Searching the RRID Resource Information Network
Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.
SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
| Resource Name | Proper Citation | Abbreviations | Resource Type |
Description |
Keywords | Resource Relationships | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
Criminal Justice Drug Abuse Treatment Studies Resource Report Resource Website |
Criminal Justice Drug Abuse Treatment Studies (RRID:SCR_006996) | CJ-DATS, CJDATS | knowledge environment | A cooperative research program to explore the issues related to the complex system of offender treatment services. Nine research centers and a Coordinating Center were created in partnership with researchers, criminal justice professionals, and drug abuse treatment practitioners to form a national research infrastructure. The establishment of CJ-DATS is an outstanding example of cooperation among Federal agencies with the research community... We need to understand how to provide better drug treatment services for criminal justice offenders to alter their drug use and criminal behavior. - Dr. Nora Volkow, Director of NIDA. CJ-DATS PHASE I In 2002, NIDA launched the National Criminal Justice����������Drug Abuse Treatment Studies (CJ-DATS). CJ-DATS is a multisite research program aimed at improving the treatment of offenders with drug use disorders and integrating criminal justice and public health responses to drug involved offenders. From 2002 through 2008, CJ-DATS researchers from 9 research centers, a coordinating center, and NIDA worked together with federal, state, and local criminal justice partners to develop and test integrated approaches to the treatment of offenders with drug use disorders. The areas that were studied included: * Assessing Offender Problems * Measuring Progress in Treatment and Recovery * Linking Criminal Justice and Drug Abuse Treatment * Adolescent Interventions * HIV and Hepatitis Risk Reduction * Understanding Systems CJ-DATS PHASE II In 2008, CJ-DATS began to focus on the problems of implementing research-based practices drug treatment practices. This research concerns the organizational and systems processes involved in implementing valid, evidence-based practices to reduce drug use and drug-related recidivism for individuals in the criminal justice system. 12 CJ-DATS Research Centers are conducting implementation research in three primary domains: * Research to improve the implementation of evidence-based assessment processes for offenders with drug problems * Implementing effective treatment for drug-involved offenders * Implementing evidence-based interventions to improve an HIV continuum-of-care for offenders | drug, aids, criminal, health, hiv, offender, treatment, justice, drug abuse, drug treatment service, criminal justice offender, drug use, criminal behavior, recovery, adolescent, intervention, hepatitis |
is related to: NIDA Networking Project: Facilitating information exchange and research collaboration has parent organization: National Institute on Drug Abuse |
Drug use disorder | NIDA | nif-0000-10202 | SCR_006996 | Criminal Justice-Drug Abuse Treatment Studies | 2026-02-07 02:07:17 | 0 | ||||||
|
FINDTHECAT Resource Report Resource Website |
FINDTHECAT (RRID:SCR_016036) | software resource, software application | Software that conducts a jspsych test for response time evaluation. Used in the ABCD Study. | psych, jspsych, psychology, response, time, evaluation, task, test, abcd, adolescent | NIDA U24 DA041123 | Free, Available for download | SCR_016036 | 2026-02-07 02:14:44 | 0 | ||||||||||
|
stroop-task Resource Report Resource Website 1+ mentions |
stroop-task (RRID:SCR_016033) | software resource, software application | Software that conducts the Stroop Color Task. Used in the ABCD Study. | stroop, task, color, vision, abcd, adolesence, study | NIDA U24 DA041123 | Free, Available for download | SCR_016033 | 2026-02-07 02:14:46 | 1 | ||||||||||
|
OmicsGAN Resource Report Resource Website 1+ mentions |
OmicsGAN (RRID:SCR_022976) | software resource, software application | Software generative adversarial network to integrate two omics data and their interaction network to generate one synthetic data corresponding to each omics profile that can result in better phenotype prediction. Used to capture information from interaction network as well as two omics datasets and fuse them to generate synthetic data with better predictive signals. | integrate two omics data, interaction network, generate one synthetic data corresponding to each omics profile, phenotype prediction | NSF III1755761; NIGMS R01GM113952; NIDA DK097771 |
PMID:34415323 | Free, Available for download, Freely available | SCR_022976 | Omics Generative Adversarial Network | 2026-02-07 02:14:54 | 1 | ||||||||
