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http://www.ngfn.de/en/start.html
The program of medical genome research is a large-scale biomedical research project which extends the national genome research net (NGFN) and will be funded by the federal ministry of education and research (BMBF) from 2008-2013. Currently the program includes two fields: * Research ** NGFN-Plus: With the aim on combating diseases that are central to health policy, several hundred researchers are systematically investigating the complex molecular interactions of the human body. They are organized in 26 Integrated Genome Research Networks. * Application ** NGFN-Transfer: The rapid transfer of results from medical genome research into medical and industrial application is the aim of the scientists from research institutes and biomedical enterprises that cooperate in eight Innovation Alliances. AREAS OF DISEASE * Cardiovascular disease * Cancer * Neuronal diseases * Infections and Inflammations * Environmental factors
Proper citation: National Genome Research Network (RRID:SCR_006626) Copy
http://sharedresources.fredhutch.org/core-facilities/cceh-administration
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July,27,2022. Core facility that provides scientific and budgetary oversight for all CCEH activities. This includes training programs, high school summer internships, and and pilot and feasibility program for new projects.
Proper citation: Fred Hutchinson Cancer Research Center Co-operative Center for Excellence in Hematology (RRID:SCR_015320) Copy
https://dctd.cancer.gov/programs/cdp/organization/bbrb
BBRB supports medical discovery and precision medicine by providing leadership, tools, and resources to the biobanking community. Provides input on policy related to biobanking and supports the availability of biospecimens for research. Develops standardized procedures for biospecimen science and research; conducts and sponsors research on the effects of biospecimen preanalytical factors; leads and supports major scientific initiatives requiring high-quality biospecimens; and supports investigations into the ethical, legal, and social issues concerning biospecimen collection and use.
Proper citation: Biorepositories and Biospecimens Research Branch (RRID:SCR_013979) Copy
http://www.lji.org/faculty-research/scientific-cores/functional-genomics-sequencing-core/#overview
Non profit collaborative research organization located in La Jolla, California, UCSD Research Park. Institute researches immunology and immune system diseases to pinpoint specific genes involved, accelerate progress toward development of new treatments and vaccines to prevent and cure type 1 diabetes, cancer and infectious disease. Developer of Immune Epitope Database (IEDB). Provides core facilities with access to equipment, technologies, training and expertise to support innovative research.
Proper citation: La Jolla Institute for Immunology (RRID:SCR_014837) Copy
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
Center includes studies for responsiveness and resistance to anti cancer drugs. Committed to training students and postdocs, promoting junior faculty and ensuring that data and software are reproducible, reliable and publicly accessible. Member of National Cancer Institute’s Cancer Systems Biology Consortium.
Proper citation: Harvard Medical School Center for Cancer Systems Pharmacology (RRID:SCR_022831) Copy
Software used to simulate tumor progression in various stages of growth in order to study the process' dynamics. The input can be fitness landscape, mutation rate, and cell division time. The output is growth dynamics and other relevant statistics, such as expected tumor detection time and expected appearance time of surviving mutants. The tool is implemented in Java and runs on all operating systems which run a Java Virtual Machine (JVM) of version 1.7 or above.
Proper citation: Tool for Tumor Progression (RRID:SCR_014700) 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
https://github.com/wenmm/EssSubgraph/tree/main
A model algorithm that integrates omics data and network data to predict essential genes.
Proper citation: EssSubgraph (RRID:SCR_027354) 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
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
canSAR is an integrated database that brings together biological, chemical, pharmacological (and eventually clinical) data. Its goal is to integrate this data and make it accessible to cancer research scientists from multiple disciplines, in order to help with hypothesis generation in cancer research and support translational research. This cancer research and drug discovery resource was developed to utilize the growing publicly available biological annotation, chemical screening, RNA interference screening, expression, amplification and 3D structural data. Scientists can, in a single place, rapidly identify biological annotation of a target, its structural characterization, expression levels and protein interaction data, as well as suitable cell lines for experiments, potential tool compounds and similarity to known drug targets. canSAR has, from the outset, been completely use-case driven which has dramatically influenced the design of the back-end and the functionality provided through the interfaces. The Web interface provides flexible, multipoint entry into canSAR. This allows easy access to the multidisciplinary data within, including target and compound synopses, bioactivity views and expert tools for chemogenomic, expression and protein interaction network data.
