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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

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

http://ccb.jhu.edu/software/glimmerhmm/

A gene finder based on a Generalized Hidden Markov Model (GHMM). Although the gene finder conforms to the overall mathematical framework of a GHMM, additionally it incorporates splice site models adapted from the GeneSplicer program and a decision tree adapted from GlimmerM. It also utilizes Interpolated Markov Models for the coding and noncoding models . Currently, GlimmerHMM's GHMM structure includes introns of each phase, intergenic regions, and four types of exons (initial, internal, final, and single).

Proper citation: GlimmerHMM (RRID:SCR_002654) 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://neurospy.org

neurospy is a free software for functional imaging of fast neuronal activity. neurospy is a modular cross-platform application framework written in Java for the NetBeans Platform. At this time it runs on Windows XP-based LeCroy oscilloscopes and drives acousto-optic scanners via USB using the Analog Devices 9959 Direct Digital Synthesis chip. This combination makes one of the most powerful systems for scanning microscopy available today at any price. neurospy is very easy to port to other kinds of acquisition and scanning hardware.

Proper citation: neurospy (RRID:SCR_007016) 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://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

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

https://www.biotech.cornell.edu/core-facilities-brc/facilities/epigenomics-facility

Provides service that maps protein DNA interactions genome wide, tracks experimental metadata, and implements quality controlled data processing and research based analysis pipelines. Provides epigenomic and bioinformatic research resources and services that include sample preparation services and data generation. Open source platforms enable and reinforce FAIR data practices. Core is able to receive and process cell and tissue samples for various diagnostic epigenetic assays.

Proper citation: Cornell University BRC Epigenomics Core Facility (RRID:SCR_021287) Copy   

•   Source: SciCrunch Registry

https://brcf.medicine.umich.edu/cores/bioinformatics-core/

Core helps researchers identify and interpret patterns in RNA and DNA by placing sequencing data into biologically meaningful context. Services include experimental design, developing reproducible workflows, analyzing next-generation sequencing data, and supporting manuscript development/publication.

Proper citation: University of Michigan Medical School Bioinformatics Core (RRID:SCR_019168) 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://bivi.co/visualisation/apinatomy

Software toolkit for visualizing multiscale anatomy schematics with phenotype related information. Used for visualisation of multiscale physiology circuitboards and to support clinical and scientific graphical user interfaces and dashboards for biomedical resource management and data analytics. Creates FAIR models of vascular and neural connectivity information for molecular, subcellular, cellular and tissue conduits across multiple scales. Provides interface between physiology knowledge and data relevant to physiology through intuitive graphical interface for managing semantic metadata and ontologies relevant to physiology. Brings together expertise in computer science, image processing, bioengineering and medicine to manage knowledge in physiology and pathology., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: ApiNATOMY (RRID:SCR_018998) Copy   

•   Source: SciCrunch Registry

https://ncats.nih.gov/n3c/about

Portal for centralized national data to study COVID-19 and identify potential treatments.Centralized, secure analytics platform where patient privacy is protected. Enables collection and analysis of clinical, laboratory and diagnostic data from hospitals and health care plans. Data are provided after executing data transfer agreement with National Center for Advancing Translational Sciences. N3C is partnership among NCATS supported Clinical and Translational Science Awards Program hubs and National Center for Data to Health with overall stewardship by NCATS.

Proper citation: National COVID Cohort Collaborative (RRID:SCR_018757) Copy   

•   Source: SciCrunch Registry

https://portal.imaging.datacommons.cancer.gov

Portal for finding and analyzing cancer imaging data. Part of Cancer Research Data Commons to support cancer imaging research. Provides cloud based access to medical imaging data and library of analytical tools and workflows to share, analyze, and visualize multi modal imaging data from both clinical and basic cancer research studies.

Proper citation: NCI Imaging Data Commons (RRID:SCR_019127) Copy   

•   Source: SciCrunch Registry

https://datacommons.cancer.gov

Cloud based data science infrastructure that provides secure access to cancer research data from NCI programs and key external cancer programs. Serves as coordinated resource for public data sharing of NCI funded programs. Users can explore and use analytical and visualization tools for data analysis. Enables to search and aggregate data across repositories including Cancer Data Service, Clinical Trial Data Commons, Genomic Data Commons, Imaging Data Commons, Integrated Canine Data Commons, Proteomic Data Commons.

Proper citation: Cancer Research Data Commons (RRID:SCR_019128) Copy   

•   Source: SciCrunch Registry

https://www.fdilab.org

UCSD based bioinformatics lab composed of several projects in different biomedical disciplines. Established in 2008 as Neuroscience Information Framework and has since expanded to include broader field of biomedical research. Leader in developing and providing novel informatics infrastructure and tools for making data FAIR: Findable, Accessible, Interoperable and Reusable. FAIR Data informatics laboratory develops SciCrunch.org platform.

Proper citation: FAIR Data Informatics Laboratory (RRID:SCR_019235) Copy   

•   Source: SciCrunch Registry