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http://www.bioconductor.org/packages/devel/bioc/html/VegaMC.html

Software package that enables the detection of driver chromosomal imbalances including loss of heterozygosity (LOH) from array comparative genomic hybridization (aCGH) data. It performs a joint segmentation of a dataset and uses a statistical framework to distinguish between driver and passenger mutation. VegaMC has been implemented so that it can be immediately integrated with the output produced by PennCNV tool. In addition, it produces in output two web pages that allows a rapid navigation between both the detected regions and the altered genes. In the web page that summarizes the altered genes, the link to the respective Ensembl gene web page is reported.

Proper citation: VegaMC (RRID:SCR_001267) Copy   

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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   

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http://www.ncibi.org/

The Center develops conceptual models, computational infrastructure, an integrated knowledge repository, and query and analysis tools that enable scientists to effectively access and integrate the wealth of biological data. The National Center for Integrative Biomedical Informatics (NCIBI) was founded in October 2005 and is one of seven National Centers for Biomedical Computing (NCBC) in the NIH Roadmap. NCIBI is based at the University of Michigan as a part of the Center for Computational Medicine and Biology (CCMB). NCIBI is composed of biomedical researchers, computational biologists, computer scientists, developers and human-computer interaction specialists organized into seven major core functions. They work in interdisciplinary teams to collectively develop tools that are not only computationally powerful but also biologically relevant and meaningful. The four initial Driving Biological Projects (prostate cancer progression, Type 1 and type 2 diabetes and bipolar disorder) provide the nucleation point from which tool development is informed, launched, and tested. In addition to testing tools for function, a separate team is dedicated to testing usability and user interaction that is a unique feature of this Center. Once tools are developed and validated the goal of the Center is to share and disseminate data and software throughout the research community both internally and externally. This is achieved through various mechanisms such as training videos, tutorials, and demonstrations and presentations at national and international scientific conferences. NCIBI is supported by NIH Grant # U54-DA021519.

Proper citation: National Center for Integrative Biomedical Informatics (RRID:SCR_001538) Copy   

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

Software that identifies cell population in flow cytometry data. It demonstrates significant advantages in proper identification of populations with non-elliptical shapes, low density populations close to dense ones, minor subpopulations of a major population and rare populations. It samples large data such that spectral clustering is possible while preserving density information in edge weights. More specifically, given a matrix of coordinates as input, SamSPECTRAL first builds the communities to sample the data points. Then, it builds a graph and after weighting the edges by conductance computation, the graph is passed to a classic spectral clustering algorithm to find the spectral clusters. The last stage of SamSPECTRAL is to combine the spectral clusters. The resulting connected components estimate biological cell populations in the data sample.

Proper citation: SamSPECTRAL (RRID:SCR_001858) Copy   

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http://www.cancergenomics.org/

Consortium promoting communication and collaboration among cancer cytogenomics laboratories, who are interested in applying microarray technologies to cancer diagnosis and cancer research. Their oals are to (1) establish platform-neutral and cancer specific microarray designs for diagnostic purposes, (2) share cancer microarray data between participating institutions for education purposes, (3) create a public cancer array database, and (4) carry out multicenter cancer genome translational research. Collaboration amongst the different laboratories and researchers will not only provide validation for the microarray design(s) but ultimately provide more comprehensive molecular information and more accurate interpretation to better serve cancer patients and further cancer research. The CGC was officially incorporated in June 2010 as a not-for-profit organization.

Proper citation: Cancer Genomics Consortium (RRID:SCR_002384) Copy   

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http://hardinmd.lib.uiowa.edu/index.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 2, 2025. A medical database with lists, or directories, of information in health and medicine and images of medical conditions. Users may search Hardin MD, browse through the Medical picture gallery, and sort search results by disease or alphabetical letter.

Proper citation: Hardin MD (RRID:SCR_002364) Copy   

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https://cghub.ucsc.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on March 17, 2022. A secure repository for storing, cataloging, and accessing cancer genome sequences, alignments, and mutation information from the Cancer Genome Atlas (TCGA) consortium and related projects. CGHub gives scientific researchers the statistical power of large cancer genome datasets to attack the molecular complexity of cancer.

