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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://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://www.socr.umich.edu/

SOCR designs, validates and freely disseminates knowledge. The Resource develops AI/ML tools, mathematical models, and end-to-end data analytic protocols for biomedical and health studies. It provides portable online aids for probability, statistics and health science education, promotes technology enhanced instruction, supports efficient statistical computing, supports AI-services, and advances predictive big data analytics. The SOCR platform includes repository of interactive apps, datasets and case-studies, computational tools, visualization approaches, instructional resources, learning materials, and curricular components. SOCR faculty, staff, and students support data and information science collaborations and analytic partnerships involving biomedical, healthcare, and biostatistical investigations.

Proper citation: University of Michigan Statistics Online Computational Resource Core Facility (RRID:SCR_022917) Copy   

•   Source: SciCrunch Registry

http://bard.nih.gov/

Database that allows scientists without specialized training to effectively utilize Molecular Libraries Program (MLP) data. It allows the research community to utilize and develop new chemical probes to explore biological functions by building a central, permanently accessible link to all aspects of chemical biology data and analyses. The project is split into two basic segments, the first segment delivering functionality for a data dictionary, as well as assay protocol and data entry tools. The second builds a data warehouse for analysis and visualization, accessible through a public RESTful API. They will initially deploy two clients that will use this API - a web-based interface and a desktop application. Advanced access to data and the platforms will also be available to support plug-in development and the repackaging of data by others. Initially the project will focus on small molecule assays. Features: * allow scientists to annotate assay data using a common, shared language * provide facile access to data, integrating existing chemical biology and computational resources * enable meaningful analysis and interpretation of discovery data by the research community * support hypothesis generation for iterative probe- and drug-discovery projects * inform the entire small molecule discovery and development process, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: BARD (RRID:SCR_006283) Copy   

•   Source: SciCrunch Registry

http://www.cpc.unc.edu/projects/addhealth

Longitudinal study of a nationally representative sample of adolescents in grades 7-12 in the United States during the 1994-95 school year. Public data on about 21,000 people first surveyed in 1994 are available on the first phases of the study, as well as study design specifications. It also includes some parent and biomarker data. The Add Health cohort has been followed into young adulthood with four in-home interviews, the most recent in 2008, when the sample was aged 24-32. Add Health combines longitudinal survey data on respondents social, economic, psychological and physical well-being with contextual data on the family, neighborhood, community, school, friendships, peer groups, and romantic relationships, providing unique opportunities to study how social environments and behaviors in adolescence are linked to health and achievement outcomes in young adulthood. The fourth wave of interviews expanded the collection of biological data in Add Health to understand the social, behavioral, and biological linkages in health trajectories as the Add Health cohort ages through adulthood. The restricted-use contract includes four hours of free consultation with appropriate staff; after that, there''s a fee for help. Researchers can also share information through a listserv devoted to the database.

Proper citation: Add Health (National Longitudinal Study of Adolescent Health) (RRID:SCR_007434) Copy   

•   Source: SciCrunch Registry

http://compbio.soe.ucsc.edu/yeast_introns.html

Database of information about the spliceosomal introns of the yeast Saccharomyces cerevisiae. Listed are known spliceosomal introns in the yeast genome and the splice sites actually used are documented. Through the use of microarrays designed to monitor splicing, they are beginning to identify and analyze splice site context in terms of the nature and activities of the trans-acting factors that mediate splice site recognition. In version 3.0, expression data that relates to the efficiency of splicing relative to other processes in strains of yeast lacking nonessential splicing factors is included. These data are displayed on each intron page for browsing and can be downloaded for other types of analysis.

