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2024　Design Theory in Biological Systems

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Academic unit or major
Graduate major in Artificial Intelligence
Instructor(s)
Yamamura Masayuki  Sekijima Masakazu  Takinoue Masahiro  Hamada Shogo 
Class Format
Lecture    (HyFlex)
Media-enhanced courses
Day/Period(Room No.)
Mon5-6(S2-202 (S223)，G1-106 (G112))  Thr5-6(S2-202 (S223)，G1-106 (G112))  
Group
-
Course number
ART.T546
Credits
2
Academic year
2024
Offered quarter
2Q
Syllabus updated
2024/3/14
Lecture notes updated
-
Language used
English
Access Index

Course description and aims

Students will gain an understanding of the fundamentals of design principles of biological systems from a systems-theoretic perspective, learn a broad range of relevant computational methods, and gain a broad understanding of the applied fields of bioinformatics, including synthetic biology, systems biology, bioinformatics, molecular computing, and molecular robotics.

Student learning outcomes

The mathematical basics are provided in the linear/non-linear differential equation systems, statistical physics, thermodynamic systems, automata, and stochastic processes as the design principles 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 systems 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 and to design novel molecular information devices, molecular computers, etc. using biomolecules.

Keywords

Synthetic biology, Systems biology, Evolutionary computation, Molecular simulation, Biophysics, Molecular computing, Molecular robotics, Bioinformatics

Competencies that will be developed

✔ Specialist skills Intercultural skills Communication 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 Molecular Simulation / Bioinformatics 1:bioinformaticss understanding bioinformatics basics
Class 7 Molecular Simulation / Bioinformatics 2:molecular dynamics simulation understanding formulas on molecular dynamics
Class 8 Molecular Simulation / Bioinformatics 3:docking simulation understanding geometric simulation basics
Class 9 Molecular Computing 1: Basics of molecular computing understanding the basic concept of molecular computers
Class 10 Molecular Computing 1: Thermodynamics of DNA/RNA, DNA/RNA secondary structure prediction and sequence design (free energy and Hamming distance) understanding of thermodynamics and free energy, secondary structure of biopolymers and its prediction methods
Class 11 Molecular Computing 3: DNA computing and chemical reaction models understanding chemical reaction equations
Class 12 Molecular Robotics 1: DNA nanotechnology and DNA nanostructures Understanding the basics of DNA nanotechnology including DNA nanostructures
Class 13 Molecular Robotics 2: Molecular devices Understanding biomolecular devices (sensors, processors, and actuators)
Class 14 Molecular Robotics 3: Integration examples and their applications Understanding the integration of biomolecular devices as systems

Out-of-Class Study Time (Preparation and Review)

To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to textbooks and other course material.

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

  • CSC.T353 ： Biological Data Analysis
  • ART.T543 ： Bioinformatics
  • ART.T545 ： Molecular Simulation
  • ART.T456 ： Non-linear Dynamical Systems

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

Contact in advance

Other

none

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