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| Resource Name | Proper Citation | Abbreviations | Resource Type |
Description |
Keywords | Resource Relationships | |||||||||||||
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Sal-Site Resource Report Resource Website 50+ mentions |
Sal-Site (RRID:SCR_002850) | Sal-Site | data or information resource, topical portal, production service resource, analysis service resource, database, service resource, image collection, data analysis service, portal, organism-related portal | Portal that supports Ambystoma-related research and educational efforts. It is composed of several resources: Salamander Genome Project, Ambystoma EST Database, Ambystoma Gene Collection, Ambystoma Map and Marker Collection, Ambystoma Genetic Stock Center, and Ambystoma Research Coordination Network. | gene, genomic, expressed sequence tag, blast, model organism, genome, salamander, animal model, genetic map, genetic marker, gene expression, limb regeneration, microarray, quantitative-pcr, rna-seq, nanostring, husbandry, embryo, limb, mutant, strain, neural, olfaction, phentotype, regeneration, renal, retina, sequence, vision, human, chicken, xenopus tropicalis, FASEB list | has parent organization: University of Kentucky; Kentucky; USA | NSF OB0242833; NSF DBI0443496; NCRR R24 RR016344; NIH Office of the Director R24 OD010435 |
PMID:16359543 | Free, Freely available | nif-0000-25309 | https://orip.nih.gov/comparative-medicine/programs/vertebrate-models | SCR_002850 | Ambystoma Resources for Model Amphibians Database | 2026-02-17 09:59:52 | 92 | ||||
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Brain Operation Database Resource Report Resource Website |
Brain Operation Database (RRID:SCR_003050) | BODB | data or information resource, database, service resource, storage service resource | THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 4, 2023. BODB offers a way to document computational models of brain function by linking each model to Brain Operating Principles (BOPs), related brain regions, Summaries of Simulation Results (SSRs)and Summaries of Experimental Data (SEDs) used either to design or to test the model. Tools are provided to search for related models and to compare their coverage of SEDs. This allows automatic benchmarking of a model against a cluster of models addressing similar BOPs or SEDs or brain regions. Tools allow display of brain imaging results against a human brain applet; a new tool will link data to a macaque brain applet. | model, brain operating principle, summary of experimental data, summary of simulation results, neural networks, mirror neuron, action, vision, language, usc brain project |
has parent organization: University of Southern California; Los Angeles; USA is parent organization of: Model: Hebbian Mirror Neuron System (H-MNS) (Keysers - Perrett) |
NSF 0924674 | THIS RESOURCE IS NO LONGER IN SERVICE | nif-0000-03080 | http://bodb.usc.edu | SCR_003050 | BODB (Brain Operation DataBase) | 2026-02-17 10:00:10 | 0 | |||||
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GOLEM An interactive, graphical gene-ontology visualization, navigation, and analysis tool Resource Report Resource Website 1+ mentions |
GOLEM An interactive, graphical gene-ontology visualization, navigation, and analysis tool (RRID:SCR_003191) | GOLEM | production service resource, analysis service resource, source code, service resource, software resource, data analysis service | THIS RESOURCE IS NO LONGER IN SERVICE, documented July 7, 2017. Welcome to the home of GOLEM: An interactive, graphical gene-ontology visualization, navigation,and analysis tool on the web. GOLEM is a useful tool which allows the viewer to navigate and explore a local portion of the Gene Ontology (GO) hierarchy. Users can also load annotations for various organisms into the ontology in order to search for particular genes, or to limit the display to show only GO terms relevant to a particular organism, or to quickly search for GO terms enriched in a set of query genes. GOLEM is implemented in Java, and is available both for use on the web as an applet, and for download as a JAR package. A brief tutorial on how to use GOLEM is available both online and in the instructions included in the program. We also have a list of links to libraries used to make GOLEM, as well as the various organizations that curate organism annotations to the ontology. GOLEM is available as a .jar package and a macintosh .app for use on- or off- line as a stand-alone package. You will need to have Java (v.1.5 or greater) installed on your system to run GOLEM. Source code (including Eclipse project files) are also available. GOLEM (Gene Ontology Local Exploration Map)is a visualization and analysis tool for focused exploration of the gene ontology graph. GOLEM allows the user to dynamically expand and focus the local graph structure of the gene ontology hierarchy in the neighborhood of any chosen term. It also supports rapid analysis of an input list of genes to find enriched gene ontology terms. The GOLEM application permits the user either to utilize local gene ontology and annotations files in the absence of an Internet connection, or to access the most recent ontology and annotation information from the gene ontology webpage. GOLEM supports global and organism-specific searches by gene ontology term name, gene ontology id and gene name. CONCLUSION: GOLEM is a useful software tool for biologists interested in visualizing the local directed acyclic graph structure of the gene ontology hierarchy and searching for gene ontology terms enriched in genes of interest. It is freely available both as an application and as an applet. | gene ontology, ontology visualization, ontology analysis |
