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Tytuł:
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IGLOSS: iterative gapless local similarity search.
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Autorzy:
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Rabar B; Mathematics Department, Faculty of Natural Sciences and Mathematics, Zagreb, Croatia.
Zagorščak M; Department of Biotechnology and Systems Biology, National Institute of Biology, Ljubljana, Slovenia.
Ristov S; Division of Electronics, Ruđer Bošković Institute, Zagreb, Croatia.
Rosenzweig M; Mathematics Department, Faculty of Natural Sciences and Mathematics, Zagreb, Croatia.
Goldstein P; Mathematics Department, Faculty of Natural Sciences and Mathematics, Zagreb, Croatia.
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Źródło:
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Bioinformatics (Oxford, England) [Bioinformatics] 2019 Sep 15; Vol. 35 (18), pp. 3491-3492.
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Typ publikacji:
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Journal Article; Research Support, Non-U.S. Gov't
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Język:
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English
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Imprint Name(s):
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Original Publication: Oxford : Oxford University Press, c1998-
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MeSH Terms:
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Algorithms*
Software*
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Entry Date(s):
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Date Created: 20190206 Date Completed: 20200610 Latest Revision: 20200610
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Update Code:
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20240105
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DOI:
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10.1093/bioinformatics/btz086
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PMID:
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30721953
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Summary: Searching for local sequence patterns is one of the basic tasks in bioinformatics. Sequence patterns might have structural, functional or some other relevance, and numerous methods have been developed to detect and analyze them. These methods often depend on the wealth of information already collected. The explosion in the number of newly available sequences calls for novel methods to explore local sequence similarity. We have developed a new method for iterative motif scanning that will look for ungapped sequence patterns similar to a submitted query. Using careful parameter estimation and an adaptation of a fast string-matching algorithm, the method performs significantly better in this context than the existing software.
Availability and Implementation: The IGLOSS web server is available at http://compbioserv.math.hr/igloss/.
Supplementary Information: Supplementary data are available at Bioinformatics online.
(© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)
