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https://cde.nlm.nih.gov/

A repository of Common Data Elements (CDE). The CDE is a standardized, precisely defined question, paired with a set of allowable responses, used systematically across different sites, studies, or clinical trials to ensure consistent data collection. Multiple CDEs (from one or more Collections) can be curated into Forms. Forms in the Repository might be original, or might recreate the format of real-world data collection instruments or case report forms. NIH has endorsed collections of CDEs that meet established criteria. NIH-endorsed CDEs are designated with a gold ribbon. Users can Browse NIH-Endorsed CDEs, Browse All CDEs, or Browse Forms.

Proper citation: NIH Common Data Element Repository (RRID:SCR_001390) Copy   

•   Source: SciCrunch Registry

https://www.bioconductor.org/packages/release/bioc/html/OLIN.html

Software functions for normalization of two-color microarrays by optimised local regression and for detection of artifacts in microarray data.

Proper citation: OLIN (RRID:SCR_001304) Copy   

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http://www.bioconductor.org/packages/release/bioc/html/simpleaffy.html

Software package that provides high level functions for reading Affy .CEL files, phenotypic data, and then computing simple things with it, such as t-tests, fold changes and the like. It makes heavy use of the affy library. It also has some basic scatter plot functions and mechanisms for generating high resolution journal figures.

Proper citation: Simpleaffy (RRID:SCR_001302) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/qcmetrics.html

Software package that provides a framework for generic quality control of data. It permits to create, manage and visualise individual or sets of quality control metrics and generate quality control reports in various formats.

Proper citation: qcmetrics (RRID:SCR_001303) Copy   

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https://www.bioconductor.org/packages//2.12/bioc/html/dexus.html

Software package that identifies differentially expressed genes in RNA-Seq data under all possible study designs such as studies without replicates, without sample groups, and with unknown conditions. It works also for known conditions, for example for RNA-Seq data with two or multiple conditions. RNA-Seq read count data can be provided both by the S4 class Count Data Set and by read count matrices. Differentially expressed transcripts can be visualized by heatmaps, in which unknown conditions, replicates, and samples groups are also indicated. This software is fast since the core algorithm is written in C. For very large data sets, a parallel version of DEXUS is provided in this package. DEXUS is a statistical model that is selected in a Bayesian framework by an EM algorithm. It does not need replicates to detect differentially expressed transcripts, since the replicates (or conditions) are estimated by the EM method for each transcript. The method provides an informative/non-informative value to extract differentially expressed transcripts at a desired significance level or power.

Proper citation: DEXUS (RRID:SCR_001309) Copy   

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http://www.opencolleges.edu.au/informed/learning-strategies/

Interactive infographic of a brain exploring more than 100,000 chemical reactions, highlighted by areas and explanations of what that area is known to do.

Proper citation: Open Colleges Interactive Brain (RRID:SCR_001427) Copy   

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http://radiology.arizona.edu/CGRI/

Biomedical technology resource center that develops new gamma-ray imaging instruments and techniques that yield substantially improved spatial and temporal resolutions. The Center makes its imagers and expertise available to a wide community of biomedical and clinical researchers through collaborative and service-oriented interactions. The collaborative research applies these new imaging tools to basic research in functional genomics, proteomics, cancer, cardiovascular disease and cognitive neuroscience, and to clinical research in tumor detection and other selected topics. There are five core research projects: * Detector technology research and development * Reconstruction algorithms and system modeling * Data acquisition, signal processing, and system development * Image-quality assessment and system optimization * Techniques for molecular imaging

Proper citation: Center for Gamma Ray Imaging (RRID:SCR_001384) Copy   

•   Source: SciCrunch Registry

https://factory.euromov.eu/sml/index.php

Open source Java library dedicated to semantic measures computation and analysis. Tools based on the SML are also provided through the SML-Toolkit, a command line software giving access to some of the functionalities of the library. The SML and the toolkit can be used to compute semantic similarity and semantic relatedness between semantic elements (e.g. concepts, terms) or entities semantically characterized (e.g. entities defined in a semantic graph, documents annotated by concepts defined in an ontology).

Proper citation: Semantic Measures Library (RRID:SCR_001383) Copy   

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https://codr.c-path.org/

A repository of de-identified control arm data of patients from clinical studies of Alzheimer's disease and Mild Cognitive Impairment. It provides the ability to analyze the data online with the R statistical analysis program, create and download standard reports, run complex queries, or download data to a desktop for further analysis. Additional data will be added to the database over time. Critical Path Institute consortia members and qualified researchers may upload and work on scientific data relevant to biomarkers of drug toxicity, neurodegenerative diseases, and patient-reported outcomes.

