Searching the RRID Resource Information Network

Our searching services are busy right now. Please try again later

  • Register
X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

X

Leaving Community

Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.

No
Yes

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.

Search

Type in a keyword to search

On page 467 showing 9321 ~ 9340 out of 27,030 results
Snippet view Table view Download Top 1000 Results
Click the to add this resource to a Collection

http://www.patika.org/

The human pathway database which contains different biological entities and reactions and software tools for analysis. PATIKA Database integrates data from several sources, including Entrez Gene, UniProt, PubChem, GO, IntAct, HPRD, and Reactome. Users can query and access this data using the PATIKAweb query interface. Users can also save their results in XML or export to common picture formats. The BioPAX and SBML exporters can be used as part of this Web service.

Proper citation: Pathway Analysis Tool for Integration and Knowledge Acquisition (RRID:SCR_002100) Copy   


  • RRID:SCR_004001

    This resource has 1+ mentions.

http://www.asiancancerresearchgroup.org/

An independent, not-for-profit consortium to accelerate research, and improve treatment for patients affected with the most commonly-diagnosed cancers in Asia by generating a genomic data resource for the most prevalent cancers in Asia. ACRG is focusing its initial efforts on Asian liver, gastric and lung cancers. Goals * Generate comprehensive genomics data sets for Asia-prevalent cancers * Conduct all research under good clinical practices and in accordance with local laws * Uncover key mutations and pathways for developing targeted therapies * Discover molecular tumor classifiers for patient stratification * Discover prognostic markers to identify high-risk patients * Freely share resulting raw data with scientific community to empower researchers globally and enable development of new diagnostics and medicines * Publish data analysis results jointly in prominent scientific journals Over the next two years, Lilly, Merck and Pfizer have committed to create an extensive pharmacogenomic cancer database that will be composed of data from approximately 2,000 tissue samples from patients with lung and gastric cancer that will be made publicly available to researchers and, over time, further populated with clinical data from a longitudinal analysis of patients. Comparison of the contrasting genomic signatures of these cancers could inform new approaches to treatment. Lilly has assumed responsibility for ultimately providing the data to the research public through an open-source concept managed by Lilly''''s Singapore research site. Moreover, Lilly, Merck and Pfizer will each provide technical and intellectual expertise. One dataset can be found at http://gigadb.org/dataset/100034

Proper citation: Asian Cancer Research Group (RRID:SCR_004001) Copy   


http://www.nmr.mgh.harvard.edu/DOT/resources/tmcimg/

Software application that uses a Monte Carlo algorithm to model the transport of photons through 3D volumes with spatially varying optical properties. Both highly-scattering tissues (e.g. white matter) and weakly scattering tissues (e.g. cerebral spinal fluid) are supported. Using the anatomical information provided by MRI, X-ray CT, or ultrasound, accurate solutions to the photon migration forward problems are computed in times ranging from minutes to hours, depending on the optical properties and the computing resources available.

Proper citation: Monte Carlo Simulation Software: tMCimg (RRID:SCR_002588) Copy   


  • RRID:SCR_002863

    This resource has 50+ mentions.

http://hcv.lanl.gov/

The Hepatitis C Virus (HCV) Database Project strives to present HCV-associated genetic and immunologic data in a user-friendly way, by providing access to the central database via web-accessible search interfaces and supplying a number of analysis tools.

Proper citation: HCV Databases (RRID:SCR_002863) Copy   


  • RRID:SCR_002862

    This resource has 1+ mentions.

http://code.google.com/p/annotation-ontology/

Provides vocabulary for performing several types of annotation - comment, entities annotation (or semantic tags), textual annotation (classic tags), notes, examples, erratum... - on any kind of electronic document (text, images, audio, tables...) and document parts. AO is not providing any domain ontology but it is fostering the reuse of the existing ones for not breaking the principle of scalability of the Semantic Web.

Proper citation: Annotation Ontology (RRID:SCR_002862) Copy   


http://www.geosamples.org/

Sample Catalog and Registry for the International Geo Sample Number. SESAR catalogs and preserves sample metadata profiles, and provides access to the sample catalog via the Global Sample Search.

