This course focuses on teaching students the Pennsylvania flora, both native and naturalized. Through weekly field trips, students will gain an appreciation for the diversity of plant species and plant communities in PA, and observe and discuss ecological and historical forces that influence plant species occurrences and plant communities. The ability to quickly and accurately identify plants in the field, through both sight identification and the use of a dichotomous key, is the major thrust of this course. Students will also learn how to appropriately collect plant materials for further study/identification in the laboratory and for archiving in an herbarium collection.

This course focuses on teaching students the Pennsylvania flora, both native and naturalized. Through weekly field trips, students will gain an appreciation for the diversity of plant species and plant communities in PA, and observe and discuss ecological and historical forces that influence plant species occurrences and plant communities. The ability to quickly and accurately identify plants in the field, through both sight identification and the use of a dichotomous key, is the major thrust of this course. Students will also learn how to appropriately collect plant materials for further study/identification in the laboratory and for archiving in an herbarium collection.

This course will cover various mathematical models and tools that are used to study modern biological problems. Mathematical models may be drawn from cell biology, physiology, population genetics, or ecology. Tools in dynamical systems or stochastic processes will be introduced as necessary. No prior knowledge of biology is needed to take this course, but some familiarity with differential equations and probability will be assumed.

Integrative seminar on current biological research for first-year PhD students.

The goal of this course is to develop a deeper understanding of techniques and concepts used in Computational Biology. The course will strive to focus on a small set of approaches to gain both theoretical and practical understanding of the methods. We will aim to cover practical issues such as programming and the use of programs, as well as theoretical issues such as algorithm design, statistical data analysis, theory of algorithms and statistics. This course WILL NOT provide a broad survey of the field nor teach specific tools but focus on a deep understanding of a small set of topics. We will discuss string algorithms, hidden markov models, dimension reduction, and machine learning (or phylogeny estimation) for biomedical problems.

The goal of this course is to develop a deeper understanding of techniques and concepts used in Computational Biology. The course will strive to focus on a small set of approaches to gain both theoretical and practical understanding of the methods. We will aim to cover practical issues such as programming and the use of programs, as well as theoretical issues such as algorithm design, statistical data analysis, theory of algorithms and statistics. This course WILL NOT provide a broad survey of the field nor teach specific tools but focus on a deep understanding of a small set of topics. We will discuss string algorithms, hidden markov models, dimension reduction, and machine learning (or phylogeny estimation) for biomedical problems.