Most functional RNA molecules have characteristic secondary structures that are highly conserved in evolution. Here we present a method for computing the consensus structure of a set aligned RNA sequences taking into account both thermodynamic stability and sequence covariation. Comparison with phylogenetic structures of rRNAs shows that a reliability of prediction of more than 80% is achieved ...

Various systems have been proposed to predict secondary structures of RNAs using their sequence information. Among them, Uemura et al. [2] described a system that recognizes some typical RNA secondary structures such as hairpin loops and pseudoknots with Tree Adjoining Grammar. However, their work captures only known sub-structures, and not those unknown sub-structures that might also exist. Te...

RNA secondary structure prediction and classification are two important problems in the field of RNA biology. Here, we propose a new permutation based approach to create logical non-disjoint clusters of different secondary structures of a single class or type. Many different types of techniques exist to classify RNA secondary structure data but none of them have ever used permutation based appr...

Pseudoknots are widely occurring structural motifs in RNA. Pseudoknots have been shown to be functionally important in different RNAs which play regulatory, catalytic, or structural roles in cells. Current biophysical methods to identify the presence of pseudoknots are extremely time consuming and expensive. Therefore, bioinformatics approaches to accurately predict such structures are highly d...

RNA secondary structure prediction with pseudoknots is important, since pseudoknots are part of functionally improtant RNAs in cells. State of the art dynamic programming algorithms due to Akutsu et al [7] and Deogun et al [8] perform well on single RNA sequences. Our aim of this project is to be able to predict secondary structure of real life RNA sequences, which can be more than 700 nucleoti...

Consider the network of all secondary structures of a given RNA sequence, where nodes are connected when the corresponding structures have base pair distance one. The expected degree of the network is the average number of neighbors, where average may be computed with respect to the either the uniform or Boltzmann probability. Here, we describe the first algorithm, RNAexpNumNbors, that can comp...

Using a rigorous mathematical analysis, the prediction of RNA secondary structure as a function of free energy is obtained. The iterative method effectively allows a search over the entire configuration space of the RNA molecule not possible by earlier methods. The approach also allows for the direct inclusion of the nearest neighbor or stacking energies.

Ribosomal RNA precursors and mature 28S ribosomal RNA from HeLa cells display a highly reproducible secondary structure of hairpin loops after they are spread and examined in an electron microscope. This structure was used to map the linear arrangement of these molecules. Partial digestion with 3'-exonuclease from ascites cell nuclei established that the 28S RNA region is located at the 5'-end ...

MOTIVATION RNA secondary structure contains many non-canonical base pairs of different pair families. Successful prediction of these structural features leads to improved secondary structures with applications in tertiary structure prediction and simultaneous folding and alignment. RESULTS We present a theoretical model capturing both RNA pair families and extended secondary structure motifs ...

There are questions concerning the functions of artemin, an abundant stress protein found in Artemiaduring embryo development. It has been reported that artemin binds RNA at high temperatures in vitro, suggesting an RNA protective role. In this study, we investigated the possibility of the presence of RNA-bindingsites and their structural properties in artemin, using docking energy ...