Proper citation: System for Earth Sample Registration (RRID:SCR_002222) Copy   


  • RRID:SCR_002464

    This resource has 10+ mentions.

http://abi.inf.uni-tuebingen.de/Services/YLoc/webloc.cgi

An interpretable web server for predicting subcellular localization. In addition to the predicted location, YLoc gives a reasoning why this prediction was made and which biological properties of the protein sequence lead to this prediction. Moreover, a confidence estimate helps users to rate predictions as trustworthy. YLoc+ is able to predict the location of multiple-targeted proteins with high accuracy. The YLoc webserver is also accessible via SOAP.

Proper citation: YLoc (RRID:SCR_002464) Copy   


  • RRID:SCR_003150

    This resource has 10+ mentions.

http://genome.unmc.edu/ngLOC/index.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 5, 2023.An n-gram-based Bayesian classifier that predicts subcellular localization of proteins both in prokaryotes and eukaryotes. The downloadable version of this software with source code is freely available for academic use under the GNU General Public License.

Proper citation: ngLOC (RRID:SCR_003150) Copy   


http://code.google.com/p/opl-ontology/

A reference ontology that models the life cycle stage details of various parasites, including Trypanosoma sp., Leishmania major, and Plasmodium sp., etc. In addition to life cycle stages, the ontology also models necessary contextual details, such as host information, vector information, and anatomical location. OPL is based on the Basic Formal Ontology (BFO) and follows the rules set by the OBO Foundry consortium.

Proper citation: Ontology for Parasite LifeCycle (RRID:SCR_003427) Copy   


http://www.loni.ucla.edu/~thompson/thompson.html

The UCLA laboratory of neuroimaging is working in several areas to enhance knowledge of anatomy, including brain mapping in large human populations, HIV, Schizophrenia, methamphetamine, tumor growth and 4d brain mapping, genetics and detection of abnormalities.

Proper citation: University of California at Los Angeles, School of Medicine: Neuro Imaging Lab of Thompson (RRID:SCR_001924) Copy   


http://nsidc.org/agdc/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 2, 2025. Archives and distributes Antarctic glaciological and cryospheric system data collected by the U.S. Antarctic Program. The Data Catalog contains data sets collected by individual investigators and products assembled from many different PI data sets, published literature, and other sources. The catalog provides useful compilations of important geophysical parameters, such as accumulation rate or ice velocity. The NSF OPP Guidelines and Award Conditions for Scientific Data state that PIs should submit data collected as a result of their OPP grant to a designated data center as soon as possible, but no later than two years after the data are collected.

Proper citation: Antarctic Glaciological Data Center (RRID:SCR_002219) Copy   


https://code.google.com/p/ontology-for-genetic-interval/

An ontology that formalized the genomic element by defining an upper class genetic interval using BFO as its framework. The definition of genetic interval is the spatial continuous physical entity which contains ordered genomic sets (DNA, RNA, Allele, Marker,etc.) between and including two points (Nucleic_Acid_Base_Residue) on a chromosome or RNA molecule which must have a liner primary sequence structure.

Proper citation: Ontology for Genetic Interval (RRID:SCR_003423) Copy   


  • RRID:SCR_003147

    This resource has 10+ mentions.

http://www.morphbank.net/

An NSF supported image repository of over 374,000 high-resolution photographs of approximately 4,000 species for research and education, used largely but not exclusively in the area of biodiversity research. Images can be annotated by users and browsed by specimen, view, taxonomy, location, collection, or annotation.

Proper citation: MorphBank (RRID:SCR_003147) Copy   


  • RRID:SCR_002178

    This resource has 100+ mentions.

https://www.biodiscovery.com/search/node?keys=Imagene

Software tool as convolutional neural network to quantify natural selection from genomic data.Supervised machine learning algorithm to predict natural selection and estimate selection coefficients from population genomic data. Can be used to estimate any parameter of interest from evolutionary population genetics model., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: ImaGene (RRID:SCR_002178) Copy   


  • RRID:SCR_003812

https://peerlibrary.org/

Open source project providing a collaborative layer of knowledge over academic publications by allowing users to share real-time highlights and annotations. Participate in open discussion that drives ideas and academia forward. It provides a supportive space to learn about research and ask questions of peers and experts. Follow authors and other users to understand their perspectives, make connections, and discover new ideas.

