title: SCFGs in RNA secondary structure prediction RNA secondary structure prediction: a hands-on approach.
abstract: Stochastic context-free grammars (SCFGs) were first established in the context of natural language modelling, and only later found their applications in RNA secondary structure prediction. In this chapter, we discuss the basic SCFG algorithms (CYK and inside-outside algorithms) in an application-centered manner and use the pfold grammar as a case study to show how the algorithms can be adapted to a grammar in a nonstandard form. We extend our discussion to the use of grammars with additional information (such as evolutionary information) to improve the quality of predictions. Finally, we provide a brief survey of programs that use stochastic context-free grammars for RNA secondary structure prediction and modelling.
authors.affiliation: Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark.
authors.forename: Zsuzsanna
authors.initials: Z
authors.lastname: Sükösd
authors.forename: Ebbe S
authors.initials: ES
authors.lastname: Andersen
authors.forename: Rune
authors.initials: R
authors.lastname: Lyngsø
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D009690:Nucleic Acid Conformation; D012313:RNA / Q000737:chemistry*; D059370:RNA Folding; D017423:Sequence Analysis, RNA; D012984:Software; D013816:Thermodynamics
chemical_list: D012313:RNA