Livny Jonathan
Tufts University School of Medicine.
Methods Mol Biol. 2007;395:475-88. doi: 10.1007/978-1-59745-514-5_30.
sRNAs are small noncoding RNAs that have been shown to perform diverse regulatory roles in a number of prokaryotes. Although several bioinformatic approaches have proven effective in identifying bacterial sRNAs, implementing these approaches presents significant computational challenges that have limited their use. To address these computational challenges, the author has developed and made publicly available sRNAPredict2, a program that facilitates the efficient prediction of putative sRNA-encoding genes in the intergenic regions of bacterial genomes. sRNAPredict2 identifies putative sRNAs by integrating genome-wide predictions of several different genetic features that are commonly associated with sRNA-encoding genes and identifying instances in which these features are colocalized in intergenic regions of the genome.
小RNA（sRNAs）是一类小的非编码RNA，已被证明在许多原核生物中发挥多种调控作用。尽管几种生物信息学方法已被证明在识别细菌sRNA方面有效，但实施这些方法面临重大的计算挑战，这限制了它们的应用。为应对这些计算挑战，作者开发并公开了sRNAPredict2，这是一个有助于在细菌基因组基因间区域高效预测假定sRNA编码基因的程序。sRNAPredict2通过整合几种通常与sRNA编码基因相关的不同遗传特征的全基因组预测，并识别这些特征在基因组基因间区域共定位的实例，来识别假定的sRNA。
