Gapped Local Similarity Search with Provable Guarantees

Author(s):  
Manikandan Narayanan ◽  
Richard M. Karp
Biology ◽  
2014 ◽  
Vol 3 (1) ◽  
pp. 220-242
Author(s):  
Ruby Moritz ◽  
Matthias Bernt ◽  
Martin Middendorf

2015 ◽  
Vol 159 ◽  
pp. 144-150 ◽  
Author(s):  
Hong Liu ◽  
Aiwen Jiang ◽  
Mingwen Wang ◽  
Jianyi Wan

Author(s):  
Georgios Chatzigeorgakidis ◽  
Dimitrios Skoutas ◽  
Kostas Patroumpas ◽  
Themis Palpanas ◽  
Spiros Athanasiou ◽  
...  

2019 ◽  
Vol 35 (18) ◽  
pp. 3491-3492
Author(s):  
Braslav Rabar ◽  
Maja Zagorščak ◽  
Strahil Ristov ◽  
Martin Rosenzweig ◽  
Pavle Goldstein

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.


Author(s):  
Pei Wang ◽  
Chuan Xiao ◽  
Jianbin Qin ◽  
Wei Wang ◽  
Xiaoyang Zhang ◽  
...  

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