub for information on small molecules of biological interest gathered from electronic databases and the scientific literature. Each metabolite entry in the MMCD is supported by information in separate data fields, which provide the chemical formula, names and synonyms, structure, physical and chemical properties, NMR and MS data on pure compounds under defined conditions where available, NMR chemical shifts determined by empirical and/or theoretical approaches, calculated isotopomer masses, information on the presence of the metabolite in different biological species, and links to images, references, and other public databases. The MMCD search engine supports versatile data mining and allows users to make individual or bulk queries on the basis of experimental NMR and/or MS data plus other criteria.
Proper citation: Madison Metabolomics Consortium Database (RRID:SCR_007803) Copy
A public database that enhances understanding of the effects of environmental chemicals on human health. Integrated GO data and a GO browser add functionality to CTD by allowing users to understand biological functions, processes and cellular locations that are the targets of chemical exposures. CTD includes curated data describing cross-species chemical–gene/protein interactions, chemical–disease and gene–disease associations to illuminate molecular mechanisms underlying variable susceptibility and environmentally influenced diseases. These data will also provide insights into complex chemical–gene and protein interaction networks.
Proper citation: Comparative Toxicogenomics Database (CTD) (RRID:SCR_006530) Copy
http://users.loni.ucla.edu/~shattuck/brainsuite/
Suite of image analysis tools designed to process magnetic resonance images (MRI) of the human head. BrainSuite provides an automatic sequence to extract genus-zero cortical surface mesh models from the MRI. It also provides a set of viewing tools for exploring image and surface data. The latest release includes graphical user interface and command line versions of the tools. BrainSuite was specifically designed to guide its users through the process of cortical surface extraction. NITRC has written the software to require minimal user interaction and with the goal of completing the entire process of extracting a topologically spherical cortical surface from a raw MR volume within several minutes on a modern workstation. The individual components of BrainSuite may also be used for soft tissue, skull and scalp segmentation and for surface analysis and visualization. BrainSuite was written in Microsoft Visual C using the Microsoft Foundation Classes for its graphical user interface and the OpenGL library for rendering. BrainSuite runs under the Windows 2000 and Windows XP Professional operating systems. BrainSuite features include: * Sophisticated visualization tools, such as MRI visualization in 3 orthogonal views (either separately or in 3D view), and overlayed surface visualization of cortex, skull, and scalp * Cortical surface extraction, using a multi-stage user friendly approach. * Tools including brain surface extraction, bias field correction, voxel classification, cerebellum removal, and surface generation * Topological correction of cortical surfaces, which uses a graph-based approach to remove topological defects (handles and holes) and ensure a tessellation with spherical topology * Parameterization of generated cortical surfaces, minimizing a harmonic energy functional in the p-norm * Skull and scalp surface extraction
Proper citation: BrainSuite (RRID:SCR_006623) Copy
http://www.ncrr.nih.gov/comparative_medicine/resource_directory/primates.asp
THIS RESOURCE IS NO LONGER IN SERVICE, documented on October 16, 2013. NCRR has been absorbed into other parts of the National Institutes of Health. This organizational structure is no longer available. Provides laboratory scientists and clinical researchers with the resources and tools they need to understand, detect, treat and prevent a wide range of diseases. Animal models, such as nonhuman primates, are a critical component of biomedical research, having profound implications for public health. Scientists depend on laboratory animals and other nonhuman models for investigating biological processes, studying the causes of diseases and testing promising new therapies. Nonhuman primates, in particular, are important for translational research because of their close physiological similarities to humans. They enable discoveries that have direct application to human studies, bridging the gap between basic science and human medicine. Discoveries in animal models are helping scientists test treatments for human conditions such as drug addiction, obesity, malaria, HIV/AIDS and neurodegenerative diseases, accelerating the pace at which these research advances can be translated into treatments for patients. Through its Division of Comparative Medicine, NCRR offers a wide variety of primate resources for NIH-funded scientists across the nation. Additionally, funding opportunities are available to National Primate Research Centers. Eight National Primate Research Centers (NPRCs) located throughout the country provide animals, facilities and expertise in all aspects of nonhuman primate biology and husbandry. These facilities and resources enable collaborative research among NPRC staff scientists, investigators from the NPRC host institution and other NIH-funded researchers. Major areas of research benefiting from the primate centers include AIDS, avian flu, Alzheimer''s disease, Parkinson''s disease, diabetes, asthma and endo-metriosis. The centers????????????????? specialized resources are intended to support investigators who receive their primary research project funding from NIH, but they also may be used by investigators who are funded by other federal, state and local agencies, as well as by research foundations and the private sector. Together the primate centers have more than 28,000 nonhuman primates of 20 different species. This portal covers the following topics: * National Primate Research Centers * Monkey Research Resources * Chimpanzee Research Resources * Chimpanzee Management Program * Specific-Pathogen-Free Macaque Resources * Nonhuman Primate Research Reagents
Proper citation: National Center for Research Resources - Primate Resources (RRID:SCR_006863) Copy
https://skyline.gs.washington.edu/labkey/project/home/software/Skyline/begin.view
Software tool as Windows client application for targeted proteomics method creation and quantitative data analysis. Open source document editor for creating and analyzing targeted proteomics experiments. Used for large scale quantitative mass spectrometry studies in life sciences.
