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http://www.dukecancerinstitute.org/

One of 40 centers in the country designated by the National Cancer Institute (NCI) as a comprehensive cancer center, it combines cutting-edge research with compassionate care. Its vision is to accelerate research advances related to cancer and improve Duke''s ability to translate these discoveries into the most advanced cancer care to patients by uniting hundreds of cancer physicians, researchers, educators, and staff across the medical center, medical school, and health system under a shared administrative structure.

Proper citation: Duke Cancer Institute (RRID:SCR_004338) Copy   

•   Source: SciCrunch Registry

http://discovery.hsci.harvard.edu/

An online database of curated cancer stem cell (CSC) experiments coupled to the Galaxy analytical framework. Driven by a need to improve our understanding of molecular processes that are common and unique across cancer stem cells (CSCs), the SCDE allows users to consistently describe, share and compare CSC data at the gene and pathway level. The initial focus has been on carefully curating tissue and cancer stem cell-related experiments from blood, intestine and brain to create a high quality resource containing 53 public studies and 1098 assays. The experimental information is captured and stored in the multi-omics Investigation/Study/Assay (ISA-Tab) format and can be queried in the data repository. A linked Galaxy framework provides a comprehensive, flexible environment populated with novel tools for gene list comparisons against molecular signatures in GeneSigDB and MSigDB, curated experiments in the SCDE and pathways in WikiPathways. Investigation/Study/Assay (ISA) infrastructure is the first general-purpose format and freely available desktop software suite targeted to experimentalists, curators and developers and that: * assists in the reporting and local management of experimental metadata (i.e. sample characteristics, technology and measurement types, sample-to-data relationships) from studies employing one or a combination of technologies; * empowers users to uptake community-defined minimum information checklists and ontologies, where required; * formats studies for submission to a growing number of international public repositories endorsing the tools, currently ENA (genomics), PRIDE (proteomics) and ArrayExpress (transcriptomics). Galaxy allows you to do analyses you cannot do anywhere else without the need to install or download anything. You can analyze multiple alignments, compare genomic annotations, profile metagenomic samples and much much more. Best of all, Galaxy''''s history system provides a complete analyses record that can be shared. Every history is an analysis workflow, which can be used to reproduce the entire experiment. The code for this Galaxy instance is available for download from BitBucket.

Proper citation: Stem Cell Discovery Engine (RRID:SCR_004453) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://cancer.ucsf.edu/

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   

•   Source: SciCrunch Registry

http://wiki.chasmsoftware.org/index.php/Main_Page

CHASM is a method that predicts the functional significance of somatic missense mutations observed in the genomes of cancer cells, allowing mutations to be prioritized in subsequent functional studies, based on the probability that they give the cells a selective survival advantage. SNV-Box is a database of pre-computed features of all possible amino acid substitutions at every position of the annotated human exome. Users can rapidly retrieve features for a given protein amino acid substitution for use in machine learning.

Proper citation: CHASM/SNV-Box (RRID:SCR_006445) Copy   

•   Source: SciCrunch Registry

http://p53.fr

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   

•   Source: SciCrunch Registry

http://www.proteinatlas.org/

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

https://proteomics.cancer.gov/programs/cptac

Clinical proteomic tumor analysis consortium to systematically identify proteins that derive from alterations in cancer genomes and related biological processes, in order to understand molecular basis of cancer that is not possible through genomics and to accelerate translation of molecular findings into clinic. Operates through Proteome Characterization Centers, Proteogenomic Translational Research Centers, and Proteogenomic Data Analysis Centers. CPTAC investigators collaborate, share data and expertise across consortium, and participate in consortium activities like developing standardized workflows for reproducible studies.

Proper citation: CPTAC (RRID:SCR_017135) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://ucsd.researchaccelerator.org/

Software platform that allows researchers to easily collaborate on research and share reagents, antibodies, cell lines and more. It is designed to increase scientific collaboration across disciplines and geographical boundaries. Among the institutions now using the platform include Yale University, U of Pennsylvania, U of Chicago, Washington U, Cambridge University, University College London. The platform is licensed to select institutions. ResearchAccelerator.org allows researchers to form targeted, data driven collaborations. Researchers can search for data based on gene, disease and pathway, and they can post data which would otherwise be orphaned. The resulting collaborations, which are likely to be transdisciplinary, can greatly amplify impact and research productivity.

Proper citation: Research Accelerator (RRID:SCR_006051) Copy   

•   Source: SciCrunch Registry

http://lincs.hms.harvard.edu/db/

Database that contains all publicly available HMS LINCS datasets and information for each dataset about experimental reagents and experimental and data analysis protocols. Experimental reagents include small molecule perturbagens, cells, antibodies, and proteins.

Proper citation: HMS LINCS Database (RRID:SCR_006454) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.lincsproject.org/

Project to create network based understanding of biology by cataloging changes in gene expression and other cellular processes when cells are exposed to genetic and environmental stressors. Program to develop therapies that might restore pathways and networks to their normal states. Has LINCS Data Coordination and Integration Center and six Data and Signature Generation Centers: Drug Toxicity Signature Generation Center, HMS LINCS Center, LINCS Center for Transcriptomics, LINCS Proteomic Characterization Center for Signaling and Epigenetics, MEP LINCS Center, and NeuroLINCS Center.

Proper citation: LINCS Project (RRID:SCR_016486) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.Ablynx.com

A biopharmaceutical company engaged in the discovery and development of Nanobodies, a novel class of antibody-derived therapeutic proteins based on single-domain antibody fragments, for a range of serious life-threatening human diseases including inflammation, hematology, oncology and pulmonary disease.

Proper citation: Ablynx (RRID:SCR_002940) Copy   

•   Source: SciCrunch Registry

http://www.wikicancer.org/

A place where people connected to cancer can share real-life experiences -- fears, insights, stories, and advice. Adding perspectives is easy, and every contribution builds the site into a more valuable and unique community resource. Content, resources, and support on wikiCancer: * Just been diagnosed with cancer? * Living with cancer * For cancer survivors * How to support someone with cancer * Connect with other cancer patients, survivors, family and caregivers

Proper citation: wikiCancer (RRID:SCR_001824) Copy   

•   Source: SciCrunch Registry