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http://www.binfo.ncku.edu.tw/TAG/GeneDoc.php

A database of oncogenes and tumor suppressor genes. Users can search by genes, chromosomes, and keywords. The coAnsensus domain analysis tool functions to identify conserved protein domains and GO terms among selected TAG genes, while the “oncogenic domain analysis” can analyze oncogenic potential of any user-provided protein based on a weighed term frequency table calculated from the TAG proteins. The completion of human genome sequences allows one to rapidly identify and analyze genes of interest through the use of computational approach. The available annotations including physical characterization and functional domains of known tumor-related genes thus can be used to study the role of genes involved in carcinogenesis. The tumor-associated gene (TAG) database was designed to utilize information from well-characterized oncogenes and tumor suppressor genes to facilitate cancer research. All target genes were identified through text-mining approach from the PubMed database. A semi-automatic information retrieving engine was built to collect specific information of these target genes from various resources and store in the TAG database. At current stage, 519 TAGs including 198 oncogenes, 170 tumor suppressor genes, and 151 genes related to oncogenesis were collected. Information collected in TAG database can be browsed through user-friendly web interfaces that provide searching genes by chromosome or by keywords. The “consensus domain analysis” tool functions to identify conserved protein domains and GO terms among selected TAG genes. In addition, the “oncogenic domain analysis” can analyze oncogenic potential of any user-provided protein based on a weighed term frequency table calculated from the TAG proteins. This study was supported by grant from National research program for genomic medicine (NRPGM) and personnel from Bioinformatics Center of Center for Biotechnology and Biosciences in the National Cheng Kung University, Taiwan.

Proper citation: Tumor Associated Gene database (RRID:SCR_005754) Copy   

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http://www.bioinfo.org.cn/hptaa/

To accelerate the process of tumor antigen discovery, we generated a publicly available Human Potential Tumor Associated Antigen database (HPtaa) with pTAAs identified by insilico computing. 3518 potential targets have been included in the database, which is freely available to academic users. It successfully screened out 41 of 82 known Cancer-Testis antigens, 6 of 18 differentiation antigen, 2 of 2 oncofetal antigen, and 7 of 12 FDA approved cancer markers that have Gene ID, therefore will provide a good platform for identification of cancer target genes. This database utilizes expression data from various expression platforms, including carefully chosen publicly available microarray expression data, GEO SAGE data, Unigene expression data. In addition, other relevant databases required for TAA discovery such as CGAP, CCDS, gene ontology database etc, were also incorporated. In order to integrate different expression platforms together, various strategies and algorithms have been developed. Known tumor antigens are gathered from literature and serve as training sets. A total tumor specificity penalty was computed from positive clue penalty for differential expression in human cancers, the corresponding differential ratio, and normal tissue restriction penalty for each gene. We hope this database will help with the process of cancer immunome identification, thus help with improving the diagnosis and treatment of human carcinomas.

Proper citation: Human Potential Tumor Associated Antigen database (RRID:SCR_002938) Copy   

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http://apps.sanbi.ac.za/ddoc/

:DDOC provides a comprehensive compilation of the published research related to the genes associated with ovarian cancer. DDOC provides details of the cell line, tissue or cell type, expression status, disease stage, tumor grade, OC type and laboratory method provided in the literature. The links to the relevant sources of data used to extract information related to genes are also included. Many aspects of the information provided in the DDOC were curated by biologists, which increases its accuracy. DDOC is freely accessible for academic and non-profit users.

Proper citation: Dragon Database for Exploration of Ovarian Cancer Genes (RRID:SCR_007621) Copy   

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http://chromium.lovd.nl/LOVD2/home.php?select_db=CDKN2A

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. The CDKN2A Database presents the germline and somatic variants of the CDKN2A tumor suppressor gene recorded in human disease through June 2003, annotated with evolutionary, structural, and functional information, in a format that allows the user to either download it or manipulate it for their purposes online. The goal is to provide a database that can be used as a resource by researchers and geneticists and that aids in the interpretation of CDKN2A missense variants. Most online mutation databases present flat files that cannot be manipulated, are often incomplete, and have varying degrees of annotation that may or may not help to interpret the data. They hope to use CDKN2A as a prototype for integrating computational and laboratory data to help interpret variants in other cancer-related genes and other single nucleotide polymorphisms (SNPs) found throughout the genome. Another goal of the lab is to interpret the functional and disease significance of missense variants in cancer susceptibility genes. Eventually, these results will be relevant to the interpretation of single nucleotide polymorphisms (SNPs) in general. The CDKN2A locus is a valuable model for assessing relationships among variation, structure, function, and disease because: Variants of this gene are associated with hereditary cancer: Familial Melanoma (and related syndromes); somatic alterations play a role in carcinogenesis; allelic variants occur whose functional consequences are unknown; reliable functional assays exist; and crystal structure is known. All variants in the database are recorded according to the nomenclature guidelines as outlined by the Human Genome Variation Society. This database is currently designed for research purposes only and is not yet recommended as a clinical resource. Many of the mutations reported here have not been tested for disease association and may represent normal, non-disease causing polymorphisms.

Proper citation: CDKN2A Database (RRID:SCR_008179) Copy   

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

The web site includes genomic data for humans and mice, including transcript sequence, gene expression patterns, single-nucleotide polymorphisms, clone resources, and cytogenetic information. Descriptions of the methods and reagents used in deriving the CGAP datasets are also provided. An extensive suite of informatics tools facilitates queries and analysis of the CGAP data by the community. One of the newest features of the CGAP web site is an electronic version of the Mitelman Database of Chromosome Aberrations in Cancer. The data in the Mitelman Database is manually culled from the literature and subsequently organized into three distinct sub-databases, as follows: -The sub-database of cases contains the data that relates chromosomal aberrations to specific tumor characteristics in individual patient cases. It can be searched using either the Cases Quick Searcher or the Cases Full Searcher. -The sub-database of molecular biology and clinical associations contains no data from individual patient cases. Instead, the data is pulled from studies with distinct information about: -Molecular biology associations that relate chromosomal aberrations and tumor histologies to genomic sequence data, typically genes rearranged as a consequence of structural chromosome changes. -Clinical associations that relate chromosomal aberrations and/or gene rearrangements and tumor histologies to clinical variables, such as prognosis, tumor grade, and patient characteristics. It can be searched using the Molecular Biology and Clinical (MBC) Associations Searcher -The reference sub-database contains all the references culled from the literature i.e., the sum of the references from the cases and the molecular biology and clinical associations. It can be searched using the Reference Searcher. CGAP has developed six web search tools to help you analyze the information within the Mitelman Database: -The Cases Quick Searcher allows you to query the individual patient cases using the four major fields: aberration, breakpoint, morphology, and topography. -The Cases Full Searcher permits a more detailed search of the same individual patient cases as above, by including more cytogenetic field choices and adding search fields for patient characteristics and references. -The Molecular Biology Associations Searcher does not search any of the individual patient cases. It searches studies pertaining to gene rearrangements as a consequence of cytogenetic aberrations. -The Clinical Associations Searcher does not search any of the individual patient cases. It searches studies pertaining to clinical associations of cytogenetic aberrations and/or gene rearrangements. -The Recurrent Chromosome Aberrations Searcher provides a way to search for structural and numerical abnormalities that are recurrent, i.e., present in two or more cases with the same morphology and topography. -The Reference Searcher queries only the references themselves, i.e., the references from the individual cases and the molecular biology and clinical associations. Sponsors: This database is sponsored by the University of Lund, Sweden and have support from the Swedish Cancer Society and the Swedish Children''s Cancer Foundation

Proper citation: Mitelman Database of Chromosome Aberrations in Cancer (RRID:SCR_012877) Copy   

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https://hive.biochemistry.gwu.edu/tools/bioxpress/

BioXpress is a gene expression and cancer association database in which the expression levels are mapped to genes using RNA-seq data obtained from The Cancer Genome Atlas, International Cancer Genome Consortium, Expression Atlas and publications. BioXpress can be searched by gene name or cancer type. To search the database by gene name, select the appropriate identifier type from the dropdown menu and type in the corresponding identifier in the adjacent text box. The results are computed and presented to the user with information such as variable expression levels and tumor expression. To search by cancer type, select the desired type from the dropdown menu, such as "Cancer Type", "Significant", "Expression", "Adjusted p-value" and "p-value". Results are shown in a graph displaying the top 10 differentially expressed genes for the specified cancer type in terms of the frequency of significant altered expression between the tumor and normal pairs.

