Editing DNA (section)

=== Bioinformatics ===
{{further|Bioinformatics}}
[[Bioinformatics]] involves the development of techniques to store, [[data mining|data mine]], search and manipulate biological data, including DNA [[nucleic acid sequence]] data. These have led to widely applied advances in [[computer science]], especially [[string searching algorithm]]s, [[machine learning]], and [[database theory]].<ref>{{cite book | vauthors = Baldi P, Brunak S |author1-link=Pierre Baldi |title=Bioinformatics: The Machine Learning Approach |publisher= MIT Press |year=2001| isbn=978-0-262-02506-5 |oclc=45951728}}</ref> String searching or matching algorithms, which find an occurrence of a sequence of letters inside a larger sequence of letters, were developed to search for specific sequences of nucleotides.<ref>{{cite book | vauthors = Gusfield D | title = Algorithms on Strings, Trees, and Sequences: Computer Science and Computational Biology | publisher = [[Cambridge University Press]] | date = 15 January 1997 | isbn = 978-0-521-58519-4 }}</ref> The DNA sequence may be [[sequence alignment|aligned]] with other DNA sequences to identify [[Sequence homology|homologous sequences]] and locate the specific [[mutation]]s that make them distinct. These techniques, especially [[multiple sequence alignment]], are used in studying [[phylogenetics|phylogenetic]] relationships and protein function.<ref>{{cite journal | vauthors = Sjölander K | title = Phylogenomic inference of protein molecular function: advances and challenges | journal = Bioinformatics | volume = 20 | issue = 2 | pages = 170–79 | date = January 2004 | pmid = 14734307 | doi = 10.1093/bioinformatics/bth021 | citeseerx = 10.1.1.412.943 }}</ref> Data sets representing entire genomes' worth of DNA sequences, such as those produced by the [[Human Genome Project]], are difficult to use without the annotations that identify the locations of genes and regulatory elements on each chromosome. Regions of DNA sequence that have the characteristic patterns associated with protein- or RNA-coding genes can be identified by [[Gene prediction|gene finding]] algorithms, which allow researchers to predict the presence of particular [[gene product]]s and their possible functions in an organism even before they have been isolated experimentally.<ref name="Mount">{{cite book | vauthors = Mount DM |title=Bioinformatics: Sequence and Genome Analysis |edition= 2nd |publisher= Cold Spring Harbor Laboratory Press |year= 2004 |isbn= 0-87969-712-1|oclc= 55106399|location=Cold Spring Harbor, NY}}</ref> Entire genomes may also be compared, which can shed light on the evolutionary history of particular organism and permit the examination of complex evolutionary events.