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https://www.feinberg.northwestern.edu/sites/cam/

Core offers instrumentation and services for study of biological processes at whole animal, tissue, cellular and subcellular levels. This includes light microscopy, electron microscopy and image analysis. Light microscopy offerings include super resolution microscopy (MINFLUX, STED, NSPARC, SORA), fluorescent laser scanning and spinning disk microscopy, fluorescent lifetime imaging, automated high throughput tissue cytometry, atomic force microscopy, laser capture microdissection, mutliphoton imaging, and whole animal bioluminescent and fluorescent imaging. Electron microscopy includes sample prep and imaging for TEM, SEM, platinum replicas, immuno gold and CLEM. We also provide microinjection equipment, chambers for stable live cell observation, and anesthesia equipment. CAM provides training on numerous different instrument platforms, consultation on experiment design, as well as digital image processing and image analysis.CAM is one of two Nikon Imaging Centers in the US, allowing us access and excellent support from Nikon to develop innovative solutions for the cutting edge imaging needs of users.

Proper citation: Northwestern University Feinberg School of Medicine Center for Advanced Microscopy and Nikon Imaging Center Core Facility (RRID:SCR_020996) Copy   

•   Source: SciCrunch Registry

https://fgf.uchicago.edu/

Facility offers Next-Gen Illumina and Pacific Biosciences Sequencing and Library prep services, Micro-array Illumina genotyping and EPIC arrays services, Sanger DNA Sequencing, and Bioanalyzer/Fragment analyzer sample QC services. For Single Cell sequencing project Facility operates DROP-SEQ and 10X Genomics instrument., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: University of Chicago Functional Genomics Core Facility (RRID:SCR_019196) Copy   

•   Source: SciCrunch Registry

https://med.nyu.edu/research/scientific-cores-shared-resources/applied-bioinformatics-laboratories

Core provides computational analysis for high throughput genomic data, including but not limited to, next generation sequencing data. Our mission is to accelerate scientific discoveries by guiding experimental design, performing robust data quality assessment, and carrying out comprehensive computational analyses. Registration to iLab required.

Proper citation: New York University Grossman School of Medicine Applied Bioinformatics Laboratories Facility (RRID:SCR_019178) Copy   

•   Source: SciCrunch Registry

https://www.lsi.umich.edu/science/centers-technologies/center-structural-biology

Comprehensive structural biology resource.Provides high throughput protein laboratory for protein engineering, protein purification facilities for small- and large-scale protein production, macromolecular crystallization and crystallography laboratories for solving crystal structures of biological molecules, and X-ray facility with access to high energy synchrotron radiation. Provides expert guidance to researchers through every stage of project, collaborating and consulting with researchers who use the facilities. Service categories are Chemical, Material and Protein Characterization, Molecular Biology. Services include Cloning, Crystallization, Differential thermal analysis, Drug development, NMR (small molecule), PCR, Protein crystallography, Protein engineering, Protein production, Structure determination, Xray.

Proper citation: University of Michigan Center for Structural Biology Core Facility (RRID:SCR_021065) Copy   

•   Source: SciCrunch Registry

http://proteogenomics.musc.edu/ma/arrayQuest.php?page=home&act=manage

A web-accessible program for the analysis of DNA microarray data. ArrayQuest is designed to apply any type of DNA microarray analysis program executable on a Linux system (i.e., Bioconductor statistical and graphical methods written in R as well as BioPerl and C++ based scripts) to DNA microarray data stored in the MUSC DNA Microarray Database, the Gene Expression Omnibus (GEO) or in a password protected private database uploaded to the center point server. ArrayQuest analyses are performed on a computer cluster.

