Local structural alignment of RNA with affine gap model

Thomas K.F. Wong, Brenda W.Y. Cheung, T. W. Lam, S. M. Yiu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Predicting new non-coding RNAs (ncRNAs) of a family can be done by aligning the potential candidate with a member of the family with known sequence and secondary structure. Existing tools either only consider the sequence similarity or cannot handle local alignment with gaps. In this paper, we consider the problem of finding the optimal local structural alignment between a query RNA sequence (with known secondary structure) and a target sequence (with unknown secondary structure) with the affine gap penalty model. We provide the algorithm to solve the problem. Based on a preliminary experiment, we show that there are ncRNA families in which considering local structural alignment with gap penalty model can identify real hits more effectively than using global alignment or local alignment without gap penalty model.

Original languageEnglish
Title of host publicationBioinformatics Research and Applications - 6th International Symposium, ISBRA 2010, Proceedings
Pages191-202
Number of pages12
DOIs
Publication statusPublished - 2010
Externally publishedYes
Event6th International Symposium on Bioinformatics Research and Applications, ISBRA 2010 - Storrs, CT, United States
Duration: 23 May 201026 May 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6053 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference6th International Symposium on Bioinformatics Research and Applications, ISBRA 2010
Country/TerritoryUnited States
CityStorrs, CT
Period23/05/1026/05/10

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