Tools   Select Another Resource Report Type

http://danstem.ku.dk/

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.epo-berlin.com/

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   

•   Source: SciCrunch Registry

http://www.alacris.de/

Commercial organization that uses next generation sequencing technologies coupled with computational modeling of tumor and somatic tissues in order to identify individualized therapies for cancer patients. The company also uses these technologies to help pharmaceutical partners stratify patients for their clinical trials. Alacris has an exclusive worldwide commercial license for the computational modeling of tumors and somatic tissues using proprietary computational systems modeling technologies ModCell developed at the Max Planck Institute for Molecular Genetics (MPI-MG) in Berlin coupled with next generation sequencing and genotyping technology developed at Harvard Medical School in Boston. The company also is building up the first next generation sequencing center in Europe for clinical operations.

Proper citation: Alacris Theranostics (RRID:SCR_003953) Copy   

•   Source: SciCrunch Registry

https://hoosiercancer.org/

An independent nonprofit cancer research organization that provides full-service clinical trial management and support, from conception and study design through project completion and publication. Established to explore and develop leading edge cancer treatments across the United States and internationally, their clinical trials, developed in collaboration with academic and community oncologists, are conducted within a member network of more than 130 clinical research sites. Their vision and mission is to form unparalleled relationships between academic, community, pharmaceutical, and biotech partners with the goal of advancing cancer research, education, and patient advocacy. There are no costs to become a member.

Proper citation: Hoosier Cancer Research Network (RRID:SCR_004026) Copy   

•   Source: SciCrunch Registry

http://www.bccancer.bc.ca/default.htm

A portal that provides a province-wide, population-based cancer control program for the residents of British Columbia and the Yukon. The BC Cancer Agency''s mandate covers the spectrum of cancer care, from prevention and screening, to diagnosis, treatment, and through to rehabilitation. The BC Cancer Agency''s mandate is driven by a three-fold mission: 1. To reduce the incidence of cancer; 2. To reduce the mortality rate of people with cancer; 3. To improve the quality of life of people living with cancer. This mission drives everything we do, including providing screening, diagnosis and care, setting treatment standards, and conducting research into causes of, and cures for, cancer. The BC Cancer Agency operates five regional cancer centers, providing assessment and diagnostic services, chemotherapy, radiation therapy, and supportive care. Each of the BC Cancer Agency''s centers delivers cancer treatment based on provincial standards and guidelines established by the Agency. We work in partnership with communities to provide a network of chemotherapy clinics so patients can receive care closer to home. Research is an essential part of the BC Cancer Agency''s mission to not only find the causes of cancer, but to find better treatments for prolonged life and better quality of life. With direct links between the BC Cancer Agency''s physicians and researchers at our five centers, the Deeley Research Centre (located in Victoria) and the BC Cancer Agency''s Research Centre (located in Vancouver), we can quickly translate new discoveries into clinical applications. The BC Cancer Agency''s Research Centre includes eight specialty laboratories including the Genome Sciences Centre, and the Terry Fox Laboratory. The BC Cancer Foundation raises funds for cancer research and enhancements to care at the BC Cancer Agency.

Proper citation: BC Cancer Agency (RRID:SCR_004201) Copy   

•   Source: SciCrunch Registry

http://www.cancerdiagnosis.nci.nih.gov/

National program to improve the diagnosis and assessment of cancer by moving scientific knowledge into clinical practice by coordinating and funding resources and research for the development of innovative in vitro diagnostics, novel diagnostic technologies and appropriate human specimens. The Cancer Diagnosis Program is divided into four branches: Biorepository and Biospecimen Research Branch (BBRB), Diagnostic Biomarkers and Technology Branch (DBTB), Diagnostics Evaluation Branch (DEB), and the Pathology Investigation and Resources Branch (PIRB).

Proper citation: CDP (RRID:SCR_004236) Copy   

•   Source: SciCrunch Registry

http://www.decode.com/

A biopharmaceutical company applying its discoveries in human genetics to develop drugs and diagnostics for common diseases. They specialize in gene discovery - their population approach and resources have enabled them to isolate key genes contributing to major public health challenges from cardiovascular disease to cancer. The company's genotyping capacity is now one of the highest in the world. They have a large population-based biobank containing whole blood and DNA samples with extensive relevant phenotypic information from around 120.000 Icelanders. In the company's work in more than 50 disease projects, their statistical and informatics departments have established themselves in data processing and analysis. deCODE genetics is widely recognized as a center of excellence in genetic research.

Proper citation: deCODE genetics (RRID:SCR_003334) Copy   

•   Source: SciCrunch Registry

http://ncit.nci.nih.gov/

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   

•   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   

•   Source: SciCrunch Registry

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   

•   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://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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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

http://www.nitrc.org/projects/tumorsim/

Simulation software that generates pathological ground truth from a healthy ground truth. The software requires an input directory that describes a healthy anatomy (anatomical probabilities, mesh, diffusion tensor image, etc) and then outputs simulation images.

Proper citation: TumorSim (RRID:SCR_002604) Copy   

•   Source: SciCrunch Registry

http://seer.cancer.gov/resources/

Portal provides SEER research data and software SEER*Stat and SEER*Prep. SEER incidence and population data associated by age, sex, race, year of diagnosis, and geographic areas can be used to examine stage at diagnosis by race/ethnicity, calculate survival by stage at diagnosis, age at diagnosis, and tumor grade or size, determine trends and incidence rates for various cancer sites over time. SEER releases new research data every Spring based on the previous November’s submission of data.

Proper citation: SEER Datasets and Software (RRID:SCR_003293) Copy   

•   Source: SciCrunch Registry