Parallel computing methods and genetic data analysis

This article discusses the importance of parallel computing methods in the analysis of genetic data. Classical methods are ineffective in analyzing large amounts of data obtained from genome sequencing. Parallel computing technologies allow performing several operations simultaneously, accelerating the analysis process. The article discusses modern parallel algorithms used for analyzing genetic data, their efficiency and specific applications, such as SNP analysis and disease diagnostics. As a result, the role of parallel computing in genetic research is emphasized.