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 891 at MSU). This course introduces biologists to computational thinking, practical computational techniques, and research topics in computational evolution. The course consists of three intensive hands-on 5-week modules: computational competence in UNIX; data mining and hypothesis generation using the Avida digital life platform and computational analysis of large-scale resequencing data from the Lenski Lab E. coli long-term evolution experiment.
Evolutionary Biology for non-Life Scientists (Instructor: Alex Shingleton – ZOL 890 at MSU). The purpose of the course is to provide students with a working understanding of biological evolution so that you will be able to form productive collaborations with evolutionary biologists. Students will need to know much more than just the ‘facts’ of evolutionary biology – they will need to be able to ‘think’ like an evolutionary biologist. Life-scientists in general, and evolutionary biologists in particular, have a particular way of looking at the world, a perspective that may seem unfamiliar, unusual or even wrong to those outside of science. In this class, students begin to view the world from this perspective.
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.
Mentoring
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.
