2018 Design Theory in Biological Systems

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Academic unit or major
Graduate major in Artificial Intelligence
Instructor(s)
Yamamura Masayuki  Aonishi Toru  Sekijima Masakazu  Takinoue Masahiro  Komiya Ken   
Course component(s)
Lecture
Day/Period(Room No.)
Mon5-6(S223,G311)  Thr5-6(S223,G311)  
Group
-
Course number
ART.T546
Credits
2
Academic year
2018
Offered quarter
2Q
Syllabus updated
2018/3/20
Lecture notes updated
-
Language used
English
Access Index

Course description and aims

This course provides an introduction to the design principle of life in the viewpoint of system theory, through lecturing topics on related computational methodology.

Student learning outcomes

The mathematical basics are provided in the linear/non-linear differential equation systems, statistical physics, thermodynamic systems, automata and stochastic process as the design principle of life. The following topics are also provided: modeling and simulation on biological networks including genetic circuits and neural circuits, design and implementation methods of novel device systems inspired by life system and computational science methods including bioinformatics and biological molecular simulation. Students will be able to select and explain how such modeling and simulation technique is used.

Keywords

synthetic biology, systems biology, evolutionary computation, computational neuroscience, molecular simulation, molecular robotics

Competencies that will be developed

Intercultural skills Communication skills Specialist skills Critical thinking skills Practical and/or problem-solving skills
- - - -

Class flow

In every class, instructors lecture independent topics with original handouts. Every class includes simple exercises to be solved by individual students or by groups. These exercises help understand the principle and will be used as materials for final evaluation.

Course schedule/Required learning

  Course schedule Required learning
Class 1 Mathematical Basics 1: modeling and simulation with linear/non-linear differential equations solving linear / non-linear differential equations
Class 2 Mathematical Basics 2: modeling and simulation with automata and stochastic process solving stochastic processes
Class 3 Systems Biology / Synthetic Biology 1: Biological Information Flow and metabolism in cells understanding the central dogma
Class 4 Systems Biology / Synthetic Biology 2: Design and analysis of Artificial Genetic Circuits understanding the concept of genetic circuit
Class 5 Systems Biology / Synthetic Biology 3: Evolution in Artificial Life implementation of evolutionary computation
Class 6 Computational Neuro Science 1 : What is Computational Neuro-Science understanding neuro-science basics
Class 7 Computational Neuro Science 2 : Deriving equivalent circuit models for cellular membrane and Hodgkin-Huxley model solving equivalent circuits
Class 8 Computational Neuro Science 3: FitzHugh-Nagumo model and bifurcation theory understanding bifurcation theory
Class 9 Molecular Simulation / Bioinformatics 1:bioinformaticss understanding bioinformatics basics
Class 10 Molecular Simulation / Bioinformatics 2:molecular dynamics simulation understanding formulas on molecular dynamics
Class 11 Molecular Simulation / Bioinformatics 3:docking simulation understanding geometric simulation basics
Class 12 Molecular Robotics 1: DNA sequence design (free energy and Hamming distance) understanding the concept of free energy
Class 13 Molecular Robotics 2: Calculation of DNA/RNA secondary structure and its application to DNA nanotechnology understanding secondary structure formation
Class 14 Molecular Robotics 3: DNA computing and chemical reaction models understanding chemical reaction equations
Class 15 Group work: Design Competition for new life forms by small groups designing artificial lives

Textbook(s)

Unspecified.

Reference books, course materials, etc.

For every class, teachers lecture independent topics with original handouts.

Assessment criteria and methods

Every class also includes simple exercises by individual students or by groups. These exercises help to understand the principle and also become materials for final evaluation.

Related courses

  • Biological Data Analysis
  • Bioinformatics
  • Molecular Simulation

Prerequisites (i.e., required knowledge, skills, courses, etc.)

none

Contact information (e-mail and phone)    Notice : Please replace from "[at]" to "@"(half-width character).

e-mail : my[at]c.titech.ac.jp, tel. : 045-924-5212

Office hours

Suzukake-dai campus J2 build, rm1706, Mon&Thu 17:00—18:00

Other

none

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