Proper citation: CODR: C PATH On Line Data Repository (RRID:SCR_001388) Copy   

•   Source: SciCrunch Registry

https://scicrunch.org/scicrunch/data/source/nlx_154697-1/search?q=*&l=

Integrated Animals is a virtual database currently indexing available animal strains and mutants from: AGSC (Ambystoma), BCBC (mice), BDSC (flies), CWRU Cystic Fibrosis Mouse Models (mice), DGGR (flies), FlyBase (flies), IMSR (mice), MGI (mice), MMRRC (mice), NSRRC (pig), NXR (Xenopus), RGD (rats), Sperm Stem Cell Libraries for Biological Research (rats), Tetrahymena Stock Center (Tetrahymena), WormBase (worms), XGSC (Xiphophorus), ZFIN (zebrafish), and ZIRC (zebrafish).

Proper citation: Integrated Animals (RRID:SCR_001421) Copy   

•   Source: SciCrunch Registry

http://c-path.org/programs/camd/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 8, 2022. Consortium developing new technologies and methods to accelerate the development and review of medical products for neurodegenerative diseases. It is focused on accelerating drug development for patients with chronic neurodegenerative disease, namely, Alzheimer's disease (AD) and Parkinson's disease (PD), by advancing drug development tools for evaluating drug efficacy, conducting clinical trials, and streamlining the process of regulatory review. The consortium focuses on sharing precompetitive patient-level data from the control arms of legacy clinical trials, developing new tools to be submitted to the regulatory agencies, and developing consensus data standards. CAMD has the following areas of focus: (1) qualification of biomarkers, (2) development of common data standards, (3) creation of integrated databases for clinical trials data, and (4) development of quantitative model-based tools for drug development. Regulatory milestones include a qualification opinion with EMA for the use of low baseline hippocampal volume for patient enrichment in pre-dementia trials, and most recently, positive regulatory decisions from the FDA and EMA for the use of a clinical trial simulation tool to aid in trials for mild to moderate stages of AD., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: CAMD (RRID:SCR_001389) Copy   

•   Source: SciCrunch Registry

https://github.com/vital-ai/vital-documentation/wiki/Vital-AI-Ontology

Ontology for the four consensus human vital signs: blood pressure, body temperature, respiration rate, pulse rate. It provides a controlled structured vocabulary for describing vital signs measurement data, the various processes of measuring vital signs, and the various devices and anatomical entities participating in such measurements.

Proper citation: Vital Signs Ontology (RRID:SCR_001422) Copy   

•   Source: SciCrunch Registry

http://www.jcu.edu.au/

Public university in Townsville, Australia that functions as a research and teaching institution. Some well-known divisions of the university include the division of Tropical Environments and Societies, Tropical Health and Medicine, and Research and Innovation.

Proper citation: James Cook University; Townsville; Australia (RRID:SCR_001420) Copy   

•   Source: SciCrunch Registry

http://mugsy.sourceforge.net/

Software resource for multiple whole genome alignment. It uses Nucmer, a custom graph-based segmentation procedure, for pairwise alignment, and the Seqan:TCoffee's multiple alignment strategy.

Proper citation: Mugsy (RRID:SCR_001414) Copy   

•   Source: SciCrunch Registry

https://cismm.web.unc.edu/

Biomedical technology research center that develops force technologies applicable over a wide range of biological settings, from the single molecule to the tissue, with integrated systems that orchestrate facile instrument control, multimodal imaging, and analysis through visualization and modeling. The Force Microscope Technologies Core designs instruments in an area of science where there are unusual opportunities: the measurement of forces and the integration with optical microscopy. Force technologies play the obvious role of both measuring events in the sample and modifying the sample during the experiment. It is through the microscope that the force data is correlated with simultaneous 3D optical images. The force technology development includes the magnetic bead technology in the 3D Force Microscope project, Atomic Force Microscopy in the nanoManipulator project, and Control Software to drive the instrumentation. This core is focused on providing the physical capability to perform the experiments and probe structure/property correlations. The Ideal User Interfaces core makes the connection between the user and the instrument, the model building, and the data. This includes control systems that allow the user to move the bead inside the cell culture with a handheld pen and the visualization techniques to view the optical microscope data as a rendered 3D image collocated with the force data. Using data to create, change, and understand a model is the focus of the Advanced Model Fitting and Analysis core. The quantitative reduction of images to structural, shape, and velocity parameters is the goal of Image Analysis. The immediate understanding of correlations across image fields and between data sets in the challenge of Visualization. The power of combining the strength of a computer science graphics group with a microscopy technology group is most evident in the Graphics Hardware Acceleration project, which seeks to harness the speed of graphics processors for microscope data analysis and simulation. The Advanced Technology core pushes the boundaries of the Human Computer Interface through the investigation of improved techniques for the interaction of users with virtual environments, the real time lighting of virtual settings, and the enabling of multi-person collaboration. These techniques are validated and evaluated through physiological measures in virtual environments effectiveness evaluation studies.