|
JAX Animal Behavior System Resource Report Resource Website |
JAX Animal Behavior System (RRID:SCR_023721) | JABS | software resource | Video based phenotyping platform for laboratory mouse. Provides complete details of software and hardware, including 3D designs used for data collection. Data acquisition system consists of video collection hardware and software, behavior labeling and active learning app, and online database for sharing classifiers. Hardware and software solution collects high quality data for behavior analysis. | OpenBehavior, data acquisition system, integrated mouse phenotyping platform, behavior analysis, | is listed by: OpenBehavior | Jackson Laboratory Directors Innovation Fund ; NIDA DA041668; NIDA DA048634 |
DOI:10.1101/2022.01.13.476229 | Free, Available for download, Freely available | SCR_023721 | 2026-02-07 02:12:15 | 0 | |||||||
|
Substructure Index-based Approximate Graph Alignment Resource Report Resource Website 10+ mentions |
Substructure Index-based Approximate Graph Alignment (RRID:SCR_003434) | SAGA | software resource, software application | SAGA (Substructure Index-based Approximate Graph Alignment) is a tool for querying a biological graph database to retrieve matches between subgraphs of molecular interactions and biological networks. SAGA implements an efficient approximate subgraph matching algorithm that can be used for a variety of biological graph matching problems such as the pathway matching SAGA uses to compare pathways in KEGG and Reactome. You can also use SAGA to find matches in literature databases that have been parsed into semantic graphs. In this use of SAGA, portions of PubMed have been parsed into graphs that have nodes representing gene names. A link is drawn between two genes if they are discussed in the same sentence (indicating there is potential association between the two genes). SAGA lets you match graphs between different databases even though the content is distinct and the databases organize pathways in different ways. This cross-database matching is achieved by SAGA's flexible approximate subgraph matching model that computes graph similarity, and allows for node gaps, node mismatches, and graph structural differences. Comparing pathways from different databases can be a useful precursor to pathway data integration. SAGA is very efficient for querying relatively small graphs, but becomes prohibitory expensive for querying large graphs. Large graph data sets are common in many emerging database applications, and most notably in large-scale scientific applications. To fully exploit the wealth of information encoded in graphs, effective and efficient graph matching tools are critical. Due to the noisy and incomplete nature of real graph datasets, approximate, rather than exact, graph matching is required. Furthermore, many modern applications need to query large graphs, each of which has hundreds to thousands of nodes and edges. TALE is an approximate subgraph matching tool for matching graph queries with a large number of nodes and edges. TALE employs a novel indexing technique that achieves a high pruning power and scales linearly with the database size. | gene, algorithm, alignment, biological, graph, interaction, literature, molecular, pathway, query, reactome, structural, subgraph, substructure, tool, graph similarity |
is listed by: Biositemaps has parent organization: National Center for Integrative Biomedical Informatics has parent organization: University of Michigan; Ann Arbor; USA |
Microsoft ; NIDA 1-U54-DA021519-01A1 |
PMID:17110368 | Access free via the web; Binaries are also freely available. If you use SAGA for any work that leads to a publication you must cite paper. | nif-0000-33157 | SCR_003434 | SAGA (Substructure Index-based Approximate Graph Alignment), SAGA - Substructure Index-based Approximate Graph Alignment, SAGA: A Fast and Flexible Graph Matching Tool | 2026-02-07 02:14:16 | 24 | |||||
|
Antibody Watch Resource Report Resource Website |
Antibody Watch (RRID:SCR_027424) | knowledge base | Text mining antibody specificity from literature. Helps researchers identify potential problems with antibody specificity. By mining the scientific literature and linking findings to Research Resource Identifiers (RRIDs), it provides alerts on antibodies that may yield unreliable results, supporting reproducibility in biomedical research. | Text mining antibody specificity, identify potential problems with antibody specificity, identify potential problems, antibody specificity, antibody, scientific literature, | Ministry of Science and Technology ; Taiwan ; NIDDK U24DK097771; NIDA U24DA039832 |
