2017 Genome Informatics

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Academic unit or major
Undergraduate major in Life Science and Technology
Instructor(s)
Itoh Takehiko  Yamada Takuji  Kurokawa Ken  Kotera Masaaki 
Course component(s)
Lecture
Day/Period(Room No.)
Tue3-4(H101)  Fri3-4(H101)  
Group
-
Course number
LST.A351
Credits
2
Academic year
2017
Offered quarter
3Q
Syllabus updated
2017/4/27
Lecture notes updated
-
Language used
Japanese
Access Index

Course description and aims

This course focuses on the genome informatics which is a branch of bioinformatics. Genome informatics is a field which has achieved rapid development in recent years. Students will be acquired the knowledge of both genome biology and genome informatics fields.

Student learning outcomes

By the end of this course, students will be able to:
1) Understand the basic experimental methods in genome sequence analysis.
2) Understand the computational analysis methods in genome informatics fields.
3) Understand the latest topics in genome informatics.

Keywords

Genome informatics, sequence analysis, Next Generation Sequnecer

Competencies that will be developed

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

Class flow

Before coming to class, students should read the course schedule and check what topics will be
covered. Required learning should be completed outside of the classroom for preparation and review
purposes.

Course schedule/Required learning

  Course schedule Required learning
Class 1 Introduction to genome informatics Understand the outline of genome informatics.
Class 2 Genome sequence determination -- DNA sequencing -- Understand the fundamental experimental methods of DNA sequencing.
Class 3 Genome sequence determination -- Computational methods-- Understand the outline of computational methods in genome sequence determination.
Class 4 Genetic sequence analysis (cDNA, microarray) Understand the outline of genetic sequence analysis.
Class 5 Principles of Next Generation Sequencers Understand the outline sequence principles of Next Generation Sequencers.
Class 6 Computational analysis of Next Generation Sequencing data Understand the outline of computational analysis methods of Next Generation Sequencing data.
Class 7 Gene prediction from prokaryote genomes Understand the outline of gene prediction algorithms from prokaryote genomes.
Class 8 Gene prediction from eukaryote genomes(1) Understand the outline of gene prediction algorithms from eukaryote genomes (1).
Class 9 Gene prediction from prokaryote genomes(2) Understand the outline of gene prediction algorithms from eukaryote genomes (2).
Class 10 Functional annotation (homology search) Understand the functional annotation using homology search.
Class 11 Functional annotation (motif search, GO annotation etc.) Understand the functional annotation using motif search or GO annotation.
Class 12 Comparative genomics Understand the outline of comparative genomics.
Class 13 Latest topics of genome analysis (metagenomics 1) Understand the latest topics of genome analysis (metagenomics 1)
Class 14 Latest topics of genome analysis (metagenomics 2) Understand the latest topics of genome analysis (metagenomics 2)
Class 15 Latest topics of genome analysis (single cell analysis) Understand the latest topics of genome analysis (single cell analysis)

Textbook(s)

None

Reference books, course materials, etc.

T.A. Brown Genomes (3rd edition)
David Mount. Bioinformatics: Sequence and Genome Analysis 2nd Edition

Assessment criteria and methods

Exercise 50%, Final exam 50%

Related courses

  • LST.A246 : Bioinformatics
  • LST.A241 : Biostatistics

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

No prerequisites.

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