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National Institute of Allergy and Infectious Diseases is a leading research institution to understand, treat, and prevent infectious, immunologic, and allergic diseases.
Proper citation: NIAID (RRID:SCR_016598) Copy
https://niaid.github.io/spice/
Software application for data mining and visualization. Used for analyzes of large FLOWJO data sets from polychromatic flow cytometry and organizing the normalized data graphically.
Proper citation: SPICE (RRID:SCR_016603) Copy
https://sleepdata.org/datasets/cfs
Portal for family based study of sleep apnea. Contains data for quantifying the familial aggregation of sleep apnea. The polysomnographic (PSG) montage signals: EEG, ECG, EOG, EMG, SpO2, plethysmography, airflow (thermistor), nasal pressure, respiratory effort, position, snore.
Proper citation: Cleveland Family Study (RRID:SCR_016585) 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
Free, cloud-based platform for publishing, sharing, and processing standardized neurophysiology data, primarily using the Neurodata Without Borders (NWB) format. Supported by the BRAIN Initiative, it enables researchers to collaborate, reuse datasets, and adhere to FAIR data principles.
Proper citation: Distributed Archives for Neurophysiology Data Integration (RRID:SCR_017571) Copy
https://bioinformaticshome.com/tools/rna-seq/descriptions/LIGER.html
Software R package for integrating and analyzing multiple single-cell datasets. It relies on integrative non-negative matrix factorization to identify shared and dataset-specific factors. Used for analysis of multiple scRNA-seq data sets.
Proper citation: LIGER (RRID:SCR_018100) Copy
Generate gene trap insertions using mutagenic polyA trap vectors, followed by sequence tagging to develop a library of mutagenized ES cells freely available to the scientific community. This library is searchable by sequence or key word searches including gene name or symbol, chromosome location, or Gene Ontology (GO) terms. In addition,they offer a custom email alert service in which researchers are able to submit search criteria. Researchers will receive automated e-mail notification of matching gene trap clones as they are entered into the library and database. The resource features the use of complementary second and third generation polyA trap vectors developed by the Stanford lab and the laboratory of Professor Yasumasa Ishida of the Nara Institute of Science and Technology (NAIST) in Japan to mutagenize murine embryonic stem (ES) cells. CMHD gene trap clones are distributed by the Canadian Mouse Mutant Repository(CMMR). Information about ordering, services, and pricing can be found on their web site (http://www.cmmr.ca/services/index.html)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 15,2026.
Proper citation: Centre for Modeling Human Disease Gene Trap Resource (RRID:SCR_002785) Copy
Gene expression data and maps of mouse central nervous system. Gene expression atlas of developing adult central nervous system in mouse, using in situ hybridization and transgenic mouse techniques. Collection of pictorial gene expression maps of brain and spinal cord of mouse. Provides tools to catalog, map, and electrophysiologically record individual cells. Application of Cre recombinase technologies allows for cell-specific gene manipulation. Transgenic mice created by this project are available to scientific community.
Proper citation: Gene Expression Nervous System Atlas (RRID:SCR_002721) Copy
http://hapmap.ncbi.nlm.nih.gov/
THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. A multi-country collaboration among scientists and funding agencies to develop a public resource where genetic similarities and differences in human beings are identified and catalogued. Using this information, researchers will be able to find genes that affect health, disease, and individual responses to medications and environmental factors. All of the information generated by the Project will be released into the public domain. Their goal is to compare the genetic sequences of different individuals to identify chromosomal regions where genetic variants are shared. Public and private organizations in six countries are participating in the International HapMap Project. Data generated by the Project can be downloaded with minimal constraints. HapMap project related data, software, and documentation include: bulk data on genotypes, frequencies, LD data, phasing data, allocated SNPs, recombination rates and hotspots, SNP assays, Perlegen amplicons, raw data, inferred genotypes, and mitochondrial and chrY haplogroups; Generic Genome Browser software; protocols and information on assay design, genotyping and other protocols used in the project; and documentation of samples/individuals and the XML format used in the project.
