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| Resource Name | Proper Citation | Abbreviations | Resource Type |
Description |
Keywords | Resource Relationships | |||||||||||||
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Swami: The Next Generation Biology Workbench Resource Report Resource Website 1+ mentions |
Swami: The Next Generation Biology Workbench (RRID:SCR_007217) | NGBW | service resource | THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. The Next Generation Biology Workbench is a free resource for research and education in Bioinformatics, Genomics, Proteomics, and Phylogenetics. The NGBW is a re-engineering of the Biology Workbench which was designed by Shankar Subramaniam and his group to provide an integrated environment where tools, user data, and public data resources can be easily accessed. The NGBW is designed to be an organic tool that evolves with the needs of the Biomedical research and education communities. The Next Generation Biology Workbench (NGBW) is now available for public use, in its production release. | has parent organization: University of California at San Diego; California; USA | IBM Corporation ; Microsoft Research ; NIGMS 5R01GM073931 |
THIS RESOURCE IS NO LONGER IN SERVICE | nlx_14257 | http://www.ngbw.org/ | SCR_007217 | Next Generation Biology Workbench, Swami | 2026-09-03 04:49:11 | 2 | ||||||
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MCell Resource Report Resource Website 50+ mentions |
MCell (RRID:SCR_007307) | simulation software, software application, software resource | Software modeling tool for realistic simulation of cellular signaling in complex 3-D subcellular microenvironment in and around living cells. Program that uses spatially realistic 3D cellular models and specialized Monte Carlo algorithms to simulate movements and reactions of molecules within and between cells. | Monte Carlo, simulator, cellular, microphysiology, living, cell, BRAIN Initiative |
is recommended by: BRAIN Initiative is related to: CellOrganizer |
NIGMS P41 GM103712 | Free, Available for download, Freely available | nif-0000-00160 | https://github.com/mcellteam/mcell | SCR_007307 | Monte Carlo simulator of cellular microphysiology | 2026-09-03 04:49:08 | 62 | ||||||
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eMERGE Network: electronic Medical Records and Genomics Resource Report Resource Website 1+ mentions |
eMERGE Network: electronic Medical Records and Genomics (RRID:SCR_007428) | eMERGE | data or information resource, portal, topical portal | A national consortium formed to develop, disseminate, and apply approaches to research that combine DNA biorepositories with electronic medical record (EMR) systems for large-scale, high-throughput genetic research. The consortium is composed of seven member sites exploring the ability and feasibility of using EMR systems to investigate gene-disease relationships. Themes of bioinformatics, genomic medicine, privacy and community engagement are of particular relevance to eMERGE. The consortium uses data from the EMR clinical systems that represent actual health care events and focuses on ethical issues such as privacy, confidentiality, and interactions with the broader community. | human, clinical, dna, alzheimer's disease, genome, genomics, gene, genetic, nervous system disease, nucleotide polymorphism, phenotype, bioinformatics, genomic medicine, privacy, community engagement, emr, electronic medical record |
is related to: PheKB is related to: NCBI database of Genotypes and Phenotypes (dbGap) is related to: PheWAS Catalog has parent organization: Vanderbilt University; Tennessee; USA |
Aging | NIGMS ; NHGRI |
Available to the research community | nif-0000-00539 | SCR_007428 | eMERGE Network: electronic Medical Records & Genomics - A consortium of biorepositories linked to electronic medical records data for conducting genomics studies, eMERGE Network: electronic Medical Records Genomics, eMERGE Network: electronic Medical Records & Genomics, eMERGE Network, electronic Medical Records & Genomics, The eMERGE Network: electronic Medical Records & Genomics | 2026-09-03 04:49:08 | 2 | |||||
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GeneWays: A System for Extracting, Analyzing, Visualizing and Integrating Molecular Pathway Data Resource Report Resource Website 10+ mentions |
