Teaching

COURSES TAUGHT:

BIOL2010 - Ecology and Evolution (spring 2024) - example syllabus

Foundational course required for Biology majors with a focus on the ecology and resilience of living systems across all levels of spatial scales. Topics introduced in this course include evolution, population dynamics, behavioral ecology, ecosystems, co-evolution, and human ecology.

BIOL2300 - Biostatistics (fall 2024) - example syllabus (fall), example syllabus (summer)

This course will introduce students to the basic statistical techniques that are used in conducting biological and medical research. There is an emphasis on the investigation of real biological data, and students will learn to conduct analyses using the open-source software R. The course is divided into four main parts: (1) introduction to statistics, probability, and hypothesis testing, (2) analyzing proportions and frequencies; (3) comparing numerical values, and (4) regression and correlation.

BIOL4075: Research in Molecular Phylogenetics (fall 2024) - example syllabus

A phylogenetic tree is a diagram that depicts the relationships among a set of taxa or genes, and is a critical tool for many analyses of evolutionary history. This course covers the basic methods of phylogenetic inference from DNA sequence data, including data collection, alignment, and tree building using parsimony, distance, likelihood, and Bayesian techniques. Lectures will introduce the logical basis of these methods, and computational labs will give students hands-on experience with these methods using a variety of phylogenetic software packages. Pre-requisites: BIOL3050 Genetics or BIOL3150 Introduction to Genomics. Recommended but not required: BIOL4200 Introduction to Bioinformatics

BIOL4110 - Ornithology (TBD) - example syllabus

This course will review the evolution, functional morphology, physiology, ecology, and behavior of birds. Topics covered include dinosaur ancestry, adaptations for flight, breeding behaviors, migration, and conservation. Students will also review the biodiversity and natural history of extant birds, and learn to identify common local birds using morphology and vocalizations.

BIOL4450 - Behavioral Ecology (spring 2025) - example syllabus

This course will examine the adaptive significance of behavior in an ecological context. Lectures and readings from the primary literature will review basic concepts and theory as well as model-based and experimental approaches to exploring questions in the field. Topics covered include social behavior, reproductive behavior, life history strategies, optimal foraging, territoriality, co-evolution, and communication.  Prerequisites: BIOL2010 and BIOL3150 or BIOL3190.

BIOL4802 - Research in Evolutionary Genomics (TBD) - example syllabus

This course will provide hands-on training in the collection and analysis of genome-scale data from non-model organisms. Students will learn good laboratory practices while preparing samples for next-generation DNA sequencing, which will be run in the department's core sequencing facility. Students will also learn basic Linux/Unix computational skills and several bioinformatics tools that will be applied in managing and analyzing the massive amounts of data generated by this sequencing technology. Through data analyses and reviews of the primary literature, students will gain exposure to modern methods in phylogenetics and population genetics. This course is recommended for students interested in advanced topics in genomics, bioinformatics, and evolution. Prerequisites: BIOL2010 and BIOL2040. Recommended: BIOL3150 and BIOL4200.

BIOL6160 - Graduate Bioinformatics (TBD) - example syllabus

The biological sciences are in an exciting period of transformation with the arrival of a “big data” age, in which advances in tools and computational abilities have made the collection of large, complex data sets more tractable. The analysis of big data, however, introduces substantial computational challenges, and thus biologists across a wide array of fields are increasingly challenged to broaden their computational comprehension in order to maximize their research potential. The aim of this course is to equip graduate students with a general background in bioinformatics and computational biology. The course introduces working in the Unix/Linux command-line, coding in Python, next-generation DNA sequencing analysis, phylogenetics, and statistical analyses in R.

BIOL7020 - Statistics for Biologists (Summer 2024)

This course serves as an introduction to or refresher of  statistics for biology graduate students. Topics covered include statistics vocabulary, hypothesis testing, analyses of frequency data, comparing means, and linear regression. All statistical work is conducted in teh open-source software R, and students also get an introduction to Python and Linux.