tool for generating samples under neutral models.
INTENDED AUDIENCE: anyone who's interested in learing about exciting
developments at the intersection of evolutionary biology and computing.
It is expected the students have had an algorithms course, can program, and are not
afraid of math (if you do not satisfy at least one of these three, this course is
not for you!). Knowledge of biology is a plus, but is not required.
The coalescent model (genetic drift, mutation, recombination, ARGs, etc.)
Phylogenomics (gene trees and species phylogenies, gene duplication/loss,
HGT, introgression, incomplete lineage sortng, etc.)
Molecular evolution (the neutral theory of evolution, measures of
divergence and polymorphism, measures of selection, etc.)
Population genomics (application of population genetics to genome-wide
The grades will be based on a midterm (30%), a set of
homework assignments (30%), and a project (40%). The homework assignments will be
done individually, whereas the projects will be done in teams.
STUDENTS WITH DISABILITY: Any student with a documented disability needing academic adjustments
or accommodations is requested to speak with me during the first two
weeks of class. All discussions will remain confidential. Students
with disabilities will need to also contact Disability Support
Services in the student center.