Core bioinformatics technologies
Core bioinformatics technologies
As the technology for collecting genomic data has improved, so has the need for new methods for management and analysis of the massive amounts of accumulated data. The term bioinformatics has evolved to include the mathematical, statistical, and computational analysis of genomic data. Work in bioinformatics ranges from database design to systems engineering to artificial intelligence to applied mathematics and statistics, all with an underlying focus on genomic science. A variety of bioinformatics topics may be illustrated using the core technologies described in the preceding section. It is necessary to carry out sequence alignments in order to assemble sequence fragments. All of these sequences, along with the vital information about their sources, functions, and so on, must be stored in databases, which must be readily available to users in a variety of locations. Once a sequence has been obtained, it is necessary to annotate its function. One of the most fundamental annotation tasks is that of computational gene finding, in which a genome or chromosome sequence is input to an algorithm that subsequently outputs the predicted location of genes. A gene sequence, whether predicted or experimentally determined, must have its function predicted, and many bioinformatics tools are available for this task. Once microarray data are available, it is necessary to identify subsets of coregulated genes and to identify genes that are differentially expressed between two or more treatments or tissue types. Polymorphism data from SNPs are used to search for correlations with, for example, the presence or absence of a disease in family pedigrees. These questions are all of fundamental importance and draw on many different fields. By necessity, bioinformatics is a highly multidisciplinary field.
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