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UNIST Bioinformatics course syllabus

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Syllabus 2019
Course Information  Bioinformatics

Instructor Information Dugwoo Nam & Jong Bhak

Course Code

BIO43101
Instructor

Course Title

Bioinformatics
Office

 Room 301-8, Bldg 110

Year/Semester
2019/1st
Telephone
010 4644 6754 (JB)
School
SLS
E-mail

Course Classification

TE-BIO/TE-BME/TE-BMS

Office Hours

Any time

Classroom/Class Time

FRI 13:00-15:30 (NSB S205)

Grading Type

Letter grade
Course Objectives & Description

Bioinformatics course contains introductory information in how to process biological data using computers.

During the class, students will learn the concepts by short lectures and hands-on experiences. So, please bring a laptop computer to the class from the second week.

 

The second part of the course taught by Jong Bhak will focus on:

1)     What Bioinformatics is

2)     How to independently read research papers

3)     How to critically analyze research papers and topics

4)     How to choose a research topic in bioinformatics and design an experiment and perform research

5)     How to write research report(paper) to make the results known to the public.

6)     The course will be done through active action-oriented learning method(AAO)

7)     Students are required to motivate themselves and bring their research topics after reading research papers.

Grading
Science paper writing on bioinformatics topics.
 
 
 
 
 
 
Text
Category

Book and PPT files, on-line links

 
Title
Bioinformatics
 
Author
Jong Bhak
 
ISBN
 
 
Remarks
 
 

Course Reserves Designation

 
 
References
Category
Book, on-line links
 
 
Title
Bioinformatics
 
 
Author
Jong Bhak
 
 
ISBN
 
 
 
Remarks
 
 
 

Course Reserves Designation

 
 
 
 
Weekly Schedule

 

Week
Contents
01

Introduction to Bioinformatics, Introduction to Microarray, RNA-seq

02

Microarray & gene data analysis I: Normalization, Identification of DEGs (R language), Gene list analysis with DAVID and STRING(web)

03

Microarray & gene data analysis II: Clustering, (R, cluster, treeview), Dimension Reduction (PCA), survival analysis

04
Test 1
05

Gene-set and pathway analysis with GSEA, Introduction to classification analysis (SVM)

06
RNA-seq, ChIP-seq data analysis
07

Introduction to NCBI databases: data and literature search

08
Test 2
09
10
11
12
13
14
15
 

UNIST Bioinformatics course  Bioinformatics.ws