Course Information
Course title
 Introduction to Bioinformatics 
Semester
 112-1 
Designated for
 COLLEGE OF BIO-RESOURCES AND AGUICULTURE  DEPARTMENT OF AGRONOMY  
Instructor
 STEVEN HUNG-HSI WU 
Curriculum Number
 Agron5050 
Curriculum Identity Number
 621EU6390 
Class
  
Credits
 3.0 
Full/Half
Yr.
 Half 
Required/
Elective
 Elective 
Time
 Friday 6,7,8(13:20~16:20) 
Remarks
 The upper limit of the number of students: 45. 
  
Course introduction video
 
Table of Core Capabilities and Curriculum Planning
 Table of Core Capabilities and Curriculum Planning
Course Syllabus
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Course Description

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

Direct_poll
 

Course Objective
  • 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.
 
Course Requirement
  • 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.
 
Student Workload (expected study time outside of class per week)
 2-5 hours (depending on the background knowledge). 
Office Hours
  
Designated reading
  
References
  
Grading
    
Progress
Week
Date
Topic
Week 1
 Sep/08  Overview of bioinformatics 
Week 2
 Sep/15  M1 - Basic bioinformatics skills: Statistics and R programming 
Week 3
 Sep/22  M1 - Basic bioinformatics skills: Command line 
Week 4
 Sep/29  Holiday 
Week 5
 Oct/06  M1- Basic bioinformatics skills: Regular expression 
Week 6
 Oct/13  M2 - Molecular evolution: Sequence alignment 
Week 7
 Oct/20  M2 - Molecular evolution: Sequence alignment 
Week 8
 Oct/27  M2 - Molecular evolution: Phylogenetic analysis 
Week 9
 Nov/03  M2 - Molecular evolution: Phylogenetic analysis 
Week 10
 Nov/10  M3 - Next generation sequencing (NGS) analysis: Modern sequencing methods 
Week 11
 Nov/17  M3 - NGS analysis: Genome assembly 
Week 12
 Nov/24  M3 - NGS analysis: Genome annotation 
Week 13
 Dec/01  M3 - NGS analysis: SNP calling 
Week 14
 Dec/08  Other topics in bioinformatics - Part 1 
Week 15
 Dec/15  Other topics in bioinformatics - Part 2 
Week 16
 Dec/22  Group project - Presentation