Proper citation: Skyline (RRID:SCR_014080) Copy
http://www.nitrc.org/projects/laplacebeltrami/
A filter which allows the Laplace-Beltrami operator to determine surface harmonics in terms of PointData at each vertex. It determines the requested N most significant harmonics of a surface.
Proper citation: Laplace Beltrami Filter on QuadEdge Meshes (RRID:SCR_014133) Copy
http://biositemaps.ncbcs.org/rds/search.html
Resource Discovery System is a web-accessible and searchable inventory of biomedical research resources. Powered by the Resource Discovery System (RDS) that includes a standards-based informatics infrastructure * Biositemaps Information Model * Biomedical Resource Ontology Extensions * Web Services distributed web-accessible inventory framework * Biositemap Resource Editor * Resource Discovery System Source code and project documentation to be made available on an open-source basis. Contributing institutions: University of Pittsburgh, University of Michigan, Stanford University, Oregon Health & Science University, University of Texas Houston. Duke University, Emory University, University of California Davis, University of California San Diego, National Institutes of Health, Inventory Resources Working Group Members
Proper citation: Resource Discovery System (RRID:SCR_005554) Copy
http://www.informatics.jax.org/home/recombinase
Curated data about all recombinase-containing transgenes and knock-ins developed in mice providing a comprehensive resource delineating known activity patterns and allows users to find relevant mouse resources for their studies.
Proper citation: Recombinase (cre) Activity (RRID:SCR_006585) Copy
https://open.med.harvard.edu/display/SHRINE/Community
Software providing a scalable query and aggregation mechanism that enables federated queries across many independently operated patient databases. This platform enables clinical researchers to solve the problem of identifying sufficient numbers of patients to include in their studies by querying across distributed hospital electronic medical record systems. Through the use of a federated network protocol, SHRINE allows investigators to see limited data about patients meeting their study criteria without compromising patient privacy. This software should greatly enable population-based research, assessment of potential clinical trials cohorts, and hypothesis formation for followup study by combining the EHR assets across the hospital system. In order to obtain the maximum number of cases representing the study population, it is useful to aggregate patient facts across as many sites as possible. Cutting across institutional boundaries necessitates that each hospital IRB remain in control, and that their local authority is recognized for each and every request for patient data. The independence, ownership, and legal responsibilities of hospitals predetermines a decentralized technical approach, such as a federated query over locally controlled databases. The application comes with the SHRINE Core Ontology but it can be used with any ontology, even one that is disease specific. The Core Ontology is designed to enable the widest range of studies possible using facts gathered in the EMR during routine patient care. SHRINE allows multiple ontologies to be used for different research purposes on the same installed systems.
Proper citation: SHRINE (RRID:SCR_006293) Copy
http://www.wakehealth.edu/Research/WFUPC/Cynomolgus-Breeding-Colony-Request-Form-Instructions.htm
The Wake Forest Cynomolgus Breeding Colony (CBC) is a colony of cynomolgus macaques (crab-eating macaques, Macaca fascicularis). The cynomolgus colony is designed to produce specific pathogen free (SPF) cynomolgus monkeys for use in biomedical research. The colony, supported by a grant from the NCRR, addresses the growing need for investigators to use in their protocols animals defined for the absence of specific diseases including CHV-1 (Herpes B), simian immunodeficiency virus, and simian retroviruses. An additional important characteristic of this colony is that, unlike many breeding colonies, the NHPs will be fed two defined diets. The first diet is a soy-free diet, not commercial monkey chow. The second diet has the same macronutrients but the protein source is from soy; similar in isoflavone content. A drawback of chow diets is that the exact nutritional product composition is unknown from lot to lot. However, they are always rich in soy bean meal, isoflavones and other constituents of soy bean meal that are known confounders of several types of research projects. All research using the cynomolgus colony must be reviewed and approved by the colony''s scientific board and the Wake Forest Animal Care and Use Committee (ACUC) before any work can be initiated. The scientific board meets regularly to assess the scientific value of each request and to determine whether or not animals/samples/data can be made available. This includes all requests for: # The purchase of animals for use outside the colony # The use of animals within the colony for the collection of blood/tissue samples, behavioral observations or other kinds of testing # The use of the CBC sample/tissue repository # The use of the CBC data repository
Proper citation: Wake Forest Cynomolgus Breeding Colony (RRID:SCR_006605) 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
THIS RESOURCE IS NO LONGER IN SERVICE, documented on June 23, 2013. Homophila utilizes the sequence information of human disease genes from the NCBI OMIM (Online Mendelian Inheritance in Man) database in order to determine if sequence homologs of these genes exist in the current Drosophila sequence database (FlyBase). Sequences are compared using NCBI's BLAST program. The database is updated weekly and can be searched by human disease, gene name, OMIM number, title, subtitle and/or allelic variant descriptions.