Proper citation: International HapMap Project (RRID:SCR_002846) Copy
http://www.broadinstitute.org/gsea/
Software package for interpreting gene expression data. Used for interpretation of a large-scale experiment by identifying pathways and processes.
Proper citation: Gene Set Enrichment Analysis (RRID:SCR_003199) Copy
http://www.humanconnectomeproject.org/
A multi-center project comprising two distinct consortia (Mass. Gen. Hosp. and USC; and Wash. U. and the U. of Minn.) seeking to map white matter fiber pathways in the human brain using leading edge neuroimaging methods, genomics, architectonics, mathematical approaches, informatics, and interactive visualization. The mapping of the complete structural and functional neural connections in vivo within and across individuals provides unparalleled compilation of neural data, an interface to graphically navigate this data and the opportunity to achieve conclusions about the living human brain. The HCP is being developed to employ advanced neuroimaging methods, and to construct an extensive informatics infrastructure to link these data and connectivity models to detailed phenomic and genomic data, building upon existing multidisciplinary and collaborative efforts currently underway. Working with other HCP partners based at Washington University in St. Louis they will provide rich data, essential imaging protocols, and sophisticated connectivity analysis tools for the neuroscience community. This project is working to achieve the following: 1) develop sophisticated tools to process high-angular diffusion (HARDI) and diffusion spectrum imaging (DSI) from normal individuals to provide the foundation for the detailed mapping of the human connectome; 2) optimize advanced high-field imaging technologies and neurocognitive tests to map the human connectome; 3) collect connectomic, behavioral, and genotype data using optimized methods in a representative sample of normal subjects; 4) design and deploy a robust, web-based informatics infrastructure, 5) develop and disseminate data acquisition and analysis, educational, and training outreach materials.
Proper citation: MGH-USC Human Connectome Project (RRID:SCR_003490) Copy
Ontology that describes structures from the dimensional range encompassing cellular and subcellular structure, supracellular domains, and macromolecules. It is built according to ontology development best practices (re-use of existing ontologies; formal definitions of terms; use of foundational ontologies). It describes the parts of neurons and glia and how these parts come together to define supracellular structures such as synapses and neuropil. Molecular specializations of each compartment and cell type are identified. The SAO was designed with the goal of providing a means to annotate cellular and subcellular data obtained from light and electron microscopy, including assigning macromolecules to their appropriate subcellular domains. The SAO thus provides a bridge between ontologies that describe molecular species and those concerned with more gross anatomical scales. Because it is intended to integrate into ontological efforts at these other scales, particular care was taken to construct the ontology in a way that supports such integration.
Proper citation: Subcellular Anatomy Ontology (RRID:SCR_003486) Copy
http://elementsofmorphology.nih.gov/
Data set of standardized terms used to describe human morphology including definitions of terms for the craniofacies in general, the major components of the face, and the hands and feet. This provides a uniform and internationally accepted terms to describe the human phenotype.
Proper citation: elements of morphology (RRID:SCR_003707) Copy
https://bioportal.bioontology.org/ontologies/NEMO/?p=summary
Ontology that describes classes of event-related brain potentials (ERP) and their properties, including spatial, temporal, and functional (cognitive / behavioral) attributes, and data-level attributes (acquisition and analysis parameters). Its aim is to support data sharing, logic-based queries and mapping/integration of patterns across data from different labs, experiment paradigms, and modalities (EEG/MEG).
Proper citation: NEMO Ontology (RRID:SCR_003386) 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
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Database of human nutrition research and research training activities supported by the federal government. Information regarding trends in nutrition research, specific institutions and investigators involved in this research, or areas of agency emphases can be obtained from database searches or from published summary reports. Data for the system is prepared and submitted by participating agencies, and is updated annually. The database contains several thousand projects for each of fiscal years 1985present. Participating agencies include the Department of Health and Human Services, the U.S. Department of Agriculture, the Department of Veteran Affairs, the Agency for International Development, the Department of Defense, Department of Commerce, National Science Foundation, and the National Aeronautics and Space Administration.
Proper citation: Human Nutrition Research Information Management (RRID:SCR_001471) Copy
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