課程資訊
課程名稱
生物資訊學導論
Introduction to Bioinformatics 
開課學期
112-1 
授課對象
生物資源暨農學院  農藝學系  
授課教師
吳泓熹 
課號
Agron5050 
課程識別碼
621EU6390 
班次
 
學分
3.0 
全/半年
半年 
必/選修
選修 
上課時間
星期五6,7,8(13:20~16:20) 
上課地點
 
備註
本課程以英語授課。教室:智農中心電腦教室(鄭江樓南棟506室)
總人數上限:45人 
 
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課程概述

Please refer to the English version for the latest information: Syllabus

Bioinformatics is a rapidly evolving field, and it is actively used in multiple areas of research. This interdisciplinary field integrates biology, statistics, and computer science together to analyse and interpret biological data. The course covers the most important and fundamental concepts, methods, and tools used in bioinformatics. Students will be able to use these bioinformatics tools to solve the problems for their own research.

Modules in this course

  1. Basic bioinformatics skills: basic statistics and programming.
  2. Molecular evolution: Multiple sequence alignment and phylogenetic analysis.
  3. Next generation sequencing (NGS) analysis: Genome assembly, genome annotation, and metagenomics.
  4. Other topics in bioinformatics
Course selection: This is a Type 3 course, hence there is no permission number.
 

DirectPoll

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課程目標
  • Understand that bioinformatics is an interdisciplinary field and communicate with researchers from different backgrounds.
  • Evaluate and identify appropriate bioinformatics software for your own research.
  • Develop problem-solving skills in bioinformatics. Integrate a range of bioinformatics techniques to extract information from biological data.
  • Work collaboratively in groups to solve challenges in the interdisciplinary fields.
 
課程要求
  • This course will be taught in English. All materials are available in English only.
  • Cheating and plagiarism in assignments, exams or any other assessments are serious academic misconduct. All instances will be handled according to the university policy.
  • There are no strict prerequisites for this course. However, it is recommended that students have a basic understanding of molecular biology, genetics, and statistics with basic programming in R or any other language.
 
預期每週課後學習時數
2-5 hours (depending on the background knowledge). 
Office Hours
 
指定閱讀
 
參考書目
 
評量方式
(僅供參考)
   
課程進度
週次
日期
單元主題
第0週
  Please refer to the English version for the latest information: Syllabus