ANT 315: Ancient DNA: Human Evolution & Adaptation

Description: The relatively new field of Ancient DNA has proved transformative in the understanding of evolution in humans and other species. By accessing the genetic martial of a population from known archeological contexts, we are now capable of examining evolution in both space and time. In this course, we will focus on both the key methods adopted in the study of ancient DNA, such as next generation sequencing and population genetics, as well as a thematic approach to the major evolutionary questions broached thus far. Topics include human migrations, archaic humans, plant and animal domestication, ancient pathogens, the origins of auto-immune
disorders, and adaptations to ancient environments.

ANT 332: Race in the Age of Genomics

This is the “Age of Genomics”, and yet people who study race, culture, and law often resist integrating biological insights into their understanding of human psychology and behavior. One reason for this resistance is historical: pseudo-biological concepts of race have more often than not played a pernicious role in distorting legal and social policy. The response of many social scientists has been to avoid biological paradigms altogether and suggest that racial concepts reflect social construction. Popular belief in race nevertheless persists and continues to play a major role in many social interactions. In this course, we will examine the historical, ethical, and philosophical foundations of race and push them through a modern scientific lens. We will examine the biological and cultural processes that have shaped human traits and how genomics can help us better understand our “differences” in a culture influenced by subjective racial classifications. 

ANT 585: Computational Genomics

In recent years, advances in DNA sequencing technology has produced an explosion of genomic data. The ability to leverage the power of computing clusters is now playing a central role in genomics: from assembling DNA sequences to analyzing thousands of genomes in order to detect natural selection. The area of computational genomics includes both applications of older statistical methods and the development of novel algorithms. This course aims to present some of the most useful algorithms for sequence analysis and statistical methods to address a variety of evolutionary and medical questions. Sequence alignments, hidden Markov models, multiple alignment algorithms, and the probabilistic interpretation of alignments will be covered.