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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://odin.mdacc.tmc.edu/~xsu1/VirusSeq.html
An algorithmic software tool for detecting known viruses and their integration sites using next-generation sequencing of human cancer tissue. VirusSeq takes FASTQ files (paired-end reads) as input.
Proper citation: VirusSeq (RRID:SCR_005206) Copy
http://snpeff.sourceforge.net/
Genetic variant annotation and effect prediction software toolbox that annotates and predicts effects of variants on genes (such as amino acid changes). By using standards, such as VCF, SnpEff makes it easy to integrate with other programs.
Proper citation: SnpEff (RRID:SCR_005191) Copy
http://gmt.genome.wustl.edu/somatic-sniper/current/
Software program to identify single nucleotide positions that are different between tumor and normal (or, in theory, any two bam files). It takes a tumor bam and a normal bam and compares the two to determine the differences. It outputs a file in a format very similar to Samtools consensus format. It uses the genotype likelihood model of MAQ (as implemented in Samtools) and then calculates the probability that the tumor and normal genotypes are different. This probability is reported as a somatic score. The somatic score is the Phred-scaled probability (between 0 to 255) that the Tumor and Normal genotypes are not different where 0 means there is no probability that the genotypes are different and 255 means there is a probability of 1 ? 10(255/-10) that the genotypes are different between tumor and normal. This is consistent with how the SAM format reports such probabilities. It is currently available as source code via github or as a Debian APT package.
Proper citation: SomaticSniper (RRID:SCR_005108) Copy
Tool for calling indels in Tumor-Normal paired sample mode.
Proper citation: SomaticIndelDetector (RRID:SCR_005107) Copy
A biomedical research institute that aims to understand and develop more effective treatments for human disease, focusing on critical research areas such as heart disease, cancer, lupus and Alzheimer's disease.
Proper citation: Oklahoma Medical Research Foundation (RRID:SCR_005287) Copy
https://www.urmc.rochester.edu/neurosurgery/specialties/neurooncology.aspx
Collaborative neuro-oncology research program with a tissue repository (tumor bank) containing a wide range of clinical specimens, which they make available to researchers in order to study the effects of new drugs on a large number and wide range of tumor specimens. They provide highly coordinated, complex care in neurosurgery, radiation oncology, medical oncology, and neurology to patients afflicted with tumors of the brain and spine by combining the newest technologies and treatments available anywhere in the world. The program is formed from a multidisciplinary group with a goal of helping patients navigate the complex issues surrounding brain and spinal cancer care. The researchers are working to increase the number of targets that could be considered for anti-angiogenesis therapy. Many of their studies focus on the blood vessel cells (endothelial cells) themselves, which, unlike tumor cells, rarely mutate and so might be less likely to become resistant to therapy and are also more easily reached through the bloodstream. Their researchers are also attempting to better understand the changes in the blood-brain barrier (BBB) that are associated with fluid accumulation and brain swelling (edema) in neuro-oncology patients. Normal brain tissue is shielded from the rest of the body by the BBB. This barrier is composed of very tight blood vessels that prevent most substances from entering the brain. Brain tumors have a leaky BBB ����?? this feature can be used to identify tumors on MRI scans. They have identified specific molecules that appear to be associated with the leaky, abnormal vessels while the normal blood vessels with intact BBB produce these molecules at very low levels or not at all. Inhibiting the function of these molecules may help control or prevent disruption of the BBB and limit cerebral edema in brain tumor patients, as well as patients suffering from stroke or traumatic brain injury.
Proper citation: University of Rochester Program for Brain Tumors and Spinal Tumors (RRID:SCR_005343) Copy
http://cancer.ucsf.edu/research/cores/biostatistics
The Biostatistics Core provides statistical support for cancer-related research at UCSF, focusing particulary on applications in clinical trials and population studies. The Computational Biology Core supports applications to genomics, genetics and molecular biology. Core faculty have expertise in study design, protocol and proposal development and review, data analysis, and publication of results. Support for Cancer Center investigators participating in established Site Committees is typically handled by the faculty member assigned to that committee. Other requests can be directed to the consulting service request page maintained by the UCSF Clinical & Translational Science Institute (CTSI). These requests will then be assigned to a Core faculty member. Basic consulting services are generally provided free of charge to Cancer Center Members. Members requiring frequent assistance are encouraged to provide regular salary support to a Core statistician when possible to support more extensive requests and for long-term projects. Services: * Study Design * Guidance on Study Conduct * Data Analysis and Reporting of Study Results * Teaching resources
Proper citation: UCSF Helen Diller Family Comprehensive Cancer Center Biostatistics Core (RRID:SCR_005701) Copy
The Terry Fox Foundation is responsible for supporting close to $20 million in discovery based research each year in Canada - all monies raised outside Canada must be distributed to (a) an institute approved by the Foundation and its advisors or (b) remitted to Canada. The Terry Fox Research Institute (TFRI) is a recipient of TFF funding for translational research. TFRI is an exciting new initiative whose goal is to translate rapidly today''s best science into better cancer treatment and diagnosis for all Canadians. The Institute will bring scientists and clinicians together across the country into a functionally integrated, geographically dispersed Institute with nodes in several provinces. Terry Fox was diagnosed with osteogenic sarcoma (bone cancer) in his right leg in 1977 and had his leg amputated 15 cm (six inches) above the knee. While in hospital, Terry was so overcome by the suffering of other cancer patients that he decided to run across Canada to raise money for cancer research. He called his journey the Marathon of Hope. Terry''s Marathon of Hope took place in 1980 with the simple objective of informing Canadians of the importance of finding a cure for cancer. With fierce determination, he ran an average of 42 kilometres (26 miles) every day for 143 days. Terry was forced to end his run on September 1, 1980 when the cancer spread to his lungs. By February 1, 1981, Terry''s dream of raising $1 for every Canadian was realized - the Terry Fox Marathon of Hope fund totaled $24.17 million. Terry died in June 1981. On May 26, 1988, The Terry Fox Run became a Trust, independent from the Canadian Cancer Society, and received tax-exempt charitable registration as a public foundation. In addition to our signature and long-standing National Terry Fox Run Day in September of each year, The Terry Fox Foundation is proud to include in its events portfolio The National School Run Day. The Foundation recognizes the duality of its mandate. Not only does it raise money for research, but it also continues to share the story of Terry Fox. The Terry Fox Foundation strives to maintain the heroic effort and integrity that Terry embodied. It is a grassroots organization that does not allow the Terry Fox name or likeness to be commercialized or conjoined with other worthy causes. To date, over $600 million has been raised worldwide for cancer research in Terry''s name.
Proper citation: Terry Fox Foundation (RRID:SCR_005873) Copy
https://sites.google.com/site/drivermutationidentification/
Computational tool developed to help identify cancer-associated ''driver'' mutations from ''passenger'' ones in a cancer genome.
Proper citation: DMI (RRID:SCR_008599) Copy
http://dgidb.genome.wustl.edu/
A database of drug-gene relationships that provides drug-gene interactions and potential druggability data given list of genes. There are about 15 data sources that are being aggregated by DGIdb, with update date and these data sources are listed on this page: http://dgidb.genome.wustl.edu/sources, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: DGIdb (RRID:SCR_006608) Copy
The UMD TP53 Mutation Database is a novel web site exclusively dedicated to mutant TP53. The following datasets, analytical tools and software are available. * The TP53 UMD mutation database in human cancer (2012 release). This novel release (35,000 mutations, 3,600 publications) has been highly curated using an original and novel statistical procedure (See Edlung et al. PNAS 2012). * TP53MUTLOAD (MUTant Loss Of Activity Database), a novel database dedicated to detailed analysis of the properties of each TP53 mutant, ranging from transactivation to cell growth properties, change of conformation, localization or various gains of functions. The database contains more than 110,000 different entries. * TP53 Mut assessor, a novel stand-alone software available for both Windows and Mac users. Check your favorite TP53 mutants and get an instant identity card. Very useful to analyze any newly discovered TP53 mutants, as the software checks for every possible TP53 mutation. * MUT-TP53 2.0, an accurate and powerful tool that automatically manages p53 mutations and generate tables ready for publication, decreasing the risk of typing errors. MUT-TP53 2.0 also provides specific information for each TP53 mutation, allowing the user to assess the quality of the data. Up to 500 TP53 mutations can be managed simultaneously.
Proper citation: UMD p53 Mutation Database (RRID:SCR_006720) Copy
Open access resource for human proteins. Used to search for specific genes or proteins or explore different resources, each focusing on particular aspect of the genome-wide analysis of the human proteins: Tissue, Brain, Single Cell, Subcellular, Cancer, Blood, Cell line, Structure and Interaction. Swedish-based program to map all human proteins in cells, tissues, and organs using integration of various omics technologies, including antibody-based imaging, mass spectrometry-based proteomics, transcriptomics, and systems biology. All the data in the knowledge resource is open access to allow scientists both in academia and industry to freely access the data for exploration of the human proteome.
Proper citation: The Human Protein Atlas (RRID:SCR_006710) Copy
http://purl.bioontology.org/ontology/CANCO
A vocabulary that is able to describe and semantically interconnect the different paradigms of the cancer chemoprevention domain.