Proper citation: Yeast Intron Database (RRID:SCR_007144) Copy   

•   Source: SciCrunch Registry

http://crcview.hegroup.org/

Web-based microarray data analysis and visualization system powered by CRC, or Chinese Restaurant cluster, a Dirichlet process model-based clustering algorithm recently developed by Dr. Steve Qin. It also incorporates several gene expression analysis programs from Bioconductor, including GOStats, genefilter, and Heatplus. CRCView also installs from the Bioconductor system 78 annotation libraries of microarray chips for human (31), mouse (24), rat (14), zebrafish (1), chicken (1), Drosophila (3), Arabidopsis (2), Caenorhabditis elegans (1), and Xenopus Laevis (1). CRCView allows flexible input data format, automated model-based CRC clustering analysis, rich graphical illustration, and integrated Gene Ontology (GO)-based gene enrichment for efficient annotation and interpretation of clustering results. CRC has the following features comparing to other clustering tools: 1) able to infer number of clusters, 2) able to cluster genes displaying time-shifted and/or inverted correlations, 3) able to tolerate missing genotype data and 4) provide confidence measure for clusters generated. You need to register for an account in the system to store your data and analyses. The data and results can be visited again anytime you log in.

Proper citation: CRCView (RRID:SCR_007092) Copy   

•   Source: SciCrunch Registry

https://www.cores.emory.edu/iemc/

Core helps investigators use the latest technologies on structural research in their projects. Provides expertise in experimental needs.

Proper citation: Emory University Robert P. Apkarian Integrated Electron Microscopy Core Facility (RRID:SCR_023537) Copy   

•   Source: SciCrunch Registry

https://github.com/VH-Lab/vhlab-microscopyimageanalysis-matlab

Software Matlab app for analysis of high density imaging data like that from Array Tomography.

Proper citation: vhlab-microscopyimageanalysis-matlab (RRID:SCR_024450) Copy   

•   Source: SciCrunch Registry

http://www.midasplatform.org/

Open-source toolkit that enables the rapid creation of tailored, web-enabled data storage and provides a cohesive system for data management, visualization, and processing. At its core, Midas Platform is implemented as a PHP modular framework with a backend database (PostGreSQL, MySQL and non-relational databases). While the Midas Platform system can be installed and deployed without any customization, the framework has been designed with customization in mind. As building one system to fit all is not optimal, the framework has been extended to support plugins and layouts. Through integration with a range of other open-source toolkits, applications, or internal proprietary workflows, Midas Platform offers a solid foundation to meet the needs of data-centric computing. Midas Platform provides a variety of data access methods, including web, file system and DICOM server interfaces, and facilitates extending the methods in which data is stored to other relational and non-relational databases.

Proper citation: Midas Platform (RRID:SCR_002186) Copy   

•   Source: SciCrunch Registry

http://mind.loni.usc.edu

The MiND: Metadata in NIfTI for DWI framework enables data sharing and software interoperability for diffusion-weighted MRI. This site provides specification details, tools, and examples of the MiND mechanism for representing important metadata for DWI data sets at various stages of post-processing. MiND framework provides a practical solution to the problem of interoperability between DWI analysis tools, and it effectively expands the analysis options available to end users. To assist both users and developers in working with MiND-formatted files, we provide a number of software tools for download. * MiNDHeader A utility for inspecting MiND-extended files. * I/O Libraries Programming libraries to simplify writing and parsing MiND-formatted data. * Sample Files Example files for each MiND schema. * DIRAC LONI''s Diffusion Imaging Reconstruction and Analysis Collection is a DWI processing suite which utilizes the MiND framework.

Proper citation: LONI MiND (RRID:SCR_004820) Copy   

•   Source: SciCrunch Registry

http://www.sph.umich.edu/csg/abecasis/CaTS

Software tool for carrying out power calculations for large genetic association studies, including two stage genome wide association studies.

Proper citation: Calculator for Association with Two Stage design (RRID:SCR_007238) Copy   

•   Source: SciCrunch Registry

http://immport.org/immport-open/public/reference/cytokineRegistry

A registry of cytokines, chemokines, and receptors generated for the purpose of collecting, integrating, and mapping between entity names and synonyms from several resources. These resources include MeSH, the Protein Ontology, EntrezGene, HGNC, MGI, UniProt and others.

Proper citation: Cytokine Registry (RRID:SCR_014368) Copy   

•   Source: SciCrunch Registry

https://bioinformatics.niaid.nih.gov/chemokinedb/

Resource of chemokines and receptors with detailed information including taxonomy, nomenclature, structure, physiological function, tissue information, and phenotype, collected from IUPHAR/BPS, UniGene, and UniProt public databases.