PMID:34043624 | Free, Freely available | SCR_027424 | 2026-02-07 02:18:10 | 0 | |||||||||
|
MiMI Plugin for Cytoscape Resource Report Resource Website 1+ mentions |
MiMI Plugin for Cytoscape (RRID:SCR_003424) | MiMI Plugin | data visualization software, software resource, software application, data processing software | The Cytoscape MiMI Plugin is an open source interactive visualization tool that you can use for analyzing protein interactions and their biological effects. The Cytoscape MiMI Plugin couples Cytoscape, a widely used software tool for analyzing bimolecular networks, with the MiMI database, a database that uses an intelligent deep-merging approach to integrate data from multiple well-known protein interaction databases. The MiMI database has data on 119,880 molecules, 330,153 interactions, and 579 complexes. By querying the MiMI database through Cytoscape you can access the integrated molecular data assembled in MiMI and retrieve interactive graphics that display protein interactions and details on related attributes and biological concepts. You can interact with the visualization by expanding networks to the next nearest neighbors and zooming and panning to relationships of interest. You also can perceptually encode nodes and links to show additional attributes through color, size and the visual cues. You can edit networks, link out to other resources and tools, and access information associated with interactions that has been mined and summarized from the research literature information through a biology natural language processing database (BioNLP) and a multi-document summarization system, MEAD. Additionally, you can choose sub-networks of interest and use SAGA, a graph matching tool, to match these sub-networks to biological pathways. | protein interaction, network visualization, xquery, interactive database, information refining, molecular interaction, bioinformatics tool, java, protein-protein interaction, interaction network, biological effect, bimolecular, interaction, molecular, network, pathway, protein, visualization, plugin |
is listed by: Biositemaps is related to: Cytoscape is related to: Michigan Molecular Interactions has parent organization: University of Michigan; Ann Arbor; USA has parent organization: National Center for Integrative Biomedical Informatics |
NIH ; NIDA U54 DA021519; NLM R01 LM008106; NCRR P41 RR018627 |
PMID:18812364 | nif-0000-33090 | http://mimiplugin.ncibi.org/index.html | SCR_003424 | Cytoscape Plugin for MiMI, MiMI Plugin - Cytoscape Plugin for MiMI | 2026-02-10 09:54:54 | 1 | |||||
|
New Science of Addiction: Genetics and the Brain Resource Report Resource Website 1+ mentions |
New Science of Addiction: Genetics and the Brain (RRID:SCR_002770) | New Science of Addiction | portal, data or information resource, topical portal, narrative resource, training material, disease-related portal | A physiologic and molecular look at drug addiction involving many factors including: basic neurobiology, a scientific examination of drug action in the brain, the role of genetics in addiction, and ethical considerations. Designed to be used by students, teachers and members of the public, the materials meet selected US education standards for science and health. Drug addiction is a chronic disease characterized by changes in the brain which result in a compulsive desire to use a drug. A combination of many factors including genetics, environment and behavior influence a person's addiction risk, making it an incredibly complicated disease. The new science of addiction considers all of these factors - from biology to family - to unravel the complexities of the addicted brain. * Natural Reward Pathways Exist in the Brain: The reward pathway is responsible for driving our feelings of motivation, reward and behavior. * Drugs Alter the Brain's Reward Pathway: Drugs work over time to change the reward pathway and affect the entire brain, resulting in addiction. * Genetics Is An Important Factor In Addiction: Genetic susceptibility to addiction is the result of the interaction of many genes. * Timing and Circumstances Influence Addiction: If you use drugs when you are an adolescent, you are more likely to develop lifetime addiction. An individual's social environment also influences addiction risk. * Challenges and Issues in Addiction: Addiction impacts society with many ethical, legal and social issues. | drug abuse, drug delivery, drug, drug of abuse, environmental risk factor, genetic factor, genetics, addiction, gene, treatment, brain, brain circuit, pathway, human, lesson plan, neuron, reward pathway, spanish, teacher, chronic disease | has parent organization: University of Utah Genetic Science Learning Center - Learn Genetics | Substance-Related Disorder | NIDA 1 R25 DA 15461 | Free | nif-0000-00430 | SCR_002770 | 2026-02-11 10:56:32 | 3 | ||||||
