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Center that acquires, maintains, and distributes genetic stocks and information about stocks of the small free-living nematode Caenorhabditis elegans for use by investigators initiating or continuing research on this genetic model organism. A searchable strain database, general information about C. elegans, and links to key Web sites of use to scientists, including WormBase, WormAtlas, and WormBook are available.
Proper citation: Caenorhabditis Genetics Center (RRID:SCR_007341) Copy
http://genes.mit.edu/burgelab/maxent/Xmaxentscan_scoreseq.html
Software tool as a framework for modeling the sequences of short sequence motifs based on the maximum entropy principle (MEP). Used for sequence motifs such as those involved in RNA splicing.
Proper citation: MAxEntScan (RRID:SCR_016707) Copy
https://github.com/gelles-brandeis/CoSMoS_Analysis
Software tools for analyzing co-localization single-molecule spectroscopy image data.
Proper citation: CoSMoS_Analysis (RRID:SCR_016896) Copy
http://www.bx.psu.edu/~giardine/vision/
International project to analyze mouse and human hematopoiesis, and provide a tractable system with clear clinical significance and importance to NIDDK. Collection of information from the flood of epigenomic data on hematopoietic cells as catalogs of validated regulatory modules, quantitative models for gene regulation, and a guide for translation of research insights from mouse to human.
Proper citation: ValIdated Systematic IntegratiON of epigenomic data (RRID:SCR_016921) Copy
https://panoramaweb.org/project/home/begin.view?
Repository software for targeted mass spectrometry assays from Skyline. Targeted proteomics knowledge base. Public repository for quantitative data sets processed in Skyline. Facilitates viewing, sharing, and disseminating results contained in Skyline documents.
Proper citation: PanoramaWeb (RRID:SCR_017136) Copy
Repository to make datasets resulting from NIH funded research more accessible, citable, shareable, and discoverable. Data submitted will be reviewed to ensure there is no personally identifiable information in data and metadata prior to being published and in line with FAIR -Findable, Accessible, Interoperable, and Reusable principles. Data published on Figshare is assigned persistent, citable DOI (Digital Object Identifier) and is discoverable in Google, Google Scholar, Google Dataset Search, and more.Complited on July,2020. Researches can continue to share NIH funded data and other research product on figshare.com.
Proper citation: NIH Figshare Archive (RRID:SCR_017580) Copy
Integrated genomic and functional genomic database for Entamoeba and Acanthamoeba parasites. Contains genomes of three Entamoeba species and microarray expression data for E. histolytica. Integrates whole genome sequence and annotation and includes experimental data and environmental isolate sequences provided by community researchers.
Proper citation: AmoebaDB (RRID:SCR_017592) Copy
DANDI is a platform for publishing, sharing, and processing neurophysiology data funded by the BRAIN Initiative. The archive is not just an endpoint to dump data, it is intended as a living repository that enables collaboration within and across labs, and for others, the entry point for research.
Proper citation: Distributed Archives for Neurophysiology Data Integration (RRID:SCR_017571) Copy
https://github.com/galaxyproteomics/mvpapplication-git.git
Software tool as plugin to enable viewing of results produced from workflows integrating genomic sequencing data and mass spectrometry proteomics data. Plugin to Galaxy bioinformatics workbench which enables visualization of mass spectrometry-based proteomics data integrated with genomic and/or transcriptomic sequencing data. Useful for verifying quality of results and characterizing novel peptide sequences identified using multi-omic proteogenomic approach.
Proper citation: Multi-omics Visualization Platform (RRID:SCR_018077) Copy
https://icite.od.nih.gov/covid19/search/
NIH comprehensive, curated source for publications related to COVID-19. Includes articles from PubMed and pre-prints from arXiv, medRxiv, bioRxiv, and ChemRxiv. Updated daily. NIH Office of Portfolio Analysis has developed this resource to explore and analyze set of advances in COVID‑19 research as they accumulate in real time, and complements efforts by NLM to aggregate full text documents broadly related to COVID-19 and other outbreaks, and articles on COVID‑19 specific to PubMed database.
