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| Resource Name | Proper Citation | Abbreviations | Resource Type |
Description |
Keywords | Resource Relationships | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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MolProbity Resource Report Resource Website 5000+ mentions |
MolProbity (RRID:SCR_014226) | web application, software resource | A structure-validation web application which provides an expert-system consultation about the accuracy of a macromolecular structure model, diagnosing local problems and enabling their correction. MolProbity works best as an active validation tool (used as soon as a model is available and during each rebuild/refine loop) and when used for protein and RNA crystal structures, but it may also work well for DNA, ligands and NMR ensembles. It produces coordinates, graphics, and numerical evaluations that integrate with either manual or automated use in systems such as PHENIX, KiNG, or Coot. | web application, consultation, macromolecular structure, structure validation, macromolecular crystallography |
is listed by: SoftCite is related to: Phenix is related to: Coot has parent organization: Duke University; North Carolina; USA |
Howard Hughes Medical Institute Predoctoral Fellowship ; NIGMS GM-15000; NIGMS GM-61302 |
DOI:10.1107/S0907444909042073 | Acknowledgement requested, Requires Java and Javascript | https://www.phenix-online.org/documentation/reference/molprobity_tool.html | SCR_014226 | 2026-07-27 09:34:36 | 6313 | |||||||
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libRoadRunner Resource Report Resource Website 10+ mentions |
libRoadRunner (RRID:SCR_014763) | software application, simulation software, software resource | Simulation engine for systems and synthetic biology to be used with other software applications. It retains the original functionality of RoadRunner but has changes in performance, back-end design, event handling, new C++ API, and stochastic simulation support. | simulation engine, simulation software, road runner, roadrunner, systems biology, synthetic biology |
is listed by: Debian is listed by: OMICtools |
NIGMS GM081070 | DOI:10.1093/bioinformatics/btv363 | Open source, Available for download | OMICS_09368 | https://sources.debian.org/src/libroadrunner-dev/ | SCR_014763 | 2026-07-27 09:34:43 | 11 | ||||||
|
OpenSim Resource Report Resource Website 500+ mentions |
OpenSim (RRID:SCR_002683) | software application, simulation software, software resource | OpenSim is an open-source software system that lets users develop models of musculoskeletal structures and create dynamic simulations of movement. The software provides a platform on which the biomechanics community can build a library of simulations that can be exchanged, tested, analyzed, and improved through multi-institutional collaboration. The underlying software is written in ANSI C++, and the graphical user interface (GUI) is written in Java. OpenSim technology makes it possible to develop customized controllers, analyses, contact models, and muscle models among other things. These plugins can be shared without the need to alter or compile source code. Users can analyze existing models and simulations and develop new models and simulations from within the GUI. | muscle-driven simulation, musculoskeletal biomechanics, neuromuscular simulation, modeling software, simulation software |
is related to: Simtk.org is related to: Neuromuscular Models Library has parent organization: Stanford University; Stanford; California |
Simbios ; NIGMS U54 GM072970; DARPA |
Public, Free, Acknowledgement requested | nif-0000-23308 | https://simtk.org/home/opensim, http://opensim.stanford.edu/support/index.html | SCR_002683 | 2026-07-27 09:31:32 | 546 | |||||||
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Molecular Dynamics Workflow (BioKepler) Resource Report Resource Website 1+ mentions |
Molecular Dynamics Workflow (BioKepler) (RRID:SCR_014389) | software application, workflow software, software resource, data processing software | A workflow for running molecular dynamics simulations. It can be used for all-atom molecular dynamic simulations, which involve five steps of minimization, one step of heating, three steps of equilibration, and one or more instances of production. The input is a set of directories that include the MD simulation input scripts, system topology and coordinate files. Output files are list of plots, simulation trajectories, intermediate files, restart files, and the like. | workflow, MD, molecular dynamics, simulation, software, bio.tools |
is listed by: bio.tools is listed by: Debian is related to: bioKepler has parent organization: University of California at San Diego; California; USA |