is related to: Gene Ontology has parent organization: Princeton University; New Jersey; USA |
NIGMS R01 GM071966; NSF IIS-0513552; NIGMS P50 GM071508 |
PMID:17032457 | THIS RESOURCE IS NO LONGER IN SERVICE | nif-0000-30620 | https://lsi.princeton.edu/golem-interactive-graph-based-gene-ontology-navigation-and-analysis-tool | SCR_003191 | GOLEM An interactive graphical gene-ontology visualization navigation and analysis tool, GOLEM An interactive graphical gene-ontology visualization navigation analysis tool | 2026-02-17 10:00:11 | 3 | ||||
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NLSdb: a database of nuclear localization signals Resource Report Resource Website 1+ mentions |
NLSdb: a database of nuclear localization signals (RRID:SCR_003273) | NLSdb | data or information resource, production service resource, analysis service resource, database, service resource, data analysis service | A database of nuclear localization signals (NLSs) and of nuclear proteins targeted to the nucleus by NLS motifs. NLSs are short stretches of residues mediating transport of nuclear proteins into the nucleus. The database contains 114 experimentally determined NLSs that were obtained through an extensive literature search. Using "in silico mutagenesis" this set was extended to 308 experimental and potential NLSs. This final set matched over 43% of all known nuclear proteins and matches no currently known non-nuclear protein. NLSdb contains over 6000 predicted nuclear proteins and their targeting signals from the PDB and SWISS-PROT/TrEMBL databases. The database also contains over 12 500 predicted nuclear proteins from six entirely sequenced eukaryotic proteomes (Homo sapiens, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans, Arabidopsis thaliana and Saccharomyces cerevisiae). NLS motifs often co-localize with DNA-binding regions. This observation was used to also annotate over 1500 DNA-binding proteins. From this site you can: * Query NLSdb * Find out how to use NLSdb * Browse the entries in NLSdb * Find out if your protein has an NLS using PredictNLS * Predict subcellular localization of your protein using LOCtree | nuclear localization signal, nuclear protein, nucleus, motif, predict, protein | has parent organization: Columbia University; New York; USA | NIGMS 1-P50-GM62413-01; NSF DBI-0131168 |
PMID:12520032 | Free for academic use, Acknowledgement requested, All others should inquire about a commercial license | nif-0000-03191 | http://cubic.bioc.columbia.edu/db/NLSdb/ | SCR_003273 | NLSdb - a database of nuclear localization signals | 2026-02-17 09:59:58 | 4 | ||||
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Protege Resource Report Resource Website 100+ mentions |
Protege (RRID:SCR_003299) | Protege | software application, authoring tool, software resource | Protege is a free, open-source platform that provides a growing user community with a suite of tools to construct domain models and knowledge-based applications with ontologies. At its core, Protege implements a rich set of knowledge-modeling structures and actions that support the creation, visualization, and manipulation of ontologies in various representation formats. Protege can be customized to provide domain-friendly support for creating knowledge models and entering data. Further, Protege can be extended by way of a plug-in architecture and a Java-based Application Programming Interface (API) for building knowledge-based tools and applications. An ontology describes the concepts and relationships that are important in a particular domain, providing a vocabulary for that domain as well as a computerized specification of the meaning of terms used in the vocabulary. Ontologies range from taxonomies and classifications, database schemas, to fully axiomatized theories. In recent years, ontologies have been adopted in many business and scientific communities as a way to share, reuse and process domain knowledge. Ontologies are now central to many applications such as scientific knowledge portals, information management and integration systems, electronic commerce, and semantic web services. The Protege platform supports two main ways of modeling ontologies: * The Protege-Frames editor enables users to build and populate ontologies that are frame-based, in accordance with the Open Knowledge Base Connectivity protocol (OKBC). In this model, an ontology consists of a set of classes organized in a subsumption hierarchy to represent a domain's salient concepts, a set of slots associated to classes to describe their properties and relationships, and a set of instances of those classes - individual exemplars of the concepts that hold specific values for their properties. * The Protege-OWL editor enables users to build ontologies for the Semantic Web, in particular in the W3C's Web Ontology Language (OWL). An OWL ontology may include descriptions of classes, properties and their instances. Given such an ontology, the OWL formal semantics specifies how to derive its logical consequences, i.e. facts not literally present in the ontology, but entailed by the semantics. These entailments may be based on a single document or multiple distributed documents that have been combined using defined OWL mechanisms (see the OWL Web Ontology Language Guide). Protege is based on Java, is extensible, and provides a plug-and-play environment that makes it a flexible base for rapid prototyping and application development. | ontology, java, develop, manage, edit, plug-in, FASEB list |
is listed by: Biositemaps is related to: National Center for Biomedical Ontology is related to: Jambalaya has parent organization: Stanford University School of Medicine; California; USA has parent organization: Stanford Center for Biomedical Informatics Research |
