No |
ÀϽà |
°ÀÇ ³»¿ë |
´ã´ç°»ç |
1 |
2018³â 11¿ù 3ÀÏ |
Starting with R
- Introduction to R
- R installation, workspace, R package installation
- Basic R functions
|
|
2 |
11¿ù 10ÀÏ |
Data manipulation with R
- Data type
- Importing and exporting data
- Data management
- Missing values |
|
3 |
11¿ù 17ÀÏ |
Review of Basic Statistics
- Probability distributions
- Summary statistics
- Hypothesis testing, confidence intervals, bootstrap
- Exploratory data analysis using R: basic graphics, correlation coefficients, contingency table |
|
4 |
11¿ù 24ÀÏ |
[1¹Ú 2ÀÏ ÇÕ¼÷±³À°]
Statistical Analysis I: Analysis of means
- Distributions
- Parametric tests
- Non-Parametric tests |
|
5 |
12¿ù 1ÀÏ |
Statistical Analysis II: Analysis of proportions and relations
- Correlation
- Regression
- ANOVA |
|
6 |
12¿ù 8ÀÏ |
Survival Analysis
- Censoring, Survival data, Survival function
- Cox proportional-hazards regression
- Kaplan-Meier survival curve
- Statistical comparison of survival curves: log-rank, Wilcoxon test |
|
7 |
12¿ù 15ÀÏ |
Machine learning algorithms for Biomedical Informatics
- Supervised analysis
- Unsupervised analysis |
|
8 |
12¿ù 22ÀÏ |
Classification using R
- Feature selection - K-Nearest Neighbor
- Support Vector Machine
- Linear Discriminant Analysis |
|
9 |
2019³â 1¿ù 5ÀÏ |
Evaluation and Validation
- Over-fitting
- Cross validation: train/validation/test set split
- Empirical p-value, permutation test - Multiple testing correction |
|
10 |
1¿ù 12ÀÏ |
Advanced R graphics
- Line Plots, Bar charts, Histograms, Scatter plot
- Labels and legends
- Lattice package |
|
11 |
1¿ù 19ÀÏ |
Microarray Data Analysis I
- Bioconductor packages
- Introduction to Microarray Data
- Normalization methods |
|
12 |
1¿ù 26ÀÏ |
Microarray Data Analysis II
- Identifying DEG: t-test, SAM
- Volcano plot - FDR
- Probe annotation |
|
13 |
2¿ù 16ÀÏ |
Gene ontology & Pathway analysis
- Gene clustering
- GO and Pathway enrichment analysis
- R packages for semantic similarity |
|
14 |
2¿ù 23ÀÏ |
Case study: association of BRCA1 and BRCA2 mutations with survival in ovarian cancer (JAMA 2011) - DEG extraction from RNA-seq data - Clustering (K-means, hierarchical) - Correlation analysis between methylation and expression data - Survival analysis |
|
No |
ÀϽà |
°ÀÇ ³»¿ë |
´ã´ç°»ç |
1 |
2018³â 11¿ù 3ÀÏ |
°Ç°Á¤º¸½Ã½ºÅÛ EMR/EHR/PHR |
|
2 |
11¿ù 10ÀÏ |
¸í»ç ÃÊû Ư° - Network Biology |
À̱⿵ |
3 |
11¿ù 17ÀÏ |
µ¥ÀÌÅÍ¿þ¾îÇϿ콺 ±¸Ãà°ú µ¥ÀÌÅ͸¶ÀÌ´× |
¹Ú·¡¿õ |
4 |
11¿ù 24ÀÏ |
[1¹Ú 2ÀÏ ÇÕ¼÷±³À°] |
|
4 |
12¿ù 1ÀÏ |
¸í»ç ÃÊû Ư° - Datamining and its application in Biomedical Informatics |
½ÅÇöÁ¤ |
5 |
12¿ù 8ÀÏ |
ÀÇ·áÁ¤º¸¿Í ȯÀÚÁÖµµÇü °Ç° ½Ã½ºÅÛ |
|
6 |
12¿ù 15ÀÏ |
¸í»ç ÃÊû Ư° - Lessons from 1000 Genome Project |
|
7 |
12¿ù 22ÀÏ |
ÀÇ·áÁ¤º¸¿Í °³ÀÎÁ¤º¸º¸È£ |
|
8 |
2019³â 1¿ù 5ÀÏ |
¸í»ç ÃÊû Ư° - Markov Chain and Hidden Markov Model |
¼Õ°æ¾Æ |
9 |
1¿ù 12ÀÏ |
¸í»ç ÃÊû Ư° - SNOMED CT |
¹ÚÇö¾Ö |
10 |
1¿ù 19ÀÏ |
¸í»ç ÃÊû Ư° - Gamification and mHealth |
±èÁ¤Àº |
12 |
1¿ù 26ÀÏ |
¸í»ç ÃÊû Ư° - Àӻ󿬱¸/ÀÓ»ó½ÃÇèÁ¤º¸½Ã½ºÅÛ |
ÃÖÀοµ |
13 |
2¿ù 16ÀÏ |
¸í»ç ÃÊû Ư° - Drug Repositioning |
ÀοëÈ£ |
14 |
2¿ù 23ÀÏ |
¸í»ç ÃÊû Ư° - Semantic Web |
¼Õ¿µ¼ö |
No |
ÀϽà |
°ÀÇ ³»¿ë |
´ã´ç°»ç |
1 |
2018³â 11¿ù 3ÀÏ |
TCGA data introduction |
|
2 |
11¿ù 10ÀÏ |
Advanced Microarray Data Analysis |
|
3 |
11¿ù 17ÀÏ |
Next Generation Sequencing & Personal Genome Data Analysis |
|
4 |
11¿ù 24ÀÏ |
[1¹Ú 2ÀÏ ÇÕ¼÷±³À°]NGS Platforms and Application |
|
5 |
12¿ù 1ÀÏ |
Personal Genome Interpretation |
|
6 |
12¿ù 8ÀÏ |
RNA-Seq Expression Profile Analysis |
|
7 |
12¿ù 15ÀÏ |
Sequence-level Transcriptome Analysis |
|
8 |
12¿ù 22ÀÏ |
Non-Coding RNAs in RNA-Seq Data |
|
9 |
2019³â 1¿ù 5ÀÏ |
Identifing Genomic rearrangement, Gene fusion analysis from RNA sequence |
|
10 |
1¿ù 12ÀÏ |
Exome Sequencing and Cancer Genome Bioinformatics |
|
11 |
1¿ù 19ÀÏ |
Copy Number and Genomic Rearrangement
|
|
12 |
1¿ù 26ÀÏ |
GWAS and Post-GWAS, eQTL data Analysis |
|
13 |
2¿ù 16ÀÏ |
PheWAS, EWAS and Electronic Medical Records Data Analysis |
|
14 |
2¿ù 23ÀÏ |
±â¸»°í»ç |
|