Tools   Select Another Resource Report Type

https://obofoundry.org/ontology/cl.html

Ontology designed as a structured controlled vocabulary for cell types. It was constructed for use by the model organism and other bioinformatics databases. It includes cell types from prokaryotes, mammals, and fungi. The ontology is available in the formats adopted by the Open Biological Ontologies umbrella and is designed to be used in the context of model organism genome and other biological databases.

Proper citation: Cell Type Ontology (RRID:SCR_004251) Copy   

•   Source: SciCrunch Registry

http://crcns.org

Website for brain experimental data and other resources such as stimuli and analysis tools. Provides marketplace and discussion forum for sharing tools and data in neuroscience. Data repository and collaborative tool that supports integration of theoretical and experimental neuroscience through collaborative research projects. CRCNS offers funding for new class of proposals focused on data sharing and other resources.

Proper citation: CRCNS (RRID:SCR_005608) Copy   

•   Source: SciCrunch Registry

https://www.facebase.org/

A web portal that provides access to data, tools and materials that will aid in craniofacial research. Included is access to genomic and imaging based data sets from a variety of species, including zebrafish, human and mouse.

Proper citation: FaceBase (RRID:SCR_005998) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/pubmedcommons/

A forum where authors who have published in PubMed may comment on any publication in PubMed. Members of PubMed Commons are not anonymous and must agree to certain terms and guidelines concerning appropriate and inapproriate comments.

Proper citation: Pubmed Commons (RRID:SCR_014021) Copy   

•   Source: SciCrunch Registry

https://metagenote.niaid.nih.gov/

Quick and intuitive way to annotate data from genomics studies including microbiome. Project to aid researchers in applying standardized metadata describing what, where, how, and when of samples collected in genomics study. Collection of METAdata of GEnomics studies on web based NOTEbook. Metadata are stored in centralized repository and validated according to guidelines from Genomics Standard Consortium, which are also supported by repositories and large microbiome initiatives such as NCBI, European Bioinformatics Institute (EBI), and Earth Microbiome Project. Upon request from researchers, data will also be submitted for publication via NCBI Sequence Read Archive (SRA) repository.

Proper citation: METAGENOTE (RRID:SCR_018494) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://glycam.org/

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   

•   Source: SciCrunch Registry

https://nationalmaglab.org/user-facilities/icr

Facility provides service operations for sample analysis that requires ultrahigh resolution and high mass accuracy of Fourier Transform Ion Cyclotron Resonance. Used for research in biomolecular analysis, hydrogen-deuterium exchange and environmental and petrochemical analysis. Four FT-ICR mass spectrometers feature high magnetic fields including the world-record 21 tesla and are compatible with multiple ionization and fragmentation techniques.

Proper citation: National High Magnetic Field Laboratory Ion Cyclotron Resonance Core Facility (RRID:SCR_017361) Copy   

•   Source: SciCrunch Registry

https://nationalmaglab.org/user-facilities/emr/

EMR Facility offers home-built, high-frequency and high-field continuous-wave instruments providing frequency coverage from 9 GHz to 1 THz, with additional frequencies available up to 2.5 THz using molecular gas laser. EMR covers variety of magnetic resonance techniques associated with electron like Electron Paramagnetic/Spin Resonance (EPR/ESR). EPR/ESR can be performed on any sample that has unpaired electron spins and used in applications in physics, materials science, chemistry and biology, including studies of impurity states, molecular clusters, antiferromagnetic, ferromagnetic and thin film compounds, natural or induced radicals, optically excited paramagnetic states, electron spin-based quantum information devices, transition-metal based catalysts; and for structural and dynamical studies of metallo-proteins, spin-labeled proteins and other complex bio-molecules and their synthetic models.

Proper citation: National High Magnetic Field Laboratory Electron Magnetic Resonance Core Facility (RRID:SCR_017359) Copy   

•   Source: SciCrunch Registry

https://nationalmaglab.org/user-facilities/dc-field

Facility located at MagLab headquarters near Florida State University in Tallahassee. Contains 14 resistive magnet cells connected to 56 megawatt DC power supply and 15,000 square feet of cooling equipment to remove heat generated by magnets. Includes several superconducting magnets operating at millikelvin temperatures. Among these instruments is 45-tesla hybrid magnet, which offers scientists strongest continuous magnetic field in world. Research is supported by magnet plant and cryogenic system operators. Technicians design, build and repair instruments for user research.

Proper citation: National High Magnetic Field Lab DC Field Core Facility (RRID:SCR_017358) Copy   

•   Source: SciCrunch Registry

http://mass-spec.stanford.edu

Core mass spec and proteomic services include open access lab for trained users with GC/MS, LC/MS, high resolution LC/MS, and MALDI-TOF instruments, help with intact protein analysis, targeted quantitation, drug discovery support, pathway analysis, protein interactions, FFPE tissue analysis, both labeled and label-free proteomics, and more. Please contact SUMS to discuss these and other custom projects including new application development.