GeneWays: A System for Extracting, Analyzing, Visualizing and Integrating Molecular Pathway Data (RRID:SCR_008368) | GeneWays | analysis service resource, production service resource, data or information resource, service resource, data analysis service, database | A system for automatically extracting, analyzing, visualizing and integrating molecular pathway data from the research literature. The system focuses on interactions between molecular substances and actions, providing a graphical consensus view on the collected information. GeneWays is designed as an open platform, allowing researchers to query, review and critique the integrated information. Knowledge integration in the domain of molecular biology is crucial for a deeper understanding of molecular cell functions. Integration can be accomplished by gathering research results published in the scientific literature. Unfortunately, researchers are facing a true challenge how to best integrate the sheer amount of scientific publications available. GeneWays is built to help integrating research results by providing automatic tools to gather knowledge from the scientific literature. The GeneWays project team comprises experts from biology, computer science and linguistics, who use natural language processing (NLP) to scan thousands of research articles in order to automatically extract relevant molecular knowledge. The key idea is rather simple: While a single author may be an ultimate expert on a specific molecular substance, the collective knowledge of the whole research community is currently unavailable in an integrated form. Molecular interactions are frequently represented in research articles by statements such as protein A activates protein B, which can be collected and integrated into knowledge about a complex molecular network consisting of thousands of genes, proteins, small molecules (along with other substances) and their interactions. GeneWays's architecture combines various modules designed to automatically gather knowledge on signal transduction pathways from online scientific journals. The core of the system is a knowledge base of molecular actions. The knowledge is provided by various system modules, which select scientific journals of interest, mark and identify substance names in the journal text and extract interactions between these substances and other actions by means of natural language processing (NLP). The integrated knowledge stored in a database can be queried, analyzed, critiqued and visualized by interested researchers. | text mining, information extraction, molecular network, molecular interaction, artificial intelligence, knowledge engineering, machine learning, natural language processing |
is related to: OMICtools has parent organization: Columbia University; New York; USA |
NSF EIA-0121687; DOE DE-FG02-01ER25500; NIGMS GM61372 |
PMID:15016385 | nif-0000-30019 | http://anya.igsb.anl.gov/genewaysApp | SCR_008368 | GeneWays: A System for Extracting Analyzing Visualizing and Integrating Molecular Pathway Data, GeneWays: A System for Extracting Analyzing Visualizing Integrating Molecular Pathway Data | 2026-09-03 04:49:34 | 16 | |||||
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SimTKCore Resource Report Resource Website |
SimTKCore (RRID:SCR_008268) | SimTKCore | simulation software, software application, software resource | SimTK Core is one of the two packages that together constitute SimTK, the biosimulation toolkit from the Simbios Center. The other major component of SimTK is OpenMM which is packaged separately. This SimTK Core project collects together all the binaries needed for the various SimTK Core subprojects. These include Simbody, Molmodel, Simmath (including Ipopt), Simmatrix, CPodes, SimTKcommon, and Lapack. See the individual projects for descriptions. SimTK brings together in a robust, convenient, open source form the collection of highly-specialized technologies necessary to building successful physics-based simulations of biological structures. These include: strict adherence to an important set of abstractions and guiding principles, robust, high-performance numerical methods, support for developing and sharing physics-based models, and careful software engineering. Accessible High Performance Computing We believe that a primary concern of simulation scientists is performance, that is, speed of computation. We seek to build valid, approximate models using classical physics in order to achieve reasonable run times for our computational studies, so that we can hope to learn something interesting before retirement. In the choice of SimTK technologies, we are focused on achieving the best possible performance on hardware that most researchers actually have. In today''s practice, that means commodity multiprocessors and small clusters. The difference in performance between the best methods and the do-it-yourself techniques most people use can be astoundingeasily an order of magnitude or more. The growing set of SimTK Core libraries seeks to provide the best implementation of the best-known methods for widely used computations such as: Linear algebra, numerical integration and Monte Carlo sampling, multibody (internal coordinate) dynamics, molecular force field evaluation, nonlinear root finding and optimization. All SimTK Core software is in the form of C++ APIs, is thread-safe, and quietly exploits multiple CPUs when they are present. The resulting pre-built binaries are available for download and immediate use. Audience: Biosimulation application programmers interested in including robust, high-performance physics-based simulation in their domain-specific applications. | computational algorithm, high-performance, linear algebra, numerical integration, numerical method, optimization, monte carlo sampling, multibody dynamics, molecular force field evaluation, nonlinear root finding, optimizing, cpodes, simbody, ipopt, molmodel, mit license, linux, mac os x, windows |
