Introduction to Computational Biology

Catalog description

Modern DNA sequencing technologies have transformed molecular biology into a data science. Sequencing machines can now read hundreds of millions of DNA sequence fragments in a few hours and at low cost. These technologies not only enable affordable sequencing of individual genomes (human or any other species); they also allow us to investigate numerous ways in which the genome performs its biological functions in different cell types and how mutations in genomes give rise to various phenotypes. However, given the volume of data and the noisy nature of biological measurements and signals, we require intelligent and efficient computational algorithms to make sense of genomic datasets. The discipline of bioinformatics and computational biology aims to meet this need. This course focuses on understanding and applying the computational methods and algorithms that are used to analyze genomic data, in particular the large datasets arising from high-throughput DNA sequencing technologies. During the course, we will focus on several application areas in genomics that require computational analyses. These topics will be organized around three main themes: - Genomes: comparing DNA and protein sequences; locating sequences on the genome; assembling genomes. - Evolution: reconstructing evolutionary relationships; personal genomics; detecting disease-associated genome variations. - Function: understanding biochemical activities using functional genomics; discovering functional elements in genome sequences; characterizing regulatory relationships between genes. For each of the genomics topics listed above, we will focus on understanding the computational algorithms that are used to analyze data. Such algorithms may include dynamic programming (sequence alignment), graph algorithms (assembly), clustering methods (phylogenetics & metagenomics), and machine-learning approaches such as Expectation Maximization, Gibbs sampling, and Hidden Markov Models (various applications in discovering functional genomic elements). Students will also develop practical bioinformatics analysis skills throughout the course. Each bioinformatics topic will be accompanied by practical exercises. Students will also work in teams to research and develop a project that applies computational methods to a genomics-related problem.