Tools   Select Another Resource Report Type

http://code.google.com/p/drgap/

Designed to identify Driver Genes and Pathways in cancer genome sequencing studies.

Proper citation: DrGaP (RRID:SCR_008670) Copy   

•   Source: SciCrunch Registry

https://cansar.icr.ac.uk/

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   

•   Source: SciCrunch Registry

http://seer.cancer.gov/

SEER collects cancer incidence data from population-based cancer registries covering approximately 47.9 percent of the U.S. population. The SEER registries collect data on patient demographics, primary tumor site, tumor morphology, stage at diagnosis, and first course of treatment, and they follow up with patients for vital status.There are two data products available: SEER Research and SEER Research Plus. This was motivated because of concerns about the increasing risk of re-identifiability of individuals. The Research Plus databases require more rigorous process for access that includes user authentication through Institutional Account or multiple-step request process for Non-Institutional users.

Proper citation: Surveillance Epidemiology and End Results (RRID:SCR_006902) Copy   

•   Source: SciCrunch Registry

http://www.cancergenomics.org/

Consortium promoting communication and collaboration among cancer cytogenomics laboratories, who are interested in applying microarray technologies to cancer diagnosis and cancer research. Their oals are to (1) establish platform-neutral and cancer specific microarray designs for diagnostic purposes, (2) share cancer microarray data between participating institutions for education purposes, (3) create a public cancer array database, and (4) carry out multicenter cancer genome translational research. Collaboration amongst the different laboratories and researchers will not only provide validation for the microarray design(s) but ultimately provide more comprehensive molecular information and more accurate interpretation to better serve cancer patients and further cancer research. The CGC was officially incorporated in June 2010 as a not-for-profit organization.

Proper citation: Cancer Genomics Consortium (RRID:SCR_002384) Copy   

•   Source: SciCrunch Registry

http://hardinmd.lib.uiowa.edu/index.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 2, 2025. A medical database with lists, or directories, of information in health and medicine and images of medical conditions. Users may search Hardin MD, browse through the Medical picture gallery, and sort search results by disease or alphabetical letter.

Proper citation: Hardin MD (RRID:SCR_002364) Copy   

•   Source: SciCrunch Registry

https://cghub.ucsc.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on March 17, 2022. A secure repository for storing, cataloging, and accessing cancer genome sequences, alignments, and mutation information from the Cancer Genome Atlas (TCGA) consortium and related projects. CGHub gives scientific researchers the statistical power of large cancer genome datasets to attack the molecular complexity of cancer.

Proper citation: Cancer Genomics Hub (RRID:SCR_002657) Copy   

•   Source: SciCrunch Registry

http://www.celgene.com

An American global biotechnology company that manufactures drug therapies for cancer and inflammatory disorders. The company's major products are Thalomid (thalidomide), which is approved for the acute treatment of the cutaneous manifestations of moderate to severe erythema nodosum leprosum (ENL), as well as in combination with dexamethasone for patients with newly diagnosed multiple myeloma, and Revlimid (lenalidomide), for which the company has received FDA and EMA approval in combination with dexamethasone for the treatment of multiple myeloma patients who have received at least one prior therapy. Revlimid is also approved in the United States for the treatment of patients with transfusion-dependent anemia due to Low- or Intermediate-1-risk Myelodysplastic syndromes (MDS) associated with a deletion 5q cytogenetic abnormality with or without additional cytogenetic abnormalities. Both Thalomid and Revlimid are sold through proprietary risk-management distribution programs to ensure safe and appropriate use of these pharmaceuticals. Vidaza is approved for the treatment of patients with MDS. Celgene also receives royalties from Novartis Pharma AG on sales of the entire Ritalin family of drugs, which are widely used to treat Attention Deficit Hyperactivity Disorder (ADHD). (Adapted from Wikipedia) There are numerous clinical trials at major medical centers using compounds from Celgene. Investigational compounds are being studied for patients with incurable hematological and solid tumor cancers, including multiple myeloma, myelodysplastic syndromes, chronic lymphocyte leukemia (CLL), non-Hodgkin's lymphoma (NHL), glioblastoma, and ovarian, pancreatic and prostate cancer.

