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.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
Research center aimed towards increasing understanding of basic primate biology and improving human health and quality of life. Its goals include helping discover treatments, preventative measures and cures for human disease; gathering knowledge of primate biology and ecosystems; providing resources to scientists world wide; and collecting and disseminating research to the larger scientific community and public.
Proper citation: Wisconsin National Primate Research Center (RRID:SCR_012987) Copy
http://proteogenomics.musc.edu/ma/musc_madb.php?page=home&act=manage
Database that is a repository for DNA microarray data generated by MUSC investigators as well as researchers in the global research community.
Proper citation: MUSC DNA Microarray Database (RRID:SCR_010977) Copy
http://www.slicer.org/slicerWiki/index.php/Slicer3:Module:Rician_Noise_Removal
Two Slicer3 modules removing rician noise in diffusion tensor MRI
Proper citation: Slicer3 Module Rician noise filter (RRID:SCR_009614) Copy
http://www.loni.usc.edu/Software/BrainParser
Software that uses a novel statistical-learning technique to segment brain regions of interest (ROIs) based on a training set of data and generates 3D MRI volumes. The software comes pre-trained on a provided data set but can be retrained to work with your desired regions of interest.
Proper citation: LONI Brain Parser (RRID:SCR_009572) Copy
http://www.sci.utah.edu/cibc/software/map3d.html
A scientific visualization application written to display and edit complex, three-dimensional geometric models and scalar, time-based data associated with those models such as high resolution EEG, MEG, and ECG.
Proper citation: map3d (RRID:SCR_009628) Copy
http://www.genmapp.org/help_v2/UsingMAPPFinder.htm
MAPPFinder is an accessory program for GenMAPP. This program allows users to query any existing GenMAPP Expression Dataset Criterion against GO gene associations and GenMAPP MAPPs (microarray pathway profiles). The resulting analysis provides the user with results that can be viewed directly upon the Gene Ontology hierarchy and within GenMAPP, by selecting terms or MAPPs of interest. Platform: Windows compatible
Proper citation: MAPPFinder (RRID:SCR_005791) Copy
Software suite for processing magnetoencephalography and electroencephalography data. Open source Python software for exploring, visualizing, and analyzing human neurophysiological data including MEG, EEG, sEEG, ECoG . Implements all functionality of MNE Matlab tools in Python and extends capabilities of MNE Matlab tools to, e.g., frequency-domain and time-frequency analyses and non-parametric statistics.
Proper citation: MNE software (RRID:SCR_005972) Copy
Software tool for identification of cross-linked peptides from mass spectra. Used for analysis of chemically cross-linked protein complexes. Used to analyze both novel and existing data sets.
Proper citation: Kojak (RRID:SCR_021028) Copy
http://emg.nysbc.org/redmine/projects/leginon/wiki/Leginon_Homepage
System designed for automated collection of images from a transmission electron microscope.
Proper citation: Leginon (RRID:SCR_016731) Copy
https://sleepdata.org/datasets/cfs
Portal for family based study of sleep apnea. Contains data for quantifying the familial aggregation of sleep apnea. The polysomnographic (PSG) montage signals: EEG, ECG, EOG, EMG, SpO2, plethysmography, airflow (thermistor), nasal pressure, respiratory effort, position, snore.
Proper citation: Cleveland Family Study (RRID:SCR_016585) Copy
Web tool to search multiple public variant databases simultaneously and provide a unified interface to facilitate the search process. Used for integration of human and model organism genetic resources to facilitate functional annotation of the human genome. Used for analysis of human genes and variants by cross-disciplinary integration of records available in public databases to facilitate clinical diagnosis and basic research.
Proper citation: MARRVEL (RRID:SCR_016871) Copy
https://github.com/fmaguire/Bridger_Assembler
Software package as de novo trascriptome assembler for RNA-Seq data. Framework for de novo transcriptome assembly using RNA-seq data. Can assemble all transcripts from short reads without using reference. Input RNA-Seq reads in fasta or fastq format, and ouput all assembled candidate transcripts in fasta format. Operating system Unix/Linux.
Proper citation: Bridger (RRID:SCR_017039) Copy
https://modbase.compbio.ucsf.edu/foxs/
Web server for computing theoretical scattering profile of structure and fitting of experimental profile. Computes SAXS profile of given atomistic model and fits it to experimental profile. Used for structural modeling applications with small angle X-ray scattering data.
