title: Assessing computational tools for the discovery of small RNA genes in bacteria.
abstract: Over the past decade, a number of biocomputational tools have been developed to predict small RNA (sRNA) genes in bacterial genomes. In this study, several of the leading biocomputational tools, which use different methodologies, were investigated. The performance of the tools, both individually and in combination, was evaluated on ten sets of benchmark data, including data from a novel RNA-seq experiment conducted in this study. The results of this study offer insight into the utility as well as the limitations of the leading biocomputational tools for sRNA identification and provide practical guidance for users of the tools.
authors.affiliation: Department of Bacteriology, University of Wisconsin, Madison, Wisconsin 53706, USA.
authors.forename: Xiaojun
authors.initials: X
authors.lastname: Lu
authors.forename: Heidi
authors.initials: H
authors.lastname: Goodrich-Blair
authors.forename: Brian
authors.initials: B
authors.lastname: Tjaden
mesh_terms: D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D005798:Genes, Bacterial; D012329:RNA, Bacterial / Q000235:genetics*; D058727:RNA, Small Untranslated / Q000235:genetics*; D012343:RNA, Transfer / Q000235:genetics; D017423:Sequence Analysis, RNA; D012984:Software; D020593:Xenorhabdus / Q000235:genetics
chemical_list: D012329:RNA, Bacterial; D058727:RNA, Small Untranslated; D012343:RNA, Transfer