Proper citation: Cancer Genomics Hub (RRID:SCR_002657) Copy   

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http://www.celgene.com

An American global biotechnology company that manufactures drug therapies for cancer and inflammatory disorders. The company's major products are Thalomid (thalidomide), which is approved for the acute treatment of the cutaneous manifestations of moderate to severe erythema nodosum leprosum (ENL), as well as in combination with dexamethasone for patients with newly diagnosed multiple myeloma, and Revlimid (lenalidomide), for which the company has received FDA and EMA approval in combination with dexamethasone for the treatment of multiple myeloma patients who have received at least one prior therapy. Revlimid is also approved in the United States for the treatment of patients with transfusion-dependent anemia due to Low- or Intermediate-1-risk Myelodysplastic syndromes (MDS) associated with a deletion 5q cytogenetic abnormality with or without additional cytogenetic abnormalities. Both Thalomid and Revlimid are sold through proprietary risk-management distribution programs to ensure safe and appropriate use of these pharmaceuticals. Vidaza is approved for the treatment of patients with MDS. Celgene also receives royalties from Novartis Pharma AG on sales of the entire Ritalin family of drugs, which are widely used to treat Attention Deficit Hyperactivity Disorder (ADHD). (Adapted from Wikipedia) There are numerous clinical trials at major medical centers using compounds from Celgene. Investigational compounds are being studied for patients with incurable hematological and solid tumor cancers, including multiple myeloma, myelodysplastic syndromes, chronic lymphocyte leukemia (CLL), non-Hodgkin's lymphoma (NHL), glioblastoma, and ovarian, pancreatic and prostate cancer.

Proper citation: Celgene (RRID:SCR_002955) Copy   

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http://bsec.ornl.gov/AdaptiveCrawler.shtml

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 9,2022. A web crawler that can intelligently acquire social media content on the Internet to meet the specific online data source acquisition needs of cancer researchers.

Proper citation: AdaptiveCrawler (RRID:SCR_000573) Copy   

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http://www.stanford.edu/group/nusselab/cgi-bin/wnt/

A resource for members of the Wnt community, providing information on progress in the field, maps on signaling pathways, and methods. The page on reagents lists many resources generously made available to and by the Wnt community. Wnt signaling is discussed in many reviews and in a recent book. There are usually several Wnt meetings per year.

Proper citation: Wnt homepage (RRID:SCR_000662) Copy   

•   Source: SciCrunch Registry
  

https://www.athensresearch.com/

Commercial supplier of bioproducts for studies of inflammation, autoimmune disease, cancer, coronary disease, Alzheimer's Disease and more. These include antibodies, enzymes, coagulation factors, and assay kits.

Proper citation: Athens Research and Technology (RRID:SCR_001079) Copy   

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http://www.iro.umontreal.ca/~csuros/quadgt/

Software package for calling single-nucleotide variants in four sequenced genomes comprising a normal-tumor pair and the two parents. Genotypes are inferred using a joint model of parental variant frequencies, de novo germline mutations, and somatic mutations. The model quantifies the descent-by-modification relationships between the unknown genotypes by using a set of parameters in a Bayesian inference setting. Note that you can use it on any subset of the four related genomes, including parent-offspring trios, and normal-tumor pairs without parental samples.

Proper citation: QuadGT (RRID:SCR_000073) Copy   

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https://code.google.com/p/nfuse/

Software that predicts fusion transcripts and associated CGRs from matched RNA-seq and Whole Genome Shotgun Sequencing (WGSS).

Proper citation: nFuse (RRID:SCR_000066) Copy   

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http://www.ariad.com/

Cambridge, Massachusetts-based biotechnology company focused on cancer. Focus areas are blood cancers and solid tumors. Compounds: ponatinib, AP26113, ridaforolimus and AP1903., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: ARIAD (RRID:SCR_008559) Copy   

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http://www.zbh.uni-hamburg.de/?id=292

A web-based software tool for the integrative analysis of cancer genomics data. It stores different kinds of downstream processed data from multiple samples in a single database. A powerful search interface allows to dynamically filter the data to be displayed with respect to different criteria. The combination of AJAX technology and a fast visualization engine facilitates a highly dynamic visualization for large amounts of data. FISH Oracle 2 is able to simultaneously display different data sets, thus simplifying their comparison. Filter and display options can be changed on the fly. High quality image export enables the life scientist to easily communicate the results, e.g. in presentations or publications. A comprehensive data administration assures to keep track of the data stored in the database.

Proper citation: FISH Oracle (RRID:SCR_010927) Copy   

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http://www.tfri.ca/terryfox/

Launched in October 2007, TFRI is the brainchild of the Terry Fox Foundation. TFRI involves collaboration between cancer hospitals and research organizations across Canada, and will occur initially in British Columbia, Alberta, Ontario and Quebec. TFRI will support translational cancer research projects with the potential to significantly improve the health of cancer patients. TFRI is organized into functionally integrated yet geographically dispersed nodes. Regional cancer hospitals and research organizations participate in each node by providing space for researchers and by arranging for the participation of cancer patients in research projects. At each node, two node co-ordinators provide leadership, and bring together local scientific and clinical research teams to propose and manage specific projects. The TFRI headquarters team liaises with the TFRI nodes and provides direction, co-ordination and facilitates communication across the entire organization. The Terry Fox Foundation has committed a minimum of $50 million (CAN) over five years from donations obtained during the 25th anniversary of the Terry Fox Marathon of Hope and from new funds anticipated and those raised since 2005. Other partners sharing the same vision are being sought who will be asked to commit additional resources to support the ongoing work of the TFRI.

Proper citation: Terry Fox Research Institute (RRID:SCR_011568) Copy   

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http://www.broadinstitute.org/cancer/cga/absolute

Software to estimate purity / ploidy, and from that compute absolute copy-number and mutation multiplicities. When DNA is extracted from an admixed population of cancer and normal cells, the information on absolute copy number per cancer cell is lost in the mixing. The purpose of ABSOLUTE is to re-extract these data from the mixed DNA population. This process begins by generation of segmented copy number data, which is input to the ABSOLUTE algorithm together with pre-computed models of recurrent cancer karyotypes and, optionally, allelic fraction values for somatic point mutations. The output of ABSOLUTE then provides re-extracted information on the absolute cellular copy number of local DNA segments and, for point mutations, the number of mutated alleles.

Proper citation: ABSOLUTE (RRID:SCR_005198) Copy   

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http://www.qcmg.org/bioinformatics/tiki-index.php

A single nucleotide variant caller optimised for identifying somatic variants in low cellularity cancer samples.

Proper citation: qSNP (RRID:SCR_005105) Copy   

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http://statgenpro.psychiatry.hku.hk/limx/kggseq/

A biological Knowledge-based mining platform for Genomic and Genetic studies using Sequence data. The software platform, constituted of bioinformatics and statistical genetics functions, makes use of valuable biologic resources and knowledge for sequencing-based genetic mapping of variants / genes responsible for human diseases / traits. It facilitates geneticists to fish for the genetic determinants of human diseases / traits in the big sea of DNA sequences. KGGSeq has paid attention to downstream analysis of genetic mapping. The framework was implemented to filter and prioritize genetic variants from whole exome sequencing data.

Proper citation: KGGSeq (RRID:SCR_005311) Copy   

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http://www.cancer.fi/syoparekisteri/en/

The Finnish Cancer Registry maintains a nation-wide database on all cancer cases in Finland going back to 1953. It is also an internationally active institute for statistical and epidemiological cancer research. The Mass Screening Registry is a department of the Finnish Cancer Registry, and is responsible of planning and evaluating national cancer screening programs in Finland. The site contains information on cancer research and up to date statistics on the prevalence of different types of cancer in Finland, the Nordic countries and on a global level. The web pages include information for participants in cancer screening and for professionals involved in organizing such screening.

Proper citation: Finnish Cancer Registry (RRID:SCR_005881) Copy   

•   Source: SciCrunch Registry