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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
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
http://code.google.com/p/drgap/
Designed to identify Driver Genes and Pathways in cancer genome sequencing studies.
Proper citation: DrGaP (RRID:SCR_008670) Copy
http://purl.bioontology.org/ontology/CTCAE
A coding system for reporting adverse events that occur in the course of cancer therapy. It was derived from the Common Toxicity Criteria (CTC) v2.0 and is maintained by the Cancer Therapy Evaluation Program (CTEP) at the National Cancer Institution (NCI).
Proper citation: Common Terminology Criteria for Adverse Events (RRID:SCR_010296) Copy
http://purl.bioontology.org/ontology/CANONT
Upper-level ontology for cancer.
Proper citation: Upper-Level Cancer Ontology (RRID:SCR_010443) Copy
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
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
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
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
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
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
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
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
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
A reference terminology and core biomedical ontology for NCI that covers approximately 100,000 key biomedical concepts with terms, codes, definitions, and more than 200,000 inter-concept relationships. It is the reference terminology for NCI, NCI Metathesaurus and NCI informatics infrastructure covering vocabulary for clinical care, translational and basic research, and public information and administrative activities. It includes broad coverage of the cancer domain, including cancer related diseases, findings and abnormalities; anatomy; agents, drugs and chemicals; genes and gene products and so on. In certain areas, like cancer diseases and combination chemotherapies, it provides the most granular and consistent terminology available. It combines terminology from numerous cancer research related domains, and provides a way to integrate or link these kinds of information together through semantic relationships. NCIt features: * Stable, unique codes for biomedical concepts; * Preferred terms, synonyms, definitions, research codes, external source codes, and other information; * Links to NCI Metathesaurus and other information sources; * Over 200,000 cross-links between concepts, providing formal logic-based definition of many concepts; * Extensive content integrated from NCI and other partners, much available as separate NCIt subsets * Updated frequently by a team of subject matter experts. NCIt is a widely recognized standard for biomedical coding and reference, used by a broad variety of public and private partners both nationally and internationally including the Clinical Data Interchange Standards Consortium Terminology (CDISC), the U.S. Food and Drug Administration (FDA), the Federal Medication Terminologies (FMT), and the National Council for Prescription Drug Programs (NCPDP).
Proper citation: NCI Thesaurus (RRID:SCR_003563) Copy
Pharmaceutical company with a mission to discover and develop innovative medicines that ease patients'' suffering, and solve the most important unmet medical needs of our time. As one of the Janssen Pharmaceutical Companies, their strategy is to identify the biggest unmet medical needs and match them with the best science, internal or external, to find solutions for patients worldwide. They leverage their world-class discovery and development expertise, and operational excellence, to bring innovative, effective treatments in five therapeutic areas: cardiovascular and metabolism, immunology, infectious diseases and vaccines, neuroscience, and oncology.
Proper citation: Janssen Research and Development (RRID:SCR_003904) Copy
A biomedical company in Spain focused on the development of new tools for diagnosis and personalized treatment of oncological diseases and precancerous. It has three areas of activity in permanent innovation: Assistance in Diagnosis / Prognosis in solid and hematological tumors, Translational Research covering the gap between basic and clinical research and advanced radiotherapy treatments based image-guided single dose (SD-IGRT). Their objectives are: * Provide an integrated tissue and tumor molecular phenotype analysis using the most advanced technologies in diagnosis, to guide the most appropriate treatment for each patient. * Discover and validate molecular patterns by molecular systems and platforms including pathology, to generate predictive algorithms through computational biology, evolution and determining the response of patients with a particular tumor profile. Althia has laboratories equipped with the most advanced equipment and technologies in Barcelona and Granada Genyo Center, with offices in Madrid.
Proper citation: Althia (RRID:SCR_003918) Copy
A consortium that aims to transform cancer research through collaborative oncology trials that leverage the scientific and clinical expertise of the Big Ten universities. The goal is to align the conduct of cancer research through collaborative, hypothesis-driven, highly translational oncology trials that leverage the scientific and clinical expertise. The clinical trials that will be developed will be linked to molecular diagnostics, enabling researchers to understand what drives the cancers to grow and what might be done to stop them from growing. The consortium also leverages geographical locations and existing relationships among the cancer centers. One of the consortium's goals is to harmonize contracts and scientific review processes to expedite clinical trials. The consortium will only focus on phase 0 to II trials because larger trials - even a randomized phase II trial - are difficult to conduct at a single cancer center.
Proper citation: Big Ten Cancer Research Consortium (RRID:SCR_004025) Copy
Center consisting of 9 research groups who all address basic questions in stem cell and developmental biology with the overall aim of developing new stem cell-based therapeutic approaches for diabetes and cancer. DanStem comprises two sections: * The Novo Nordisk Foundation Section for Basic Stem Cell Biology (BasicStem) * The Section for Strategic Translational Stem Cell Research and Therapy (TransStem) DanStem was established as a result of a series of international recruitments coupled with internationally recognized research groups focused on insulin producing beta cells and cancer research already located at the University of Copenhagen. They all have well-established, international collaborations and actively participate in several international scientific consortia. DanStem is also active in training undergraduates, PhD students and postdocs.
Proper citation: DanStem (RRID:SCR_004021) Copy
http://datacatalog.med.nyu.edu/
A searchable data catalog that facilitates researchers'' access to large datasets available either publicly or through institutional or individual licensing. Dataset records include information about the content of the dataset, how to access the dataset, and local experts within NYULMC and NYU to assist in the use of these datasets. The data catalog will expand to include internally generated datasets from NYULMC and NYU in the near future. Use the contact form if you are interested in submitting a dataset to the data catalog.
Proper citation: NYU Data Catalog (RRID:SCR_004012) Copy
A small and medium-sized enterprise (SME) that has expertise in preclinical pharmacology, pharmacokinetics, and toxicology for the characterization of novel anticancer therapeutics and predictive biomarkers like: cytostatics, biologicals (peptides, antibodies), (anti)-hormones, immunomodulators (cytokines), and gene therapeutics. EPO has modern laboratories licensed for animal experiments and gene technology (S2) and a broad panel of murine and human tumor models growing in immunocompetent (SPF-quality, syngeneic strains) or immunodeficient mice (nude, SCID, NOD/SCID). EPO has established imaging technologies to monitor in vivo tumor growth.
Proper citation: Experimental Pharmacology and Oncology Berlin-Buch (RRID:SCR_003954) Copy
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