Results 1 - 10
of
611
Backofen R: MARNA: multiple alignment and consensus structure prediction of RNAs based on sequence structure comparisons
- Bioinformatics
, 2005
"... of RNAs based on sequence structure comparisons ..."
(Show Context)
Prediction and validation of microRNAs and their targets
- FEBS Lett
"... Abstract MicroRNAs are short non-coding RNAs that inhibit translation of target genes by binding to their mRNAs, and have been shown to play a central role in gene regulation in health and disease. Sophisticated computer-based prediction approaches of microRNAs and of their targets, and effective bi ..."
Abstract
-
Cited by 75 (0 self)
- Add to MetaCart
(Show Context)
Abstract MicroRNAs are short non-coding RNAs that inhibit translation of target genes by binding to their mRNAs, and have been shown to play a central role in gene regulation in health and disease. Sophisticated computer-based prediction approaches of microRNAs and of their targets, and effective biological validation techniques for validating these predictions, now play a central role in discovery of microRNAs and elucidating their functions.
Pure multiple RNA secondary structure alignments: a progressive profile approach
- IEEE/ACM Trans. Comput. Biol. Bioinform
"... Abstract—In functional, noncoding RNA, structure is often essential to function. While the full 3D structure is very difficult to determine, the 2D structure of an RNA molecule gives good clues to its 3D structure, and for molecules of moderate length, it can be predicted with good reliability. Stru ..."
Abstract
-
Cited by 73 (3 self)
- Add to MetaCart
(Show Context)
Abstract—In functional, noncoding RNA, structure is often essential to function. While the full 3D structure is very difficult to determine, the 2D structure of an RNA molecule gives good clues to its 3D structure, and for molecules of moderate length, it can be predicted with good reliability. Structure comparison is, in analogy to sequence comparison, the essential technique to infer related function. We provide a method for computing multiple alignments of RNA secondary structures under the tree alignment model, which is suitable to cluster RNA molecules purely on the structural level, i.e., sequence similarity is not required. We give a systematic generalization of the profile alignment method from strings to trees and forests. We introduce a tree profile representation of RNA secondary structure alignments which allows reasonable scoring in structure comparison. Besides the technical aspects, an RNA profile is a useful data structure to represent multiple structures of RNA sequences. Moreover, we propose a visualization of RNA consensus structures that is enriched by the full sequence information. Index Terms—Alignment of trees, RNA secondary structures, noncoding RNAs.
PF: Hairpins in a Haystack: recognizing microRNA precursors in comparative genomics data
- Bioinformatics
, 2006
"... doi:10.1093/bioinformatics/btl257 ..."
Partition function and base pairing probabilities of RNA heterodimers
- Algorithms Mol Biol
, 2006
"... Abstract Background: RNA has been recognized as a key player in cellular regulation in recent years. In many cases, noncoding RNAs exert their function by binding to other nucleic acids, as in the case of microRNAs and snoRNAs. The specificity of these interactions derives from the stability of inte ..."
Abstract
-
Cited by 65 (14 self)
- Add to MetaCart
(Show Context)
Abstract Background: RNA has been recognized as a key player in cellular regulation in recent years. In many cases, noncoding RNAs exert their function by binding to other nucleic acids, as in the case of microRNAs and snoRNAs. The specificity of these interactions derives from the stability of inter-molecular base pairing. The accurate computational treatment of RNA-RNA binding therefore lies at the heart of target prediction algorithms. Methods: The standard dynamic programming algorithms for computing secondary structures of linear singlestranded RNA molecules are extended to the co-folding of two interacting RNAs. Results: We present a program, RNAcofold, that computes the hybridization energy and base pairing pattern of a pair of interacting RNA molecules. In contrast to earlier approaches, complex internal structures in both RNAs are fully taken into account. RNAcofold supports the calculation of the minimum energy structure and of a complete set of suboptimal structures in an energy band above the ground state. Furthermore, it provides an extension of McCaskill's partition function algorithm to compute base pairing probabilities, realistic interaction energies, and equilibrium concentrations of duplex structures.
Thermodynamics of RNA-RNA Binding
, 2005
"... Background: Reliable predictions of RNA-RNA binding energies is crucial e.g. for the understanding on RNAi, microRNA-mRNA binding, and antisense interactions. The thermodynamics of such RNA-RNA interactions can be understood as the sum of two energy contributions: (1) the energy necessary to “open ” ..."
Abstract
-
Cited by 63 (13 self)
- Add to MetaCart
(Show Context)
Background: Reliable predictions of RNA-RNA binding energies is crucial e.g. for the understanding on RNAi, microRNA-mRNA binding, and antisense interactions. The thermodynamics of such RNA-RNA interactions can be understood as the sum of two energy contributions: (1) the energy necessary to “open ” the binding site, and (2) the energy gained from hybridization. Methods: We present an extension of the standard partition function approach to RNA secondary structures that computes the probabilities Pu[i, j] that a sequence interval [i, j] is unpaired. Results: Comparison with experimental data shows that Pu[i, j] can be applied as a significant determinant of local target site accessibility for RNA interference (RNAi). Furthermore, these quantities can be used to rigorously determine binding free energies of short oligomers to large mRNA targets. The resource consumption is comparable to a single partition function computation for the large target molecule. We can show that RNAi efficiency correlates well with the binding energies of siRNAs to their respective mRNA target.
Kinefold web server for RNA/DNA folding path and structure prediction including pseudoknots and knots
- Nucleic Acids Res
, 2005
"... The Kinefold web server provides a web interface for stochastic folding simulations of nucleic acids on second to minute molecular time scales. Renaturation or co-transcriptional folding paths are simulated at the level of helix formation and dissociation in agreement with the seminal experimental r ..."
Abstract
-
Cited by 54 (1 self)
- Add to MetaCart
The Kinefold web server provides a web interface for stochastic folding simulations of nucleic acids on second to minute molecular time scales. Renaturation or co-transcriptional folding paths are simulated at the level of helix formation and dissociation in agreement with the seminal experimental results. Pseudoknots and topologically ‘entangled ’ helices (i.e. knots) are efficiently predicted taking into account simple geometrical and topological constraints. To encourage interactivity, simulations launched as immediate jobs are automatically stopped after a few seconds and return adapted recommendations. Users can then choose to continue incomplete simulations using the batch queuing system or go back and modify suggested options in their initial query. Detailed output provide (i) a series of low free energy structures, (ii) an online animated folding path and (iii) a programmable trajectory plot focusing on a few helices of interest to each user. The service can be accessed at
Evolution of microRNA genes by inverted duplication of target gene sequences in Arabidopsis thaliana
- Nat Genet
, 2004
"... ..."
Human microRNA prediction through a probabilistic co-learning model of sequence and structure
- Nucleic Acids Res
, 2005
"... and structure ..."
(Show Context)
Molecular evolution of a microRNA cluster
- J. Mol. Biol
, 2004
"... MicroRNAs (miRNAs) form a class of noncoding RNA genes whose products are small single-stranded RNAs with a length of about 22 nt. These are involved in the regulation of translation ..."
Abstract
-
Cited by 51 (6 self)
- Add to MetaCart
MicroRNAs (miRNAs) form a class of noncoding RNA genes whose products are small single-stranded RNAs with a length of about 22 nt. These are involved in the regulation of translation