is listed by: Biositemaps has parent organization: Stanford University; Stanford; California has parent organization: Simtk.org |
NIGMS U54 GM072970 | PMID:20107615 | nif-0000-23310 | SCR_008268 | 2026-09-03 04:49:38 | 0 | |||||||
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Hippocampal Slice Wave Animations Resource Report Resource Website |
Hippocampal Slice Wave Animations (RRID:SCR_008372) | animation software, data or information resource, data processing software, data visualization software, portal, resource, simulation software, software application, software resource, topical portal | THIS RESOURCE IS NO LONGER IN SERVICE, documented on January 29, 2013. Supplemental data for the paper Changes in mitochondrial function resulting from synaptic activity in the rat hippocampal slice, by Vytautas P. Bindokas, Chong C. Lee, William F. Colmers, and Richard J. Miller that appears in the Journal of Neuroscience June 15, 1998. You can view digital movies of changes in fluorescence intensity by clicking on the title of interest. | animation, hippocampal, hippocampus, mitochondrial, movie, neuroscience, rat, slice, wave | MRC of Canada MT10520; NIDA DA02575; NIDA DA02121; NIMH MH40165; NIDDK DK42086; NIDDK DK44840; NINDS NS-33502; NIGMS 5T32GM07151-22; NICHD HD07009 |
PMID:9614233 | THIS RESOURCE IS NO LONGER IN SERVICE | nif-0000-25609 | SCR_008372 | GIF Animations | 2026-09-03 04:49:42 | 0 | |||||||
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MODELLER Resource Report Resource Website 5000+ mentions |
MODELLER (RRID:SCR_008395) | data or information resource, portal, simulation software, software application, software resource, topical portal | Software tool as Program for Comparative Protein Structure Modelling by Satisfaction of Spatial Restraints. Used for homology or comparative modeling of protein three dimensional structures. User provides alignment of sequence to be modeled with known related structures and MODELLER automatically calculates model containing all non hydrogen atoms. | comparative, protein, structure, modelling, satisfaction, spatial, restrain, homology, 3D, alignment, sequence, hydrogen, atom, cluster |
is listed by: SoftCite has parent organization: University of California at San Francisco; California; USA |
IBM ; Intel ; NIGMS P01 GM71790; NIGMS R01 GM54762; NIGMS U54 GM62529; NIH P01 A135707; Sandler Family Supporting Foundation |
Restricted | nif-0000-30054 | SCR_008395 | 2026-09-03 04:49:31 | 5873 | ||||||||
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Systems Biology Graphical Notation Resource Report Resource Website 1+ mentions |
Systems Biology Graphical Notation (RRID:SCR_004671) | SBGN | data or information resource, international standard specification, meeting resource, narrative resource, portal, software resource, standard specification, topical portal, training resource | The Systems Biology Graphical Notation (SBGN) project aims to develop high quality, standard graphical languages for representing biological processes and interactions. Each SBGN language is based on the consensus of the broad international SBGN community of biologists, curators and software developers. Over the course of its development many individuals, organizations and companies made invaluable contributions to the SBGN through participating in discussions and meetings, providing feedback on the documentation and worked examples, adopting the standard and spreading the word. Circuit diagrams and Unified Modeling Language diagrams are just two examples of standard visual languages that help accelerate work by promoting regularity, removing ambiguity and enabling software tool support for communication of complex information. Ironically, despite having one of the highest ratios of graphical to textual information, biology still lacks standard graphical notations. The recent deluge of biological knowledge makes addressing this deficit a pressing concern. Toward this goal, we present the Systems Biology Graphical Notation (SBGN), a visual language developed by a community of biochemists, modelers and computer scientists. SBGN consists of three complementary languages: process diagram, entity relationship diagram and activity flow diagram. Together they enable scientists to represent networks of biochemical interactions in a standard, unambiguous way. We believe that SBGN will foster efficient and accurate representation, visualization, storage, exchange and reuse of information on all kinds of biological knowledge, from gene regulation, to metabolism, to cellular signaling. A list of software packages known to provide (or have started to develop) support for SBGN notations is available. | New Energy and Industrial Technology Development Organization ; Okinawa Institute of Science and Technology ; BBSRC ; National Institute of Advanced Industrial Science and Technology of Japan ; European Media Laboratory EML Research GmbH ; California Institute of Technology; California; USA ; NIGMS 1R01GM081070-01 |