Proper citation: BioXpress (RRID:SCR_014191) Copy   

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http://glioblastoma.alleninstitute.org/

Platform for exploring the anatomic and genetic basis of glioblastoma at the cellular and molecular levels that includes two interactive databases linked together by de-identified tumor specimen numbers to facilitate comparisons across data modalities: * The open public image database, here, providing in situ hybridization data mapping gene expression across the anatomic structures inherent in glioblastoma, as well as associated histological data suitable for neuropathological examination * A companion database (Ivy GAP Clinical and Genomic Database) offering detailed clinical, genomic, and expression array data sets that are designed to elucidate the pathways involved in glioblastoma development and progression. This database requires registration for access. The hope is that researchers all over the world will mine these data and identify trends, correlations, and interesting leads for further studies with significant translational and clinical outcomes. The Ivy Glioblastoma Atlas Project is a collaborative partnership between the Ben and Catherine Ivy Foundation, the Allen Institute for Brain Science and the Ben and Catherine Ivy Center for Advanced Brain Tumor Treatment.

Proper citation: Ivy Glioblastoma Atlas Project (RRID:SCR_005044) Copy   

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http://www.niehs.nih.gov/news/newsletter/2006/march/science-genetic.cfm

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. The NIEHS Genetic Alterations in Cancer (GAC) knowledgebase is a comprehensive collection of data compiled from studies reported in the published literature on genetic alterations in tumors associated with exposure to specific chemical, physical, or biological agents that can be linked to genes implicated in the development of cancers. GAC provides access to data from peer reviewed journals for hundreds of studies of gene mutations, loss of heterozygosity, and/or chromosome changes in tumors from humans, mice, or rats. Results are summarized in tables and graphic profiles that show the incidence (percent) of tumors with alterations in each gene that has been studied. Detailed data tables display results for each subject studied in the cited reference and the reference ID is hyperlinked to its PubMed abstract for more information. A mutation spectrum for individual genes and links to gene information from The Cancer Genome Anatomy Project and the Rat Genome Database are also provided.

Proper citation: Genetic Alterations in Cancer (RRID:SCR_010533) Copy   

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http://cancer.sanger.ac.uk/cancergenome/projects/cosmic/

Database to store and display somatic mutation information and related details and contains information relating to human cancers. The mutation data and associated information is extracted from the primary literature. In order to provide a consistent view of the data a histology and tissue ontology has been created and all mutations are mapped to a single version of each gene. The data can be queried by tissue, histology or gene and displayed as a graph, as a table or exported in various formats.
Some key features of COSMIC are:
* Contains information on publications, samples and mutations. Includes samples which have been found to be negative for mutations during screening therefore enabling frequency data to be calculated for mutations in different genes in different cancer types.
* Samples entered include benign neoplasms and other benign proliferations, in situ and invasive tumours, recurrences, metastases and cancer cell lines.

Proper citation: COSMIC - Catalogue Of Somatic Mutations In Cancer (RRID:SCR_002260) Copy   

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http://www.ncbi.nlm.nih.gov/Web/Newsltr/Spring04/cancer.html

Cancer Chromosomes is an integration of three databases, the NCI/NCBI SKY/M-FISH & CGH Database, the NCI Mitelman Database of Chromosome Aberrations in Cancer, and the NCI Recurrent Aberrations in Cancer, which all focus on various aspects of cancer and cancer genes. The goal of the SKY/M-FISH and CGH database is to provide a public platform for investigators to share and compare their molecular cytogenetic data. The database is open to everyone and all users can view an individual investigator''s public data or compare public cases from different investigators. The information in the Mitelman Database of Chromosome Aberrations in Cancer relates chromosomal aberrations to tumor characteristics, based either on individual cases or associations. All the data have been manually culled from the literature. Complete karyotypes, patient characteristics, and references are found in the Mitelman Database of Chromosome Aberrations in Cancer. Users can search all three databases for cytogenetic, clinical, and/or reference information.

