BSCI 483 - Insects, Pathogens and Public Health
BSCI 483 Syllabus (3 credits, offered fall semester of each year)
BSCI 483 Course Overview
Vector-borne diseases represent over 15% of global human infectious disease cases and annually cause over 700,000 deaths. The burden of vector-mediated infectious disease transmission is borne by inhabitants of tropical and subtropical regions of the world. Yet cases of vector-borne are rising in North America, due to our changing climate coupled to introduction of invasive pests and pathogens. This course explores the ecology, evolution and human-health costs of interactions between arthropods, vertebrate animals and humans that lead to pathogen transmission. Broad course themes include disease ecology, insect behavior and genetics, morphology and taxonomy of disease-transmitting insects, and insect-borne disease transmission control strategies.
ENTM 699M - Tools & Techniques in Genomics Research for the Applied Biologist (Part I)
ENTM 699M Syllabus (1 credit, first 7 weeks of spring semester in even years)
ENTM 699M Course Overview
Genomics research is central to unraveling complex processes governing structure and function in biological systems. Yet many biologists find that they lack the basic computing skills required to work with large and complex genomic data sets. This highly interactive course introduces basic programming principles to biologists/entomologists with no previous programming experience. It's primary aim is to give students the basic tools to work with large scientific data sets, as well as instill best practices to enhance repeatability, reproducibility, and efficiency for “big” scientific data analyses.
ENTM 699N - Tools & Techniques in Genomics Research for the Applied Biologist (Part II)
ENTM 699N Syllabus (1 credit, second 7 weeks of spring semester in even years)
ENTM 699N Course Overview
Part II of "Tools and Techniques" introduces the basics of second and third generation sequencing data analysis. Course topics vary by semester (for example, Spring 2022 covered differential gene expression analysis), and graduate students are encouraged to suggest a topic at least 1 semester in advance of the course start date. Throughout the course, students develop a basic understanding of tools needed to analyze genomic data in a highly interactive setting. Students discuss primary literature and review articles that illustrate key concepts in genomic data analysis, as well as follow along with instructor live-coding to construct a bioinformatic pipeline.