2025 (Current Year) Faculty Courses School of Life Science and Technology Undergraduate major in Life Science and Technology
Bioinformatics(LST)
- Academic unit or major
- Undergraduate major in Life Science and Technology
- Instructor(s)
- Akio Kitao / Takuji Yamada / Kengo Sato / Koichiro Uriu / Takehiko Itoh
- Class Format
- Lecture (Face-to-face)
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - 3-4 Tue (M-103(H114)) / 3-4 Fri (M-103(H114))
- Class
- -
- Course Code
- LST.A246
- Number of credits
- 200
- Course offered
- 2025
- Offered quarter
- 4Q
- Syllabus updated
- Sep 8, 2025
- Language
- Japanese
Syllabus
Course overview and goals
This course focuses on the basics of bioinformatics, which is an integrated field of life science and information science.
Kitao: Learning statistical mechanics to connect biological microscopic states and macroscopic states (3 lectures)
Sato: Understanding basics of data science in bioinformatics (3 lectures)
Uriu: Understanding basics of mathematical modeling in life sciences (3 lectures)
Yamada: Understanding basics of bioinformatics for metagenome analysis (3 lectures)
Itoh: Understanding basics of bioinformatics for genome analysis (2 lectures)
Course description and aims
Kitao: Understanding the relation between statistical mechanics and biological phenomena
Sato: Understanding basics of data science and machine learning
Uriu: Grasping the overview of mathematical modeling in life sciences
Yamada: Understanding basics of metagenome analysis
Itoh: Understanding basics of genome analysis
Keywords
Bioinformatics, data science, database, sequence analysis, phylogenetic analysis, machine learning, metagenome,
mathmatical modeling, thermodynancs, statistical mechanics
Competencies
- Specialist skills
- Intercultural skills
- Communication skills
- Critical thinking skills
- Practical and/or problem-solving skills
Class flow
Lecture is given for each topic, followed by some practices when necessary.
Course schedule/Objectives
| Course schedule | Objectives | |
|---|---|---|
| Class 1 | Microscopic states and their probabilities |
Understand the relation between and microscopic states and their probablities |
| Class 2 | Introduction to statistical ensembles |
Understanding statisitical ensembles |
| Class 3 | Applications of statistical ensembles |
Understanding of some applications of statistical ensembles |
| Class 4 | Statistical data anlysis |
Understanding basics of statistical data anlysis |
| Class 5 | Hidden Markov Model |
Understanding basics of probabilistic sequence analysis |
| Class 6 | Introduction to machine learning |
Applications of machine learning in life science |
| Class 7 | Mathematical modeling in life sciences (Introduction) |
Understanding why mathematical modeling is required in life sciences |
| Class 8 | Modeling of gene regulation |
Understanding functions of various gene regulatory network motifs |
| Class 9 | Modeling of synchronization and collective movement of cell population |
Understanding synchronization and collective movement of cell population |
| Class 10 | The fundamental concepts and significance of metagenomic analysis. |
Understand the fundamental concepts and significance of metagenomic analysis. |
| Class 11 | The usage of public metagenomic databases |
Understand the structure and usage of public metagenomic databases. |
| Class 12 | The methods and algorithms for estimating microbial community structure. |
Understand the methods and algorithms for estimating microbial community structure |
| Class 13 | The basic principles of sequence analysis and alignment |
|
| Class 14 | The sequence database and homology search |
Understand the sequence database and homology search |
Study advice (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)
None.
Reference books, course materials, etc.
Japanese Society of Bioinformatics. Bioinformatics Nyumon (Japanese), ISBN-13: 978-4766422511
David Mount. Bioinformatics: Sequence and Genome Analysis 2nd Edition, ISBN-13: 978-0879697129
Evaluation methods and criteria
Evaluation of assignments imposed during the lecture and those submitted after the lecture.
Related courses
- LST.A241 ： Biostatistics
- LST.A351 ： Genome Informatics
- LST.A201 ： Physical Chemistry I
- LST.A206 ： Physical Chemistry II
- LST.A211 ： Physical Chemistry III
- LST.A341 ： Biophysical Chemistry
Prerequisites
None.