At BEACON, graduate students are offered interdisciplinary training in biological and computational evolution.
Courses at MSU (open to students at BEACON partner universities):
Introduction to Computational Methods in Biology (Instructor: Arend Hintze – CSE 801 at MSU).
Fall 2015, Tuesdays and Thursdays 12:40-2:00 pm, starting Thursday September the 4th 2015, in 1455A BPS (BEACON classroom)
Like in every other science advances in computing increase the amount of data scientists are confronted with. It becomes imperative for modern day research to be able to use computational tools, be it storing and analyzing data, doing statistics, or using computational models. This course will introduce students to computational thinking and data literacy in Biology. This is not your typical programming class. Forget sorting lists, or compound interest examples – we are doing biology here. Think of it as the “Swiss army knife course for computational methods in Biology”! This course is intended for graduate students with little or no previous programming experience. There are no prerequisites, but you should bring a laptop to class.
The learning objectives for this course include:
- Students will learn to use the Python programming language and iPython notebook to do open and reproducible science
- Students will learn how to make publication ready data analysis and plots using spreadsheet data as well as data from SQL databases
- Students will learn hot to make computational models to understand ecosystems, game theory, and evolution
- Students will get an introduction to the statistics language R
While there is no mid-term or final-exam, your grade will be based on weekly homework exercises, spontaneous quizzes, and an individual project that shows your newly learned skills. Expect an intense but very rewarding learning experience that will enable you to become a computational and data savvy scientist.
Evolutionary Biology for non-Life Scientists (Instructor: Louise Mead, Mike Wiser – IBIO 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 firstname.lastname@example.org as soon as possible to work out scheduling and registration.
Multidisciplinary approaches to the study of evolution (Instructor: Chris Adami – 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.