NIGMS P41GM103426 | Requires Linux | biotools:ambergpumdsimulation | http://nbcr.ucsd.edu/data/downloads/workflows/, https://bio.tools/ambergpumdsimulation | SCR_014389 | Molecular Dynamics Workflow, AmberGPUMDSimulation, Molecular Dynamics Workflow Software, Amber GPUMD Simulation | 2026-07-27 09:34:37 | 1 | ||||||
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iDEP: Integrated Differential Expression and Pathway analysis Resource Report Resource Website 1+ mentions |
iDEP: Integrated Differential Expression and Pathway analysis (RRID:SCR_027373) | iDEP | web application, software resource | Integrated web application for differential expression and pathway analysis of RNA-Seq data. | differential expression, pathway analysis, RNA-Seq data, | NIGMS GM083226; NSF ; State of South Dakota |
PMID:30567491 | Free, Freely available | SCR_027373 | 2026-07-27 09:37:51 | 8 | ||||||||
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GONUTS Resource Report Resource Website 1+ mentions |
GONUTS (RRID:SCR_000653) | GONUTS | database, data or information resource, wiki, narrative resource | A wiki where users of the Gene Ontology can contribute and view notes about how specific GO terms are used. GONUTS can also be used as a GO term browser, or to search for GO annotations of specific genes from included organisms. The rationale for this wiki is based on helping new users of the gene ontology understand and use it. The GONUTS wiki is not an official product of the the Gene Ontology consortium. The GO consortium has a public wiki at their website, http://wiki.geneontology.org/. Maintaining the ontology involves many decisions to carefully choose terms and relationships. These decisions are currently made at GO meetings and via online discussion using the GO mailing lists and the Sourceforge curator request tracker. However, it is difficult for someone starting to use GO to understand these decisions. Some insight can be obtained by mining the tracker, the listservs and the minutes of GO meetings, but this is difficult, as these discussions are often dispersed and sometimes don't contain the GO accessions in the relevant messages. Wikis provide a way to create collaboratively written documentation for each GO term to explain how it should be used, how to satisfy the true path requirement, and whether an annotation should be placed at a different level. In addition, the wiki pages provide a discussion space, where users can post questions and discuss possible changes to the ontology. GONUTS is currently set up so anyone can view or search, but only registered users can edit or add pages. Currently registered users can create new users, and we are working to add at least one registered user for each participating database (So far we have registered users at EcoliHub, EcoCyc, GOA, BeeBase, SGD, dictyBase, FlyBase, WormBase, TAIR, Rat Genome Database, ZFIN, MGI, UCL and AgBase... | ontology or annotation browser, ontology or annotation search engine, ontology or annotation editor, protein |
is listed by: Gene Ontology Tools is listed by: OMICtools is related to: Gene Ontology has parent organization: EcoliHub |
NIGMS 1U24 GM077905-01; NIGMS U24 GM088849 |
PMID:22110029 | Free for academic use, The community can contribute to this resource | OMICS_02268, nlx_30164 | SCR_000653 | Gene Ontology Normal Usage Tracking System, GONUTS wiki | 2026-07-28 09:40:04 | 1 | |||||
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Morpholino Database Resource Report Resource Website 1+ mentions |
Morpholino Database (RRID:SCR_001378) | MODB | service resource, data or information resource, data repository, database, storage service resource | Central database to house data on morpholino screens currently containing over 700 morpholinos including control and multiple morpholinos against the same target. A publicly accessible sequence-based search opens this database for morpholinos against a particular target for the zebrafish community. Morpholino Screens: They set out to identify all cotranslationally translocated genes in the zebrafish genome (Secretome/CTT-ome). Morpholinos were designed against putative secreted/CTT targets and injected into 1-4 cell stage zebrafish embryos. The embryos were observed over a 5 day period for defects in several different systems. The first screen examined 184 gene targets of which 26 demonstrated defects of interest (Pickart et al. 2006). A collaboration with the Verfaillie laboratory examined the knockdown of targets identified in a comparative microarray analysis of hematopoietic stem cells demonstrating how microarray and morpholino technologies can be used in conjunction to enrich for defects in specific developmental processes. Currently, many collaborations are underway to identify genes involved in morphological, kidney, skin, eye, pigment, vascular and hematopoietic development, lipid