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https://pdc.cancer.gov/pdc/

Portal to make cancer related proteomic datasets easily accessible to public. Facilitates multiomic integration in support of precision medicine through interoperability with other resources. Developed to advance our understanding of how proteins help to shape risk, diagnosis, development, progression, and treatment of cancer. One of several repositories within NCI Cancer Research Data Commons which enables researchers to link proteomic data with other data sets (e.g., genomic and imaging data) and to submit, collect, analyze, store, and share data throughout cancer data ecosystem. PDC provides access to highly curated and standardized biospecimen, clinical, and proteomic data, intuitive interface to filter, query, search, visualize and download data and metadata. Provides common data harmonization pipeline to uniformly analyze all PDC data and provides advanced visualization of quantitative information. Cloud based (Amazon Web Services) infrastructure facilitates interoperability with AWS based data analysis tools and platforms natively. Application programming interface (API) provides cloud-agnostic data access and allows third parties to extend functionality beyond PDC. Structured workspace that serves as private user data store and also data submission portal. Distributes controlled access data, such as patient-specific protein fasta sequence databases, with dbGaP authorization and eRA Commons authentication.

Proper citation: Proteomic Data Commons (RRID:SCR_018273) 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://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://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://portal.imaging.datacommons.cancer.gov

Portal for finding and analyzing cancer imaging data. Part of Cancer Research Data Commons to support cancer imaging research. Provides cloud based access to medical imaging data and library of analytical tools and workflows to share, analyze, and visualize multi modal imaging data from both clinical and basic cancer research studies.

Proper citation: NCI Imaging Data Commons (RRID:SCR_019127) Copy   

•   Source: SciCrunch Registry

https://datacommons.cancer.gov

Cloud based data science infrastructure that provides secure access to cancer research data from NCI programs and key external cancer programs. Serves as coordinated resource for public data sharing of NCI funded programs. Users can explore and use analytical and visualization tools for data analysis. Enables to search and aggregate data across repositories including Cancer Data Service, Clinical Trial Data Commons, Genomic Data Commons, Imaging Data Commons, Integrated Canine Data Commons, Proteomic Data Commons.

Proper citation: Cancer Research Data Commons (RRID:SCR_019128) 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://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://www.lyonbiopole.com/index-en.html

A worldwide competitiveness cluster centered on pharmaceutical activities including the fight against human and animal infectious diseases and cancers. Designed as a tool interface and public / private approximation, the division has implemented measures to encourage collaborative R & D, help in setting up projects and find funding, increase strategic and financial partnerships for economic development and international companies, provide access to reception areas, technological shared platforms such as the Infectious Diseases Center Lyonbiop��le. It aims to strengthen the competitiveness of the sector health and the attractiveness of the Rh��ne-Alpes area, mainly on the Lyon-Grenoble axis. (adapted from the translated Wikipedia)

Proper citation: Lyonbiopole (RRID:SCR_003733) Copy   

•   Source: SciCrunch Registry

http://www.thesgc.org/

Charity registered in United Kingdom whose mission is to accelerate research in new areas of human biology and drug discovery.Not for profit, public-private partnership that carries out basic science of relevance to drug discovery whose core mandate is to determine 3D structures on large scale and cost effectively targeting human proteins of biomedical importance and proteins from human parasites that represent potential drug targets.

Proper citation: Structural Genomics Consortium (RRID:SCR_003890) Copy   

•   Source: SciCrunch Registry

http://www.eortc.org/clinical-trials

A database that contains information about EORTC (European Organisation for Research and Treatment of Cancer) clinical trials but also clinical trials from other organizations, in which EORTC has been/is participating. The protocol database may be browsed by EORTC Research Group, tumor site, treatment, or drug.

Proper citation: EORTC Clinical Trials (RRID:SCR_004011) Copy   

•   Source: SciCrunch Registry

http://norccentral.org

Portal to research centers and core facilities specifically support obesity research and better understand the relationship between health and nutrition.

Proper citation: Nutrition and Obesity Research Centers (RRID:SCR_004131) Copy   

•   Source: SciCrunch Registry

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

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