Blank Michael
AptaIT GmbH, Goethestr. 52, 80336, Munich, Germany.
Methods Mol Biol. 2016;1380:85-95. doi: 10.1007/978-1-4939-3197-2_7.
In silico analysis of next-generation sequencing data (NGS; also termed deep sequencing) derived from in vitro selection experiments enables the analysis of the SELEX procedure (Systematic Evolution of Ligands by EXponential enrichment) in an unprecedented depth and improves the identification of aptamers. Besides quality control and optimization of starting libraries, advanced screening strategies for difficult targets or early identification of rare but high quality aptamers which are otherwise lost in the in vitro selection experiments become possible. The high information content of sequence data obtained from selection experiments is furthermore useful for subsequent lead optimization.
对源自体外筛选实验的下一代测序数据(NGS;也称为深度测序)进行计算机分析,能够以前所未有的深度分析SELEX程序(指数富集配体系统进化),并改进适体的鉴定。除了对起始文库进行质量控制和优化外,针对难以筛选的靶点采用先进的筛选策略,或早期鉴定那些在体外筛选实验中可能会丢失的稀有但高质量的适体也成为可能。此外,从筛选实验中获得的序列数据的高信息含量对后续的先导物优化也很有用。