Sheng, Y., Engstrom, P.G. and Lenhard, B. (2007) Mam- malian microRNA prediction through a support vector machine model of sequence and structure. PLoS One, 2, e946. doi:10.1371/journal.pone.0000946

has been cited by the following article:

• TITLE: Next generation sequencing for profiling expression of miRNAs: technical progress and applications in drug development

  AUTHORS: Jie Liu, Steven F. Jennings, Weida Tong, Huixiao Hong

  KEYWORDS: MiRNAs; Next-Generation Sequencing; Expression; Data Analysis; Drug Development

  JOURNAL NAME: Journal of Biomedical Science and Engineering, Vol.4 No.10, October 17, 2011

  ABSTRACT: miRNAs are non-coding RNAs that play a regulatory role in expression of genes and are associated with diseases. Quantitatively measuring expression levels of miRNAs can help understanding the mechanisms of human diseases and discovering new drug targets. There are three major methods that have been used to measure the expression levels of miRNAs: real-time reverse transcription PCR (qRT-PCR), microarray, and the newly introduced next-generation sequencing (NGS). NGS is not only suitable for profiling of known miRNAs that qRT-PCR and microarray can do too but also able to detect unknown miRNAs that the other two methods are incapable. Profiling of miRNAs by NGS has been progressed rapidly and is a promising field for applications in drug development. This paper will review the technical advancement of NGS for profiling miRNAs, including comparative analyses between different platforms and software packages for analyzing NGS data. Examples and future perspectives of applications of NGS profiling miRNAs in drug development will be discussed.