Proper citation: Celgene (RRID:SCR_002955) Copy   

•   Source: SciCrunch Registry

http://cgap.nci.nih.gov/

Project to determine the gene expression profiles of normal, precancer, and cancer cells, whose generated resources are available to the cancer community. Interconnected modules provide access to all CGAP data, bioinformatic analysis tools, and biological resources allowing the user to find in silico answers to biological questions in a fraction of the time it once took in the laboratory. * Genes * Tissues * Pathways * RNAi * Chromosomes * SAGE Genie * Tools

Proper citation: Cancer Genome Anatomy Project (RRID:SCR_003072) Copy   

•   Source: SciCrunch Registry

http://www.dtp.nci.nih.gov

Portal for preclinical information and research materials, including web-accessible data and tools, NCI-60 Tumor Cell Line Screen, compounds in vials and plates, tumor cells, animals, and bulk drugs for investigational new drug (IND)-directed studies. DTP has been involved in the discovery or development of more than 70 percent of the anticancer therapeutics on the market today, and will continue helping the academic and private sectors to overcome various therapeutic development barriers, particularly through supporting high-risk projects and therapeutic development for rare cancers. Initially DTP made its drug discovery and development services and the results from the human tumor cell line assay publicly accessible to researchers worldwide. At first, the site offered in vitro human cell line data for a few thousand compounds and in vitro anti-HIV screening data for roughly 42,000 compounds. Today, visitors can find: * Downloadable in vitro human tumor cell line data for some 43,500 compounds and 15,000 natural product extracts * Results for 60,000 compounds evaluated in the yeast assay * In vivo animal model results for 30,000 compounds * 2-D and 3-D chemical structures for more than 200,000 compounds * Molecular target data, including characterizations for at least 1,200 targets, plus data from multiple cDNA microarray projects In addition to browsing DTP's databases and downloading data, researchers can request individual samples or sets of compounds on 96-well plates for research, or they can submit their own compounds for consideration for screening via DTP's online submission form. Once a compound is submitted for screening, researchers can follow its progress and retrieve data using a secure web interface. The NCI has collected information on almost half a million chemical structures in the past 50 years. DTP has made this information accessible and useful for investigators through its 3-D database, a collection of three-dimensional structures for more than 200,000 drugs. Investigators use the 3-D database to screen compounds for anticancer therapeutic activity. Also available on DTP's website are 127,000 connection tables for anticancer agents. A connection table is a convenient way of depicting molecular structures without relying on drawn chemical structures. As unique lists of atoms and their connections, the connection tables can be indexed and stored in computer databases where they can be used for patent searches, toxicology studies, and precursor searching, for example., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Developmental Therapeutics Program (RRID:SCR_003057) Copy   

•   Source: SciCrunch Registry

http://www.dana-farber.org/

Cancer institute that provides expert, compassionate care to children and adults with cancer while advancing the understanding, diagnosis, treatment, cure, and prevention of cancer and related diseases. As an affiliate of Harvard Medical School and a Comprehensive Cancer Center designated by the National Cancer Institute, the Institute also provides training for new generations of physicians and scientists, designs programs that promote public health particularly among high-risk and underserved populations, and disseminates innovative patient therapies and scientific discoveries to their target community across the United States and throughout the world.

Proper citation: Dana-Farber Cancer Institute (RRID:SCR_003040) Copy   

•   Source: SciCrunch Registry

https://sites.google.com/site/oncosnp/

An analytical software tool for characterizing copy number alterations and loss-of-heterozygosity (LOH) events in cancer samples from SNP genotyping data.

