IGLOSS: iterative gapless local similarity search

Author:

Rabar Braslav1,Zagorščak Maja2,Ristov Strahil3,Rosenzweig Martin1,Goldstein Pavle1

Affiliation:

1. Mathematics Department, Faculty of Natural Sciences and Mathematics, Zagreb, Croatia

2. Department of Biotechnology and Systems Biology, National Institute of Biology, Ljubljana, Slovenia

3. Division of Electronics, Ruđer Bošković Institute, Zagreb, Croatia

Abstract

Abstract 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.

Funder

European Regional Development Fund

Slovenian Research Agency

Croatian Science Foundation

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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