Proper citation: canSAR (RRID:SCR_006794) Copy
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
http://www.bwhct.nhs.uk/wmrgl/biobank-cehrb
The Central England Haemato-Oncology Research Biobank stores excess material from oncology samples referred for diagnostic testing and disease monitoring at the West Midlands Regional Genetics Laboratory (WMRGL). The bank is housed within the WMRGL. Types of material stored include viable cells, fixed cell suspensions, DNA, RNA / cDNA, and plasma. The material is made available to all cancer research groups both locally and nationally. Excess sample (mainly from blood and bone marrow) is stored from diagnostic patient material and from samples received throughout their disease course. The WMRGL serves a population of about 5.5 million and is the largest UK NHS genetic Lab. Due to the large patient population CEHRB is able to collate sufficient research material from all classifications of neoplastic haematological disorders including those that are rare.
Proper citation: Central England Haemato-Oncology Research Biobank (RRID:SCR_004637) Copy
http://ccr.coriell.org/Sections/Collections/Wistar/?SsId=74
Collection of cell lines developed by Wistar scientists that includes a group of hybridomas that produce monoclonal antibodies that are useful in influenza research and vaccine development, melanoma cell lines derived from patients with diseases ranging from mild dysplasia to advanced metastatic cancer and a range of human endothelial cell lines.
Proper citation: Wistar Institute Collection at Coriell (RRID:SCR_004660) Copy
HTAN is National Cancer Institute funded Cancer Moonshot initiative to construct 3-dimensional atlases of dynamic cellular, morphological, and molecular features of human cancers as they evolve from precancerous lesions to advanced disease.Provides three dimensional atlases of cancer transitions for diverse set of tumor types. Efforts to map healthy organs and previous large-scale cancer genomics approaches focused on bulk sequencing at single point in time. Data portal for Human Tumor Atlas Network. Data available on HTAN Portal is open access. Certain data types with potential for re-identification are available in restricted access through dbGAP.
Proper citation: Human Tumor Atlas Network (RRID:SCR_023364) Copy
Cancer research platform that aggregates clinical, genomic and functional data from various types of patient derived cancer models, xenographs, organoids and cell lines. Open catalog of harmonised patient-derived cancer models. Standardises, harmonises and integrates clinical metadata, molecular and treatment-based data from academic and commercial providers worldwide. Data is FAIR and underpins generation and testing of new hypotheses in cancer mechanisms and personalised medicine development. PDCM Finder have expanded to organoids and cell lines and is now called CancerModels.Org. PDCM Finder was launched in April 2022 as successor of PDX Finder portal, which focused solely on patient-derived xenograft models.
Proper citation: CancerModels.Org (RRID:SCR_023931) Copy
Regularly collects nationally representative data about American public’s knowledge of, attitudes toward, and use of cancer and health related information. HINTS data are used to monitor changes in fields of health communication and health information technology and to create more effective health communication strategies across different populations. Weighted, nationally representative probability based survey of civilian, non-institutionalized adults administered by National Cancer Institute on knowledge of and attitudes toward cancer relevant information.
Proper citation: Health Information National Trends Survey (RRID:SCR_023943) Copy
https://seer.cancer.gov/csr/1975_2016/
Platform to report outlining trends in cancer statistics and methods to derive various cancer statistics from the Surveillance, Epidemiology, and End Results (SEER) program. Authoritative source for cancer statistics in the United States.
Proper citation: NCI SEER Cancer Statistics Review (RRID:SCR_024685) Copy
https://ganjoho.jp/public/index.html
Portal provides information on Cancer Statistics in Japan. Official website operated by National Cancer Center for cancer information.
Proper citation: Cancer Information Service (RRID:SCR_024445) Copy
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