A unifying framework for seed sensitivity and its application to subset seeds

Gregory Kucherov, Laurent Noé, Mikhail Roytberg

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2 Цитирования (Scopus)

Аннотация

We propose a general approach to compute the seed sensitivity, that can be applied to different definitions of seeds. It treats separately three components of the seed sensitivity problem - a set of target alignments, an associated probability distribution, and a seed model - that are specified by distinct unite automata. The approach is then applied to a new concept of subset seeds for which we propose an efficient automaton construction. Experimental results confirm that sensitive subset seeds can be efficiently designed using our approach, and can then be used in similarity search producing better results than ordinary spaced seeds.

Язык оригиналаАнглийский
Название основной публикацииLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Страницы251-263
Число страниц13
DOI
СостояниеОпубликовано - 2005
Опубликовано для внешнего пользованияДа
Событие5th International Workshop on Algorithms in Bioinformatics, WABI 2005 - Mallorca, Испания
Продолжительность: 3 окт. 20056 окт. 2005

Серия публикаций

НазваниеLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Том3692 LNBI
ISSN (печатное издание)0302-9743
ISSN (электронное издание)1611-3349

Конференция

Конференция5th International Workshop on Algorithms in Bioinformatics, WABI 2005
Страна/TерриторияИспания
ГородMallorca
Период3/10/056/10/05

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