metabolism and more. The screen types referred to in the search functions are the specific areas of development that were examined during the various screens, which include behavior, general morphology, pigmentation, toxicity, Pax2 expression, and development of the craniofacial structures, eyes, kidneys, pituitary, and skin. Only data pertaining to specific tests performed are presented. Due to the complexity of this international collaboration and time constraints, not all morpholinos were subjected to all screen types. They are currently expanding public access to the database. In the future we will provide: * Mortality curves and dose range for each morpholino * Preliminary data regarding the effectiveness of each morpholino * Expanded annotation for each morpholino * External linkage of our morpholino sequences to ZFIN and Ensembl. To submit morpholino-knockdown results to MODB please contact the administrator for a user name and password. | morpholino, target mrna, embryonic zebrafish, sequence, target, blast, phenotype, anatomy, development, behavior, morphology, pigmentation, toxicity, pax2 expression, craniofacial structure, eye, kidney, pituitary, skin, name, target name, target sequence, gene target, genetic, mortality, toxicity, defect, function, gene annotation, genome, data analysis service |
uses: Zebrafish Information Network (ZFIN) uses: PATO has parent organization: Mayo Clinic Minnesota; Minnesota; USA |
NIGMS GM63904; NIA CA65493 |
PMID:18179718 | THIS RESOURCE IS NO LONGER IN SERVICE | nlx_152566 | SCR_001378 | MODB (MOprholino DataBase) | 2026-07-28 09:40:10 | 1 | |||||
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Diseasome Resource Report Resource Website 1+ mentions |
Diseasome (RRID:SCR_002792) | Diseasome | map, service resource, narrative resource, data set, data or information resource, book, image | A disease / disorder relationships explorer and a sample of a map-oriented scientific work. It uses the Human Disease Network dataset and allows intuitive knowledge discovery by mapping its complexity. The Human Disease Network (official) dataset, a poster of the data and related book (Biology - The digital era, ISBN: 978-2-271-06779-1) are available. This kind of data has a network-like organization, and relations between elements are at least as important as the elements themselves. More data could be integrated to this prototype and could eventually bring closer phenotype and genotype. Results should be visual, but also printable. Creating posters can enhance collaborative work. It facilitates discussion and sharing of ideas about the data. This website initiative is an invitation to think about the benefits of networks exploration but above all it tries to outline future designs of scientific information systems. | disease, disorder, genotype, phenotype, poster, network |
is related to: Allen Institute Neurowiki has parent organization: Gephi |
Dana-Farber Cancer Institute ; W. M. Keck Foundation ; NHGRI ; NIGMS |
PMID:17502601 | Free, Freely Available | nif-0000-24580 | SCR_002792 | Diseaseome | 2026-07-28 09:40:31 | 1 | |||||
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Patterns of Gene Expression in Drosophila Embryogenesis Resource Report Resource Website 50+ mentions |
Patterns of Gene Expression in Drosophila Embryogenesis (RRID:SCR_002868) | BDGP insitu | data or information resource, database, source code, software resource, image collection | Database of embryonic expression patterns using a high throughput RNA in situ hybridization of the protein-coding genes identified in the Drosophila melanogaster genome with images and controlled vocabulary annotations. At the end of production pipeline gene expression patterns are documented by taking a large number of digital images of individual embryos. The quality and identity of the captured image data are verified by independently derived microarray time-course analysis of gene expression using Affymetrix GeneChip technology. Gene expression patterns are annotated with controlled vocabulary for developmental anatomy of Drosophila embryogenesis. Image, microarray and annotation data are stored in a modified version of Gene Ontology database and the entire dataset is available on the web in browsable and searchable form or MySQL dump can be downloaded. So far, they have examined expression of 7507 genes and documented them with 111184 digital photographs. | embryo, embryogenesis, gene, anatomy, microarray, pattern, protocol, rna, gene expression, expression pattern, embryonic drosophila, in situ hybridization, annotation, est, FASEB list |
is related to: Gene Ontology has parent organization: Berkeley Drosophila Genome Project |
Howard Hughes Medical Institute ; NIH ; NIGMS R01 GM076655; NHGRI HG00750; NHGRI P41 HG00739 |
PMID:17645804 PMID:12537577 |