Defense Advanced Research Projects Agency ; eBay ; NCI ; NIST - National Institute of Standards and Technology ; National Centers for Biomedical Computing ; NSF ; Neural ElectroMagnetic Ontologies NEMO ; Pfizer ; NLM LM007885 |
PMID:17687607 | Free, download Freely available | nif-0000-31708 | SCR_003299 | Protégé, Protege Project | 2026-02-17 10:00:14 | 147 | |||||
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PIRSF Resource Report Resource Website 10+ mentions |
PIRSF (RRID:SCR_003352) | PIRSF | data or information resource, narrative resource, standard specification, database | A SuperFamily classification system, with rules for functional site and protein name, to facilitate the sensible propagation and standardization of protein annotation and the systematic detection of annotation errors. The PIRSF concept is being used as a guiding principle to provide comprehensive and non-overlapping clustering of UniProtKB sequences into a hierarchical order to reflect their evolutionary relationships. The PIRSF classification system is based on whole proteins rather than on the component domains; therefore, it allows annotation of generic biochemical and specific biological functions, as well as classification of proteins without well-defined domains. There are different PIRSF classification levels. The primary level is the homeomorphic family, whose members are both homologous (evolved from a common ancestor) and homeomorphic (sharing full-length sequence similarity and a common domain architecture). At a lower level are the subfamilies which are clusters representing functional specialization and/or domain architecture variation within the family. Above the homeomorphic level there may be parent superfamilies that connect distantly related families and orphan proteins based on common domains. Because proteins can belong to more than one domain superfamily, the PIRSF structure is formally a network. The FTP site provides free download for PIRSF. | protein annotation, classification, protein, superfamily, functional site, protein name, bio.tools |
is listed by: OMICtools is listed by: bio.tools is listed by: Debian is related to: UniProtKB has parent organization: Protein Information Resource |
NHGRI U01-HG02712; NSF DBI-0138188; NSF ITR-0205470 |
PMID:19455212 PMID:14681371 |
Free, Freely available | biotools:pirsf, nif-0000-03294, OMICS_01697 | https://bio.tools/pirsf | http://pir.georgetown.edu/pirsf/ | SCR_003352 | PIR SuperFamily, Protein Information Resource SuperFamily | 2026-02-17 09:59:59 | 28 | |||
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MouseNET Resource Report Resource Website 1+ mentions |
MouseNET (RRID:SCR_003357) | mouseNet | data or information resource, production service resource, analysis service resource, database, service resource, data analysis service | A functional network for laboratory mouse based on integration of diverse genetic and genomic data. It allows the users to accurately predict novel functional assignments and network components. MouseNET uses a probabilistic Bayesian algorithm to identify genes that are most likely to be in the same pathway/functional neighborhood as your genes of interest. It then displays biological network for the resulting genes as a graph. The nodes in the graph are genes (clicking on each node will bring up SGD page for that gene) and edges are interactions (clicking on each edge will show evidence used to predict this interaction). Most likely, the first results to load on the results page will be a list of significant Gene Ontology terms. This list is calculated for the genes in the biological network created by the mouseNET algorithm. If a gene ontology term appears on this list with a low p-value, it is statistically significantly overrepresented in this biological network. The graph may be explored further. As you move the mouse over genes in the network, interactions involving these genes are highlighted.If you click on any of the highlighted interactions graph, evidence pop-up window will appear. The Evidence pop-up lists all evidence for this interaction, with links to the papers that produced this evidence - clicking these links will bring up the relevant source citation(s) in PubMed. | gene, network, mouse, protein function, visualization, open reading frame, graph |
is listed by: OMICtools is related to: Gene Ontology is related to: mouseMAP has parent organization: Princeton University; New Jersey; USA |
NSF DBI-0546275; NIGMS R01 GM071966; NSF IIS-0513552; NIGMS P50 GM071508 |
PMID:18818725 | Free, Freely available | OMICS_01550, nif-0000-32003 | SCR_003357 | MouseNET | 2026-02-17 10:00:17 | 3 | |||||
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Structural Biology Grid Resource Report Resource Website 50+ mentions |
Structural Biology Grid (RRID:SCR_003511) | SBGrid | storage service resource, data or information resource, computational hosting, service resource, data set, data repository | Computing resources structural biologists need to discover the shapes of the molecules of life, it provides access to web-enabled structural biology applications, data sharing facilities, biological data sets, and other resources valuable to the computational structural biology community. Consortium includes X-ray crystallography, NMR and electron microscopy laboratories worldwide.SBGrid Service Center is located at Harvard Medical School.SBGrid's NIH-compliant Service Center supports SBGrid operations and provides members with access to Software Maintenance, Computing Access, and Training. Consortium benefits include: * remote management of your customized collection of structural biology applications on Linux and Mac