Proper citation: ChemokineDB (RRID:SCR_016593) Copy   

•   Source: SciCrunch Registry

http://software.broadinstitute.org/gsea/msigdb/index.jsp

Collection of annotated gene sets for use with Gene Set Enrichment Analysis (GSEA) software.

Proper citation: Molecular Signatures Database (RRID:SCR_016863) Copy   

•   Source: SciCrunch Registry

http://www.orbitproject.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on May 29, 2014. The orbit project was a registry of biomedical resources.

Proper citation: OrbitProject (RRID:SCR_010463) Copy   

•   Source: SciCrunch Registry

http://ods.od.nih.gov/Research/CARDS_Database.aspx

Database of federally funded research projects pertaining to dietary supplements. CARDS contains projects funded by the United States Department of Agriculture (USDA), the Department of Defense (DOD) and the Institutes and Centers (ICs) of the National Institutes of Health (NIH) beginning with fiscal year 1999, the first year that NIH ICs began reporting research related to dietary supplements. Projects funded by other Federal agencies will be added to CARDS as they become available. The Office of Dietary Supplements (ODS) will post notices on its website and listserv when CARDS updates are completed. Codes assigned to each research project allow the CARDS user to identify: * research related to specific dietary supplement ingredients; for example, vitamin E or St. John''''s wort * the type of study; for example, a Phase III study or an animal study * health outcomes or biological effects; for example, osteoporosis or antioxidant function * whether the research is directly related or indirectly related to dietary supplements. For example, a clinical trial comparing bone density in women given a daily calcium supplement versus a placebo would be classified as directly related to dietary supplements. A study examining the activation of steroid hormone receptors by supplemental vitamin D in cell culture would be classified as indirectly related to dietary supplements because the direct physiological or health effects of vitamin D supplementation are not being studied. A search of the CARDS database can be used to sort and tabulate information for a variety of purposes. For example, a researcher may want to know which ICs at the NIH fund research on herbal supplement ingredients. A consumer may want to know if the Federal government is supporting research on a popular dietary supplement ingredient such as vitamin C.

Proper citation: CARDS Database (RRID:SCR_009011) Copy   

•   Source: SciCrunch Registry

https://www.pharmgkb.org/

NIH-funded resource that provides information about how human genetic variation affects response to medications. PharmGKB collects, curates and disseminates knowledge about clinically actionable gene-drug associations and genotype-phenotype relationships.

Proper citation: PharmKGB (RRID:SCR_025580) Copy   

•   Source: SciCrunch Registry

https://sparc.science/about/consortia/precision

Project titled Program to Reveal and Evaluate Cells-to-gene Information that Specify Intricacies, Origins, and Nature of Human Pain (PRECISION) Network to develop meaningful resource for knowledge transfer, and to integrate and share Human Pain Associated Genes and Cell Datasets. Building knowledge platform to visualize, query, and interact with these data will support researchers and help accelerate dissemination of vital data to the larger scientific community. These goals align with NIH Helping to End Addiction Long-term (HEAL) Initiative, which seeks to accelerate the discovery and successful translation of non-addictive pain therapeutics. PRECISION Human Pain Network will leverage prior interdisciplinary collaboration to create workflows, tools, and infrastructure to define data and metadata types, to improve data management and sharing, and to integrate datasets and visualization tools.

Proper citation: NIH PRECISION Human Pain Network (RRID:SCR_025458) Copy   

•   Source: SciCrunch Registry

https://www.ou.edu/structuralbiology/cobre-core-facilities/mcl

Offers access to instrumentation, training and services for structure determination of macromolecular molecules using single crystal X-ray diffraction and/or cryo-EM Single Particle Analysis (SPA). Instrumentation is available for initial crystallization trials, optimization of crystallization, single crystal X-ray diffraction and data collection at synchrotron radiation facilities, as well as electron microscopy grid preparation for cryo-EM (SPA), screening and data collection using a Thermo Scientific Tundra Cryo-TEM and assistance for data collection at national laboratories.

Proper citation: University of Oklahoma Biomolecular Structure Core Facility (RRID:SCR_028074) Copy   

•   Source: SciCrunch Registry