Free, Freely available, Available for download | nif-0000-25550, r3d100011327 | https://doi.org/10.17616/R32H0K | http://www.fruitfly.org/cgi-bin/ex/insitu.pl | SCR_002868 | BDGP Embryonic Expression Patterns | 2026-07-28 09:40:33 | 64 | |||
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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 | service resource, data analysis service, source code, software resource, production service resource, analysis service resource | 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 | 2026-07-28 09:40:39 | 3 | ||||
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I2D Resource Report Resource Website 10+ mentions |
I2D (RRID:SCR_002957) | I2D | service resource, data or information resource, data analysis service, database, production service resource, analysis service resource | Database of known and predicted mammalian and eukaryotic protein-protein interactions, it is designed to be both a resource for the laboratory scientist to explore known and predicted protein-protein interactions, and to facilitate bioinformatics initiatives exploring protein interaction networks. It has been built by mapping high-throughput (HTP) data between species. Thus, until experimentally verified, these interactions should be considered predictions. It remains one of the most comprehensive sources of known and predicted eukaryotic PPI. It contains 490,600 Source Interactions, 370,002 Predicted Interactions, for a total of 846,116 interactions, and continues to expand as new protein-protein interaction data becomes available. | interaction, prediction, protein-protein interaction, high-throughput, model organism, mammal, eukaryote, visualization, interolog, protein |
is related to: Interaction Reference Index is related to: IMEx - The International Molecular Exchange Consortium is related to: PSICQUIC Registry is related to: IntAct has parent organization: University of Toronto; Ontario; Canada |
National Science and Engineering Research Council RGPIN 203833-02; NIGMS P50-GM62413 |
PMID:17535438 PMID:15657099 |
Free, Available for download, Freely available | nif-0000-03005, r3d100010675 | https://doi.org/10.17616/R3BG8R | SCR_002957 | Interologous Interaction Database, OPHID, I2D - Interologous Interaction Database | 2026-07-28 09:40:42 | 23 | ||||
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Database of Interacting Proteins (DIP) Resource Report Resource Website 100+ mentions |
Database of Interacting Proteins (DIP) (RRID:SCR_003167) | DIP | service resource, data or information resource, data repository, data analysis service, storage service resource, database, production service resource, analysis service resource | Database to catalog experimentally determined interactions between proteins combining information from a variety of sources to create a single, consistent set of protein-protein interactions that can be downloaded in a variety of formats. The data were curated, both, manually and also automatically using computational approaches that utilize the the knowledge about the protein-protein interaction networks extracted from the most reliable, core subset of the DIP data. Because the reliability of experimental evidence varies widely, methods of quality assessment have been developed and utilized to identify the most reliable subset of the interactions. This CORE set can be used as a reference when evaluating the reliability of high-throughput protein-protein interaction data sets, for development of prediction methods, as well as in the studies of the properties of protein interaction networks. Tools are available to analyze, visualize and integrate user's own experimental data with the information about protein-protein interactions available in the DIP database. The DIP database lists protein pairs that are known to interact with each other. By interact they mean that two amino acid chains were experimentally identified to bind to each other. The database lists such pairs to aid those studying a particular protein-protein interaction but also those investigating entire regulatory and signaling pathways as well as those studying the organization and complexity of the protein interaction network at the cellular level. Registration is required to gain access to most of the DIP features. Registration is free to the members of the academic community. Trial accounts for the commercial users are also available. | blast, cellular network, ligand-receptor complex, ligand, network, protein, protein interaction, protein ligand, protein-protein interaction, protein receptor, receptor, sequence, interaction, regulatory pathway, signaling pathway, protein binding, bio.tools, FASEB list |
