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수강신청
아주 쉬운 유전체 분석 - 이론편 (2019)
과정소개
강의목차
| 차시 | 강의명 |
|---|---|
| 1차시 | 유전체 연구 소개 (아주대 우현구)- 1. introduction |
| 2차시 | 유전체 연구 소개 (아주대 우현구)- History of Human Genome |
| 3차시 | 유전체 연구 소개 (아주대 우현구)- Functional Genomics |
| 4차시 | 유전체 연구 소개 (아주대 우현구)- Precision Medicine |
| 5차시 | Introduction to Next generation sequencing (NGS) (아주대 우현구) |
| 6차시 | Next generation sequencing (아주대 우현구)- 2. RNA-SEQ |
| 7차시 | Single Cell RNA sequencing in health and disease (삼성유전체연구소 이혜옥)- 1. Introduction to single Cell genomics |
| 8차시 | Single Cell RNA sequencing in health and disease (삼성유전체연구소 이혜옥)- 2. Application field for single cell DNA analysis |
| 9차시 | Single Cell RNA sequencing in health and disease (삼성유전체연구소 이혜옥)- 3. Data processing |
| 10차시 | Single Cell RNA sequencing in health and disease (삼성유전체연구소 이혜옥)- 4. Technology development |
| 11차시 | Epigenomics (포항공대 노태영)- 1. 환경과 유전 |
| 12차시 | Epigenomics (포항공대 노태영)- 2. Epigenomics |
| 13차시 | Epigenomics (포항공대 노태영)- 3. Epigenomic Analysis |
| 14차시 | Epigenomics (포항공대 노태영)- 4. Stem cell epigenomics |
| 15차시 | Dissecting cellular heterogeneity using single-cell RNA sequencing (DGIST 김종경)- 1. History of scRNA-seq |
| 16차시 | Dissecting cellular heterogeneity using single-cell RNA sequencing (DGIST 김종경)- 2. Experimental methods of scRNA-seq |
| 17차시 | Dissecting cellular heterogeneity using single-cell RNA sequencing (DGIST 김종경)- 3. Challenges in scRNA-seq |
| 18차시 | Dissecting cellular heterogeneity using single-cell RNA sequencing (DGIST 김종경)- 4. Workflow and practical application |
| 19차시 | Applications of Deep Sequencing (아주대 박대찬)- 1. Introduction |
| 20차시 | Applications of Deep Sequencing (아주대 박대찬)- 2. Self growing DNA(origin of life) |
| 21차시 | Applications of Deep Sequencing (아주대 박대찬)- 3. 4 reads generation(Discovery of therapeutic antibodies) |
| 22차시 | Cancer Genome, intratumoral heterogeneity and pharmacogenomics (아주대 이진구)- 1. Overview of cancer genome |
| 23차시 | Cancer Genome, intratumoral heterogeneity and pharmacogenomics (아주대 이진구)- 2. Intratumoral heterogeneity |
| 24차시 | Cancer Genome, intratumoral heterogeneity and pharmacogenomics (아주대 이진구)- 3. Pharmacogenomics |
| 25차시 | Genome, Genomic Variation and Precision Medicinencer Genome Data Analysis (연세대 김상우)- 1. Genes to Genomic data |
| 26차시 | Genome, Genomic Variation and Precision Medicinencer Genome Data Analysis (연세대 김상우)- 2. Genomic variation and Precision medicine |
| 27차시 | Genome, Genomic Variation and Precision Medicinencer Genome Data Analysis (연세대 김상우)- 3. Determination of Variants |
| 28차시 | Genome, Genomic Variation and Precision Medicinencer Genome Data Analysis (연세대 김상우)- 4. Analysis of genetic variations and application |
| 29차시 | Gene set analysis and Machine learning (아주대 우현구)- 1. Differential expression analysis |
| 30차시 | Gene set analysis and Machine learning (아주대 우현구)- 2. Gene set analysis |
| 31차시 | Gene set analysis and Machine learning (아주대 우현구)- 3. Machine learning and Classification |
| 32차시 | 후성유전체학 |