Next-Generation Analysis of Deep Sequencing Data: Bringing Light into the Black Box of SELEX Experiments
作者： Michael Blank
DOI: 10.1007/978-1-4939-3197-2_7
关键词: Computer science 、 Aptamer 、 Genomic library 、 Bioinformatics 、 In vitro 、 SELEX Aptamer Technique 、 Computational biology 、 DNA sequencing 、 Selection (genetic algorithm) 、 Systematic evolution of ligands by exponential enrichment 、 Deep sequencing 、 In silico
摘要: In silico analysis of next-generation sequencing data (NGS; also termed deep sequencing) derived from in vitro selection experiments enables the SELEX procedure (Systematic Evolution Ligands by EXponential enrichment) an unprecedented depth and improves identification aptamers. Besides quality control optimization starting libraries, advanced screening strategies for difficult targets or early rare but high aptamers which are otherwise lost become possible. The information content sequence obtained is furthermore useful subsequent lead optimization.
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