is recommended by: NIDDK Information Network (dkNET) is recommended by: National Library of Medicine is recommended by: NIDDK - National Institute of Diabetes and Digestive and Kidney Diseases is listed by: OMICtools is listed by: re3data.org is listed by: NIH Data Sharing Repositories is listed by: bio.tools is listed by: Debian is related to: IMEx - The International Molecular Exchange Consortium is related to: IMEx - The International Molecular Exchange Consortium is related to: MPIDB is related to: TissueNet - The Database of Human Tissue Protein-Protein Interactions is related to: InteroPorc is related to: Interaction Reference Index is related to: ConsensusPathDB is related to: NIH Data Sharing Repositories is related to: PSICQUIC Registry is related to: Agile Protein Interactomes DataServer has parent organization: University of California at Los Angeles; California; USA |
NIGMS | PMID:14681454 | Free, Available for download, Freely available | OMICS_01905, nif-0000-00569, r3d100010882, biotools:dip | https://dip.doe-mbi.ucla.edu/dip/Main.cgi, https://bio.tools/dip, https://doi.org/10.17616/R3431F | SCR_003167 | , Database of Interacting Proteins, DIP, Database of Interacting Proteins (DIP) | 2026-07-28 09:40:37 | 153 | ||||
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MouseNET Resource Report Resource Website 1+ mentions |
MouseNET (RRID:SCR_003357) | mouseNet | service resource, data or information resource, data analysis service, database, production service resource, analysis service resource | 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 | 2026-07-28 09:40:46 | 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 | service resource, data or information resource, data analysis service, database, production service resource, analysis service resource | 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 | 2026-07-28 09:40:45 | 4 | ||||
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EMDataResource.org Resource Report Resource Website 100+ mentions |
EMDataResource.org (RRID:SCR_003207) | EMDB, EMDataResource | service resource, data or information resource, project portal, data repository, storage service resource, portal | Portal for deposition and retrieval of cryo electron microscopy (3DEM) density maps, atomic models, and associated metadata. Global resource for 3 Dimensional Electron Microscopy structure data archiving and retrieval, news, events, software tools, data standards, validation methods. | deposition, retrival, cryo, electron, microscopy, 3DEM, density, maps, atomic, model, metadata, structure |
is recommended by: NIDDK Information Network (dkNET) is recommended by: NIDDK - National Institute of Diabetes and Digestive and Kidney Diseases is listed by: 3DVC is listed by: re3data.org is affiliated with: Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) is related to: Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) is related to: Electron Microscopy Data Bank at PDBe (MSD-EBI) is related to: PDBe - Protein Data Bank in Europe is related to: National Center for Macromolecular Imaging has parent organization: Rutgers University; New Jersey; USA has parent organization: European Bioinformatics Institute has parent organization: Baylor University; Texas; USA |
NIGMS R01 GM079429; BBSRC BBG022577 |
PMID:20935055 PMID:20888470 |
Free, Freely available | r3d100010552, nif-0000-30776 | https://doi.org/10.17616/R3T61P | EMDataBank.org | SCR_003207 | EMDataResource, EMDResource, EMDB, EMDataBank.org, EMDataBank - Unified Data Resource for 3DEM, EMDataBank | 2026-07-28 09:40:39 | 168 | |||
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GenePattern Resource Report Resource Website 1000+ mentions |
GenePattern (RRID:SCR_003201) | GenePattern | software application, software resource, data analysis software, data processing software | A powerful genomic analysis platform that provides access to hundreds of tools for gene expression analysis, proteomics, SNP analysis, flow cytometry, RNA-seq analysis, and common data processing tasks. A web-based interface provides easy access to these tools and allows the creation of multi-step analysis pipelines that enable reproducible in silico research. | gene expression, analysis, genomic, pattern, proteomics, silico, snp, workflow, analysis pipeline, flow cytometry, rna-seq, data processing, bio.tools |
is listed by: bio.tools is listed by: Debian is listed by: SoftCite is affiliated with: GenePattern Notebook is related to: TIGRESS has parent organization: Broad Institute |
NCI ; NIGMS |
PMID:16642009 | Free, Freely available | biotools:genepattern, OMICS_01855, nif-0000-30654 | https://bio.tools/genepattern | SCR_003201 | 2026-07-28 09:40:44 | 1078 | |||||
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Cell Image Library (CIL) Resource Report Resource Website 10+ mentions |
