Course title
情報処理・生物統計学   [Computer science and Biostatistics]
Course category   Requirement   Credit 2 
Department   Year 1  Semester 1st 
Course type 1st  Course code 01an1002
Instructor(s)
仲里 猛留   [NAKAZATO Takeru]
Facility affiliation Graduate School of Agriculture Office 3-211  Email address

Course description
This course provides a way to handle and publish own data (information search, retrieve, analysis, visualization, and publishing). Additionally, hot topics of information science and biological statistics are also covered.
Expected Learning
- To develop the skill of searching and getting useful resources
- To develop the skill of analyzing and mining their own data
- To develop the skill of visualize and publishing their own data

Corresponding criteria in the Diploma Policy:
See the Curriculum maps.
(URL: https://www.tuat.ac.jp/campuslife_career/campuslife/policy/ )
Course schedule
1. Guidance and set-up own account
2. Introduction
3. Computers: Hardware and software, Operating system
4. Internets and search information: Useful resources, search engines
5.-7. Treating and publishing information:
Word: Documents
PowerPoint: Slides, effective presentations
(Web page: HTML)
8.-9. Data analysis with small data (Excel): string and numerical value, functions, graphs
10.-12. Data analysis with big data (R language): Setting up, data treatment, Visualization, QTL analysis, gene expression data analysis
13.-15. Hot topics of computer science: Bioinformatics, and data mining

Note: Curriculums may be changed to reflect students’ literacy levels and requests.
Prerequisites
Nothing special required.

Required Text(s) and Materials
No textbooks specified.
Materials will be distributed in a class.
References
No reference specified. TBA in a class.
Assessment/Grading
Reports
Message from instructor(s)
It is essential for students and researchers to get and analysis information in big data era. Also, in agriculture areas, information treatment and biological statistics are powerful tools to utilize genomics data. These seem to be difficult to approach and forgettable, so I’ll try to give lectures to make them seem closer by using real biological data in research field.
Course keywords
Internet, Search Engine, Bioinformatics, Big data, Data mining, AI, R language, QTL analysis, Gene Expression Analysis
Office hours
I come to office in TUAT only on Tuesday because I am a part-time lecturer, but please don’t hesitate to contact me by e-mail anytime. (My e-mail address will be announced in the class.)
Remarks 1
I’ll prepare English materials if you want. Please inform me.
Remarks 2
Related URL
Lecture Language
Japanese
Language Subject
Last update
3/28/2019 1:25:19 PM