Linguistic metaphors have been woven into the fabric of molecular biology since its
inception. The determination of the human genome sequence has brought these metaphors …

Probabilistic models are becoming increasingly important in analysing the huge amount of
data being produced by large-scale DNA-sequencing efforts such as the Human Genome …

We describe a dynamic programming algorithm for predicting optimal RNA secondary
structure, including pseudoknots. The algorithm has a worst case complexity of O (N6) in …

RNA molecules are sequences of nucleotides that serve as more than mere intermediaries
between DNA and proteins, eg, as catalytic molecules. Computational prediction of RNA …

This paper shows simple dynamic programming algorithms for RNA secondary structure
prediction with pseudoknots. For a basic version of the problem (ie, maximizing the number …

Non protein-coding RNAs (ncRNAs) are a research hotspot in bioinformatics. Recent
discoveries have revealed new ncRNA families performing a variety of roles, from gene …

Motivation: In a previous paper, we presented a polynomial time dynamic programming
algorithm for predicting optimal RNA secondary structure including pseudoknots. However …

In this paper, we are concerned with identifying a subclass of tree adjoining grammars
(TAGs) that is suitable for the application to modeling and predicting RNA secondary …

Thoroughly Describes Biological Applications, Computational Problems, and Various
Algorithmic Solutions Developed from the author's own teaching material, Algorithms in …

Background Pairwise stochastic context-free grammars (Pair SCFGs) are powerful tools for
evolutionary analysis of RNA, including simultaneous RNA sequence alignment and …