Optimization of the Next-Generation Sequencing Data Alignment

This thesis presents short DNA alignment tools optimization. These short DNA reads are products of next\nobreakdash-generation sequencing technologies. The results produced by existing align\-ment tools can be influenced by various parameters. For this purpose, an optimization framework to find the optimal values of selected parameters was developed. This framework is based on differencial evolution algorithm and its main goal is to maximize the alignment accuracy. The functionality of the framework was tested on both real and generated data sets of short DNA reads. An accurate alignment is crucial for correct prediction of various genetic characteristics