workstations; * access to commercial applications exclusively licensed to members of the Consortium, such as NMRPipe, Schrodinger Suite (limited tokens) and the Incentive version of Pymol; remote management of supporting scientific applications (e.g., bioinformatics, computational chemistry and utilities); * access to SBGrid seminars and events; and * advice about hardware configurations, operating system installations and high performance computing. Membership is restricted to academic/non-profit research laboratories that use X-ray crystallography, 2D crystallography, NMR, EM, tomography and other experimental structural biology technologies in their research. Most new members are fully integrated with SBGrid within 2 weeks of the initial application. | structure, x-ray crystallography, nuclear magnetic resonance, electron microscopy, structural biology, software application, computation, chemistry, meeting, software service, molecule, data sharing, biomedical |
is recommended by: NIDDK Information Network (dkNET) is recommended by: NIDDK - National Institute of Diabetes and Digestive and Kidney Diseases has parent organization: Harvard Medical School; Massachusetts; USA |
NSF | PMID:22514186 | Membership is restricted to academic/non-profit research laboratories that use X-ray crystallography, 2D crystallography, NMR, EM, Tomography and other experimental structural biology technologies in their research., The community can contribute to this resource | nif-0000-37641, r3d100010234 | https://doi.org/10.17616/R3NS3R | http://sbgrid.org/index.php | SCR_003511 | SBGrid Software Consortium, SBGrid Science Portal, SBGrid Consortium | 2026-02-17 10:00:01 | 56 | |||
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Statistics Online Computational Resource Resource Report Resource Website 10+ mentions |
Statistics Online Computational Resource (RRID:SCR_003378) | SOCR | narrative resource, software application, data or information resource, training material, software resource, software toolkit | A hierarchy of portable online interactive aids for motivating, modernizing probability and statistics applications. The tools and resources include a repository of interactive applets, computational and graphing tools, instructional and course materials. The core SOCR educational and computational components include the following suite of web-based Java applets: * Distributions (interactive graphs and calculators) * Experiments (virtual computer-generated games and processes) * Analyses (collection of common web-accessible tools for statistical data analysis) * Games (interfaces and simulations to real-life processes) * Modeler (tools for distribution, polynomial and spectral model-fitting and simulation) * Graphs, Plots and Charts (comprehensive web-based tools for exploratory data analysis), * Additional Tools (other statistical tools and resources) * SOCR Java-based Statistical Computing Libraries * SOCR Wiki (collaborative Wiki resource) * Educational Materials and Hands-on Activities (varieties of SOCR educational materials), * SOCR Statistical Consulting In addition, SOCR provides a suite of tools for volume-based statistical mapping (http://wiki.stat.ucla.edu/socr/index.php/SOCR_EduMaterials_AnalysesCommandLine) via command-line execution and via the LONI Pipeline workflows (http://www.nitrc.org/projects/pipeline). Course instructors and teachers will find the SOCR class notes and interactive tools useful for student motivation, concept demonstrations and for enhancing their technology based pedagogical approaches to any study of variation and uncertainty. Students and trainees may find the SOCR class notes, analyses, computational and graphing tools extremely useful in their learning/practicing pursuits. Model developers, software programmers and other engineering, biomedical and applied researchers may find the light-weight plug-in oriented SOCR computational libraries and infrastructure useful in their algorithm designs and research efforts. The three types of SOCR resources are: * Interactive Java applets: these include a number of different applets, simulations, demonstrations, virtual experiments, tools for data visualization and analysis, etc. All applets require a Java-enabled browser (if you see a blank screen, see the SOCR Feedback to find out how to configure your browser). * Instructional Resources: these include data, electronic textbooks, tutorials, etc. * Learning Activities: these include various interactive hands-on activities. * SOCR Video Tutorials (including general and tool-specific screencasts). | probability, statistics, instruction, statistical computing, applet, computational tool, graphing tool, course material, computation, java, statistical mapping, graphing, computational neuroscience, java, loni pipeline, educator, student, tool developer |
is listed by: NeuroImaging Tools and Resources Collaboratory (NITRC) is listed by: Biositemaps has parent organization: University of California at Los Angeles; California; USA |
NIH Roadmap for Medical Research ; NSF 0442992; NSF DUE 0716055; NSF 1023115; NCRR U54 RR021813 |
PMID:21451741 PMID:21297884 |
Free, Freely available | nif-0000-32655 | http://www.nitrc.org/projects/socr | SCR_003378 | 2026-02-17 10:00:09 | 13 | |||||
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Michigan Molecular Interactions Resource Report Resource Website 1+ mentions |
