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Autorenporträt
Professor. Ju Han Kim, Division of Biomedical Informatics, Seoul National University College of Medicine, Seoul , South Korea.
Inhaltsangabe
Part 1. BIOINFORMATICS FOR LIFE AND PERSONAL GENOME INTERPRETATION.- Chapter 1. Bioinformatics For Life.- Chapter 2. Next Generation Sequencing and Personal Genome Data Analysis.- Chapter 3. Personal Genome Data Analysis.- Chapter 4. Personal Genome Interpretation and Disease Risk Prediction.- Part 2. ADVANCED MICROARRAY DATA ANALYSIS.- Chapter 5. Advanced Microarray Data Analysis.- Chapter 6. Gene Expression Data Analysis.- Chapter 7. Gene Ontology and Biological Pathway-based Analysis.- Chapter 8. Gene-set Approaches and Prognostic Subgroup Prediction.- Chapter 9. MicroRNA Data Analysis.- Part 3. NETWORK BIOLOGY, SEQUENCE, PATHWAY AND ONTOLOGY INFORMATICS.- Chapter 10. Network Biology, Sequence, Pathway and Ontology Informatics.- Chapter 11. Motif and Regulatory Sequence Analysis.- Chapter 12. Molecular Pathways and Gene Ontology.- Chapter 13. Biological Network Analysis.- Part 4. SNPS, GWAS AND CNVS, INFORMATICS FOR GENOME VARIANTS.- Chapter 14. SNPs, GWAS, CNVs: Informatics for Human Genome Variations.- Chapter 15. SNP Data Analysis.- Chapter 16. GWAS Data Analysis.- Chapter 17. CNV Data Analysis.- Part 5. METAGENOME AND EPIGENOME, BASIC DATA ANALYSIS.- Chapter 18. