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Logol: Expressive Pattern Matching in sequences. Application to Ribosomal Frameshift Modeling
Abstract : Most of the current practice of pattern matching tools is oriented towards finding efficient ways to compare sequences. This is useful but insufficient: as the knowledge and understanding of some functional or structural aspects of living systems improve, analysts in molecular biology progressively shift from mere classification tasks to modeling tasks. People need to be able to express global sequence architectures and check various hypotheses on the way their sequences are structured. It appears necessary to offer generic tools for this task,allowing to build more expressive models of biological sequence families, on the basis of their content and structure. This article introduces Logol, a new application designed to achieve pattern matching in possibly large sequences with customized biological patterns. Logol consists in both a language for describing patterns, and the associated parser for effective pattern search in sequences (RNA, DNA or protein) with such patterns. The Logol language, based on an high level grammatical formalism, allows to express flexible patterns (with mispairings and indels) composed of both sequential elements (such as motifs) and structural elements (such as repeats or pseudoknots). Its expressive power is presented through an application using the main components of the language: the identification of -1 programmed ribosomal frameshifting (PRF) events in messenger RNA sequences.
Cited literature [21 references]
https://hal.inria.fr/hal-01059506
Contributor : Catherine Belleannée Connect in order to contact the contributor
Submitted on : Monday, September 1, 2014 - 10:56:02 AM
Last modification on : Thursday, January 20, 2022 - 4:20:29 PM
Long-term archiving on: : Tuesday, December 2, 2014 - 10:11:25 AM
Contributor : Catherine Belleannée Connect in order to contact the contributor
Submitted on : Monday, September 1, 2014 - 10:56:02 AM
Last modification on : Thursday, January 20, 2022 - 4:20:29 PM
Long-term archiving on: : Tuesday, December 2, 2014 - 10:11:25 AM
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