Michigan Molecular Interactions (RRID:SCR_003521) | MiMI | data access protocol, data or information resource, production service resource, analysis service resource, database, service resource, software resource, web service, data analysis service | MiMi Web gives you an easy to use interface to a rich NCIBI data repository for conducting your systems biology analyses. This repository includes the MiMI database, PubMed resources updated nightly, and text mined from biomedical research literature. The MiMI database comprehensively includes protein interaction information that has been integrated and merged from diverse protein interaction databases and other biological sources. With MiMI, you get one point of entry for querying, exploring, and analyzing all these data. MiMI provides access to the knowledge and data merged and integrated from numerous protein interactions databases and augments this information from many other biological sources. MiMI merges data from these sources with deep integration into its single database with one point of entry for querying, exploring, and analyzing all these data. MiMI allows you to query all data, whether corroborative or contradictory, and specify which sources to utilize. MiMI displays results of your queries in easy-to-browse interfaces and provides you with workspaces to explore and analyze the results. Among these workspaces is an interactive network of protein-protein interactions displayed in Cytoscape and accessed through MiMI via a MiMI Cytoscape plug-in. MiMI gives you access to more information than you can get from any one protein interaction source such as: * Vetted data on genes, attributes, interactions, literature citations, compounds, and annotated text extracts through natural language processing (NLP) * Linkouts to integrated NCIBI tools to: analyze overrepresented MeSH terms for genes of interest, read additional NLP-mined text passages, and explore interactive graphics of networks of interactions * Linkouts to PubMed and NCIBI's MiSearch interface to PubMed for better relevance rankings * Querying by keywords, genes, lists or interactions * Provenance tracking * Quick views of missing information across databases. Data Sources include: BIND, BioGRID, CCSB at Harvard, cPath, DIP, GO (Gene Ontology), HPRD, IntAct, InterPro, IPI, KEGG, Max Delbreuck Center, MiBLAST, NCBI Gene, Organelle DB, OrthoMCL DB, PFam, ProtoNet, PubMed, PubMed NLP Mining, Reactome, MINT, and Finley Lab. The data integration service is supplied under the conditions of the original data sources and the specific terms of use for MiMI. Access to this website is provided free of charge. The MiMI data is queryable through a web services api. The MiMI data is available in PSI-MITAB Format. These files represent a subset of the data available in MiMI. Only UniProt and RefSeq identifiers are included for each interactor, pathways and metabolomics data is not included, and provenance is not included for each interaction. If you need access to the full MiMI dataset please send an email to mimi-help (at) umich.edu. | gene, interaction, molecule, protein, protein interaction, protein-protein interaction |
is related to: MiMI Plugin for Cytoscape has parent organization: National Center for Integrative Biomedical Informatics |
Michigan Center for Biological Information ; National Center for Integrative Biomedical Informatics ; Pfizer ; Medical and Academic Partnerships ; Howard Hughes Medical Institute ; Microsoft Corporation ; NLM R01 LM008106; NIDA U54 DA021519; NSF IIS 0219513 |
PMID:18978014 PMID:17130145 |
nif-0000-00214 | SCR_003521 | 2026-02-17 10:00:12 | 5 | |||||||
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Karma Resource Report Resource Website 50+ mentions |
Karma (RRID:SCR_003732) | Karma | data management software, software application, software resource | An information integration software tool that enables users to integrate data from a variety of data sources including databases, spreadsheets, delimited text files, XML, JSON, KML and Web APIs. Users integrate information by modeling it according to an ontology of their choice using a graphical user interface that automates much of the process. Karma learns to recognize the mapping of data to ontology classes and then uses the ontology to propose a model that ties together these classes. Users then interact with the system to adjust the automatically generated model. During this process, users can transform the data as needed to normalize data expressed in different formats and to restructure it. Once the model is complete, users can publish the integrated data as RDF or store it in a database. | integration, FASEB list |
is related to: GitHub has parent organization: University of Southern California; Los Angeles; USA |
Air Force Research Laboratory FA8750-14-C-0240; NCRR 1 U24 RR025736-01; NCRR 1 UL1 RR031986-01; NSF IIS-1117913; NSF CMMI-0753124 |
PMID:15215426 | Apache License, v2 | nlx_157923 | https://github.com/InformationIntegrationGroup/Web-Karma | SCR_003732 | Karma A Data Integration Tool, Karma - A Data Integration Tool | 2026-02-17 10:00:05 | 83 | ||||
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GREAT: Genomic Regions Enrichment of Annotations Tool Resource Report Resource Website 50+ mentions |
GREAT: Genomic Regions Enrichment of Annotations Tool (RRID:SCR_005807) | GREAT | production service resource, analysis service resource, source code, service resource, software resource, data analysis service | Data analysis service that predicts functions of cis-regulatory regions identified by localized measurements of DNA binding events across an entire genome. Whereas previous methods took into account only binding proximal to genes, GREAT is able to properly incorporate distal binding sites and control for false positives using a binomial test over the input genomic regions. GREAT incorporates annotations from 20 ontologies and is available as a web application. The utility of GREAT extends to data generated for transcription-associated factors, open chromatin, localized epigenomic markers and similar functional data sets, and comparative genomics sets. Platform: Online tool | term enrichment, cis-regulatory region, function, gene, genomic, annotation, ontology, chromatin immunoprecipitation, sequencing, chip-seq, comparative genomics, transcription factor binding |