|
Macaque.org Resource Report Resource Website 1+ mentions |
Macaque.org (RRID:SCR_002767) | Macaque.org | portal, data or information resource, topical portal, organization portal, laboratory portal, research forum portal, disease-related portal | THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone.. Documented on June 8, 2020.Macaque genomic and proteomic resources and how they are providing important new dimensions to research using macaque models of infectious disease. The research encompasses a number of viruses that pose global threats to human health, including influenza, HIV, and SARS-associated coronavirus. By combining macaque infection models with gene expression and protein abundance profiling, they are uncovering exciting new insights into the multitude of molecular and cellular events that occur in response to virus infection. A better understanding of these events may provide the basis for innovative antiviral therapies and improvements to vaccine development strategies. | genomic, hiv, infection, proteomic, virus, simian immunodeficiency virus, influenza virus, animal model | has parent organization: University of Washington; Seattle; USA | Viral infection, Infectious disease | NCRR ; NIAID ; NHLBI ; NIDA |
THIS RESOURCE IS NO LONGER IN SERVICE | nif-0000-24370 | SCR_002767 | Macaque.org | 2026-02-11 10:56:39 | 3 | |||||
|
Inter-university Consortium for Political and Social Research (ICPSR) Resource Report Resource Website 10+ mentions |
Inter-university Consortium for Political and Social Research (ICPSR) (RRID:SCR_003194) | ICPSR | organization portal, portal, data or information resource, consortium | Data archive of more than 500,000 files of research in the social sciences, hosting 16 specialized collections of data in education, aging, criminal justice, substance abuse, terrorism, and other fields. ICPSR comprises a consortium of about 700 academic institutions and research organizations providing training in data access, curation, and methods of analysis for the social science research community. ICPSR welcomes and encourages deposits of digital data. ICPSR's educational activities include the Summer Program in Quantitative Methods of Social Research external link, a comprehensive curriculum of intensive courses in research design, statistics, data analysis, and social methodology. ICPSR also leads several initiatives that encourage use of data in teaching, particularly for undergraduate instruction. ICPSR-sponsored research focuses on the emerging challenges of digital curation and data science. ICPSR researchers also examine substantive issues related to our collections, with an emphasis on historical demography and the environment. | psychiatry, survey, digital, social science, data archive, education, criminal justice, terrorism, child care, early education, data sharing, health, medical care, minority, mental health, political science, demography, economics, history, gerontology, public health, terrorism, psychology, sociology, foreign policy, terrorism, psychology, law |
uses: DataCite lists: Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) lists: Mexican Health and Aging Study lists: Human Mortality Database lists: Religion Aging and Health Survey lists: Resources for Enhancing Alzheimers Caregiver Health lists: Seattle Longitudinal Study lists: Social Environment and Biomarkers of Aging Study in Taiwan lists: Indonesia Family Life Survey lists: Piedmont Health Survey of the Elderly lists: English Longitudinal Study of Ageing lists: Luxembourg Income Study lists: Alameda County Health and Ways of Living Study lists: Second Malaysian Family Life Survey lists: Charleston Heart Study lists: Census Microdata Samples Project lists: Chinese Longitudinal Healthy Longevity Survey (CLHLS) lists: Established Populations for Epidemiologic Studies of the Elderly lists: Los Angeles Family and Neighborhood Survey lists: Health and Retirement Study lists: Iowa 65+ Rural Health Study lists: Longitudinal Study of Generations lists: Longitudinal Study of Elderly Mexican American Health lists: Matlab Health and Socio-Economic Survey lists: National Long Term Care Survey lists: National Longitudinal Mortality Study lists: National Longitudinal Survey of Older Men lists: National Nursing Home Survey Follow-Up lists: National Social Life Health and Aging Project (NSHAP) lists: National Survey of the Japanese Elderly lists: National Survey of Midlife Development in the United States lists: Nihon University Japanese Longitudinal Study of Aging lists: Panel Study of Income Dynamics lists: Public Use