Sequence alignment: Difference between revisions

Revision as of 03:13, 24 January 2020

Revision as of 21:14, 28 January 2020

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[[File:Histone Alignment.png|thumb|595px|A sequence alignment, produced by [[ClustalO]], of mammalian [[histone]] proteins. <br />

Sequences are the [[Amino acid#Table of standard amino acid abbreviations and side chain properties|amino acids]] for residues 120-180 of the proteins. Residues that are conserved across all sequences are highlighted in grey. Below the protein sequences is a key denoting [[conserved sequence]] (*), [[conservative mutation]]s (:), semi-conservative mutations (.), and [[segregating site|non-conservative mutations]] ( ).<ref>{{cite web|url=http://www.ebi.ac.uk/Tools/msa/clustalw2/help/faq.html#23|website=Clustal |title= Clustal FAQ #Symbols|accessdate=8 December 2014|archive-url=https://web.archive.org/web/20161024045656/http://www.ebi.ac.uk/Tools/msa/clustalw2/help/faq.html#23|archive-date=24 October 2016|url-status=dead}}</ref>]]

==Interpretation==

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==Non-biological uses==

The methods used for biological sequence alignment have also found applications in other fields, most notably in [[natural language processing]] and in social sciences, where the [[Needleman-Wunsch algorithm]] is usually referred to as [[Optimal matching]].<ref>{{cite journal|author1=Abbott A. |author2=Tsay A. | year=2000 | title=Sequence Analysis and Optimal Matching Methods in Sociology, Review and Prospect | journal=Sociological Methods and Research | volume=29|issue=1 | pages=3–33 | doi=10.1177/0049124100029001001}}</ref> Techniques that generate the set of elements from which words will be selected in natural-language generation algorithms have borrowed multiple sequence alignment techniques from bioinformatics to produce linguistic versions of computer-generated mathematical proofs.<ref name=Barzilay>{{cite journal|author1=Barzilay R |author2=Lee L. |year=2002 | title= Bootstrapping Lexical Choice via Multiple-Sequence Alignment | journal=Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP) | pages=164–171 | url=http://www.cs.cornell.edu/home/llee/papers/gen-msa.pdf| volume=10| doi=10.3115/1118693.1118715|arxiv=cs/0205065}}</ref> In the field of historical and comparative [[linguistics]], sequence alignment has been used to partially automate the [[comparative method (linguistics)|comparative method]] by which linguists traditionally reconstruct languages.<ref>{{cite journal |author=Kondrak, Grzegorz |title=Algorithms for Language Reconstruction |publisher=University of Toronto, Ontario |year=2002 |url=http://www.cs.ualberta.ca/~kondrak/papers/thesis.pdf |accessdate = 2007-01-21 |journal= |archive-url=https://web.archive.org/web/20081217043010/http://www.cs.ualberta.ca/~kondrak/papers/thesis.pdf |archive-date=17 December 2008 |url-status=dead }}</ref> Business and marketing research has also applied multiple sequence alignment techniques in analyzing series of purchases over time.<ref name=prinzie>{{cite journal|author1=Prinzie A. |author2=D. Van den Poel |year=2006 | url=http://econpapers.repec.org/paper/rugrugwps/05_2F292.htm | title=Incorporating sequential information into traditional classification models by using an element/position-sensitive SAM | journal=Decision Support Systems | volume=42 | issue=2| pages= 508–526 | doi=10.1016/j.dss.2005.02.004}} See also Prinzie and Van den Poel's paper {{cite journal | url=http://econpapers.repec.org/paper/rugrugwps/07_2F442.htm | title=Predicting home-appliance acquisition sequences: Markov/Markov for Discrimination and survival analysis for modeling sequential information in NPTB models | year=2007 | journal=Decision Support Systems | volume=44 | issue=1 | pages= 28–45 | doi=10.1016/j.dss.2007.02.008 | author=Prinzie, A | last2=Vandenpoel | first2=D}}</ref>

==Software==