Proper citation: PeerLibrary (RRID:SCR_003812) Copy   


  • RRID:SCR_003019

http://sig.biostr.washington.edu/projects/MindSeer/index.html

A cross-platform application for 3D brain visualization for multi-modality neuroimaging data written in Java/Java3D, that runs in both standalone and client-server mode. It supports basic data management capabilities, visualization of 3D surfaces (SPM's output or OFF files), volumes (Analyze, NIFTI or Minc) and label sets. MindSeer has 2 different modes: # Client/Server is designed to allow users to visualize data that is stored centrally and enhance collaboration. # Standalone mode is available to view local data and is built for more performance than Client/Server Both modes have the same interface and support the same features. It has a modular architecture and is designed to be extensible. Requirements: # Java 5.0 or above. # Java Web Start. # Java3D (installed automatically by Web Start).

Proper citation: MindSeer (RRID:SCR_003019) Copy   


  • RRID:SCR_003414

    This resource has 10+ mentions.

http://www.pristionchus.org

This data resource is a genetic, molecular, and genomic toolkit that establishes one particular species, Pristionchus pacificus, as a major satellite system for evolutionary developmental biology. Users may download Pristionchus Sequences and use the Pristionchus pacificus genome browser where they may find gene or gene prediction data. Users can also use the BLAST feature, which allows users to search the assembly for position information of bacs, reads and contigs using the mapping tool. The center of the site's research is the evolutionary analysis of vulva formation. The general aim of the Department is to develop the nematode vulva as a suitable case study into the evolutionary alterations of developmental processes. By studying and comparing two distantly related species of the same phylum, such as P. pacificus and C. elegans, macroevolutionary alterations of developmental processes and mechanisms can be identified. The final goal of the Department is to achieve a comprehensive description of macro- and microevolutionary changes of developmental mechanisms at the molecular level in a phylogenetic and ecological context.

Proper citation: Pristionchus.org (RRID:SCR_003414) Copy   


  • RRID:SCR_002604

    This resource has 1+ mentions.

http://www.nitrc.org/projects/tumorsim/

Simulation software that generates pathological ground truth from a healthy ground truth. The software requires an input directory that describes a healthy anatomy (anatomical probabilities, mesh, diffusion tensor image, etc) and then outputs simulation images.

Proper citation: TumorSim (RRID:SCR_002604) Copy   


  • RRID:SCR_002005

    This resource has 1+ mentions.

http://www.tc.umn.edu/~konox006/Code/SNPMeta/

A Python and BioPython-based tool to generate metadata for single nucleotide polymorphisms (SNPs) for easy filtering, or submission to SNP databases. Information reported includes gene name, whether the SNP is coding or noncoding, and whether the SNP is synonymous or nonsynonymous. SNPMeta outputs in either a dbSNP submission report format, or a tab-delimited format. There is a also Web-based version available that only annotates with default settings, and only annotates a maximum of 20 SNPs at one time. The script may be downloaded for full functionality.

Proper citation: SNPMeta (RRID:SCR_002005) Copy   


  • RRID:SCR_003293

    This resource has 10+ mentions.

http://seer.cancer.gov/resources/

Portal provides SEER research data and software SEER*Stat and SEER*Prep. SEER incidence and population data associated by age, sex, race, year of diagnosis, and geographic areas can be used to examine stage at diagnosis by race/ethnicity, calculate survival by stage at diagnosis, age at diagnosis, and tumor grade or size, determine trends and incidence rates for various cancer sites over time. SEER releases new research data every Spring based on the previous November’s submission of data.

Proper citation: SEER Datasets and Software (RRID:SCR_003293) 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.

Can't find the RRID you're searching for? X
  1. NIDDK Information Network Resources

    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.

  2. Navigation

    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.

  3. Logging in and Registering

    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.

  4. Searching

    Here is the search term that is being executed, you can type in anything you want to search for. Some tips to help searching:

    1. Use quotes around phrases you want to match exactly
    2. You can manually AND and OR terms to change how we search between words
    3. You can add "-" to terms to make sure no results return with that term in them (ex. Cerebellum -CA1)
    4. You can add "+" to terms to require they be in the data
    5. Using autocomplete specifies which branch of our semantics you with to search and can help refine your search
  5. Save Your Search

    You can save any searches you perform for quick access to later from here.

  6. Query Expansion

    We recognized your search term and included synonyms and inferred terms along side your term to help get the data you are looking for.

  7. Collections

    If you are logged into dkNET you can add data records to your collections to create custom spreadsheets across multiple sources of data.

  8. Sources

    Here are the sources that were queried against in your search that you can investigate further.

  9. Categories

    Here are the categories present within dkNET that you can filter your data on

  10. Subcategories

    Here are the subcategories present within this category that you can filter your data on

  11. Further Questions

    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.

X