Microdata Sample for the Older Population lists: International Data Base lists: German Socio-Economic Panel lists: New Beneficiary Data System lists: Longitudinal Studies of Aging lists: National Survey of Families and Households lists: National Survey of Self-Care and Aging lists: Epidemiology of Chronic Disease in the Oldest Old lists: Aging Status and Sense of Control (ASOC) is listed by: re3data.org has parent organization: University of Michigan; Ann Arbor; USA is parent organization of: National Addiction and HIV Data Archive Program (NAHDAP) is parent organization of: National Archive of Computerized Data on Aging (NACDA) is parent organization of: Substance Abuse and Mental Health Data Archive |
Aging, Substance abuse, Addiction, HIV | NIH ; NIA ; NICHD ; NIDA |
nif-0000-00615 | http://www.icpsr.umich.edu/icpsrweb/landing.jsp | SCR_003194 | Interuniversity Consortium for Political Social Research, Inter-university Consortium for Political Social Research (ICPSR), Interuniversity Consortium for Political and Social Research | 2026-02-11 10:56:42 | 39 | |||||
|
Mouse Phenome Database (MPD) Resource Report Resource Website 100+ mentions |
Mouse Phenome Database (MPD) (RRID:SCR_003212) | MPD | data repository, data or information resource, database, narrative resource, experimental protocol, service resource, storage service resource | Database enables integration of genomic and phenomic data by providing access to primary experimental data, data collection protocols and analysis tools. Data represent behavioral, morphological and physiological disease-related characteristics in naive mice and those exposed to drugs, environmental agents or other treatments. Collaborative standardized collection of measured data on laboratory mouse strains to characterize them in order to facilitate translational discoveries and to assist in selection of strains for experimental studies. Includes baseline phenotype data sets as well as studies of drug, diet, disease and aging effect., protocols, projects and publications, and SNP, variation and gene expression studies. Provides tools for online analysis. Data sets are voluntarily contributed by researchers from variety of institutions and settings, or retrieved by MPD staff from open public sources. MPD has three major types of strain-centric data sets: phenotype strain surveys, SNP and variation data, and gene expression strain surveys. MPD collects data on classical inbred strains as well as any fixed-genotype strains and derivatives that are openly acquirable by the research community. New panels include Collaborative Cross (CC) lines and Diversity Outbred (DO) populations. Phenotype data include measurements of behavior, hematology, bone mineral density, cholesterol levels, endocrine function, aging processes, addiction, neurosensory functions, and other biomedically relevant areas. Genotype data are primarily in the form of single-nucleotide polymorphisms (SNPs). MPD curates data into a common framework by standardizing mouse strain nomenclature, standardizing units (SI where feasible), evaluating data (completeness, statistical power, quality), categorizing phenotype data and linking to ontologies, conforming to internal style guides for titles, tags, and descriptions, and creating comprehensive protocol documentation including environmental parameters of the test animals. These elements are critical for experimental reproducibility. | female, genomic location, genotype, inbred strain, male, mouse strain, phenome, phenotype, qtl, reference data, single-nucleotide polymorphism, strain allele, strain characteristic, strain, trait, gene expression, variation, hypothesis testing, data set, bio.tools, FASEB list |
is used by: NIF Data Federation is used by: Integrated Datasets is used by: NIH Heal Project is listed by: re3data.org is listed by: bio.tools is listed by: Debian is related to: Special Mouse Strains Resource is related to: Vertebrate Trait Ontology is related to: GenomeMUSter has parent organization: Jackson Laboratory |
NIDA ; NHGRI HG003057; NHLBI HL66611; NIA AG025707; NIA AG038070; NIMH MH071984; NIDA DA028420 |
PMID:24243846 PMID:22102583 PMID:18987003 PMID:17151079 |
Free, Freely available | biotools:mpd, nif-0000-03160, r3d100010101 | https://bio.tools/mpd https://doi.org/10.17616/R3PC7F |
http://www.jax.org/phenome | SCR_003212 | Mouse Phenome Database | 2026-02-11 10:56:42 | 221 | |||
|
Michigan Molecular Interactions Resource Report Resource Website 1+ mentions |
Michigan Molecular Interactions (RRID:SCR_003521) | MiMI | production service resource, data or information resource, database, software resource, web service, data access protocol, data analysis service, service resource, analysis service resource | 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 | 2026-02-11 10:56:45 | 5 | |||||||
