Results 1 - 10
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43
Unifying evolutionary and thermodynamic information for RNA folding of multiple alignments
, 2008
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PARTS: probabilistic alignment for RNA joinT secondary structure prediction
- Nucleic Acids Res
, 2008
"... A novel method is presented for joint prediction of alignment and common secondary structures of two RNA sequences. The joint consideration of common secondary structures and alignment is accom-plished by structural alignment over a search space defined by the newly introduced motif called matched h ..."
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Cited by 17 (6 self)
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A novel method is presented for joint prediction of alignment and common secondary structures of two RNA sequences. The joint consideration of common secondary structures and alignment is accom-plished by structural alignment over a search space defined by the newly introduced motif called matched helical regions. The matched helical region formulation generalizes previously employed con-straints for structural alignment and thereby better accommodates the structural variability within RNA families. A probabilistic model based on pseudo free energies obtained from precomputed base pairing and alignment probabilities is utilized for scoring structural alignments. Maximum a posteriori (MAP)
Partition function and base pairing probabilities for RNA-RNA interaction prediction
- PROCEEDINGS OF THE DIVERSITY IN DOCUMENT RETRIEVAL 2001 WORKSHOP
, 2011
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Lightweight comparison of RNAs based on exact sequence-structure matches
- Bioinformatics
, 2009
"... Abstract: Specific functions of 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 paper we introduce a new RNA sequence-structure comparison method which maintai ..."
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Cited by 11 (7 self)
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Abstract: Specific functions of 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 paper 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. Based on a fast detectable set of overlapping and crossing substructure matches for two nested RNA secondary structures, our method computes the longest colinear sequence of substructures common to two RNAs in O(n 2 m 2) time and O(nm) space. Applied to different RNAs, our method correctly identifies sequence-structure similarities between two RNAs. The results of our experiments are in good agreement with existing alignment-based methods, but can be obtained in a fraction of running time, in particular for larger RNAs. The proposed algorithm is implemented in the program expaRNA, which is available from our website (www.bioinf.uni-freiburg.de/Software). 1
Lifting prediction to alignment of rna pseudoknots
- In Research in Computational Molecular Biology, 13th Annual International Conference, RECOMB 2009
"... Prediction and alignment of RNA pseudoknot structures are NP-hard. Nevertheless, several efficient prediction algorithms by dynamic programming have been proposed for restricted classes of pseudoknots. We present a general scheme that yields an efficient alignment algorithm for arbitrary such classe ..."
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Cited by 11 (4 self)
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Prediction and alignment of RNA pseudoknot structures are NP-hard. Nevertheless, several efficient prediction algorithms by dynamic programming have been proposed for restricted classes of pseudoknots. We present a general scheme that yields an efficient alignment algorithm for arbitrary such classes. Moreover, we show that such an alignment algorithm benefits from the class restriction in the same way as the corresponding structure prediction algorithm does. We look at six of these classes in greater detail. The time and space complexity of the alignment algorithm is increased by only a linear factor over the respective prediction algorithm. For five of the classes, no efficient alignment algorithms were known. For the sixth, most general class, we improve the previously best complexity of O(n 5 m 5) time to O(nm 6), where n and m denote sequence lengths. Finally, we apply our fastest algorithm with O(nm 4) time and O(nm 2) space to comparative de-novo pseudoknot prediction. Keywords: alignment, dynamic programming, RNA, structures Joint first authors
Fixed Parameter Tractable Alignment of RNA Structures Including Arbitrary Pseudoknots
"... Abstract. We present an algorithm for computing the edit distance of two RNA structures with arbitrary kinds of pseudoknots. A main benefit of the algorithm is that, despite the problem is NP-hard, the algorithmic complexity adapts to the complexity of the RNA structures. Due to fixed parameter trac ..."
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Cited by 6 (2 self)
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Abstract. We present an algorithm for computing the edit distance of two RNA structures with arbitrary kinds of pseudoknots. A main benefit of the algorithm is that, despite the problem is NP-hard, the algorithmic complexity adapts to the complexity of the RNA structures. Due to fixed parameter tractability, we can guarantee polynomial run-time for a parameter which is small in practice. Our algorithm can be considered as a generalization of the algorithm of Jiang et al. [1] to arbitrary pseudoknots. In their absence, it gracefully degrades to the same polynomial algorithm. A prototypical implementation demonstrates the applicability of the method.
Backofen R: Exact pattern matching for RNA structure ensembles
- In Proceedings of the 16th International Conference on Research in Computational Molecular Biology (RECOMB 2012), Volume 7262 of LNCS. Edited by
"... Abstract. ExpaRNA’s core algorithm computes, for two fixed RNA structures, a maximal non-overlapping set of maximal exact matchings. We introduce an algorithm ExpaRNA-P that solves the lifted problem of finding such sets of exact matchings in entire Boltzmann-distributed structure ensembles of two R ..."
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Cited by 5 (4 self)
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Abstract. ExpaRNA’s core algorithm computes, for two fixed RNA structures, a maximal non-overlapping set of maximal exact matchings. We introduce an algorithm ExpaRNA-P that solves the lifted problem of finding such sets of exact matchings in entire Boltzmann-distributed structure ensembles of two RNAs. Due to a novel kind of structural sparsification, the new algorithm maintains the time and space complexity of the algorithm for fixed input structures. Furthermore, we generalized the chaining algorithm of ExpaRNA in order to compute a compatible subset of ExpaRNA-P’s exact matchings. We show that ExpaRNA-P outperforms ExpaRNA in BRAliBase 2.1 benchmarks, where we pass the chained exact matchings as anchor constraints to the RNA alignment tool LocARNA. Compared to LocARNA, this novel approach shows similar accuracy but is six times faster. 1
Stochastic sampling of the rna structural alignment space
- Nucleic Acids Res
, 2009
"... A novel method is presented for predicting the common secondary structures and alignment of two homologous RNA sequences by sampling the ‘structural alignment ’ space, i.e. the joint space of their alignments and common secondary structures. The structural alignment space is sampled according to a p ..."
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Cited by 4 (1 self)
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A novel method is presented for predicting the common secondary structures and alignment of two homologous RNA sequences by sampling the ‘structural alignment ’ space, i.e. the joint space of their alignments and common secondary structures. The structural alignment space is sampled according to a pseudo-Boltzmann distribution based on a pseudo-free energy change that combines base pairing probabilities from a thermodynamic model and alignment probabilities from a hidden Markov model. By virtue of the implicit comparative analysis between the two sequences, the method offers an improvement over single sequence sampling of the Boltzmann ensemble. A cluster analysis shows that the samples obtained from joint sampling of the structural alignment space cluster more closely than samples generated by the single sequence method. On average, the representative (centroid) structure and alignment of the most populated cluster in the sample of structures and alignments generated by joint sampling are more accurate than single sequence sampling and alignment based on sequence alone, respectively. The ‘best ’ centroid structure that is closest to the known structure among all the centroids is, on average, more accurate than structure predictions of other methods. Additionally, cluster analysis identifies, on average, a few clusters, whose centroids can be presented as alternative candidates. The source code for the proposed method can be downloaded at
Comparative genomics beyond sequence based alignments: RNA structures in the ENCODE regions
"... 1 Recent computational scans for noncoding RNAs (ncRNAs) in multiple organisms have relied on existing multiple sequence alignments. However, as sequence similarity drops, a key signal of RNA structure—frequent compensating base changes—is increasingly likely to cause sequence-based alignment method ..."
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Cited by 2 (0 self)
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1 Recent computational scans for noncoding RNAs (ncRNAs) in multiple organisms have relied on existing multiple sequence alignments. However, as sequence similarity drops, a key signal of RNA structure—frequent compensating base changes—is increasingly likely to cause sequence-based alignment methods to misalign, or even refuse to align, homologous ncRNAs, consequently obscuring that structural signal. We have used CMfinder, a structure-oriented local alignment tool, to search the ENCODE regions of vertebrate multiple alignments. In agreement with other studies, we find a large number of potential RNA structures in the ENCODE regions. We report 6,587 candidate regions with an estimated false positive rate of 50%. More intriguingly, many of these candidates may be better represented by alignments taking the RNA secondary structure into account than those based on primary sequence alone, often quite dramatically. For example, approximately one quarter of our predicted motifs show revisions in more than 50 % of their aligned positions. Furthermore, our results are strongly complementary to those discovered by sequencealignment-based approaches—84 % of our candidates are not covered by Washietl et al., increasing
Multimodal Document Alignment: Feature-based Validation to Strengthen Thematic Links
"... In this paper, we present a validation approach of detected alignment links between dialog transcript and discussed documents, in the context of a multimodal document alignment framework of multimedia events (meetings and lectures). The validation approach consists in an entailment process of the de ..."
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Cited by 2 (1 self)
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In this paper, we present a validation approach of detected alignment links between dialog transcript and discussed documents, in the context of a multimodal document alignment framework of multimedia events (meetings and lectures). The validation approach consists in an entailment process of the detected alignment links. This entailment process exploits several features, from the structural level of aligned documents to the linguistic level of their tokens. The implemented entailment strategies were evaluated on several multimodal corpora. The obtained results prove that the choice of the relevant entailment strategy depends on the types of documents that are available in the corpus, on their content, and also on the nature of the corpus.
