A batch algorithm for maintaining a topological order
ACSC '10 Proceedings of the Thirty-Third Australasian Conferenc on Computer Science - Volume 102
Exact pattern matching for RNA structure ensembles
RECOMB'12 Proceedings of the 16th Annual international conference on Research in Computational Molecular Biology
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Motivation: Whole-genome screens suggest that eukaryotic genomes are dense with non-coding RNAs (ncRNAs). We introduce a novel approach to RNA multiple alignment which couples a generative probabilistic model of sequence and structure with an efficient sequence annealing approach for exploring the space of multiple alignments. This leads to a new software program, Stemloc-AMA, that is both accurate and specific in the alignment of multiple related RNA sequences. Results: When tested on the benchmark datasets BRalibase II and BRalibase 2.1, Stemloc-AMA has comparable sensitivity to and better specificity than the best competing methods. We use a large-scale random sequence experiment to show that while most alignment programs maximize sensitivity at the expense of specificity, even to the point of giving complete alignments of non-homologous sequences, Stemloc-AMA aligns only sequences with detectable homology and leaves unrelated sequences largely unaligned. Such accurate and specific alignments are crucial for comparative-genomics analysis, from inferring phylogeny to estimating substitution rates across different lineages. Availability:Stemloc-AMA is available from http://biowiki.org/StemLocAMA as part of the dart software package for sequence analysis. Contact:lpachter@math.berkeley.edu; ihh@berkeley.edu Supplementary information:Supplementary data are available at Bioinformatics online.