Workflow for a Computational Analysis of an sRNA Candidate in Bacteria

Patrick R Wright; Jens Georg

doi:10.1007/978-1-4939-7634-8_1

Workflow for a Computational Analysis of an sRNA Candidate in Bacteria

Methods Mol Biol. 2018:1737:3-30. doi: 10.1007/978-1-4939-7634-8_1.

Authors

Patrick R Wright¹, Jens Georg²

Affiliations

¹ Bioinformatics Group, Department of Computer Science, University of Freiburg, Freiburg im Breisgau, Germany.
² Genetics and Experimental Bioinformatics, Faculty of Biology, Institute of Biology III, University of Freiburg, Freiburg im Breisgau, Germany. jens.georg@biologie.uni-freiburg.de.

PMID: 29484584
DOI: 10.1007/978-1-4939-7634-8_1

Abstract

Computational methods can often facilitate the functional characterization of individual sRNAs and furthermore allow high-throughput analysis on large numbers of sRNA candidates. This chapter outlines a potential workflow for computational sRNA analyses and describes in detail methods for homolog detection, target prediction, and functional characterization based on enrichment analysis. The cyanobacterial sRNA IsaR1 is used as a specific example. All methods are available as webservers and easily accessible for nonexpert users.

Keywords: Computational methods; Cyanobacteria; Functional characterization; IsaR1; Target prediction; sRNA conservation.

MeSH terms

Computational Biology / methods*
Cyanobacteria / genetics*
Genome, Bacterial*
Genomics / methods*
RNA, Bacterial / genetics*
RNA, Small Untranslated / genetics*
Workflow

Substances

RNA, Bacterial
RNA, Small Untranslated