Proper citation: FoXS (RRID:SCR_017269) Copy
http://fit.genomics.lbl.gov/cgi-bin/myFrontPage.cgi
Web tool for browsing genome wide fitness experiments for diverse bacteria from Deutschbauer lab, the Arkin lab, and collaborators. Collection of mutant phenotypes for bacterial genes of unknown function.
Proper citation: Fitness Browser (RRID:SCR_018981) Copy
https://omics.pnl.gov/software/ms-gf
Software that performs peptide identification by scoring MS/MS spectra against peptides derived from a protein sequence database.
Proper citation: MS-GF+ (RRID:SCR_015646) Copy
https://github.com/ABCD-STUDY/redcap-to-nda
Software for metadata-driven electronic data capture to export REDCap data dictionaries and data to the NIMH National Data Archive (NDA). Prepares data submissions as csv formatted spreadsheets for data dictionary spreadsheets and for data spreadsheets.
Proper citation: redcap-to-nda (RRID:SCR_016008) Copy
Biomedical technology research center that conducts, catalyzes and enables multiscale biomedical research, focusing on four key activities: 1) integrating computational, data and visualization resources in a transparent, advanced grid environment to enable better access to distributed data, computational resources, instruments and people; 2) developing and deploying advanced computational tools for modeling and simulation, data analysis, query and integration, three-dimensional image processing and interactive visualization; 3) delivering and supporting advanced grid/cyberinfrastructure for biomedical researchers; and 4) training a cadre of new researchers to have an interdisciplinary, working knowledge of computational technology relevant to biomedical scientists. NBCR enables biomedical scientists to address the challenge of integrating detailed structural measurements from diverse scales of biological organization that range from molecules to organ systems in order to gain quantitative understanding of biological function and phenotypes. Predictive multi-scale models and their driving biological research problems together address issues in modeling of sub-cellular biophysics, building molecular modeling tools to accelerate discovery, and defining tools for patient-specific multi-scale modeling. NBCR furthers these driving problems by developing tools and models based on rapid advances in mathematics and information technology, incorporating them into NBCR pipelines or problem solving environments, and addressing the inevitable changes in the underlying cyber-infrastructure technologies and continually adapting codes over time. Their technology focus integrates both the biological applications and the underlying support software into reproducible science workflows that can function across a number of physical infrastructures.
Proper citation: National Biomedical Computation Resource (RRID:SCR_002656) Copy
Biomedical technology research center that develops computer-aided, advanced microscopy for the acquisition of structural and functional data in the dimensional range of 1 nm to 100 um, a range encompassing macromolecules, subcellular structures and cells. Novel specimen-staining methods, imaging instrumentsincluding intermediate high-voltage transmission electron microscopes (IVEMs) and high-speed, large-format laser-scanning light microscopesand computational capabilities are available for addressing mesoscale biological microscopy of proteins and macromolecular complexes in their cellular and tissue environments. These technologies are developed to bridge understanding of biological systems between the gross anatomical and molecular scales and to make these technologies broadly available to biomedical researchers. NCMIR provides expertise, infrastructure, technological development, and an environment in which new information about the 3D ultrastructure of tissues, cells, and macromolecular complexes may be accurately and easily obtained and analyzed. NCMIR fulfills its mission through technology development, collaboration, service, training, and dissemination. It aims to develop preparative methods and analytical approaches to 3D microscopy applicable to neurobiology and cell biology, incorporating equipment and implementing software that expand the analysis of 3D structure. The core research activities in the areas of specimen development, instrument development, and software infrastructures maximize the advantages of higher voltage electron microscopy and correlated light microscopies to make ambitious imaging studies across scales routine, and to facilitate the use of resources by biomedical researchers. NCMIR actively recruits outside users who will not only make use of these resources, but who also will drive technology development and receive training.
Proper citation: National Center for Microscopy and Imaging Research (RRID:SCR_002655) Copy
Biomedical technology research center and training resource for the study of the structure of partially ordered biological molecules, complexes of biomolecules and cellular structures under conditions similar to those present in living cells and tissues. The goal of research at BioCAT is to determine the detailed structure and mechanism of action of biological systems at the molecular level. The techniques used are X-ray fiber diffraction, X-ray solution scattering and X-ray micro-emission and micro-absorption spectroscopy, with an emphasis on time-resolved studies and the development of novel techniques.
Proper citation: BioCAT (RRID:SCR_001440) 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.