Proper citation: Cancer Chemoprevention Ontology (RRID:SCR_006966) Copy
http://genomics.senescence.info/
Collection of databases and tools designed to help researchers study the genetics of human ageing using modern approaches such as functional genomics, network analyses, systems biology and evolutionary analyses. A major resource in HAGR is GenAge, which includes a curated database of genes related to human aging and a database of ageing- and longevity-associated genes in model organisms. Another major database in HAGR is AnAge. Featuring over 4,000 species, AnAge provides a compilation of data on aging, longevity, and life history that is ideal for the comparative biology of aging. GenDR is a database of genes associated with dietary restriction based on genetic manipulation experiments and gene expression profiling. Other projects include evolutionary studies, genome sequencing, cancer genomics, and gene expression analyses. The latter allowed them to identify a set of genes commonly altered during mammalian aging which represents a conserved molecular signature of aging. Software, namely in the form of scripts for Perl and SPSS, is made available for users to perform a variety of bioinformatic analyses potentially relevant for studying aging. The Perl toolkit, entitled the Ageing Research Computational Tools (ARCT), provides modules for parsing files, data-mining, searching and downloading data from the Internet, etc. Also available is an SPSS script that can be used to determine the demographic rate of aging for a given population. An extensive list of links regarding computational biology, genomics, gerontology, and comparative biology is also available.
Proper citation: Human Ageing Genomic Resources (RRID:SCR_007700) Copy
http://www.kreftregisteret.no/en/
Comprises 3 registries of cancer patients in Norway: the Incidence Registry, the Clinical Registry and Cancer Statistics. The Incidence Registry contains the basic data items collected from clinicians and pathologists, as well as from administrative discharge and mortality sources. It is updated continuously with information on both new cases, as well as cases diagnosed in previous years. All medical doctors in the country are instructed by law to notify new cancer cases. Clinical Registries: Registration of treatment and follow-up of Norwegian cancer patients. Clinical registries comprehensive registration schemes dedicated to specific cancers have been established to include detailed information on diagnostic measures, therapy, and follow-up. Cancer Statistics: Database of cancer statistics. The Cancer Registry of Norway is maintained by the Institute of Population-based Cancer Research and established in 1951. It is one of the oldest national cancer registries in the world. This, combined with the unique personal identification number used in Norway, makes the Cancer Registry''s data suitable, also internationally; by establishing new knowledge through research and spreading information on cancer.
Proper citation: Cancer Registry of Norway (RRID:SCR_008879) Copy
The UCSF Helen Diller Family Comprehensive Cancer Center combines basic science, clinical research, epidemiology/cancer control, and patient care throughout the University of California, San Francisco. UCSF''s long tradition of excellence in cancer research includes, notably, the Nobel Prize-winning work of J. Michael Bishop and Harold Varmus, who discovered cancer-causing oncogenes. Their work opened new doors for exploring genetic mistakes that cause cancer, and formed the basis for some of the most important cancer research happening today. * Basic Scientific Research: From understanding normal cellular processes and replication to discovering the underlying molecular and genetic causes of cancer when these processes go awry, UCSF researchers are committed to moving scientific insights beyond model systems and pursuing their relevance for clinical oncology and cancer prevention. * Clinical Research: Clinical scientists explore how greater understanding of fundamental biological events can be transformed into clinically relevant tools. New forms of cancer treatment, as well as innovations in diagnosis and prognosis, undergo rigorous evaluation for safety and efficacytranslating into improved patient outcomes and hope for the future. * Patient Care: The Helen Diller Family Comprehensive Cancer Center provides superlative cancer patient care at four San Francisco medical centers: UCSF Medical Center at Mount Zion; UCSF Medical Center at Parnassus; San Francisco General Hospital; and the San Francisco Veterans Affairs Medical Center. * Population Science: Cancer population sciences at UCSF includes a broad range of research on the causes of new cancers and the sickness and death due to the disease in order to develop ways to improve the prevention and early detection of cancer as well as the quality of life following diagnosis and treatment for all of Northern California''s diverse populations.
Proper citation: UCSF Helen Diller Family Comprehensive Cancer Center (RRID:SCR_008857) Copy
http://www.cancerimagingarchive.net/
Archive of medical images of cancer accessible for public download. All images are stored in DICOM file format and organized as Collections, typically patients related by common disease (e.g. lung cancer), image modality (MRI, CT, etc) or research focus. Neuroimaging data sets include clinical outcomes, pathology, and genomics in addition to DICOM images. Submitting Data Proposals are welcomed.
Proper citation: Cancer Imaging Archive (TCIA) (RRID:SCR_008927) Copy
http://purl.bioontology.org/ontology/NPO
An ontology that represents the basic knowledge of physical, chemical and functional characteristics of nanotechnology as used in cancer diagnosis and therapy.
Proper citation: NanoParticle Ontology (RRID:SCR_010369) Copy
http://bg.upf.edu/transfic/home
A method to transform Functional Impact scores taking into account the differences in basal tolerance to germline SNVs of genes that belong to different functional classes.
Proper citation: TransFIC (RRID:SCR_010788) Copy
http://www.c2b2.columbia.edu/danapeerlab/html/jistic.html
Software tool for analyzing datasets of genome-wide copy number variation to identify driver aberrations in cancer.
Proper citation: JISTIC (RRID:SCR_003482) Copy
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