is listed by: Gene Ontology Tools is listed by: OMICtools is related to: PRISM (Stanford database) is related to: Gene Ontology has parent organization: Stanford University School of Medicine; California; USA |
Bio-X ; Howard Hughes Medical Institute ; Stanford University; California; USA ; Packard ; Searle Scholar ; Microsoft Research ; Alfred P. Sloan Foundation ; Edward Mallinckrodt Jr. Foundation ; NIH ; Human Frontier Science Program fellowship LT000896/2009-l; NICHD 1R01HD059862; NHGRI R01HG005058; NSF CCF-0939370; DFG Hi 1423/2-1 |
PMID:20436461 PMID:23814184 |
Free for academic use, Acknowledgement requested | nlx_149295, OMICS_00635 | SCR_005807 | Genomic Regions Enrichment of Annotations Tool (GREAT), Genomic Regions Enrichment of Annotations Tool | 2026-02-17 10:00:49 | 82 | |||||
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UM-BBD Resource Report Resource Website 1+ mentions |
UM-BBD (RRID:SCR_005787) | UM-BBD, UM-BBD enzymeID, UM-BBD pathwayID, UM-BBD reactionID, UM-BBD ruleID | data or information resource, production service resource, analysis service resource, database, service resource, data analysis service, data set | THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 27, 2014. Database containing information on microbial biocatalytic reactions and biodegradation pathways for primarily xenobiotic, chemical compounds. Its goal is to provide information on microbial enzyme-catalyzed reactions that are important for biotechnology. The reactions covered are studied for basic understanding of nature, biocatalysis leading to specialty chemical manufacture, and biodegradation of environmental pollutants. Individual reactions and metabolic pathways are presented with information on the starting and intermediate chemical compounds, the organisms that transform the compounds, the enzymes, and the genes. The present database has been successfully used to teach enzymology and use of biochemical Internet information resources to advanced undergraduate and graduate students, and is being expanded primarily with the help of such students. In addition to reactions and pathways, this database also contains Biochemical Periodic Tables and a Pathway Prediction System. * Search the UM-BBD for compound, enzyme, microorganism, pathway, or BT rule name; chemical formula; chemical structure; CAS Registry Number; or EC code. * Go to Pathways and Metapathways in the UM-BBD * Lists of 203 pathways; 1400 reactions; 1296 compounds; 916 enzymes; 510 microorganism entries; 245 biotransformation rules; 50 organic functional groups; 76 reactions of naphthalene 1,2-dioxygenase; 109 reactions of toluene dioxygenase; Graphical UM-BBD Overview; and Other Graphics (Metapathway and Pathway Maps and Reaction Mechanisms). | enzyme, biocatalysis, biodegredation, chemical, pathway, reaction, microorganism, image, chemical compound, gene, enzymology | has parent organization: University of Minnesota Twin Cities; Minnesota; USA | Minnesota Supercomputing Institute ; Lhasa Limited ; University of Minnesota; Minnesota; USA ; European Union FP6 ALARM project ; NIH ; NSF 0543416; DOE DE-FG02-01ER63268; NIGMS R01GM56529; NSF 9630427 |
PMID:19767608 PMID:16381924 PMID:12519997 |
THIS RESOURCE IS NO LONGER IN SERVICE | nif-0000-03607, r3d100011317 | https://doi.org/10.17616/R33D0V | SCR_005787 | UM-BBD pathwayID, University of Minnesota Biocatalysis and Biodegradation Database, UM-BBD reactionID, Biocatalysis/Biodegradation Database, University of Minnesota Biocatalysis/Biodegradation Database, UM-BBD ruleID, Univeristy of Minnesota Biocatalysis/Biodegradation Database, UM-BBD enzymeID | 2026-02-17 10:00:57 | 9 | ||||
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UCSC Genome Browser Resource Report Resource Website 10000+ mentions Rating or validation data |
UCSC Genome Browser (RRID:SCR_005780) | data or information resource, project portal, database, service resource, portal | Portal to interactively visualize genomic data. Provides reference sequences and working draft assemblies for collection of genomes and access to ENCODE and Neanderthal projects. Includes collection of vertebrate and model organism assemblies and annotations, along with suite of tools for viewing, analyzing and downloading data. | Reference, sequence, assembly, collection, genome, visualize, genomic, data, ENCODE, Neanderthal, project, sequencing |
is used by: VizHub is used by: Blueprint Epigenome is used by: QmRLFS-finder is used by: International Human Epigenome Consortium Data Portal is used by: iPiG is listed by: re3data.org is listed by: OMICtools is listed by: Educational Resources in Neuroscience is listed by: SoftCite is related to: HEXEvent is related to: PicTar is related to: Phenotree is related to: Enhancer Trap Line Browser is related to: CistromeFinder is related to: ENCODE is related to: Human Epigenome Atlas is related to: ENCODE is related to: BigWig and BigBed is related to: PhenCode is related to: doRiNA is related to: ISCA Consortium is related to: WashU Epigenome Browser is related to: CRISPOR is related to: liftOver is related to: kent has parent organization: University of California at Santa Cruz; California; USA works with: TarBase |
UC BIOTEuropean UnionH ; Alfred P. Sloan Foundation ; David and Lucille Packard Foundation ; NIH ; HHMI ; CISI ; NHGRI ; DOE ; NSF DBI 9809007; NIGMS GM52848 |
PMID:12045153 PMID:22908213 PMID:23155063 |
