A mini-greedy algorithm for faster structural RNA stem-loop search.

Journal article

When a set of coregulated genes share a common structural RNA motif, e.g. a hairpin, most motif search approaches fail to locate the covarying but structurally conserved motif. There do exist methods that can locate structural RNA motifs, like FOLDALIGN, but the main problem with these methods is that they are computationally expensive. In FOLDALIGN, a major contribution to this is the use of a greedy algorithm to construct the multiple alignment. To ensure good quality many redundant computations must be made. However, by applying the greedy algorithm on a carefully selected subset of sequences, near full greedy quality can be obtained. The basic idea is to estimate the order in which the sequences entered a good greedy alignment. If such a ranking, found from all pairwise alignments, is in good agreement with the order of appearance in the multiple alignment, the core structural motif can be found by performing the greedy algorithm on just the top sequences in the ranking. The ranking used in this mini-greedy algorithm is found by using two complementing approaches: 1) When interpreting the FOLDALIGN score as an inner product (kernel), the sequences can be ranked according to their distance to their center of mass; 2) We construct an algorithm that attempts to find the K closest sequences in the vector space associated with the inner product, and the remaining sequences can be ranked by their minimum distance to any of the sequences, or to the center of mass in this set. The two approaches arecompared and merged, and the results discussed. We also show that structural alignments of near full greedy quality can found in significantly reduced time, using these methods. The algorithm is being included in the SLASH (Stem-Loop Align SearcH) server available at http://www.bioinf.au.dk/slash.

Authors: Gorodkin, J; Lyngso, R; Stormo, G

• Journal: Genome informatics. International Conference on Genome Informatics
• Volume: 12
• Pages: 184-193
• Publication date: 2001-01-01
• ISSN: 0919-9454
• Language: English
• Keywords: Computational Biology; RNA; Base Sequence; Databases, Nucleic Acid; Algorithms; Nucleic Acid Conformation; Sequence Alignment