Proper citation: ArrayQuest (RRID:SCR_010935) Copy   

•   Source: SciCrunch Registry

http://cancergenome.nih.gov/

Project exploring the spectrum of genomic changes involved in more than 20 types of human cancer that provides a platform for researchers to search, download, and analyze data sets generated. As a pilot project it confirmed that an atlas of changes could be created for specific cancer types. It also showed that a national network of research and technology teams working on distinct but related projects could pool the results of their efforts, create an economy of scale and develop an infrastructure for making the data publicly accessible. Its success committed resources to collect and characterize more than 20 additional tumor types. Components of the TCGA Research Network: * Biospecimen Core Resource (BCR); Tissue samples are carefully cataloged, processed, checked for quality and stored, complete with important medical information about the patient. * Genome Characterization Centers (GCCs); Several technologies will be used to analyze genomic changes involved in cancer. The genomic changes that are identified will be further studied by the Genome Sequencing Centers. * Genome Sequencing Centers (GSCs); High-throughput Genome Sequencing Centers will identify the changes in DNA sequences that are associated with specific types of cancer. * Proteome Characterization Centers (PCCs); The centers, a component of NCI's Clinical Proteomic Tumor Analysis Consortium, will ascertain and analyze the total proteomic content of a subset of TCGA samples. * Data Coordinating Center (DCC); The information that is generated by TCGA will be centrally managed at the DCC and entered into the TCGA Data Portal and Cancer Genomics Hub as it becomes available. Centralization of data facilitates data transfer between the network and the research community, and makes data analysis more efficient. The DCC manages the TCGA Data Portal. * Cancer Genomics Hub (CGHub); Lower level sequence data will be deposited into a secure repository. This database stores cancer genome sequences and alignments. * Genome Data Analysis Centers (GDACs) - Immense amounts of data from array and second-generation sequencing technologies must be integrated across thousands of samples. These centers will provide novel informatics tools to the entire research community to facilitate broader use of TCGA data. TCGA is actively developing a network of collaborators who are able to provide samples that are collected retrospectively (tissues that had already been collected and stored) or prospectively (tissues that will be collected in the future).

Proper citation: The Cancer Genome Atlas (RRID:SCR_003193) 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://www.chernobyltissuebank.com/

The CTB (Chernobyl Tissue Bank) is an international cooperation that collects, stores and disseminates biological samples from tumors and normal tissues from patients for whom the aetiology of their disease is known - exposure to radioiodine in childhood following the accident at the Chernobyl power plant. The main objective of this project is to provide a research resource for both ongoing and future studies of the health consequences of the Chernobyl accident. It seeks to maximize the amount of information obtained from small pieces of tumor by providing multiple aliquots of RNA and DNA extracted from well documented pathological specimens to a number of researchers world-wide and to conserve this valuable material for future generations of scientists. It exists to promote collaborative, rather than competitive, research on a limited biological resource. Tissue is collected to an approved standard operating procedure (SOP) and is snap frozen; the presence or absence of tumor is verified by frozen section. A representative paraffin block is also obtained for each case. Where appropriate, we also collect fresh and paraffin-embedded tissue from loco-regional metastases. Currently we do not issue tissue but provide extracted nucleic acid, paraffin sections and sections from tissue microarrays from this material. The project is coordinated from Imperial College, London and works with Institutes in the Russian Federation (the Medical Radiological Research Centre in Obninsk) and Ukraine (the Institute of Endocrinology and Metabolism in Kiev) to support local scientists and clinicians to manage and run a tissue bank for those patients who have developed thyroid tumors following exposure to radiation from the Chernobyl accident. Belarus was also initially included in the project, but is currently suspended for political reasons.

Proper citation: Chernobyl Tissue Bank (RRID:SCR_010662) Copy   

•   Source: SciCrunch Registry

https://cibersort.stanford.edu/

Software tool to provide an estimation of the abundances of member cell types in a mixed cell population, using gene expression data. Used for characterizing cell composition of complex tissues from their gene expression profiles, large scale analysis of RNA mixtures for cellular biomarkers and therapeutic targets.

Proper citation: CIBERSORT (RRID:SCR_016955) Copy   

•   Source: SciCrunch Registry

https://github.com/JonathanIrish/MEMv3

Software tool to calculate enrichment scores. Generates human and machine readable labels that quantify features enriched in sample. Used to identify multiple populations of cells and to compare each population to all of other remaining cells from original sample.

Proper citation: Marker Enrichment Modeling (RRID:SCR_022495) Copy   

•   Source: SciCrunch Registry

https://github.com/raphael-group/chisel

Software tool to infer allele and haplotype specific copy numbers in individual cells from low coverage single cell DNA sequencing data. Integrates weak allelic signals across individual cells, powering strength of single cell sequencing technologies to overcome weakness. Includes global clustering of RDRs and BAFs, and rigorous model selection procedure for inferring genome ploidy that improves both inference of allele specific and total copy numbers.

