At BEACON, graduate students are offered interdisciplinary training in biological and computational evolution.
Courses at MSU (open to students at BEACON partner universities):
Computational Science for Evolutionary Biologists (Instructor: Titus Brown – CSE 801 at MSU). Doing biology increasingly requires computational skills and quantitative reasoning abilities. This course will introduce students to computational thinking and practice through an intensive scripting and programming regimen, built around a series of models and data sets from evolutionary and molecular biology. During this course we will introduce the Python programming language, scripting and pipelining, simulations, and data analysis.
This year, we plan to have two five-week modules: NGS sequence assembly and analysis and evolutionary modeling. The advance workshops will introduce the basic tools and approaches necessary for doing data analysis, using IPython Notebook and the Amazon cloud; follow-on work will be done in the cloud or on the MSU HPC. We will primarily teach in Python, with a side serving of the shell and command line. Expect 10-20 hours of homework a week, with ~2 hours of class a week.
This course is intended for graduate students with little or no previous programming experience. There are no prerequisites other than a strong background in at least one of evolution, ecology, genetics, or molecular biology. Enrollment by permission of instructor only. This course will generally not fulfill any requirements for computational graduate students. Auditing is allowed but only if you do the work!
Evolutionary Biology for non-Life Scientists (Instructor: Louise Mead – ZOL 890 Section 601 at MSU). This interactive course will introduce computer scientists and other scientists and engineers to the principles of biological evolution. The course will comprise three intensive modules: the genetic basis of life; mechanisms of evolutionary change; analyzing evolutionary patterns and processes. By the end of the course students will understand the major concepts of evolutionary biology and be able to apply these concepts creatively and critically to address problems in biology, computer science, and engineering.
The course is intended for graduate students with little or no background in biology (let alone evolutionary biology) and there are no prerequisites.
This is a three-credit course that will be taught as two 80 minute classes per week (Tue/Thu). The course is also offered by teleconference at remote BEACON institutions and we will schedule the exact time of the course to accommodate students taking it remotely. If you are interested in taking this course, please contact email@example.com as soon as possible to work out scheduling and registration.
Multidisciplinary approaches to the study of evolution (Instructors: Charles Ofria and Ian Dworkin – CSE 891 at MSU). This course provides an introduction to engaging in multi-disciplinary research collaborations involving biologists, computer scientists, and engineers addressing fundamental questions about the dynamics of actively evolving systems (both biological and computational). Students will work on these projects in multi-disciplinary and multi-institutional teams, with guidance to help them develop an understanding of the nature and challenges of such collaborative endeavors and how to overcome discipline-specific language and conceptual issues. Additionally, students will be introduced to fundamental topics in experimental design and statistical analysis, critical to the success of any research project.
Courses at NC A&T:
Evolutionary Biology for Engineers and Computer Scientists (Instructor: Dr. Joseph Graves, COMP 790.003 for graduate students, COMP 590.005 for undergraduates.). This course explores the discipline of evolutionary biology through the range of organization that exists within the biological sciences (molecular to societal). Students will read and discuss the established principles of evolution along with new material as it arises from the primary literature. The pedagogical approach utilized in this course introduces students to how topics in evolutionary biology are approached and solved. Furthermore it examines why and how evolutionary reasoning is essential to modern biology and fully integrated into the general scientific method.
Computer Science for Biologists (Instructor: Dr. Gerry Dozier). Details to come.
Courses at U of Idaho:
Evolutionary Computation (Instructor: Terence Soule, CS J472/J572 at UI). Solving computation problems by “growing” solutions; simulates natural evolution using analogues of mutation, crossover, and other generic transformations on representations of potential solutions; standard EC techniques such as genetic algorithms and evolutionary programming, mathematical explanations of why they work, and a survey of some applications; the focus is on solving real-world problems using projects. Graduate-level research and possible paper or presentation required for grad credit. *Course is taped and available to partner sites remotely through UI’s Engineering Outreach program.
BEACON is also partnering with Michigan State University’s Center for Academic & Future Faculty Excellence to ensure that BEACON students, postdocs, and faculty participate in professional development activities and Responsible Conduct of Research training.