|
miniTUBA Resource Report Resource Website |
miniTUBA (RRID:SCR_003447) | miniTUBA | analysis service resource, service resource, production 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 | 2026-02-11 10:56:44 | 0 | |||||
|
OpenNeuro Resource Report Resource Website 100+ mentions |
OpenNeuro (RRID:SCR_005031) | OpenNeuro, OpenfMRI | data repository, data or information resource, database, image repository, service resource, storage service resource | Open platform for analyzing and sharing neuroimaging data from human brain imaging research studies. Brain Imaging Data Structure ( BIDS) compliant database. Formerly known as OpenfMRI. Data archives to hold magnetic resonance imaging data. Platform for sharing MRI, MEG, EEG, iEEG, and ECoG data. | neuroinformatics, database, storing, dataset, neuroimaging, data, MRI, MEG, EEG, iEEG, ECoG, FASEB list |
uses: Brain Imaging Data Structure (BIDs) uses: HED Tags is used by: studyforrest.org is used by: DataLad is used by: NIF Data Federation is used by: Integrated Datasets is used by: NIH Heal Project is used by: Baby Open Brains is recommended by: National Library of Medicine is recommended by: BRAIN Initiative is recommended by: NIDDK Information Network (dkNET) is recommended by: NIDDK - National Institute of Diabetes and Digestive and Kidney Diseases is listed by: NeuroImaging Tools and Resources Collaboratory (NITRC) is listed by: re3data.org is listed by: DataCite is listed by: FAIRsharing is affiliated with: NEMAR is related to: Integrated Manually Extracted Annotation has parent organization: Stanford University; Stanford; California has parent organization: Stanford Center for Reproducible Neuroscience has parent organization: BRAIN Initiative is provided by: OpenNeuro |
NSF OCI1131441; NIDA ; Laura and John Arnold Foundation ; Stanford ; Squishymedia ; BRAIN Initiative ; NIMH |
Free, Freely available | DOI:10.25504/FAIRsharing.s1r9bw, r3d100010924, nlx_144048, DOI:10.17616/R33047, DOI:10.18112 | http://www.nitrc.org/projects/openfmri https://github.com/OpenNeuroDatasets https://doi.org/10.17616/R33047 https://doi.org/10.17616/r33047 https://doi.org/10.18112/ https://dx.doi.org/10.18112/ https://fairsharing.org/10.25504/FAIRsharing.s1r9bw https://doi.org/10.17616/R33047 |
http://openfmri.org | SCR_005031 | OpenfMRI, Open fMRI, OpenNeuro | 2026-02-11 10:57:01 | 247 | ||||
|
NIDA Podcasts Resource Report Resource Website |
NIDA Podcasts (RRID:SCR_005660) | NIDA Podcasts | podcast, narrative resource, data or information resource | Audio clips that highlight research efforts at the National Institute on Drug Abuse and include interviews with prominent NIDA scientists. To listen to these clips, just click Listen Now under the clip summary. You must have Real Media Player or Windows Media Player installed to download these clips. To view a printable transcript of a clip, click View Transcript under the clip summary. | drug abuse, transcript | has parent organization: National Institute on Drug Abuse | NIDA | All of these clips are free from copyright and can be used for broadcast or other use with acknowledgement of the National Institute on Drug Abuse. | nlx_149377 | SCR_005660 | 2026-02-11 10:57:08 | 0 | |||||||
|
Open Connectome Project Resource Report Resource Website 1+ mentions |
Open Connectome Project (RRID:SCR_004232) | Open Connectome Project | production service resource, data repository, data or information resource, image repository, software resource, analysis service resource, web service, data set, data access protocol, source code, data analysis service, service resource, storage service resource | THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 9, 2023. Connectomes repository to facilitate the analysis of connectome data by providing a unified front for connectomics research. With a focus on Electron Microscopy (EM) data and various forms of Magnetic Resonance (MR) data, the project aims to make state-of-the-art neuroscience open to anybody with computer access, regardless of knowledge, training, background, etc. Open science means open to view, play, analyze, contribute, anything. Access to high resolution neuroanatomical images that can be used to explore connectomes and programmatic access to this data for human and machine annotation are provided, with a long-term goal of reconstructing the neural circuits comprising an entire brain. This project aims to bring the most state-of-the-art scientific data in the world to the hands of anybody with internet access, so collectively, we can begin to unravel connectomes. Services: * Data Hosting - Their Bruster (brain-cluster) is large enough to store nearly any modern connectome data set. Contact them to make your data available to others for any purpose, including gaining access to state-of-the-art analysis and machine vision pipelines. * Web Viewing - Collaborative Annotation Toolkit for Massive Amounts of Image Data (CATMAID) is designed to navigate, share and collaboratively annotate massive image data sets of biological specimens. The interface is inspired by Google Maps, enhanced to allow the exploration of 3D image data. View the fork of the code or go directly to view the data. * Volume Cutout Service - RESTful API that enables you to select any arbitrary volume of the 3d database (3ddb), and receive a link to download an HDF5 file (for matlab, C, C++, or C#) or a NumPy pickle (for python). Use some other programming language? Just let them know. * Annotation Database - Spatially co-registered volumetric annotations are compactly stored for efficient queries such as: find all synapses, or which neurons synapse onto this one. Create your own annotations or browse others. *Sample Downloads - In addition to being able to select arbitrary downloads from the datasets, they have also collected a few choice volumes of interest. * Volume Viewer - A web and GPU enabled stand-alone app for viewing volumes at arbitrary cutting planes and zoom levels. The code and program can be downloaded. * Machine Vision Pipeline - They are building a machine vision pipeline that pulls volumes from the 3ddb and outputs neural circuits. - a work in progress. As soon as we have a stable version, it will be released. * Mr. Cap - The Magnetic Resonance Connectome Automated Pipeline (Mr. Cap) is built on JIST/MIPAV for high-throughput estimation of connectomes from diffusion and structural imaging data. * Graph Invariant Computation - Upload your graphs or streamlines, and download some invariants. * iPad App - WholeSlide is an iPad app that accesses utilizes our open data and API to serve images on the go. | human, primary visual cortex, data sharing, male, electron microscopy, mri, connectome, annotation, image collection, array tomography |
is listed by: NeuroImaging Tools and Resources Collaboratory (NITRC) is related to: CATMAID is related to: neurodata is parent organization of: Rambo3D |
Johns Hopkins University; Maryland; USA ; JHU Applied Research Laboratory IRAD ; JHU Whiting School of Engineering ; Dean's Award ; NIBIB 1RO1EB016411-01 (CRCNS); DARPA N66001-14-1-4028 (GRAPHS); NSF ACI-1261715; NSF OCI-1040114; NIDA 1R01DA036400-01; |
PMID:23707591 | THIS RESOURCE IS NO LONGER IN SERVICE | SciRes_000189, nlx_143645 | http://openconnecto.me http://www.nitrc.org/projects/ocp/ |
SCR_004232 | openconnectomeproject, Open Connectome Project: Collectively reverse-engineering the brain one synapse at a time., Open Connectome Project: Collectively reverse-engineering the brain one synapse at a time | 2026-02-11 10:56:50 | 7 | ||||
|
Brain Architecture Project Resource Report Resource Website 10+ mentions |
Brain Architecture Project (RRID:SCR_004283) | portal, topical portal, data or information resource | Evolving portal that will provide interactive tools and resources to allow researchers, clinicians, and students to discover, analyze, and visualize what is known about the brain's organization, and what the evidence is for that knowledge. This project has a current experimental focus: creating the first brainwide mesoscopic connectivity diagram in the mouse. Related efforts for the human brain currently focus on literature mining and an Online Brain Atlas Reconciliation Tool. The primary goal of the Brain Architecture Project is to assemble available knowledge about the structure of the nervous system, with an ultimate emphasis on the human CNS. Such information is currently scattered in research articles, textbooks, electronic databases and datasets, and even as samples on laboratory shelves. Pooling the knowledge across these heterogeneous materials - even simply getting to know what we know - is a complex challenge that requires an interdisciplinary approach and the contributions and support of the greater community. Their approach can be divided into 4 major thrusts: * Literature Curation and Text Mining * Computational Analysis * Resource Development * Experimental Efforts | central nervous system, connectivity, mapping, model, neuroanatomy, organism, post-mortem, structure, nervous system, structure, human, mouse, brain, zebra finch, addiction gene, addiction |
