|Instructor||Dan DeBlasio||Time||TR 15:00-16:30|
|dfdeblasio _at_ utep.edu||Location||Online|
online until further notice:
or by appointment (calendly.deblasiolab.org).
This course will cover the algorithms that make modern computational biology and bioinformatics possible. The plan is to cover both foundational algorithms such as sequence alignment, as well as their modern applications in solving problems such a genome assembly. The focus of this course is on how computer scientists apply their knowledge to frame a computational problem inspired by a specific real-world problem and to solve such computational problems. In addition to standard algorithm development, the course will cover the influence of convex optimization (mainly integer linear programming) and machine learning on computational biology. The course assumes no previous knowledge in biology or genetics. The course will build on and enhance students’ basic understanding of the principle of algorithm design and analysis by applying such principles in the context of bioinformatics.The topics discussed are likely to include: