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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.
http://glioblastoma.alleninstitute.org/
Platform for exploring the anatomic and genetic basis of glioblastoma at the cellular and molecular levels that includes two interactive databases linked together by de-identified tumor specimen numbers to facilitate comparisons across data modalities: * The open public image database, here, providing in situ hybridization data mapping gene expression across the anatomic structures inherent in glioblastoma, as well as associated histological data suitable for neuropathological examination * A companion database (Ivy GAP Clinical and Genomic Database) offering detailed clinical, genomic, and expression array data sets that are designed to elucidate the pathways involved in glioblastoma development and progression. This database requires registration for access. The hope is that researchers all over the world will mine these data and identify trends, correlations, and interesting leads for further studies with significant translational and clinical outcomes. The Ivy Glioblastoma Atlas Project is a collaborative partnership between the Ben and Catherine Ivy Foundation, the Allen Institute for Brain Science and the Ben and Catherine Ivy Center for Advanced Brain Tumor Treatment.
Proper citation: Ivy Glioblastoma Atlas Project (RRID:SCR_005044) Copy
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
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
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
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
http://www.ibridgenetwork.org/wustl/splinter
Software that detects and quantifies short IN/DELs as well as single nucleotide substitutions in pooled-DNA samples.
Proper citation: SPLINTER (RRID:SCR_005826) Copy
The American Cancer Society is the nationwide, community-based, voluntary health organization dedicated to eliminating cancer as a major health problem by preventing cancer, saving lives, and diminishing suffering from cancer, through research, education, advocacy, and service. Together with our millions of supporters, the American Cancer Society (ACS) saves lives and creates a world with less cancer and more birthdays by helping people stay well, helping people get well, by finding cures, and by fighting back. Headquartered in Atlanta, Georgia, the ACS has 12 chartered Divisions, more than 900 local offices nationwide, and a presence in more than 5,100 communities.
Proper citation: American Cancer Society (RRID:SCR_005756) Copy
https://array.nci.nih.gov/caarray/
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on Sep 18, 2018. Open-source, web and programmatically accessible microarray data management system. caArray guides the annotation and exchange of array data using a federated model of local installations whose results are shareable across the cancer Biomedical Informatics Grid (caBIG). caArray furthers translational cancer research through acquisition, dissemination and aggregation of semantically interoperable array data to support subsequent analysis by tools and services on and off the Grid. As array technology advances and matures, caArray will extend its logical library of assay management.
Proper citation: caArray (RRID:SCR_006053) Copy
Funds patient-focused research on gliomas to develop better diagnostics and treatments that lead to long-term survival and a high quality of life for patients with brain tumors. The goal is to decrease the suffering of patients with brain tumors. With an ultimate goal to cure brain cancer, their immediate goal is to improve diagnostics and treatment. They are dedicated to improving the lives of all patients with brain cancer by funding research that they hope will lead to the doubling of life expectancy of patients with brain cancer. Their goal is to do this within the next seven years. Since 2005 they''ve committed more than $50 million to research into brain tumors, with the expectation that this will lead to better diagnostics and therapies. They are dedicated to this search because funding leads to answers, and answers lead to hope.
Proper citation: Ben and Catherine Ivy Foundation (RRID:SCR_006333) Copy
A federated data sharing platform and infrastructure that provides access to real-time clinical, imaging and biospecimen data across jurisdictions, institutions and diseases. The web-based platform provides a secure infrastructure that advances health research by linking privacy-protected and ethically approved data among a wide network of health collaborators. Access to de-identified health records data is granted to authorized researchers after an application process so patient privacy and intellectual property are protected. BioGrid Australia''s approved researchers are provided access to multiple institutional databases, via the BioGrid interface, preventing gaps in patient records and research analysis. This legal and ethical arrangement with participating collaborators allows BioGrid to connect data through a common platform where data governance and access is managed by a highly skilled team. Data governance, security and ethics are at the core of BioGrid''s federated data sharing platform that securely links patient level clinical, biospecimen, genetic and imaging data sets across multiple sites and diseases for the purpose of medical research. BioGrid''s infrastructure and data management strategies address the increasing need by authorized researchers to dynamically extract and analyze data from multiple sources whilst protecting patient privacy. BioGrid has the capability to link data with other datasets, produce tailored reports for auditing and reporting and provide statistical analysis tools to conduct more advanced research analysis. In the health sector, BioGrid is a trusted independent virtual real-time data repository. Government investment in BioGrid has facilitated a combination of technology, collaboration and ethics approval processes for data sharing that exist nowhere else in the world.
Proper citation: BioGrid Australia (RRID:SCR_006334) 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
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
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
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