is used by: BICCN lists: Allen Institute for Brain Science lists: University of California at Los Angeles; California; USA is related to: Mouse Brain Architecture Project is related to: BICCN Anatomy and Morphology Project is related to: Allen Institute for Brain Science has parent organization: Cold Spring Harbor Laboratory is parent organization of: Human Brain Connectivity Database is parent organization of: OBART is parent organization of: Zebrafinch Brain Architecture Project is parent organization of: Mouse Brain Architecture Project |
W. M. Keck Foundation ; NIMH ; NIDA ; Crick-Clay Professorship in Biomathematics at CSHL ; Mathers Foundation ; Simons Foundation |
Free, Public | nlx_143664 | SCR_004283 | BrainArchitecture.org, BrainArchitecture | 2026-02-11 10:56:51 | 14 | |||||||
|
CAMO - Cell Adhesion Molecule Ontology Resource Report Resource Website 1+ mentions |
CAMO - Cell Adhesion Molecule Ontology (RRID:SCR_004392) | CAMO | ontology, controlled vocabulary, data or information resource | CAMO (Cell Adhesion Molecule Ontology) is a set of standard vocabulary that provide a hierarchical description of cell adhesion molecules and their functions. We compiled a list for cell adhesion molecules by integrating Gene Ontology annotations, domain structure information, and keywords query against NCBI Entrez Gene annotations. Totally 496 unique human genes were identified to function as cell adhesion molecules, which is by far the most comprehensive dataset including cadherin, immunoglobulin/FNIII, integrin, neurexin, neuroligan, and catenin families. CAMO was constructed as a directed acyclic graph (DAG) using DAG-Edit to input, manage and update data. We annotated each term with name, definition and source references, as well as the relationship to other terms, based on manual reviews of domain architecture and functional annotations. If vertices represent terms and the relationships between terms are represented by edges, the terms in a DAG can be connected via a directed graph without cycles. CAMO thus provides a hierarchical description of functions of CAMs with five top-level categories: CAM gene families, CAM genetics, CAM regulation, CAM expression and CAM diseases. Each top-level term is further divided into several categories to describe the functions in detail. | cell adhesion, molecule, function, cell adhesion molecule |
has parent organization: Peking University; Beijing; China has parent organization: OKCAM: Ontology-based Knowledgebase for Cell Adhesion Molecules |
NIDA | nlx_40219 | SCR_004392 | Cell Adhesion Molecule Ontology | 2026-02-11 10:56:53 | 2 | |||||||
|
Schistosoma mansoni Database Resource Report Resource Website 10+ mentions |
Schistosoma mansoni Database (RRID:SCR_004341) | SchistoDB | data repository, data or information resource, database, service resource, storage service resource | SchistoDB is a genomic database for the parasitic organism Schistosoma mansoni, one of the major causative agents of schistosomiasis worldwide. It currently incorporates sequences and annotation for S. mansoni in a single user-friendly database. Several genomic scale analyses are available as well as ESTs, oligonucleotides, metabolic pathways and drugs. Make your data available: If you''d like to have your updates and/or datasets integrated in SchistoDB, drop us an email. | FASEB list | has parent organization: Rene Rachou Research Center - FIOCRUZ; Belo Horizonte; Brazil | NIDA 5D43TW007012-03 | PMID:18842636 | nif-0000-03438 | SCR_004341 | 2026-02-11 10:56:52 | 36 |
Can't find your Tool?
We recommend that you click next to the search bar to check some helpful tips on searches and refine your search firstly. Alternatively, please register your tool with the SciCrunch Registry by adding a little information to a web form, logging in will enable users to create a provisional RRID, but it not required to submit.
Welcome to the RRID Resources search. From here you can search through a compilation of resources used by RRID and see how data is organized within our community.
You are currently on the Community Resources tab looking through categories and sources that RRID has compiled. You can navigate through those categories from here or change to a different tab to execute your search through. Each tab gives a different perspective on data.
If you have an account on RRID then you can log in from here to get additional features in RRID such as Collections, Saved Searches, and managing Resources.
Here is the search term that is being executed, you can type in anything you want to search for. Some tips to help searching:
If you are logged into RRID you can add data records to your collections to create custom spreadsheets across multiple sources of data.
Here are the facets that you can filter the data by.
If you have any further questions please check out our FAQs Page to ask questions and see our tutorials. Click this button to view this tutorial again.