Proper citation: Computer Integrated Systems for Microscopy and Manipulation (RRID:SCR_001413) Copy   

•   Source: SciCrunch Registry

http://octresearch.org/

Biomedical technology research center that pioneers and provides access to microscopic imaging instruments for biologic and clinical research. Optical coherence tomography (OCT) has evolved over the last two decades to become a standard of care for diagnostic ophthalmic imaging and is poised to make significant impact in the fields of cardiology and gastrointestinal endoscopy. Access to state-of-the-art instrumentation, however, has been limited to a relatively few research laboratories and the optimization of instruments for new biomedical applications has hindered the investigation of new opportunities. A major focus of CBORT will be to cultivate strategic research collaborations and respond to a pressing need for application-specific OCT instrumentation and hardware.

Proper citation: Center for Biomedical OCT Research (RRID:SCR_001418) Copy   

•   Source: SciCrunch Registry

http://www.biomemsrc.org/

Biomedical technology research center that provides biomedical investigators with novel microsystems engineering tools for biological discovery, diagnostic, prognostic, and therapeutic applications. Thrust areas of interest are the development of novel living cell-based, lab-on-a-chip type devices for sorting blood cells, for high-throughput biochemistry in small volumes, and for studying cellular behavior in controlled microenvironments.

Proper citation: BioMEMS Resource Center (RRID:SCR_001417) Copy   

•   Source: SciCrunch Registry

http://amp.pharm.mssm.edu/Enrichr/

A web-based gene list enrichment analysis tool that provides various types of visualization summaries of collective functions of gene lists. It includes new gene-set libraries, an alternative approach to rank enriched terms, and various interactive visualization approaches to display enrichment results using the JavaScript library, Data Driven Documents (D3). The software can also be embedded into any tool that performs gene list analysis. System-wide profiling of genes and proteins in mammalian cells produce lists of differentially expressed genes / proteins that need to be further analyzed for their collective functions in order to extract new knowledge. Once unbiased lists of genes or proteins are generated from such experiments, these lists are used as input for computing enrichment with existing lists created from prior knowledge organized into gene-set libraries.

Proper citation: Enrichr (RRID:SCR_001575) Copy   

•   Source: SciCrunch Registry

http://neuroinformatics.kiv.zcu.cz/articles/read/eegerp-portal-eegbase-_2014-12-19

EEG base is a system for storage and management of EEG/ERP resources - data, metadata, tools and materials related to EEG/ERP experiments. EEG base advances electrophysiology research by enabling access to public data, tools and results of research groups. The system essentially offers the following set of features (the set of accessible features depends on a specific user role): * User authentication * Storage, update, and download of EEG/ERP data and metadata * Storage, update and download of EEG/ERP experimental design (experimental scenarios) * Storage, update and download of data related to testing subjects * Fulltext search * Sharing of knowledge and working in groups The system is based on tree layer architecture (MVC pattern) consisting of persistent layer (relational database), application layer (object oriented code, object relational mapping from persistence layer) and presentation layer (JSP). The persistence layer uses Hibernate framework; Oracle 11g database server is used to ensure the processing of large data files. Application and presentation layers are designed and implemented using Spring technology. This framework supports MVC architecture, Dependency injection and Aspect Oriented Programming. There were no significant difficulties with integration of both frameworks, Hibernate and Spring MVC. Spring Security framework is used to ensure management of authentication and user roles. Since the system is thought to be finally open to the whole EEG/ERP community it is necessary to protect EEG/ERP data and metadata, and especially personal data of testing subjects stored in the database from an unauthorized access. Then a restricted user policy is applied and user roles are introduced. The complete overview of the system features and user roles (use case diagram) is available in (Pergler 2009). Concerning the architectural layers there is a question which layer is more feasible for mapping of its structure into ontology. Currently we have studied two possibilities: * Mapping from the persistence layer (relational database) * Mapping from the application layer (object oriented code) The mapping from the application layer to an ontology includes the precedent object relational mapping provided by Hibernate framework.

Proper citation: EEGbase (RRID:SCR_001452) Copy   

•   Source: SciCrunch Registry

https://school.wakehealth.edu/departments/neurology

Department at the Wake Forest University's School of Medicine that hosts physicians who specialize in neurological topics such as neuromuscular disease, epilepsy, pediatric neurology, strokes, neuropsychology, neurosonology, and neurorehabilitaiton.

Proper citation: Wake Forest University School of Medicine: Department of Neurology (RRID:SCR_001453) Copy   

•   Source: SciCrunch Registry