学部・大学院区分 Undergraduate / Graduate		農・博前

時間割コード Registration Code		2930010

科目区分 Course Category		Ｃ類 Category C

科目名　【日本語】 Course Title		データサイエンス特別講義４

科目名　【英語】 Course Title		Special Lecture on Data Science 4

コースナンバリングコード Course Numbering Code

担当教員　【日本語】 Instructor		白武　勝裕 ○ COROVIC Jasmina 大谷　仁志

担当教員　【英語】 Instructor		SHIRATAKE Katsuhiro ○ COROVIC Jasmina OTANI Hitoshi

単位数 Credits		1

開講期・開講時間帯 Term / Day / Period		春集中その他その他 Intensive(Spring) Other Other

対象学年 Year		１年 1

授業形態 Course style

授業の目的　【日本語】
Goals of the Course(JPN)

データサイエンス特別講義１，２，３を基礎とし，トランスクリプトミクスやプロテオミクスの実際，またメタボロミクスを含めたマルチオミクスの概要を学ぶ．

授業の目的　【英語】
Goals of the Course

Based on Data Science 1, 2 and 3, this course introduces practical approaches of transcriptomics and proteomics, and outline of multi-omics including metabolomics.

到達目標　【日本語】
Objectives of the Course(JPN)

データサイエンス特別講義１，２，３を基礎とし，トランスクリプトミクスやプロテオミクスの実際，またメタボロミクスを含めたマルチオミクスの概要についての知識を修得する．

到達目標【英語】
Objectives of the Course

Based on Data Sciences 1, 2 and 3, in this course, students get knowledge of practical approaches of transcriptomics and proteomics, and outline of multi-omics including metabolomics.

授業の内容や構成
Course Content / Plan

1. Preparing a computing environment for NGS analysis in Linux operating system. Lecture for basics of the Linux commands. Usage instructions of bioinformatics tools for the NGS analysis.
2. Guidance for RNA-Seq data analysis pipelines (read mapping, calculation of the expression values and statistical analysis). Guidance for genome-wide DNA methylation data analysis (read mapping and calculation of DNA methylation levels).
3. Big data and bioinformatics analysis in proteomics.
4. Application of bioinformatics in peptide and protein engineering.
5. Outline of metabolomics.
6. Application of multi-omics.

履修条件・関連する科目
Course Prerequisites and Related Courses

Special Lecture on Data Science 1, 2 and 3

成績評価の方法と基準
Course Evaluation Method and Criteria

Evaluate each lesson by attendance and short report.

教科書・テキスト
Textbook

None

参考書
Reference Book

None

課外学習等（授業時間外学習の指示）
Study Load(Self-directed Learning Outside Course Hours)

After lecture, students should learn about practice of omics study by reading scientific papers and by accessing to webtools for omics study.

使用言語
Language Used in the Course

This course will be taught in Japanese or English. All course materials are in English.

授業開講形態等
Lecture format, etc.

In-person class (In case of the COVID-19 pandemic expansion, remote learning).

遠隔授業（オンデマンド型）で行う場合の追加措置
Additional measures for remote class (on-demand class)

Students can ask question or discussion by e-mail.