Proper citation: CHISEL (RRID:SCR_023220) Copy   

•   Source: SciCrunch Registry

http://www.t1diabetes.nih.gov/t1d-raid/index.shtml

NOTE: The T1D-RAID program is not currently accepting applications. Cooperative program that makes available, on a competitive basis, NCI resources for the pre-clinical development of drugs, natural products, and biologics to facilitate translation to the clinic of novel, scientifically meritorious therapeutic interventions for type 1 diabetes and its complications. A partial listing of those services includes: high-throughput screening, studies in animal models, formulation, pharmacology and toxicology studies, and bulk substances acquisition. Requests to T1D-RAID are brief (20 pages or less), and should clearly outline the resources required to ready the proposed therapeutic agent for clinical trials. T1D-RAID should enable entry into the clinic of promising molecules that are not otherwise likely to receive an adequate and timely clinical test. T1D-RAID is designed to accomplish the tasks that are rate-limiting in bringing discoveries from the laboratory to the clinic. Once a project has been approved, NIDDKstaff interact directly with the Principal Investigator (PI). NCI contractors perform the T1D-RAID-approved tasks under the direction of NIDDKand NCI staff. The required tasks will vary from project to project. In some cases T1D-RAID will support only one or two key missing steps necessary to bring a compound to the clinic; in other cases it may be necessary to supply the entire portfolio of development requirements needed to file an IND. Examples of tasks that can be supported by T1D-RAID include, but are not limited to: * Definition or optimization of dose and schedule for in vivo activity * Development of pharmacology assays * Conduct of pharmacology studies with a pre-determined assay * Acquisition of bulk substance (GMP and non-GMP) * Scale-up production from lab-scale to clinical-trials lot scale * Development of suitable formulations * Development of analytical methods for bulk substances * Production of dosage forms * Stability assurance of dosage forms * Range-finding initial toxicology * IND-directed toxicology, with correlative pharmacology and histopathology * Planning of clinical trials * Regulatory affairs, so that FDA requirements are likely to be satisfied by participating investigators seeking to test new molecular entities in the clinic * IND filing advice The output of T1D-RAID activities will be both products and information that will be made fully available to the originating investigator for support of an IND application and clinical trials. T1D-RAID does not sponsor clinical trials.

Proper citation: Type 1 Diabetes - Rapid Access to Intervention Development (RRID:SCR_000203) Copy   

•   Source: SciCrunch Registry

https://www.roswellpark.edu/shared-resources/gene-targeting-and-transgenic

Facility which provides researchers with transgenic mouse technologies, methods, and animal models. Knockout mice, transgenic mice, and mice on multiple strain backgrounds are provided.

Proper citation: RPCI Gene Targeting and Transgenic Shared Resource (RRID:SCR_001020) Copy   

•   Source: SciCrunch Registry

https://github.com/hms-dbmi/UpSetR

Software R package for visualization of intersecting sets and their properties.

Proper citation: UpSetR (RRID:SCR_026112) Copy   

•   Source: SciCrunch Registry

https://github.com/NCI-CGR/PLP_prediction_workflow/tree/autogvp

Software tool integrates ClinVar variant annotation with modified InterVar classification approach, based on American College of Medical Genetics-Association for Molecular Pathology guidelines, to output germline variant classification. Since AutoGVP input only requires VCF file, it can facilitate large-scale, clinically focused classification of germline sequence variants.

Proper citation: AutoGVP (RRID:SCR_026107) Copy   

•   Source: SciCrunch Registry

https://github.com/czc/nb_distribution

Software tool to discover somatic and germline structural variation breakpoints in whole genome sequencing data. Can report accurate breakpoints of Deletions, Duplications, Inversions and Translocations. Designed for Illumina paired-end data. Local assembly for breakpoint detection in cancer genomes.

Proper citation: NovoBreak (RRID:SCR_026032) Copy   

•   Source: SciCrunch Registry

https://oncotree.mskcc.org/

Community-driven cancer classification platform encompassing rare and common cancers that provides clinically relevant and appropriately granular cancer classification for clinical decision support systems and oncology research. Cancer classification system for precision oncology.

Proper citation: OncoTree (RRID:SCR_026218) Copy   

•   Source: SciCrunch Registry

https://genie.cbioportal.org/

International data-sharing consortium focused on generating an evidence base for precision cancer medicine by integrating clinical-grade cancer genomic data with clinical outcome data of cancer patients treated at multiple institutions worldwide.

Proper citation: AACR GENIE cBioPortal (RRID:SCR_026217) Copy   

•   Source: SciCrunch Registry

https://github.com/katerinakazantseva/strainy

Software tool for phasing and assembly of bacterial strains from long-read sequencing data (either Oxford Nanopore or PacBio). Given reference (or collapsed de novo assembly) and set of aligned reads as input, tool produces multi-allelic phasing, individual strain haplotypes and strain-specific variant calls. Used for phasing and assembly of strain haplotypes from long-read metagenome sequencing.

Proper citation: Strainy (RRID:SCR_026430) Copy   

•   Source: SciCrunch Registry

https://github.com/dviraran/xCell

Software R package for generating cell type scores and R scripts for development of xCell. Web tool that performs cell type enrichment analysis from gene expression data for immune and stroma cell types. Used for Cell types enrichment analysis.

Proper citation: xCell (RRID:SCR_026446) Copy   

•   Source: SciCrunch Registry