2016 Bioinformatics(LST)

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Academic unit or major
Undergraduate major in Life Science and Technology
Kurokawa Ken  Sakurai Minoru  Yamada Takuji  Kotera Masaaki 
Class Format
Media-enhanced courses
Day/Period(Room No.)
Tue5-6(H101)  Fri5-6(H101)  
Course number
Academic year
Offered quarter
Syllabus updated
Lecture notes updated
Language used
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Course description and aims

This course focuses on the basics of bioinformatics, which is an integrated field of life science and information technology. Topics include sequence alignment of DNA and proteins, methods of homology search and multiple alignment, and the principles of sequence motifs, molecular evolution phylogenetic prediction, protein 3D structures, and the use of various life science databases.
Bioinformatics deals with data analysis of life phenomenon using computers, and it is essential to represent and compute important biomolecules such as DNA and proteins. The need for the researchers who understand both biology and informatics is becoming more increasing, and students will be able to learn the basics.

Student learning outcomes

By the end of this course, students will be able to:
1) Explain the principles sequence alignments and execute homology search.
2) Explain the principles of multiple alignments and sequence motifs.
3) Understand molecular evolution, and interpret phylogenetic trees.
4) Use representative life science databases.
5) Understand protein 3D structure data and analysis methods


Bioinformatics, database, sequence analysis, phylogenetic analysis

Competencies that will be developed

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/Required learning

  Course schedule Required learning
Class 1 Introduction Understand the outline of bioinformatics
Class 2 Sequence alignment Understand the purpose and principles of sequence alignment.
Class 3 Probability and statistics theory of sequence alignment Understand similarity score matrices of amino acids and the statistical estimation.
Class 4 Homology search Understand the principles of homology search programs such as BLAST
Class 5 Multiple sequence alignment Understand multiple alignment, and the strategies to improve computational amount and accuracy.
Class 6 Sequence motif Understand how to represent and search for sequence motifs.
Class 7 Molecular evolution Understand the neutral theory of molecular evolution, and molecular clock.
Class 8 Phylogenetic prediction Understand basic algorithms to generate phylogenetic trees.
Class 9 International nucleotide sequence databases Understand some representative databases of nucleotide sequences.
Class 10 Protein sequence databases Understand some representative databases of protein sequences.
Class 11 Metabolic pathway databases Understand some representative databases of metabolic pathways.
Class 12 Protein 3D structure databases Understand some representative databases of protein 3D structures.
Class 13 Protein 3D structure motifs Understand protein 3D structure motifs related to protein functions.
Class 14 Protein 3D structure comparison Understand superimposition and structural alignment of proteins.
Class 15 Protein 3D structure and interaction analysis Understand the principles of interaction analysis using protein 3D structures.



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

Assessment criteria and methods

Final exam 100%.

Related courses

  • LST.A241 : Biostatistics
  • LST.A351 : Genome Informatics

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


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