Cell Image Library (CIL) (RRID:SCR_003510) | CIL | service resource, data or information resource, data repository, image repository, database, storage service resource | Freely accessible, public repository of vetted and annotated microscopic images, videos, and animations of cells from a variety of organisms, showcasing cell architecture, intracellular functionalities, and both normal and abnormal processes. Explore by Cell Process, Cell Component, Cell Type or Organism. The Cell includes images acquired from historical and modern collections, publications, and by recruitment. | microscopic image repository, microscopic video repository, cell animation repository, bio.tools |
is used by: NIF Data Federation is recommended by: National Library of Medicine is recommended by: NIDDK Information Network (dkNET) is recommended by: NIDDK - National Institute of Diabetes and Digestive and Kidney Diseases is listed by: re3data.org is listed by: bio.tools is listed by: Debian is related to: Cell Centered Database is related to: Cell Centered Database is related to: OME-TIFF Format is related to: Integrated Manually Extracted Annotation has parent organization: American Society for Cell Biology has parent organization: University of California; San Diego;National Center for Microscopy and Imaging Research - NCMIR has parent organization: University of California at San Diego; California; USA is parent organization of: Biological Imaging Methods Ontology |
NIGMS RC2 GM092708 | PMID:34218671 PMID:34218673 |
Free, Freely available | biotools:cellimagelibrary, nif-0000-37639, r3d100011601 | http://www.cellimagelibrary.org/pages/about, https://bio.tools/cellimagelibrary, https://doi.org/10.17616/R3N92J | SCR_003510 | Cell Image Library. CIL, Cell Image Library (CIL) | 2026-07-28 09:40:45 | 19 | ||||
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Reactome Resource Report Resource Website 1000+ mentions |
Reactome (RRID:SCR_003485) | service resource, data or information resource, data analysis service, database, production service resource, analysis service resource | Collection of pathways and pathway annotations. The core unit of the Reactome data model is the reaction. Entities (nucleic acids, proteins, complexes and small molecules) participating in reactions form a network of biological interactions and are grouped into pathways (signaling, innate and acquired immune function, transcriptional regulation, translation, apoptosis and classical intermediary metabolism) . Provides website to navigate pathway knowledge and a suite of data analysis tools to support the pathway-based analysis of complex experimental and computational data sets. | pathway, interaction, reaction, nucleic acid, protein, complex, small molecule, signaling pathway, immune function, transcriptional regulation, translation, apoptosis, metabolism, ortholog, visualization, protein-protein interaction, web service, book, biomart, gold standard, bio.tools, FASEB list |
is used by: NIF Data Federation is used by: DisGeNET is used by: Pathway Analysis Tool for Integration and Knowledge Acquisition is listed by: re3data.org is listed by: bio.tools is listed by: Debian is related to: WikiPathways is related to: Pathway Commons is related to: ConsensusPathDB is related to: FlyMine is related to: AmiGO is related to: PSICQUIC Registry is related to: Integrated Molecular Interaction Database is related to: NCBI BioSystems Database is related to: MOPED - Model Organism Protein Expression Database is related to: KOBAS is related to: PSICQUIC Registry is related to: Pathway Interaction Database is related to: hiPathDB - human integrated Pathway DB with facile visualization is related to: Algal Functional Annotation Tool has parent organization: Ontario Institute for Cancer Research has parent organization: Cold Spring Harbor Laboratory has parent organization: European Bioinformatics Institute has parent organization: New York University School of Medicine; New York; USA works with: PathwayMatcher |
Ontario Research Fund ; European Molecular Biology Laboratory ; NHGRI P41 HG003751; European Union FP6 ENFIN LSHG-CT-2005-518254; NIGMS GM080223; NIGMS R01 GM100039 |
PMID:21082427 PMID:21067998 |
Open source, Public, Freely available | r3d100010285, nif-0000-03390, biotools:reactome | https://bio.tools/reactome, https://doi.org/10.17616/R3V59P | SCR_003485 | Reactome Functional Interaction Network | 2026-07-28 09:40:48 | 4282 | |||||
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National Institute of General Medical Sciences Image Gallery Resource Report Resource Website |
National Institute of General Medical Sciences Image Gallery (RRID:SCR_003480) | NIGMS Image Gallery | image collection, data or information resource, video resource | Database of scientific photos, illustrations, and videos made available by the National Institute of General Medical Sciences. | training material, database, illustration, media, news, photo, research | has parent organization: National Institute of General Medical Sciences | NIGMS | Permission is granted to use these images for educational, News media or research purposes, Provided the source for each image is credited. The material in this database may not be used to promote or endorse commercial products or services. | nif-0000-33708 | SCR_003480 | 2026-07-28 09:40:48 | 0 | |||||||
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miniTUBA Resource Report Resource Website |
miniTUBA (RRID:SCR_003447) | miniTUBA | analysis service resource, service resource, storage service resource, production service resource | miniTUBA is a web-based modeling system that allows clinical and biomedical researchers to perform complex medical/clinical inference and prediction using dynamic Bayesian network analysis with temporal datasets. The software allows users to choose different analysis parameters (e.g. Markov lags and prior topology), and continuously update their data and refine their results. miniTUBA can make temporal predictions to suggest interventions based on an automated learning process pipeline using all data provided. Preliminary tests using synthetic data and laboratory research data indicate that miniTUBA accurately identifies regulatory network structures from temporal data. miniTUBA represents in a network view possible influences that occur between time varying variables in your dataset. For these networks of influence, miniTUBA predicts time courses of disease progression or response to therapies. minTUBA offers a probabilistic framework that is suitable for medical inference in datasets that are noisy. It conducts simulations and learning processes for predictive outcomes. The DBN analysis conducted by miniTUBA describes from variables that you specify how multiple measures at different time points in various variables influence each other. The DBN analysis then finds the probability of the model that best fits the data. A DBN analysis runs every combination of all the data; it examines a large space of possible relationships between variables, including linear, non-linear, and multi-state relationships; and it creates chains of causation, suggesting a sequence of events required to produce a particular outcome. Such chains of causation networks - are difficult to extract using other machine learning techniques. DBN then scores the resulting networks and ranks them in terms of how much structured information they contain compared to all possible models of the data. Models that fit well have higher scores. Output of a miniTUBA analysis provides the ten top-scoring networks of interacting influences that may be predictive of both disease progression and the impact of clinical interventions and probability tables for interpreting results. The DBN analysis that miniTUBA provides is especially good for biomedical experiments or clinical studies in which you collect data different time intervals. Applications of miniTUBA to biomedical problems include analyses of biomarkers and clinical datasets and other cases described on the miniTUBA website. To run a DBN with miniTUBA, you can set a number of parameters and constrain results by modifying structural priors (i.e. forcing or forbidding certain connections so that direction of influence reflects actual biological relationships). You can specify how to group variables into bins for analysis (called discretizing) and set the DBN execution time. You can also set and re-set the time lag to use in the analysis between the start of an event and the observation of its effect, and you can select to analyze only particular subsets of variables. | analysis, analyze, bayesian, causation, clinical, linear, medical, structure, temporal, network analysis, network, molecule, information refining, gene expression regulation, bioinformatics, statistical package, interaction network, prediction, pathway, inference, biomedical, intervention |
is listed by: Biositemaps has parent organization: National Center for Integrative Biomedical Informatics has parent organization: University of Michigan; Ann Arbor; USA |
Society of University Surgeons Foundation ; NIDA U54DA021519; NIAID 1R21AI057875-01; NIGMS K08 GM074678-01A1 |
PMID:17644819 | Free, Freely available | nif-0000-33272 | SCR_003447 | miniTUBA - Medical Inference by Network Integration of Temporal Data using Bayesian Analysis tool, Medical Inference by Network Integration of Temporal Data using Bayesian Analysis tool, Medical Inference by Network Integration of Temporal Data using Bayesian Analysis tool (miniTUBA), The Medical Inference by Network Integration of Temporal Data using Bayesian Analysis tool | 2026-07-28 09:40:48 | 0 |
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