Tree adjoining grammars for RNA structure prediction
Theoretical Computer Science - Special issue: Genome informatics
Dynamic programming algorithms for RNA secondary structure prediction with pseudoknots
Discrete Applied Mathematics - Special volume on combinatorial molecular biology
Prediction of Consensus RNA Secondary Structures Including Pseudoknots
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Thermodynamics of RNA--RNA binding
Bioinformatics
HFold: RNA pseudoknotted secondary structure prediction using hierarchical folding
WABI'07 Proceedings of the 7th international conference on Algorithms in Bioinformatics
Prediction of RNA secondary structure including kissing hairpin motifs
WABI'10 Proceedings of the 10th international conference on Algorithms in bioinformatics
| Hi-index | 5.23 |
RNA molecules are crucial in different levels of cellular function, ranging from translation and regulating genes to coding for proteins. Additionally, nucleic acids (RNA and DNA molecules) are designed for novel applications in biotechnology. Understanding the structure of a molecule is important in inferring its function, and computational methods for structure prediction have captured the interest of many researchers. Some functions of RNA molecules in cells, such as gene regulation, result from the binding of one RNA molecule to another, so-called target RNA molecule. This has led to recent interest in prediction of the secondary structure formed from interacting molecules. In this paper, we provide a brief overview of methods, applications, and challenges in computational prediction of nucleic acid secondary structure, both for single strands and for interacting strands.