Remote Interactive Lectures “Foundations of Computational Life Sciences” 2014 Curriculum

2014 Curriculum

Introduction of Computational Life Sciences
Lecturer: Yukihiro Eguchi (RIKEN)

Part 1 Life Sciences viewed from Genome

1.1　Analysis of Big Data recorded in Genome
　　　Lecturer: Yasushi Okuno (Kyoto Univ.)

1.2　Biomedical Informatics
　　　Lecturer: Yasushi Okuno (Kyoto Univ.)

1.3　Analysis of Gene Networks
　　　Lecturer: Atsushi Doi (Cell Innovator Co., Ltd.)

1.4　Systems Biology of the Cell
　　　Lecturer: Yukihiro Eguchi (RIKEN)

Part 2 Life Sciences viewed from Protein

2.1　 Foundation of Quantum Chemistry for Life Sciences
　　　Lecturer: Fumitoshi Sato(The University of Tokyo)

2.2　Quantum Chemistry for Protein Analysis
　　　Lecturer: Kaori Fukuzawa (Nihon University)

2.3　Molecular Dynamics, and Functional Analysis of Biomacromolecules
　　　Lecturer: Masahiko Nakatsui (Kobe University)

2.4　Enhanced Sampling in Molecular Dynamics
　　　Lecturer: Masahiko Nakatsui (Kobe University)

2.5　Biological Function of Proteins, and Chemical Reactions
　　　Lecturer: Shigehiko Hayashi (Kyoto University)

Part 3 Life Sciences in Medicine and Drug Discovery

3.1　Pharmaceutical Big Data Analysis
　　　Lecturers: Akio Tsuji and Yoshitake Kitanishi (Shionogi & Co., Ltd.)

3.2　Computational Life Sciences in Drug Discovery : from the view point of Molecular Dynamics　　
　　　Lecturer: Takatsugu Hirokawa (Advanced Industrial Science and Technology)

3.3　Computational Life Sciences in Drug Discovery : from the view point of Quantum Chemistry
　　　Lecturer: Kaori Fukuzawa (Nihon University)

3.4　Medical Big Data
　　　Lecturer: Hiroshi Tanaka (Tokyo Medical and Dental University)

3.5　Computational Life Sciences in Medicine: Focusing on Myocardial Activation Propagation in Arrhythmias
　　　Lecturers: Kazuo Nakazawa and Shin Inada
　　　(National Cerebral and Cardiovascular Center)
　　

Note: These lectures are delivered in Japanese. And, the official title of each lecture is written in Japanese. This translation to English is done by Yukihiro Eguchi, and is an unofficial translation.

【Feedback from Students】

・The program was very educational, with historical background, related knowledge, and new developments presented in compact form.
・I gained a good understanding of how big data is used by pharma firms, with examples from clinical statistics and data analysis.
・Thank you for lectures that gave me a sense of the extensiveness of your research.

【Classification of Registrants 】