シラバス Syllabus | Doctoral Program in Medical Sciences | ||
---|---|---|---|
科目番号 Course Number |
0BTNE31 / 0BTNE33 | 0BTNE35 / 0BTNE37 | 0BTNE39 / 0BTNE3B |
科目名 Subjects |
Lecture and Discussion in Genome and Environmental Medicine I Lecture and Discussion in Genome and Environmental Medicine II |
Seminar in Genome and Environmental Medicine I Seminar in Genome and Environmental Medicine II |
Practice in Genome and Environmental Medicine I Practice in Genome and Environmental Medicine Ⅱ |
研究分野 Laboratories |
Bioinformatics | Bioinformatics | Bioinformatics |
使用言語 Language used (Japanese, English, Bilingual) |
Bilingual | Bilingual | Bilingual |
他研究室学生の受け入れの可否(〇×) Availability for students from other lab. |
○ possible | ○ possible | TBD upon request. |
他研究室学生の問い合わせ先 Contact Information for Students from Other Lab. |
Haruka Ozaki haruka.ozaki | Haruka Ozaki haruka.ozaki | Haruka Ozaki haruka.ozaki |
授業形態 Course Type |
Lecture, presentation and discussion | Seminar | Practice |
標準履修年次 Year |
1 or 2 | 1 or 2 | 1 or 2 |
実施学期・曜時限等 Semester,Day and Period |
ⅠSpring semester / ⅡAutumn semester | ⅠSpring semester / ⅡAutumn semester | ⅠSpring semester / ⅡAutumn semester |
開講場所 Room Number |
Innovation Medical Research Institute Building, Room 307 (Kasuga area) | Innovation Medical Research Institute Building, Room 307 (Kasuga area) | Innovation Medical Research Institute Building, Room 307 (Kasuga area) |
単位数 Credit |
Spring and Autumn semester, 2 x 2 credits | Spring and Autumn semester, 2 x 2 credits | Spring and Autumn semester, 2 x 2 credits |
担当教員名・オフィスアワー等 | (make an appointment by E-mail) | (make an appointment by E-mail) | (make an appointment by E-mail) |
Faculty Members and E-mail | OZAKI Haruka: haruka.ozaki | OZAKI Haruka: haruka.ozaki | OZAKI Haruka: haruka.ozaki |
授業概要 Course overview |
Development of computational methods for interpreting massive biological data and application of bioinformatics to biomedical problems: (1) AI-based interpretation and prediction of genome functions (2) Development of methods for analyzing single-cell and spatial omics data and their application to disease research (3) Epigenome data analyses for regenerative medicine research (4) Data science research on clinical information |
In this course, through reading the original papers to the latest bioinformatics and computational biology, understanding research objectives, methods, results, and discuss the significance of the research, problems and issues. | Practical learning of programming skills and bioinformatic methods to conduct bioinformatics and computational biology research. |
学位プログラム・コンピテンスとの関係Competence |
【Generic Competence】Intellectual creativity, Communication skills 【Specific Competence】Research planning skills, Cutting-edge research execution skills, Working knowledge in the specialized field, Information and communication technology skills |
【Generic Competence】Intellectual creativity, Communication skills 【Specific Competence】Research planning skills, Cutting-edge research execution skills, Working knowledge in the specialized field, Information and communication technology skills |
【Generic Competence】Intellectual creativity, Communication skills 【Specific Competence】Research planning skills, Cutting-edge research execution skills, Working knowledge in the specialized field, Information and communication technology skills |
授業の到達目標(学修成果) Course Objectives (Learning Outcomes) ←SBO(Specific Behavior Objectives |
Students learn how to design a research proposal, present their findings and discuss their significance, and make future research plans related to bioinformatics and computational biology in a scientifically appropriate manner through presentation and discussion. 1. Develop the ability to present the purpose, methods, results, interpretation of the results and future research plan of their bioinformatics and computational biology research. 2. Develop the ability to discuss the significance and originality of their experimental and/or statistical analyses in relation to the current understanding in the research field. 3. Develop the ability to understand questions and comments on their presentation, and use them for the improvement of their future research. 4. Develop the ability to understand the significance and limitations of other students’ presentations, and make useful suggestions for the improvement of their research. 5. Develop the ability to make research plan in compliance with the guidelines for the genomic and other data usage, under the supervision of the faculty member. 6. Develop the abilities to understand the methods and techniques in bioinformatics and computational biology, and to design, make proposals, and implement appropriate research projects in the relevant research area. |
