| 교육일 | 과목 | 시간 | 세부 교과목 | 교육방법 | 교육 장소
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	| 2월 16일 오전, 오후
 | Advanced Python Programming - 1 -
 | 3 | Advanced Python Programming 1 - Regular Expression
		(Managin File, Greedy vs Non-Greedy Match, Main Methods)
 - Python Visualization
		(Matplotlib, Seaborn, Bokeh, Plotly)
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		| Advanced Python Programming - 2 -
 | 3 | Advanced Python Programming 2 - Python Machine Learning(TensorFlow, Keras, Theano)
 - Medical Informatics Practice 1(MESH, ICD)
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		| Advanced Python Programming - 3 -
 | 3 | Advanced Python Programming 3 - Medical Informatics Practice 2
 - SEER(The Cancer Surveillance, Epidermiology and End Results Program)
 - CDC(Centers for Disease Control And Prevention) Mortality Files
 
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			| 2월 17일 오전, 오후
 | Advanced R Programming - 1 -
 | 3 | Data Processing - Data Structure and File I/O
 - Data Management
 
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			| Advanced R Programming - 2 -
 | 3 | Statistical Test and Visualization - Regression Methods
 - Advanced Visualization of Statistical Test with ggpubr
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			| Advanced R Programming - 3 -
 | 3 | Machine learning - Classification
 - Decision tree and CART
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				| 2월 20일 오전, 오후
 | Advanced NGS Data Analysis - 1 -
 | 3 | Epigenome Data Analysis - Epigenetic Mechanisms
 - DNA Methylation Analysis
 - Histone Modification Analysis
 - Discovery of Epigenetic Biomarkers
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				| Advanced NGS Data Analysis - 2 -
 | 3 | Pathway and Network Analysis - Characteristics of Biological Network
			- Cancer Gene Network Construction and Clustering
			- Identification of Aberrant Pathway in Cancers
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				| Advanced NGS Data Analysis - 3 -
 | 3 | Multiomics and Precision Medicine - Genome, Transcriptome, and Proteom Integration
 - miRNA and Exosome Analysis
 - Application for Precision Medicine
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	| 2월 21일 오전, 오후
 | Methodology and Application for Next Generation Sequencing - 1 -
 | 3 | NGS Platforms and Applications - Current NGS Platforms
 - NGS Data Formats
 - NGS Data Analysis Technologies
 - NGS Applications
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	| Methodology and Application for Next Generation Sequencing - 2 -
 | 3 | NGS Data Analysis - Sequence Alignment Algorithms
 - Whole Genome and Exome Data Analysis
 - Variation Detection and Reference Genome
 
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	| Methodology and Application for Next Generation Sequencing - 3 -
 | 3 | Informatics for Cancer immunotherapy - Genomics in cancer immunotherapy
 - Tumor mutation burden(TMD) and neoantigen
 - Gene expression and immune cells
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	| 2월 22일 오전, 오후
 | Advanced Python Programming - 1 -
 | 3 | Biomedical data analysis using Python - Bioinformatics Practice
 - Python Machine Learning
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	| Advanced R Programming - 2 -
 | 3 | Expression and variants association using R - Statistical test for association (Chi-square, Fihser’s exact test and Odds ratio)
 - eQTL analysis
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	| Advanced R Programming - 3 -
 | 3 | Cancer analysis using R - Cancer somatic mutation analysis
 - Pathway analysis
 - Network visualization
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	| 2월 23일 오전, 오후
 | Cancer Genome and Multi-omic Bioinformatics - 1 -
 | 3 | The Cancer Genome Atlas (TCGA) Project and Cancer Genome Research - TCGA Introduction
 - TCGA Data and Scientific Findings
 - Impact of TCGA and Future
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	| Cancer Genome and Multi-omic Bioinformatics - 2 -
 | 3 | Advanced Cancer Genome Data Analysis - Different types of variation in cancer
 - Matched normal and tumor pair data analysis
 - Cancer clonality and sequencing depth
 - Visualizing cancer genomics data
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	| Cancer Genome and Multi-omic Bioinformatics - 3 -
 | 3 | Exome Sequencing Analysis - Exome Sequencing Data
 - Study Design and Workflow
 - Exome Sequencing of Familial Disease
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	| 2월 24일 오전, 오후
 | RNA-Seq and Transcriptome Data Analysis - 1 -
 | 3 | RNA-Seq Data Analysis - Read Alignment Methods
 - Expression Quantification Strategy
 - Differentially Expressed Genes Identification
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	| RNA-Seq and Transcriptome Data Analysis - 2 -
 | 3 | Sequence-level Transcriptome Analysis - Alternative Splicing Events
 - Alternative Polyadenylation Analysis
 - RNA Editing Analysis
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	| RNA-Seq and Transcriptome Data Analysis - 3 -
 | 3 | Non-coding RNA Analysis - miRNA-seq Expression Profile Analysis
 - Novel Transcript Discovery
 - Non-coding RNA Characterization
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