PMID:19668183 | nlx_66628 | SCR_004671 | 2026-09-03 04:47:24 | 1 | |||||||||
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EMDataResource.org Resource Report Resource Website 100+ mentions |
EMDataResource.org (RRID:SCR_003207) | EMDB, EMDataResource | data or information resource, data repository, portal, project portal, service resource, storage service resource | 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 |
BBSRC BBG022577; NIGMS R01 GM079429 |
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 | 2026-09-03 04:46:08 | 183 | |||
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Database of Interacting Proteins (DIP) Resource Report Resource Website 100+ mentions |
Database of Interacting Proteins (DIP) (RRID:SCR_003167) | DIP | analysis service resource, data analysis service, data or information resource, data repository, database, production service resource, service resource, storage 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) | 2026-09-03 04:45:58 | 167 | ||||
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GenePattern Resource Report Resource Website 1000+ mentions |
GenePattern (RRID:SCR_003201) | GenePattern | data analysis software, data processing software, software application, software resource | 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 | 2026-09-03 04:46:04 | 1135 | |||||
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MouseNET Resource Report Resource Website 1+ mentions |
MouseNET (RRID:SCR_003357) | mouseNet | analysis service resource, data analysis service, data or information resource, database, production service resource, 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 | 2026-09-03 04:46:10 | 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 | analysis service resource, data analysis service, data or information resource, database, production service resource, 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 | 2026-09-03 04:46:12 | 4 | ||||
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LONI Software Resource Report Resource Website 1+ mentions |
LONI Software (RRID:SCR_003323) | software resource, data analysis software, software repository, software application, data processing software | A portal of software resources offered by UCLA's Laboratory of Neuro Imaging. LONI Webapps allow users to analyze, visualize and interact with neuroscience data directly from their web browser. LONI aims to encourage communication between users and LONI software engineers in order to improve the effectiveness of our software and to promote its use by researchers worldwide. We have expanded our software website to include more tools, training and support. Be sure to visit LONI Forums and discuss our tools with other end-users as well as our dedicated LONI staff. | visualization, shape analysis, registration, statistical analysis, data management, image processing, pre=processing, segmentation, surface modeling, model |
is listed by: 3DVC is listed by: Biositemaps is related to: Mouse Atlas Project has parent organization: University of California at Los Angeles; California; USA |
NCRR ; NIMH ; NINDS ; NIBIB ; NIGMS ; NIH ; DOE |
http://www.loni.ucla.edu/Software/ | SCR_003323 | Laboratory of Neuro Imaging Software | 2026-09-03 04:46:15 | 2 | ||||||||
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Cell Image Library (CIL) Resource Report Resource Website 10+ mentions |
Cell Image Library (CIL) (RRID:SCR_003510) | CIL | data or information resource, data repository, database, image repository, service resource, 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) | 2026-09-03 04:46:25 | 22 | ||||
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Reactome Resource Report Resource Website 1000+ mentions |
Reactome (RRID:SCR_003485) | analysis service resource, data analysis service, data or information resource, database, production service resource, 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 |
European Molecular Biology Laboratory ; European Union FP6 ENFIN LSHG-CT-2005-518254; NHGRI P41 HG003751; NIGMS GM080223; NIGMS R01 GM100039; Ontario Research Fund |
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 | 2026-09-03 04:46:31 | 4810 | |||||
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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 | data or information resource, image collection, 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 | 2026-09-03 04:46:25 | 0 | |||||||
