Introduction to Quantitative Genomics and Bioinformatics

Genomics generates massive amounts of data, requiring specialized quantitative skills to interpret biological meaning. This course provides the foundational concepts and analytical techniques necessary to work effectively with modern genomic information. By the end of this program, you will understand the principles of population genetics, comparative genomics, and functional genomics from a computational perspective. You will be prepared to approach common bioinformatics challenges, such as analyzing sequencing results and identifying genetic variants, using modern quantitative methods. What you'll learn: * Understand the fundamental models of population and evolutionary genetics, including concepts like genetic drift and selection. * Analyze raw sequencing data and perform essential quality control steps for variant calling and genome assembly. * Master the principles of comparative genomics to identify homologous sequences and evolutionary relationships across species. * Apply statistical methods to interpret structural data, including basic concepts of proteomics and gene regulation. * Practice working with common bioinformatics file formats and command-line tools used for large-scale genomic data processing. The course begins with foundational concepts in genetics and statistics before moving into practical applications across structural, comparative, and functional genomics. The material emphasizes reading and understanding the quantitative methods that drive modern genomic discoveries. This course is designed for absolute beginners with no prior experience in bioinformatics or quantitative genomics. No prerequisites in advanced statistics or programming are required. Start building your computational genomics skillset today.