4,209 research outputs found
Fast Arc-Annotated Subsequence Matching in Linear Space
An arc-annotated string is a string of characters, called bases, augmented
with a set of pairs, called arcs, each connecting two bases. Given
arc-annotated strings and the arc-preserving subsequence problem is to
determine if can be obtained from by deleting bases from . Whenever
a base is deleted any arc with an endpoint in that base is also deleted.
Arc-annotated strings where the arcs are ``nested'' are a natural model of RNA
molecules that captures both the primary and secondary structure of these. The
arc-preserving subsequence problem for nested arc-annotated strings is basic
primitive for investigating the function of RNA molecules. Gramm et al. [ACM
Trans. Algorithms 2006] gave an algorithm for this problem using time
and space, where and are the lengths of and , respectively. In
this paper we present a new algorithm using time and space,
thereby matching the previous time bound while significantly reducing the space
from a quadratic term to linear. This is essential to process large RNA
molecules where the space is likely to be a bottleneck. To obtain our result we
introduce several novel ideas which may be of independent interest for related
problems on arc-annotated strings.Comment: To appear in Algoritmic
Composite repetition-aware data structures
In highly repetitive strings, like collections of genomes from the same
species, distinct measures of repetition all grow sublinearly in the length of
the text, and indexes targeted to such strings typically depend only on one of
these measures. We describe two data structures whose size depends on multiple
measures of repetition at once, and that provide competitive tradeoffs between
the time for counting and reporting all the exact occurrences of a pattern, and
the space taken by the structure. The key component of our constructions is the
run-length encoded BWT (RLBWT), which takes space proportional to the number of
BWT runs: rather than augmenting RLBWT with suffix array samples, we combine it
with data structures from LZ77 indexes, which take space proportional to the
number of LZ77 factors, and with the compact directed acyclic word graph
(CDAWG), which takes space proportional to the number of extensions of maximal
repeats. The combination of CDAWG and RLBWT enables also a new representation
of the suffix tree, whose size depends again on the number of extensions of
maximal repeats, and that is powerful enough to support matching statistics and
constant-space traversal.Comment: (the name of the third co-author was inadvertently omitted from
previous version
MAGNOLIA: multiple alignment of protein–coding and structural RNA sequences
MAGNOLIA is a new software for multiple alignment of nucleic acid sequences, which are recognized to be hard to align. The idea is that the multiple alignment process should be improved by taking into account the putative function of the sequences. In this perspective, MAGNOLIA is especially designed for sequences that are intended to be either protein-coding or structural RNAs. It extracts information from the similarities and differences in the data, and searches for a specific evolutionary pattern between sequences before aligning them. The alignment step then incorporates this information to achieve higher accuracy. The website is available at http://bioinfo.lifl.fr/magnolia
Lightweight comparison of RNAs based on exact sequence–structure matches
Motivation: Specific functions of ribonucleic acid (RNA) molecules are often associated with different motifs in the RNA structure. The key feature that forms such an RNA motif is the combination of sequence and structure properties. In this article, we introduce a new RNA sequence–structure comparison method which maintains exact matching substructures. Existing common substructures are treated as whole unit while variability is allowed between such structural motifs
Structator: fast index-based search for RNA sequence-structure patterns
Background
The secondary structure of RNA molecules is intimately related to their function and often more conserved than the sequence. Hence, the important task of searching databases for RNAs requires to match sequence-structure patterns. Unfortunately, current tools for this task have, in the best case, a running time that is only linear in the size of sequence databases. Furthermore, established index data structures for fast sequence matching, like suffix trees or arrays, cannot benefit from the complementarity constraints introduced by the secondary structure of RNAs.
Results
We present a novel method and readily applicable software for time efficient matching of RNA sequence-structure patterns in sequence databases. Our approach is based on affix arrays, a recently introduced index data structure, preprocessed from the target database. Affix arrays support bidirectional pattern search, which is required for efficiently handling the structural constraints of the pattern. Structural patterns like stem-loops can be matched inside out, such that the loop region is matched first and then the pairing bases on the boundaries are matched consecutively. This allows to exploit base pairing information for search space reduction and leads to an expected running time that is sublinear in the size of the sequence database. The incorporation of a new chaining approach in the search of RNA sequence-structure patterns enables the description of molecules folding into complex secondary structures with multiple ordered patterns. The chaining approach removes spurious matches from the set of intermediate results, in particular of patterns with little specificity. In benchmark experiments on the Rfam database, our method runs up to two orders of magnitude faster than previous methods.
Conclusions
The presented method's sublinear expected running time makes it well suited for RNA sequence-structure pattern matching in large sequence databases. RNA molecules containing several stem-loop substructures can be described by multiple sequence-structure patterns and their matches are efficiently handled by a novel chaining method. Beyond our algorithmic contributions, we provide with Structator a complete and robust open-source software solution for index-based search of RNA sequence-structure patterns. The Structator software is available at http://www.zbh.uni-hamburg.de/Structator webcite.Deutsche Forschungsgemeinschaft (grant WI 3628/1-1
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