Essential Bioinformatics for Global Leaders Ⅱ to begin on April 9, 2019

 Class List of Spring Semester 2019

“Essential Bioinformatics for Global LeadersⅡ” will begin on April 9. This is a class for students who are in “Minor Course of Science and Technology for Global Leaders”. But all master’s & doctoral students can take it if you have interest. The class will be conducted in English.

Theme & Objective

Prof. GouraudBioinformatics is an interdisciplinary research area at the interface between biological science and computational science, the ultimate goal of which is to better understand living cells and their functioning at the molecular level. It involves the technologies that use computers for the storage, retrieval, manipulation, understanding and distribution of information related to biological macromolecules such as DNA, RNA, protein, and even more.
To take benefit of these classes, it is recommended either to have a basic knowledge in molecular and cell biology or to have attended Essential Bioinformatics for Global Leaders I. These advanced classes aim at demonstrating the students how to apply computational methods to the analysis of big data obtained from high throughput techniques in the biological field. This course will give the students examples of common use of bioinformatics in the biological field and provide them with a practical experience with wet lab (microarray) and computer practice (data analysis) sessions.

Message to Students

This class will be a great opportunity for you to know everything about various useful bioinformatics applications among them, microarray technique. You will be especially given the opportunity to follow a real microarray experiment from beginning to end (wet lab and computational data analysis practice). Do not hesitate to join us in this fun experience!

Lecture Outline

Subject
Essential Bioinformatics for Global LeadersⅡ [19S1010
Number of Credits
2.0
Instructor
Gouraud, Sabine (Project Associate Professor of Ochanomizu University)
Target Audience
Graduate Students
Date, Time and Location
Tue., April 9, Period 5-6 (13:20-14:50) Graduate School of Humanities & Sciences Building R102
Tue., April 16, Period 5-6 (13:20-14:50) Graduate School of Humanities & Sciences Building R102
Tue., April 23, Period 5-6 (13:20-14:50) Graduate School of Humanities & Sciences Building R102
Tue., May 7, Period 5-6 (13:20-14:50) Graduate School of Humanities & Sciences Building R102
Tue., May 14, Period 5-8 (13:20-16:30) Science building 2 R202
Tue., May 21, Period 5-6 (13:20-14:50) Graduate School of Humanities & Sciences Building R102
Tue., May 28, Period 5-6 (13:20-14:50) Graduate School of Humanities & Sciences Building R102
Tue., June 4, Period 5-6 (13:20-14:50) Graduate School of Humanities & Sciences Building R102
Tue., June 11, Period 5-6 (13:20-14:50) Graduate School of Humanities & Sciences Building R102
Tue., June 18, Period 5-6 (13:20-14:50) Graduate School of Humanities & Sciences Building R102
Tue., June 25, Period 5-6 (13:20-14:50) Graduate School of Humanities & Sciences Building R102
Tue., July 2, Period 5-6 (13:20-14:50) Graduate School of Humanities & Sciences Building R102
Tue., July 9, Period 5-6 (13:20-14:50) Graduate School of Humanities & Sciences Building R102
Tue., July 23, Period 5-6 (13:20-14:50) Graduate School of Humanities & Sciences Building R102
Lecture Plan
  • Class 1- Introduction to the “omics” [style: lecture and discussion]
  • Class 2- Functional genomic databases and big data handling: Gene Ontology classification, KEGG, GEO… [style: lecture, computer practice and discussion]
  • Class 3- Proteomics techniques and applications [style: lecture and discussion]
  • Class 4- Genomics techniques and applications [style: lecture and discussion]
  • Class 5-6- Microarray experiment demonstration [style: wet lab]
  • Class 7- Microarray data visualization and retrieval [style: computer practice and discussion]
  • Class 8- Microarray data preprocessing I [style: computer practice and discussion]
  • Class 9- Microarray data preprocessing II [style: computer practice and discussion]
  • Class 10- Microarray data preprocessing III [style: computer practice and discussion]
  • Class 11- Big data analysis and mining I [style: computer practice and discussion]
  • Class 12- Big data analysis and mining II [style: computer practice and discussion]
  • Class 13- Big data analysis and mining III [style: computer practice and discussion]
  • Class 14- Big data analysis and mining IV [style: computer practice and discussion]
  • Class 15- Big data analysis conclusion [style:discussion]
Out-of-class Learning
Students may have to practice data analysis as a homework
Textbook/Reference
Various softwares and databases:
-free internet access: MeV, DAVID, GEO NCBI…..
-provided by the teacher during the class: Subioplatform, Pathway Studio, Genespring

Registration

Registration Period: Tue., April 9 through Mon., April 22
If you cannot register during above period, please contact Academic Affairs Office in Student Affairs Building.

Contact

Ochanomizu University Leading Graduate School Promotion Center
Tel: 03-5978-5775
E-mail: