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Database Institute / Organization Alteration Types Primary Source [t 1] Processed Data [t 2] Organisms Cell lines [t 3] Public Data [t 4] Restricted Data [t 5]; The BioExpress® Oncology Suite from Ocimum Bio Solutions contains gene expression data from primary, metastatic, and benign tumor samples, and normal samples, including matched adjacent controls.
Bacterial Pesticidal Protein Database [25] [26] The Cancer Genome Atlas (TCGA): provides data from hundreds of cancer samples obtained using high-throughput techniques such as gene expression profiling, copy number variation profiling, SNP genotyping, genome-wide DNA methylation profiling, microRNA profiling, and exon sequencing of at least ...
Scientists study the behaviour of isolated cells grown in the laboratory for insights into how cells function in the body in health and disease. Experiments using cell culture are used for developing new diagnostic tests and new treatments for diseases. This is a list of major breast cancer cell lines that are primarily used in breast cancer ...
Gene expression profiling is a technique used in molecular biology to query the expression of thousands of genes simultaneously. While almost all cells in an organism contain the entire genome of the organism, only a small subset of those genes is expressed as messenger RNA (mRNA) at any given time, and their relative expression can be evaluated.
Gene expression and protein expression: List of normal tissues and cancer cell lines the gene of interest is expressed in. Essentiality: a list of human cell lines in which the gene was found to be essential.
To investigate these events, the discovery sample set will include DNA from primary tumor, normal tissue (from the same individuals) and cancer cell lines. All results from this project are amalgamated and stored within the COSMIC cancer database. COSMIC also includes mutational data published in scientific literature.
The Cancer Genome Atlas (TCGA) is a project to catalogue the genomic alterations responsible for cancer using genome sequencing and bioinformatics. [1] [2] The overarching goal was to apply high-throughput genome analysis techniques to improve the ability to diagnose, treat, and prevent cancer through a better understanding of the genetic basis of the disease.
Pan-cancer studies aim to detect the genes whose mutation is conducive to oncogenesis, as well as recurrent genomic events or aberrations between different tumors.For these studies, it is necessary to standardize the data between multiple platforms, establishing criteria between different researchers to work on the data and present the results.
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