Proper citation: Homophila (RRID:SCR_007717) Copy
http://www.geneatlas.org/gene/main.jsp
This website allows visitors to search for genes of interest based on their spatial expression patterns in the Postnatal Day 7 mouse brain. Geneatlas provides two searching tools: A graphical interface for customized spatial queries; A textual interface for querying annotated structures. Geneatlas is the product of a collaboration between researchers at Baylor College of Medicine, Rice University, and University of Houston.
Proper citation: Gene Atlas (RRID:SCR_008089) Copy
http://www.sci.utah.edu/cibc-software/scirun.html
A Problem Solving Environment (PSE) for modeling, simulation and visualization of scientific problems. SCIRun now includes the biomedical components formally released as BioPSE, as well as BioMesh3D. BioMesh3D is a free, easy to use program for generating quality meshes for the use in biological simulations. The most recent stable release is version 4.6.
Proper citation: SCIRun (RRID:SCR_002541) Copy
A centralized sequence database and community resource for Tribolium genetics, genomics and developmental biology containing genomic sequence scaffolds mapped to 10 linkage groups, genetic linkage maps, the official gene set, Reference Sequences from NCBI (RefSeq), predicted gene models, ESTs and whole-genome tiling array data representing several developmental stages. The current version of Beetlebase is built on the Tribolium castaneum 3.0 Assembly (Tcas 3.0) released by the Human Genome Sequencing Center at the Baylor College of Medicine. The database is constructed using the upgraded Generic Model Organism Database (GMOD) modules. The genomic data is stored in a PostgreSQL relational database using the Chado schema and visualized as tracks in GBrowse. The genetic map is visualized using the comparative genetic map viewer CMAP. To enhance search capabilities, the BLAST search tool has been integrated with the GMOD tools. Tribolium castaneum is a very sophisticated genetic model organism among higher eukaryotes. As the member of a primitive order of holometabolous insects, Coleoptera, Tribolium is in a key phylogenetic position to understand the genetic innovations that accompanied the evolution of higher forms with more complex development. Coleoptera is also the largest and most species diverse of all eukaryotic orders and Tribolium offers the only genetic model for the profusion of medically and economically important species therein. The genome sequences may be downloaded.
Proper citation: BeetleBase (RRID:SCR_001955) Copy
http://www.loni.usc.edu/Software/ShapeTools
Software library that is a collection of Java classes that enable Java programmers to model, manipulate and visualize geometric shapes and associated data values. It simplifies the creation of application programs by providing a ready-made set of support routines. * File format readers that implement ShapeIO interface (modeled after Java ImageIO) are automatically used when appropriate. * Storage of additional metadata of arbitrary type (other than shape vertices and interconnections) is enabled by the use of data attributes. * Shapes may contain a set of child shapes allowing for the construction and manipulation of complex hierarchies of shapes. * The various components of a shape are specified as interfaces with specific implementations, making it easy to create specialized implementations of a shape component when different performance characteristics are required.
Proper citation: LONI ShapeTools (RRID:SCR_002697) Copy
https://doi.org/10.5281/zenodo.592960
Image reconstruction software for MRI. Its library provides common operations on multi-dimensional arrays, Fourier and wavelet transforms, as well as generic implementations of iterative optimization algorithms.
Proper citation: Berkeley Advanced Reconstruction Toolbox (RRID:SCR_016168) 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
http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Atlases
Probabilistic atlases covering 48 cortical and 21 subcortical structural areas, derived from structural data and segmentations kindly provided by the Harvard Center for Morphometric Analysis. T1-weighted images of 21 healthy male and 16 healthy female subjects (ages 18-50) were individually segmented by the CMA using semi-automated tools developed in-house. The T1-weighted images were affine-registered to MNI152 space using FLIRT (FSL), and the transforms then applied to the individual labels. Finally, these were combined across subjects to form population probability maps for each label. Segmentations used to create these atlases were provided by: David Kennedy and Christian Haselgrove, Centre for Morphometric Analysis, Harvard; Bruce Fischl, the Martinos Center for Biomedical Imaging, MGH; Janis Breeze and Jean Frazier from the Child and Adolescent Neuropsychiatric Research Program, Cambridge Health Alliance; Larry Seidman and Jill Goldstein from the Department of Psychiatry of Harvard Medical School.
Proper citation: Harvard - Oxford Cortical Structural Atlas (RRID:SCR_001476) 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.