Computational analysis of RNAs.
Genome sequence analysis of RNAs presents special challenges to computational biology, because conserved RNA secondary structure plays a large part in RNA analysis. Algorithms well suited for RNA secondary structure and sequence analysis have been borrowed from computational linguistics. These "stochastic context-free grammar" (SCFG) algorithms have enabled the development of new RNA gene-finding and RNA homology search software. The aim of this paper is to provide an accessible introduction to the strengths and weaknesses of SCFG methods and to describe the state of the art in one particular kind of application: SCFG-based RNA similarity searching. The INFERNAL and RSEARCH programs are capable of identifying distant RNA homologs in a database search by looking for both sequence and secondary structure conservation.
Eddy
S R
SR
Howard Hughes Medical Institute and Department of Genetics, Washington University School of Medicine, Saint Louis, Missouri 63108, USA.
D000465:Algorithms; D001483:Base Sequence; D019295:Computational Biology; D030561:Databases, Nucleic Acid; D015233:Models, Statistical; D008969:Molecular Sequence Data; D009690:Nucleic Acid Conformation; D012313:RNA / Q000032:analysis / Q000737:chemistry / Q000235:genetics; D016415:Sequence Alignment / Q000706:statistics & numerical data; D017423:Sequence Analysis, RNA / Q000706:statistics & numerical data*; D012984:Software; D013269:Stochastic Processes
D012313:RNA