High-Performance Computing (HPC) has become an indispensable tool in bioinformatics, driving advances in data analysis, modeling, and simulation. As biological data grows exponentially due to high-throughput technologies such as next-generation sequencing, proteomics, and metabolomics, traditional computing resources often need to be improved to handle the volume, variety, and velocity of the data. HPC provides the computational power and storage capacity required to process and analyze large-scale datasets efficiently. It enables the execution of complex algorithms for tasks such as genome assembly, molecular dynamics simulations, protein structure prediction, and phylogenetic analysis. Furthermore, HPC facilitates the integration of diverse data types and the development of sophisticated models to understand biological systems at a systems biology level. By leveraging parallel processing and large memory capacities, HPC allows researchers to perform large-scale analyses that would be otherwise impossible, accelerating discoveries in genomics, personalized medicine, and evolutionary biology. Thus, HPC is transforming bioinformatics by enabling more accurate, timely, and scalable computational analysis, which is essential for addressing the challenges of modern biological research. In the lecture, we will cover the basics of HPC use in bioinformatics with specific examples from the research such as The Humane Genome Project.