Lectures & Seminars by Sangsoo Kim
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Here you will find the overview and related materials for the lectures and seminars given by Sangsoo Kim.  


Soongsil University courses (active)

  • General Biology: This course is for freshmen in Dept. of Bioinformatics and offered for two semesters.  I taught this course in 2005 and not any more.
  • Introduction to Bioinformatics: This is for sophomores and covers bioinformatics databases and tools.  In 2005, the course materials were initially based on EBI's 2can.  In 2006, I have entirely rewritten it by myself, starting with a examplery JMB paper and linking it various databases and tools. Once again in 2015, I have overhaul it by presenting the Nic Volker's case of medical diagnosis using Exome-sequencing, followed by the basic concepts of bioinformatics that are required to understand the scientific report. In the end it covers most of the original materials. The prezi presentation is found here.
  • Database Design: This course is for senior class and teaches relational modeling and SQL basics.  NCBI's Entrez Gene, HomoloGene, UniGene etc are downloaded and loaded into MySQL database by each students.  For that we use Windows version of MySQL.  The emphasis of the course is, however, not so much on database skills, but on what kind of biologically interesting queries we can make once these data are on my desktop or laptop.  Examples include: What is the average number of alternative splice forms per human gene?  Which human gene has the most alternative splice forms?  What Gene Ontology terms are associated with this gene?  How many UniGene clusters are unique to fruitfly and what are common properties of these genes?  I may teach this course in the fall semester of junior class.
  • Microarray Data Analysis: In the first half of this course, I teach the basic concepts of microarray techniques and data analysis methods such as hybridization, image scanning, stastical analysis.  In the latter half, each students are given around 10 GEO datasets and associated literature articles.  Each one is supposed to duplicate the analysis reported in the article. 
  • Bioinformatics & Functional Genomics: This is a graduate course and covers the textbook by Pevsner.  Each student is supposed to present a chapter of the textbook.  Active participation in the discussion by the students are graded.
  • Introduction to Genomics: For junior students, we cover Chapters 12-18 of Pevsner's.  It introduces the history of genomics and various genome projects in the domains of virus, microbes, and eukaryotes.  Why we study the genomes and what we have learned from the genome projects are the main focuses of the lecture.  This course was first offered in the Fall of 2006. As of 2014 fall semester, a new course is open as shown below.
  • 2014 Introduction to Genomics: Starting 2014 fall semester, this course covers principles and practices of microbial genome analysis. First, we review a microbial genome sequencing paper that was based on Sanger sequencing, pinpointing some basic concepts and principles behind the project. Using Sanger trace data downloaded from NCBI, we assemble the genome and compare it with the closely related reference strain. We also predict genes from the genome sequence and annotate their functions based on COGs. Consecutive clustering of a COG category may be a potential operon. Such features are sought. See the PREZI presentation of the course here. Lecture notes can be found here.
  • NGS Data Analysis: Starting 2014 fall semester, I have opened this course instead of "Functional Genomic" that used to deal with Microarray Data Analysis. This is an undergraduate senior course, which introduces the principles of Now-Generation Sequencing and its applications. We use a microbial NGS dataset download from SRA and map it to its reference genome, followed by visual inspection of the deleted fragments or mutated loci. In order to find insertions the reads are assembled and the identity of the inserted genes are sought. In the latter part of the lecture, we use a VCF file of a tumor-normal pair and annotate the variants, discussing their functional significance. The PREZI presentation of the course is here.
  • Bio-Database Development: We reviewed the various bio-databases listed in NAR Database Issue.  Each student studies a set of databases and discusses how they have been built and what the users can expect from using them.  After the reviews are done, students are grouped and each group is supposed to come up with one's own working database.  Each team is supposed to create a web site hosting the database and submit a paper describing it.
  • Web Programming: This is a graduate course started to be offered in Spring of 2007.  It is a natural extension of 'Database Design' and 'Bio-Database Development'.  Throught this course, one may acquire the ability to run one's own web site that is capable of form handling and database connectivity.
  • Current Topics in Genome Analysis 2006: This is a graduate course that follows the lecture series offered at NHGRI since 1995, organized by A. Baxevanis and E. Green.  In 2006, it started Sept. 5 and is offered every Tuesday for 13 weeks.  The course handouts and video archives (through videocast.nih.gov) are available.  We simply follow their syllabus 1 or 2 weeks behind.  Each student is expected to review one of the lectures and present in front of other students in Korean, of course.  Students are evaluated by the activity of their participation in the discussion.
  • Computational Genomics: This is a graduate course that covers script programming, linux, database, R, and Bioconductor. Prezi presentation can be found here.
  • BIT Special Topics: As a part of BIT education program in the graduate school, we have opened a series of courses since 2013. The first four semesters hosted lecture series by domestic lecturers and abroad Korean lecturers. Since 2015 spring semester, we try replicate key findings of one or two monumental papers in the area of omic data analysis. First we invite the original author (optionally via webinar) to hear the overall story and then we struggle to reanalyze the dataset.


Seoul National University courses (Temporary Lecturer)

  • Bioinformatics: This is offered in the spring semester of 2007 at the Graduate School of Biological Sciences.  It is intended for non-bioinformatics majors, especially for experimental biologists, so that they may understand the basics of bioinformatics and utilize the tools and databases wisely.  Also they may take advantage of the wealth of explosively growing omics data in planning their experiments.
  • Drug target discovery through bioinformatics: This is a 3 hr lecture offered in Apr. 19, 2007 at the pharmaceutical expert course.

Short training courses

  • NCBI Fieldguides: Many biology or biochemistry major graduate students are often hungry of bioinformatics learning. They tend to learn the minimum skills from their senior lab members. Systematic introduction to the depth and width of NCBI databases and tools is very much appreciated by these students. NCBI Training Materials  This course was offered at SNU (2006), Ajou Med. Sch. (2006, 2007).
  • Genome Browsers: Genome browsers serve as the means of data integration and data mining tools.  BioMart and UCSC's Table Browser are the examples of the latter.  Many biologists are ignorant of these wonderful tools.  How much more idea they could have gotten! UCSC Training
  • DNA Microarray Databases: This is a new addition to my training courses.  In conjunction to NCBI Fieldguides, I teach Entrez GEO Profiles & Datasets for mining DNA microarray data.  Oncomine is also covered.
  • KOGO Statistical Genomics Workshop - Genome Analaysis Tools: Lecture Notes for 2015 are found here. YouTube video of InsilicoDB & Gene-E by DW Kim.



  • Introduction to bioinformatics: This talk basic features of bioinformatics and several examples of the application in the area of drug target identification and discovery, gene expression analysis, comparative genomics, microbial genomics etc.  First presented at the A-IMBN Delivery Lecture, Mar. 2007, Kathmandu, Nepal.
  • Cancer Gene Expression Network: This is a work done by Dr. Jung Kyoon Choi, almost entirely.  Actually, it constitutes bulk of his Ph.D. thesis, which I had priviledge to supervise.  I simply present it with some of my own interpretation and application.
  • Omics Data Integration and Mining: Various omics data are proliferating in public databases.  By integrating these data one might be able to discover novel things single data could not offer.  This is in primitive stage but has been presented several times: Korean Chemical Society Annual Conference, Oct. 2006, Kwnagju, The 6th Sino-Japan-Korea Bioinformaitcs Training Course, Mar. 2007, Shanghai.