Proper citation: Stanford University Vincent Coates Foundation Mass Spectrometry Laboratory Core Facility (RRID:SCR_017801) Copy   

•   Source: SciCrunch Registry

https://www.unmc.edu/vcr/cores/vcr-cores/flow-cytometry/index.html

Provides central location for flow cytometry instrumentation and education. Services include Flow Cytometry,Cell sorting, data analysis, training. Software packages to analyze data include ModFit LT, BD FACSDiva v6, Cell Quest Pro, and FlowJo vX, from facility workstations.

Proper citation: Nebraska University Medical Center Flow Cytometry Research Core Facility (RRID:SCR_017736) Copy   

•   Source: SciCrunch Registry

http://www.columbia.edu/cu/biology/resources/proteomics/

Core provides identification of proteins and metabolites with differential quantitative expression in cells, tissues or in protein affinity purifications. Particular emphasis is on quantitative analysis of posttranslational modifications such as phosphorylation.

Proper citation: Columbia University Quantitative Proteomics and Metabolomics Core Facility (RRID:SCR_017747) Copy   

•   Source: SciCrunch Registry

http://www.nlm.nih.gov/NIHbmic/nih_data_sharing_repositories.html

A listing of NIH supported data sharing repositories that make data accessible for reuse. Most accept submissions of appropriate data from NIH-funded investigators (and others), but some restrict data submission to only those researchers involved in a specific research network. Also included are resources that aggregate information about biomedical data and information sharing systems. The table can be sorted according by name and by NIH Institute or Center and may be searched using keywords so that you can find repositories more relevant to your data. Links are provided to information about submitting data to and accessing data from the listed repositories. Additional information about the repositories and points-of-contact for further information or inquiries can be found on the websites of the individual repositories.

Proper citation: NIH Data Sharing Repositories (RRID:SCR_003551) Copy   

•   Source: SciCrunch Registry

http://dockground.bioinformatics.ku.edu/

Data sets, tools and computational techniques for modeling of protein interactions, including docking benchmarks, docking decoys and docking templates. Adequate computational techniques for modeling of protein interactions are important because of the growing number of known protein 3D structures, particularly in the context of structural genomics. The first release of the DOCKGROUND resource (Douguet et al., Bioinformatics 2006; 22:2612-2618) implemented a comprehensive database of cocrystallized (bound) protein-protein complexes in a relational database of annotated structures. Additional releases added features to the set of bound structures, such as regularly updated downloadable datasets: automatically generated nonredundant set, built according to most common criteria, and a manually curated set that includes only biological nonobligate complexes along with a number of additional useful characteristics. Also included are unbound (experimental and simulated) protein-protein complexes. Complexes from the bound dataset are used to identify crystallized unbound analogs. If such analogs do not exist, the unbound structures are simulated by rotamer library optimization. Thus, the database contains comprehensive sets of complexes suitable for large scale benchmarking of docking algorithms. Advanced methodologies for simulating unbound conformations are being explored for the next release. The Dockground project is developed by the Vakser lab at the Center for Bioinformatics at the University of Kansas. Parts of Dockground were co-developed by Dominique Douguet from the Center of Structural Biochemistry (INSERM U554 - CNRS UMR5048), Montpellier, France.

Proper citation: Dockground: Benchmarks, Docoys, Templates, and other knowledge resources for DOCKING (RRID:SCR_007412) Copy   

•   Source: SciCrunch Registry

http://www.sb.fsu.edu/~rsref/Distribution/roadmap_distribution.htm

Software tool to display surface of macromolecule and its properties. Uses projections to map van der Waals or solvent accessible surface of macromolecule onto plane., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Roadmap (RRID:SCR_017207) Copy   

•   Source: SciCrunch Registry

http://compbio.cs.princeton.edu/conservation/

Software for scoring protein sequence conservation using the Jensen-Shannon divergence. It can be used to predict catalytic sites and residues near bound ligands.

Proper citation: Conservation (RRID:SCR_016064) Copy   

•   Source: SciCrunch Registry

https://github.com/marbl/Mash

Software tool for genome and metagenome distance estimation using MinHash. Reduces large sequences and sequence sets to small, representative sketches, from which global mutation distances can be rapidly estimated.

Proper citation: Mash (RRID:SCR_019135) Copy   

•   Source: SciCrunch Registry

https://med.nyu.edu/research/scientific-cores-shared-resources/microscopy-laboratory

Core offers comprehensive light and electron microscopy technologies. Our scientists use light microscopes and electron microscopes at resolutions ranging from centimeters to angstroms, providing clear and detailed images.We assist at every stage of your experiment, offering research-design consultation and instrument training, as well as guidance in study execution, analysis, and presentation for publication.

Proper citation: New York University School of Medicine Langone Health Microscopy Laboratory Core Facility (RRID:SCR_017934) Copy   

•   Source: SciCrunch Registry