Wright Patrick R, Georg Jens
Bioinformatics Group, Department of Computer Science, University of Freiburg, Freiburg im Breisgau, Germany.
Genetics and Experimental Bioinformatics, Faculty of Biology, Institute of Biology III, University of Freiburg, Freiburg im Breisgau, Germany.
Methods Mol Biol. 2018;1737:3-30. doi: 10.1007/978-1-4939-7634-8_1.
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.
计算方法通常有助于对单个小RNA进行功能表征,进而能够对大量小RNA候选物进行高通量分析。本章概述了计算小RNA分析的潜在工作流程,并详细描述了基于富集分析的同源物检测、靶标预测和功能表征方法。以蓝藻小RNA IsaR1作为具体示例。所有方法都作为网络服务器提供,非专业用户也可轻松访问。