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Databases for oncogenomic research are biological databases dedicated to cancer data and oncogenomic research. They can be a primary source of cancer data, offer a certain level of analysis (processed data) or even offer online data mining.
It is a group of techniques within the larger fields of phylogenetics and genomics. Phylogenomics draws information by comparing entire genomes, or at least large portions of genomes. [3] Phylogenetics compares and analyzes the sequences of single genes, or a small number of genes, as well as many other types of data.
Explore, manipulate, analyze, and simulate phylogenetic objects (alignments, trees, and MCMC logs) J.W. Brown, J.F. Walker, and S.A. Smith POY A phylogenetic analysis program that supports multiple kinds of data and can perform alignment and phylogeny inference. A variety of heuristic algorithms have been developed for this purpose
A phylogenetic convolutional neural network (Ph-CNN) is a convolutional neural network architecture proposed by Fioranti et al. in 2018 to classify metagenomics data. [19] In this approach, phylogenetic data is endowed with patristic distance (the sum of the lengths of all branches connecting two operational taxonomic units [OTU]) to select k ...
Phylogenetic trees generated by computational phylogenetics can be either rooted or unrooted depending on the input data and the algorithm used. A rooted tree is a directed graph that explicitly identifies a most recent common ancestor (MRCA), [citation needed] usually an inputed sequence that is not represented in the input.
Molecular phylogenetics is one aspect of molecular systematics, a broader term that also includes the use of molecular data in taxonomy and biogeography. [3] [4] [5] Molecular phylogenetics and molecular evolution correlate. Molecular evolution is the process of selective changes (mutations) at a molecular level (genes, proteins, etc ...
Methods (implemented by each program) that are available in the package include parsimony, distance matrix, and likelihood methods, including bootstrapping and consensus trees. Data types that can be handled include molecular sequences, gene frequencies, restriction sites and fragments, distance matrices, and discrete characters. [2]
The COSMIC (Catalogue of Somatic Mutations in Cancer) database was designed to collect and display information on somatic mutations in cancer. It was launched in 2004, with data from just four genes, HRAS, KRAS2, NRAS and BRAF. [6] These four genes are known to be somatically mutated in cancer. Since its creation, the database has expanded rapidly.