Proper citation: OncoSNP (RRID:SCR_012985) Copy   

•   Source: SciCrunch Registry

http://www.genesigdb.org

Database of traceable, standardized, annotated gene signatures which have been manually curated from publications that are indexed in PubMed. The Advanced Gene Search will perform a One-tailed Fisher Exact Test (which is equivalent to Hypergeometric Distribution) to test if your gene list is over-represented in any gene signature in GeneSigDB. Gene expression studies typically result in a list of genes (gene signature) which reflect the many biological pathways that are concurrently active. We have created a Gene Signature Data Base (GeneSigDB) of published gene expression signatures or gene sets which we have manually extracted from published literature. GeneSigDB was creating following a thorough search of PubMed using defined set of cancer gene signature search terms. We would be delighted to accept or update your gene signature. Please fill out the form as best you can. We will contact you when we get it and will be happy to work with you to ensure we accurately report your signature. GeneSigDB is capable of providing its functionality through a Java RESTful web service.

Proper citation: GeneSigDB (RRID:SCR_013275) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages//2.10/bioc/html/CancerMutationAnalysis.html

Software package that implements gene and gene-set level analysis methods for somatic mutation studies of cancer.

Proper citation: CancerMutationAnalysis (RRID:SCR_013181) Copy   

•   Source: SciCrunch Registry

https://omictools.com/l2l-tool

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone.. Documented on August 26, 2019.

Database of published microarray gene expression data, and a software tool for comparing that published data to a user''''s own microarray results. It is very simple to use - all you need is a web browser and a list of the probes that went up or down in your experiment. If you find L2L useful please consider contributing your published data to the L2L Microarray Database in the form of list files. L2L finds true biological patterns in gene expression data by systematically comparing your own list of genes to lists of genes that have been experimentally determined to be co-expressed in response to a particular stimulus - in other words, published lists of microarray results. The patterns it finds can point to the underlying disease process or affected molecular function that actually generated the observed changed in gene expression. Its insights are far more systematic than critical gene analyses, and more biologically relevant than pure Gene Ontology-based analyses. The publications included in the L2L MDB initially reflected topics thought to be related to Cockayne syndrome: aging, cancer, and DNA damage. Since then, the scope of the publications included has expanded considerably, to include chromatin structure, immune and inflammatory mediators, the hypoxic response, adipogenesis, growth factors, hormones, cell cycle regulators, and others. Despite the parochial origins of the database, the wide range of topics covered will make L2L of general interest to any investigator using microarrays to study human biology. In addition to the L2L Microarray Database, L2L contains three sets of lists derived from Gene Ontology categories: Biological Process, Cellular Component, and Molecular Function. As with the L2L MDB, each GO sub-category is represented by a text file that contains annotation information and a list of the HUGO symbols of the genes assigned to that sub-category or any of its descendants. You don''''t need to download L2L to use it to analyze your microarray data. There is an easy-to-use web-based analysis tool, and you have the option of downloading your results so you can view them at any time on your own computer, using any web browser. However, if you prefer, the entire L2L project, and all of its components, can be downloaded from the download page. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: L2L Microarray Analysis Tool (RRID:SCR_013440) Copy   

•   Source: SciCrunch Registry

http://pub.ist.ac.at/ttp/

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   

•   Source: SciCrunch Registry

http://sharedresources.fredhutch.org/core-facilities/bioinformatics

THIS RESOURCE IS NO LONGER IN SERVICE.Documented on July 27,2022. Core provides bioinformatics specialists available to assist researchers with processing, exploring, and understanding genomics data.

Proper citation: Fred Hutchinson Cancer Research Center Co-operative Center for Excellence in Hematology Bioinformatics Resource (RRID:SCR_015324) Copy   

•   Source: SciCrunch Registry

http://gepia.cancer-pku.cn

Web server for cancer and normal gene expression profiling and interactive analyses. Interactive web server for analyzing RNA sequencing expression data of tumors and normal samples from TCGA and GTEx projects, using standard processing pipeline. Provides customizable functions such as tumor or normal differential expression analysis, profiling according to cancer types or pathological stages, patient survival analysis, similar gene detection, correlation analysis and dimensionality reduction analysis.

Proper citation: Gene Expression Profiling Interactive Analysis (RRID:SCR_018294) Copy   

•   Source: SciCrunch Registry

http://www.janssenrnd.com/

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   

•   Source: SciCrunch Registry

http://www.althia.es/

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   

•   Source: SciCrunch Registry

https://www.bigtencrc.org/

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   

•   Source: SciCrunch Registry