OMICS_00926, SCR_017502, nif-0000-03603, SciEx_217, SCR_012479, r3d100010243 | http://genome.cse.ucsc.edu https://doi.org/10.17616/R3RK5C |
SCR_005780 | The Human Genome Browser at UCSC, UCSC Genome Browser Group, University of California at Santa Cruz Genome Browser, UCSC Genome Bioinformatics | 2026-02-17 10:00:39 | 10026 | ||||||
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OMGN Resource Report Resource Website |
OMGN (RRID:SCR_005781) | OMGN | data or information resource, portal, community building portal, training resource | The Oomycete Molecular Genetics Research Collaboration Network (OMGN) is a network for research collaboration for investigators interested in oomycete molecular genetics and genomics. The goals of the OMGN is to facilitate the integration of these investigators into the community and to further strengthen the cooperative culture of this community. A particular emphasis is placed on training and integrating junior faculty and faculty from institutions under-represented in the U.S. research infrastructure. Because of their economic impact as plant pathogens, molecular, genetic and genomics studies are well advanced in many oomycete species. These organisms have served as lead species for the entire Stramenopiles lineage, a major radiation of crown eukaryotes, distinct from plants, animals and fungi. The oomycete molecular genetics community has a strong culture of collaboration and communication, and sharing of techniques and resources. With the recent blossoming of genetic and genomic tools for oomycetes, many new investigators, from a variety of backgrounds, have become interested in oomycete molecular genetics and genomics. The proposed network is open to all researchers with an interest in oomycete molecular genetics and genomics, either at an experimental or a computational level. Investigators new to the field are always welcome, especially those interested in saprophytes and animal pathogens. Goals of OMGN # Provide training to o��mycete molecular genetics researchers, especially those from smaller institutions, in the use of bioinformatics and genomics resources. # Promote the entry, participation and training of new investigators into the field of o��mycete genomics, particularly junior faculty and faculty from institutions under-represented in the U.S. research infrastructure. # Promote communication and collaboration, and minimize duplication of effort, within the worldwide o��mycete genomics community. # Support an O��mycete Genomics Resources Center to maintain and distribute training and research materials produced by community genomics projects. The network''s activities have been supported by two grants from the NSF Research Collaboration Networks in Biology program. | oomycete, molecular genetics, genomics, saprophyte, animal, pathogen, stramenopile | has parent organization: Virginia Polytechnic Institute and State University; Virginia; USA | NSF EF 0130263 | nlx_149251 | SCR_005781 | OMGN - Oomycete Molecular Genetics Research Collaboration Network, Oomycete Molecular Genetics Research Collaboration Network | 2026-02-17 10:01:00 | 0 | |||||||
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GOfetcher Resource Report Resource Website |
GOfetcher (RRID:SCR_005681) | GOfetcher | data or information resource, production service resource, analysis service resource, database, service resource, data analysis service | THIS RESOURCE IS NO LONGER IN SERVICE, documented on June 29, 2012. We developed a web application, GOfetcher, with a very comprehensive search facility for the GO project and a variety of output formats for the results. GOfetcher has three different levels for searching the GO: Quick Search, Advanced Search, and Upload Files for searching. The application includes a unique search option which generates gene information given a nucleotide or protein accession number which can then be used in generating gene ontology information. The output data in GOfetcher can be saved into several different formats; including spreadsheet, comma-separated values, and the Extensible Markup Language (XML) format. Platform: Online tool | gene, nucleotide, protein, ontology, ontology or annotation browser |
is listed by: Gene Ontology Tools is related to: Gene Ontology has parent organization: University of Southern Mississippi; Mississippi; USA |
NSF EPS-0556308; U.S. Army ; Environmental Quality Program contract #W912HZ-05-P-0145 |
PMID:18728045 | THIS RESOURCE IS NO LONGER IN SERVICE | nlx_149124 | http://mcbc.usm.edu/gofetcher/ | SCR_005681 | GOfetcher: a database with complex searching facility for gene ontology | 2026-02-17 10:00:37 | 0 | ||||
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Viking Viewer for Connectomics Resource Report Resource Website 10+ mentions |
Viking Viewer for Connectomics (RRID:SCR_005986) | data management software, software application, collaboration tool, data processing software, software resource | A web-compliant application that allows connectomics visualization by converting datasets to web-optimized tiles, delivering volume transforms to client devices, and providing groups of users with connectome annotation tools and data simultaneously via conventional internet connections. Viking is an extensible tool for connectomics analysis and is generalizable to histomics applications. | annotation, 2d image, microscopy image, volume, serial section, 3d reconstruction, segmentation, microscopy, visualization, optical imaging, connectomics, synapse, retina, brain |
is listed by: NeuroImaging Tools and Resources Collaboratory (NITRC) is listed by: 3DVC has parent organization: University of Utah; Utah; USA |
Research to Prevent Blindness ; University of Utah; Utah; USA ; Graduate Research Fellowship ; Utah Science Technology and Research Initiative ; NEI R01 EY02576; NEI R01 EY015128; NEI P01 EY014800; NSF 0941717; NIDCD T32DC008553; NIBIB EB005832 |
