By Topic

Local similarity in RNA secondary structures

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
M. Hochsmann ; Int. Grad. Sch. in Bioinf. & Genome Res., Bielefeld Univ., Germany ; T. Toller ; R. Giegerich ; S. Kurtz

We present a systematic treatment of alignment distance and local similarity algorithms on trees and forests. We build upon the tree alignment algorithm for ordered trees given by Jiang et. al (1995) and extend it to calculate local forest alignments, which is essential for finding local similar regions in RNA secondary structures. The time complexity of our algorithm is O(/F1/·/F2/)·deg(F1)·deg(F2)·(deg(F1)+deg(F2)) where /Fi/ is the number of nodes in forest Fi and deg(Fi) is the degree of Fi. We provide carefully engineered dynamic programming implementations using dense, two-dimensional tables which considerably reduces the space requirement. We suggest a new representation of RNA secondary structures as forests that allow reasonable scoring of edit operations on RNA secondary structures. The comparison of RNA secondary structures is facilitated by a new visualization technique for RNA secondary structure alignments. Finally, we show how potential regulatory motifs can be discovered solely by their structural preservation, and independent of their sequence conservation and position.

Published in:

Bioinformatics Conference, 2003. CSB 2003. Proceedings of the 2003 IEEE

Date of Conference:

11-14 Aug. 2003