Computational approaches for the discovery of bacterial small RNAs.
Recent work has uncovered a growing number of bacterial small RNAs (sRNAs), some of which have been shown to regulate critical cellular processes. Computational approaches, in combination with experiments, have played an important role in the discovery of these sRNAs. In this article, we first give an overview of different computational approaches for genome-wide prediction of sRNAs. These approaches have led to the discovery of several novel sRNAs, however the regulatory roles are not yet known for a majority of these sRNAs. By contrast, several recent studies have highlighted the inverse problem where the functional role of the sRNA is already known and the challenge is to identify its genomic location. The focus of this article is on computational tools and strategies for identifying these specific sRNAs which function as key components of known regulatory pathways.
Kulkarni
Rahul V
RV
Department of Physics, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA. kulkarni@phys.vt.edu
Kulkarni
Prajna R
PR
D001419:Bacteria / Q000235:genetics; D001483:Base Sequence; D019295:Computational Biology; D004926:Escherichia coli / Q000235:genetics; D023281:Genomics / Q000379:methods / Q000706:statistics & numerical data; D035683:MicroRNAs / Q000737:chemistry / Q000235:genetics* / Q000302:isolation & purification; D008958:Models, Molecular; D008969:Molecular Sequence Data; D009690:Nucleic Acid Conformation; D012329:RNA, Bacterial / Q000737:chemistry / Q000235:genetics* / Q000302:isolation & purification
D035683:MicroRNAs; D012329:RNA, Bacterial