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miniTUBA Resource Report Resource Website |
miniTUBA (RRID:SCR_003447) | miniTUBA | analysis service resource, production service resource, service resource, storage 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 | 2026-09-03 04:46:23 | 0 | |||||
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Dictyostelium discoideum genome database Resource Report Resource Website 100+ mentions |
Dictyostelium discoideum genome database (RRID:SCR_006643) | dictyBase, dictyBase gene name, dictyBase REF, DictyBase | biomaterial supply resource, material resource, organism supplier | Model organism database for the social amoeba Dictyostelium discoideum that provides the biomedical research community with integrated, high quality data and tools for Dictyostelium discoideum and related species. dictyBase houses the complete genome sequence, ESTs, and the entire body of literature relevant to Dictyostelium. This information is curated to provide accurate gene models and functional annotations, with the goal of fully annotating the genome to provide a ''''reference genome'''' in the Amoebozoa clade. They highlight several new features in the present update: (i) new annotations; (ii) improved interface with web 2.0 functionality; (iii) the initial steps towards a genome portal for the Amoebozoa; (iv) ortholog display; and (v) the complete integration of the Dicty Stock Center with dictyBase. The Dicty Stock Center currently holds over 1500 strains targeting over 930 different genes. There are over 100 different distinct amoebozoan species. In addition, the collection contains nearly 600 plasmids and other materials such as antibodies and cDNA libraries. The strain collection includes: * strain catalog * natural isolates * MNNG chemical mutants * tester strains for parasexual genetics * auxotroph strains * null mutants * GFP-labeled strains for cell biology * plasmid catalog The Dicty Stock Center can accept Dictyostelium strains, plasmids, and other materials relevant for research using Dictyostelium such as antibodies and cDNA or genomic libraries. | genome, sequence, est, literature, gene model, functional annotation, reference genome, gene, antibody, cdna, bacteria, dictyostelium discoideum, dictyostelium purpureum, dictyostelium fasciculatum, polysphondylium pallidium, bio.tools |
is used by: NIF Data Federation is listed by: One Mind Biospecimen Bank Listing is listed by: OMICtools is listed by: bio.tools is listed by: Debian is related to: AmiGO is related to: Textpresso has parent organization: Northwestern University; Illinois; USA has parent organization: Baylor University; Texas; USA has parent organization: University of Cologne; Cologne; Germany is parent organization of: Dictyostelium Discoideum Anatomy Ontology is parent organization of: Dictyostelium Anatomy Ontology is parent organization of: dictyBase - Teaching Tools Using Dictyostelium discoideum |
European Union ; NHGRI HG0022; NIGMS GM087371; NIGMS GM64426 |
PMID:23172289 PMID:21087999 PMID:18974179 PMID:14681427 PMID:16381903 |
biotools:dictybase, nif-0000-20974, SCR_008149, nif-0000-02751, OMICS_03158 | https://bio.tools/dictybase | http://genome.imb-jena.de/dictyostelium/ | SCR_006643 | dictyBase gene name, dictyBase REF, Dicty, dictyBase, Dictyostelium discoideum | 2026-09-03 04:48:47 | 315 | ||||
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Ligand Expo Resource Report Resource Website |
Ligand Expo (RRID:SCR_006636) | data or information resource, database, resource | An integrated data resource for finding chemical and structural information about small molecules bound to proteins and nucleic acids within the structure entries of the Protein Data Bank. Tools are provided to search the PDB dictionary for chemical components, to identify structure entries containing particular small molecules, and to download the 3D structures of the small molecule components in the PDB entry. A sketch tool is also provided for building new chemical definitions from reported PDB chemical components. | element, fingerprint, formula, amino acid, aromatic ring, atom, bound, carbon, chemical, component, depot, ligand, molecular, molecule, nitrogen, nucleic acid, nucleotide, pharmaceutical, protein, small molecule, structure, macromolecule, model |
uses: Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) uses: Worldwide Protein Data Bank (wwPDB) has parent organization: Rutgers University; New Jersey; USA has parent organization: Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) |
NSF ; NIGMS ; DOE ; NLM ; NCI ; NCRR ; NIBIB ; NINDS ; NIDDK |
PMID:15059838 | nif-0000-21237, OMICS_02751 | http://ligand-depot.rutgers.edu/ | SCR_006636 | Ligand Depot | 2026-09-03 04:48:47 | 0 |
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Data set from Kravitz, Owen and Kretizer's 2012 paper "Optogenetic identification of striatal projection neuron subtypes during in vivo recordings."