Proper citation: NIH COVID-19 Portfolio (RRID:SCR_018295) Copy
https://datascience.nih.gov/covid-19-open-access-resources
COVID-19 open access data and computational resources provided by federal agencies, including NIH, public consortia, and private entities. Continuously updated as more information becomes available. These resources are being shared for scientific and public health interests, and content is responsibility of resource organizers.
Proper citation: Data and Computational Resources to Address COVID-19 (RRID:SCR_018274) Copy
Web provides tools for modeling 3D structures of molecules and complexes containing carbohydrates including oligosaccharide conformation modeling and glycoprotein 3D structure modeling. Used to simplify prediction of three dimensional structures of carbohydrates and macromolecular structures involving carbohydrates.
Proper citation: GLYCAM-Web (RRID:SCR_018260) Copy
https://mibig.secondarymetabolites.org/
MIBiG is genomic standards consortium project and biosynthetic gene cluster database used as reference dataset. Provides community standard for annotations and metadata on biosynthetic gene clusters and their molecular products. Standardised data format that describes minimally required information to uniquely characterise biosynthetic gene clusters. MIBiG 2.0 is expended repository for biosynthetic gene clusters of known function. MIBiG 3.0 is database update comprising large scale validation and re-annotation of existing entries and new entries. Community driven effort to annotate experimentally validated biosynthetic gene clusters.
Proper citation: Minimum Information about Biosynthetic Gene cluster (RRID:SCR_023660) Copy
https://www.jax.org/news-and-insights/2004/june/app-mouse-models-for-alzheimers-disease-research
An information resource about several models for mice to develop Alzheimer's-related characteristics as they age.
Proper citation: Mouse Models For Alzheimer's Disease Research (RRID:SCR_000708) Copy
https://www.jax.org/research-and-faculty/resources/knockout-mouse-project/high-throughput-production
Project is providing critical tools for understanding gene function and genetic causes of human diseases. Project KOMP is focused on generating targeted knockout mutations in mouse ES cells. Second phase, KOMP2, relies upon successful generation of strains of knockout mice from these ES cells. Information from JAX about their contributions to KOMP project.
Proper citation: Knockout Mouse Project (RRID:SCR_005571) Copy
https://commonfund.nih.gov/hmp/
NIH Project to generate resources to characterize the human microbiota and to analyze its role in human health and disease at several different sites on the human body, including nasal passages, oral cavities, skin, gastrointestinal tract, and urogenital tract using metagenomic and traditional approach to genomic DNA sequencing studies.HMP was supported by the Common Fund from 2007 to 2016.
Proper citation: Human Microbiome Project (RRID:SCR_012956) Copy
https://github.com/YuanXue1993/SegAN
Image analysis software for medical image segmentation. The software is fueled by an end-to-end adversarial neural network that generates segmentation label maps.
Proper citation: SegAN (RRID:SCR_016215) Copy
Nonhuman Primate reference transcriptome resource consisting of deep sequencing complete transcriptomes (RNA-seq) from multiple NHP species.
Proper citation: Nonhuman Primate Reference Transcriptome Resource (RRID:SCR_017534) Copy
Project to create complete mesoscale connectivity atlas of the C57Black/6 mouse brain and to subsequently generate its global neural networks.
Proper citation: Mouse Connectome Project (RRID:SCR_017313) Copy
The Dynamic Regulatory Events Miner (DREM) allows one to model, analyze, and visualize transcriptional gene regulation dynamics. The method of DREM takes as input time series gene expression data and static transcription factor-gene interaction data (e.g. ChIP-chip data), and produces as output a dynamic regulatory map. The dynamic regulatory map highlights major bifurcation events in the time series expression data and transcription factors potentially responsible for them. DREM 2.0 was released and supports a number of new features including: * new static binding data for mouse, human, D. melanogaster, A. thaliana * a new and more flexible implementation of the IOHMM supports dynamic binding data for each time point or as a mix of static/dynamic TF input * expression levels of TFs can be used to improve the models learned by DREM * the motif finder DECOD can be used in conjuction with DREM and help find DNA motifs for unannotated splits * new features for the visualization of expressed TFs, dragging boxes in the model view, and switching between representations
Proper citation: Dynamic Regulatory Events Miner (RRID:SCR_003080) Copy
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