Complex systems experiment 2

Course Goals and Aims

To learn about basic acquisition and analysis methods in molecular information and bioinformatics related to complex phenomena in materials and life through basic experiments. In addition, students will deepen understanding of various natural phenomena through mathematical modeling and computer simulation.

Course Features

The aim of the course is to acquire a basic viewpoint of complex systems, which exist in nature in various levels and scales, by adopting a broad experimental system from living systems to abstract simulation.

Syllabus

1. Introduction: explanation of schedule and outline of this experiment course. (One class time).
2. It is known that the color development in various flowers is due to self-organization of complex components and formation of macromolecules. The aim of this experiment is to understand the phenomenon through dye extraction and color development experiments. Instructor in charge: Yoshida Kumi, Assoc. Prof. (4-5 class times)
3. DNA engineering and bioinformatics are useful to understand complex and dynamic life phenomena such as environmental response, pattern formation, and evolution. Students will focus on learning to analyze their own DNA genome via various practical experiments related to those two techniques. Instructor in charge: Aoki Setsuyuki, Assoc. Prof. (4-5 class times).
4. A constructive approach is to understand emergent behaviors of living and social systems through construction and analysis of computational models. Students will learn this methodology and application by conducting some computational experiments based on an agent-based model (ABM), evolutionary computation, etc. Instructor in charge: Suzuki Reiji, Assoc. Prof. (4-5 class times).

Textbooks and References

Each instructor in charge will distribute his/her materials during the first class and designate references. Interest in chemistry, biology, evolution, simulation, etc. is desirable.

Grade evaluation

In principle, besides attending all lectures, evaluation will also be based on assigned reports. 50% of your score will be based on attendance and 50% on report scores.

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