PMID:21118201 | Open source | nlx_151360 | http://www.nitrc.org/projects/viking_viewer | SCR_005986 | Viking, Viking Connectome Annotation System, Viking Annotation System | 2026-02-17 10:00:59 | 14 | |||||
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crowdLabs Resource Report Resource Website 1+ mentions |
crowdLabs (RRID:SCR_006294) | crowdLabs | community building portal, storage service resource, data or information resource, production service resource, analysis service resource, service resource, data analysis service, portal | A social visualization repository for the scientific workflow management system VisTrails providing a platform for sharing and executing computational tasks. It adopts the model used by social Web sites and that integrates a set of usable tools and a scalable infrastructure to provide an environment for scientists to collaboratively analyze and visualize data. crowdLabs aims to foster collaboration but was specifically designed to support the needs of computational scientists, including the ability to access high-performance computers and manipulate large volumes of data. By providing mechanisms that simplify the publishing and use of analysis pipelines, it allows IT personnel and end users to collaboratively construct and refine portals. This lowers the barriers for the use of scientific analyses and enables broader audiences to contribute insights to the scientific exploration process, without the high costs incurred by traditional portals. In addition, it supports a more dynamic environment where new exploratory analyses can be added on-the-fly. | platform, computation, data sharing |
is listed by: FORCE11 is related to: VisTrails |
NSF | nif-0000-06716 | http://www.force11.org/node/4666 | SCR_006294 | crowd Labs | 2026-02-17 10:00:49 | 1 | ||||||
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PHYLIP Resource Report Resource Website 1000+ mentions |
PHYLIP (RRID:SCR_006244) | PHYLIP | software application, source code, software resource, data processing software | A free package of software programs for inferring phylogenies (evolutionary trees). The source code is distributed (in C), and executables are also distributed. In particular, already-compiled executables are available for Windows (95/98/NT/2000/me/xp/Vista), Mac OS X, and Linux systems. Older executables are also available for Mac OS 8 or 9 systems. | phylogeny prediction, evolutionary tree, bio.tools |
is listed by: bio.tools is listed by: Debian is listed by: OMICtools is listed by: SoftCite has parent organization: University of Washington; Seattle; USA works with: PAML |
NSF ; NIGMS ; DOE |
Free | nif-0000-06708, OMICS_04240, biotools:phylip | https://bio.tools/phylip https://sources.debian.org/src/phylip/ |
SCR_006244 | PHYLogeny Inference Package | 2026-02-17 10:00:53 | 3519 | |||||
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Guppy Project Resource Report Resource Website 1+ mentions |
Guppy Project (RRID:SCR_006255) | Guppy Project | data or information resource, topical portal, video resource, portal, organism-related portal | A project that observes the processes of adaptive evolution in nature, and tests evolutionary hypotheses, by studying populations of guppies on the Caribbean island of Trinidad. Darwin thought that evolution by natural selection occurred very slowly, over hundreds if not thousands of years. Evolutionary biologists now know that evolutionary changes in species can happen very quickly, over a relatively few generations. The National Science Foundation (NSF), through its Integrative Biological Research (FIBR) program, is funding a 5-year study by 13 biologists from colleges, universities, and research institutions throughout the United States and Canada, to study the relationship of adaptive evolution and environmental circumstances. The Trinidadian guppy (Poecilia reticulata) is an excellent species for these purposes because: * It matures rapidly (one generation = 3-4 months) * It inhabits different ecological environments that can be easily manipulated On Trinidad, guppies live in streams, or portions of streams, that can differ in the species of predators that the guppies have to contend with. Some streams are high-predation environments, others low-predation. Different predation environments are often right next to one another, separated by a waterfall (which neither guppies nor predators can cross). Guppies from high-predation environments experience much higher mortality rates than do guppies in low-predation environments. High mortality is associated with the following characteristics, all of which have a genetic basis: * Earlier maturity * Greater investment of resources in reproduction * More and smaller offspring. We have found that mortality rates can be manipulated by: * Transplanting guppies from high-predation localities into sites from which they and their predators had previously been excluded by natural waterfalls, thus lowering mortality rates; * Introducing predators into low-predation sites, thus increasing mortality rates. Such experiments have shown that species evolve as predicted by theory. We have also found that evolution by natural selection can be remarkably fast, on the order of four to seven orders of magnitude faster than had been inferred from the fossil record. | adaption, evolution, adaptive evolution, environment, trinidadian guppy, poecilia reticulata, image, natural selection | has parent organization: University of California at Riverside; California; USA | NSF | nlx_151840 | SCR_006255 | 2026-02-17 10:00:54 | 6 |
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