Proper citation: Cancer Chromosomes (RRID:SCR_007575) Copy   

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http://cancergenome.nih.gov/

Project exploring the spectrum of genomic changes involved in more than 20 types of human cancer that provides a platform for researchers to search, download, and analyze data sets generated. As a pilot project it confirmed that an atlas of changes could be created for specific cancer types. It also showed that a national network of research and technology teams working on distinct but related projects could pool the results of their efforts, create an economy of scale and develop an infrastructure for making the data publicly accessible. Its success committed resources to collect and characterize more than 20 additional tumor types. Components of the TCGA Research Network: * Biospecimen Core Resource (BCR); Tissue samples are carefully cataloged, processed, checked for quality and stored, complete with important medical information about the patient. * Genome Characterization Centers (GCCs); Several technologies will be used to analyze genomic changes involved in cancer. The genomic changes that are identified will be further studied by the Genome Sequencing Centers. * Genome Sequencing Centers (GSCs); High-throughput Genome Sequencing Centers will identify the changes in DNA sequences that are associated with specific types of cancer. * Proteome Characterization Centers (PCCs); The centers, a component of NCI's Clinical Proteomic Tumor Analysis Consortium, will ascertain and analyze the total proteomic content of a subset of TCGA samples. * Data Coordinating Center (DCC); The information that is generated by TCGA will be centrally managed at the DCC and entered into the TCGA Data Portal and Cancer Genomics Hub as it becomes available. Centralization of data facilitates data transfer between the network and the research community, and makes data analysis more efficient. The DCC manages the TCGA Data Portal. * Cancer Genomics Hub (CGHub); Lower level sequence data will be deposited into a secure repository. This database stores cancer genome sequences and alignments. * Genome Data Analysis Centers (GDACs) - Immense amounts of data from array and second-generation sequencing technologies must be integrated across thousands of samples. These centers will provide novel informatics tools to the entire research community to facilitate broader use of TCGA data. TCGA is actively developing a network of collaborators who are able to provide samples that are collected retrospectively (tissues that had already been collected and stored) or prospectively (tissues that will be collected in the future).

Proper citation: The Cancer Genome Atlas (RRID:SCR_003193) Copy   

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https://coremarketplace.org 

ABRF CoreMarketplace project created for core facilities tracking. CoreMarketplace (CM) is searchable list of active core facilities that perform scientific research. The CM was initially created by Vermont IDeA Network of Biomedical Research Excellence (INBRE). CoreMarketplace is associated with Association of Biomolecular Research Facilities (ABRF) which is membership association to sponsor and help members to incorporate new biotechnology into their laboratories.

Proper citation: ABRF CoreMarketplace (RRID:SCR_021196) Copy   

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http://breakpointmapper.wi.mit.edu

A database of sequence-tagged sites (STSs) and a user interface for mapping partial deletions in the male-specific region of the human Y chromosome (MSY). Naturally occurring partial deletions in the human Y chromosome are associated with diverse phenotypes including male infertility, sex reversal, Turner syndrome, and germ cell tumor formation. With the complete sequence of the euchromatic Y chromosome in hand, it is now possible to precisely demarcate each deletion and the repertoire of genes lost, and to propose mechanisms of deletion. Detailed DNA-sequence analysis of MSY deletions is most readily accomplished with Y-specific STS assays, which employ the polymerase chain reaction (PCR). Each such STS assay provides a straightforward means of determining the presence or absence, in a sample of human genomic DNA, of a specific point along the length of the Y chromosome. In the course of analyzing normal and aberrant Y chromosomes over the past two decades, we and our colleagues have generated robust, Y-specific STSs at an average spacing of less than 14 kilobases across the MSY euchromatin. MSY Breakpoint Mapper provides information about these STSs and is useful for efficiently and systematically defining the breakpoint(s) of virtually any Y chromosome deletion.

Proper citation: MSY Breakpoint Mapper (RRID:SCR_007810) Copy   

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http://www.stanford.edu/

Private, non profit university in Stanford, California, USA for research and undergraduate and graduate studies. Known for its academic strength, wealth, proximity to Silicon Valley, and ranking as one of the world's top universities. Particularly noted for its entrepreneurship and is one of the most successful universities in attracting funding for start-ups.

Proper citation: Stanford University; Stanford; California (RRID:SCR_011538) Copy   

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http://english.cas.cn/

Public university for graduate education, under the direct leadership of the Chinese Academy of Sciences.

Proper citation: Chinese Academy of Sciences; Beijing; China (RRID:SCR_012797) Copy   

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http://web.ncku.edu.tw/bin/home.php?Lang=en

National Cheng Kung University is a research-led comprehensive university in Tainan, Taiwan that has undergraduate, master's, and doctoral degree programs. This university has fields of: science, engineering, medicine, management, planning and design.

Proper citation: National Cheng Kung University; Tainan; Taiwan (RRID:SCR_000980) Copy   

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