Through reading original articles in English, study bioinformatics and computational biology. By understand leading and world's trend of research, you should be able to design your own research projects with high quality and creativity. This course has a role to train the ability to plan, implement and evaluate as a bioinformatics and computational biology researcher, based on the world trend and standard. 1. To be able to choose latest original articles to read by using major scientific magazines and on-line database. 2. To be able to understand the articles and explain the overview to other students in the fixed time. 3. To be able to understand other students’ explanation of the articles and discuss the significance and question of the research. 4. To be able to explain the historical significance and the position in the overall picture. |
To understand the bioinformatics methods practicing fundamental programming skills used in bioinformatics and computational biology research. 1. To be able to retrieve general data in the life science field from databases. 2. To be able to conduct general data preprocessing steps in the life science field. 3. To be able to conduct general data visualization methods in the life science field. 4. To be able to conduct general machine learning methods in the life science field. 5. To be able to conduct general statistical methods in the life science field. |
キーワード Keyword |
Bioinformatics, Machine learning, Computational biology | Bioinformatics, Machine learning, Computational biology | Bioinformatics, Machine learning, Computational biology |
授業計画 Course Schedule 第1回(月日、時限)担当教員名 講義内容など |
Intensive | Intensive | Intensive |
履修条件 Course prerequisite |
None | None | None |
成績評価方法 Grading Criteria |
Grading Methods and Criteria: Students are evaluated by their achievement of SBO. Students who: -acdieived SBO 1 and 2 are graded C or higher. -achieved SBO 1and 2 and actively practicing 3 are graded B or higher. -achieved 1, 2 and 3, and actively practicing 4- 6 are graded A or higher - exhibited exceptional performance are graded A+ (top 10%). |
Grading Methods and Criteria: Students are evaluated by their achievement of SBO Students who: -acdieived SBO 1 and 2 are graded C or higher. -achieved SBO 1and 2 and actively practicing 3 are graded B or higher. -achieved 1, 2 and 3, and actively practicing 4 are graded A or higher - exhibited exceptional performance are graded A+ (top 10%). |
Grading Methods and Criteria: Students are evaluated by their achievement of SBO Students who: -acdieived SBO 1 and 2 are graded C or higher. -achieved SBO 1and 2 and actively practicing 3 are graded B or higher. -achieved 1, 2 and 3, and actively practicing 4 and 5 are graded A or higher - exhibited exceptional performance are graded A+ (top 10%). |
学修時間の割り当て及び授業外における学修方法 Learning method |
Lecture 100% Out-of-class learning: Preparation for the presentation in the progress report. |
Training (Seminar) 100% Out-of-class learning: Preparation for the presentation in the journal club. |
Experiment, Practice 100% Out-of-class learning: Use the bioinformatic methods in your own study. |
教材・参考文献 Textbook |
An Introduction to Bioinformatics Algorithms, The MIT Press (2004) | An Introduction to Bioinformatics Algorithms, The MIT Press (2004) | An Introduction to Bioinformatics Algorithms, The MIT Press (2004) |
単位取得要件 Requirement to earn credit |
Requirement to earn credit: Attendance 80% or more. | Requirement to earn credit: Attendance 80% or more. | Requirement to earn credit: Fullfillment of most of SBO. Submission of experimental notebooks. |
その他(受講上の注意点等) Notes |
None | None | None |
他の授業科目との関連 Relation to Other Courses |
Seminar in Genome and Environmental Medicine I, II Practice in Genome and Environmental Medicine I, II |
Lecture and Discussion in Genome and Environmental Medicine I, II Practice in Genome and Environmental Medicine I, II |
Lecture and Discussion in Genome and Environmental Medicine I, II Seminar in Genome and Environmental Medicine I, II |
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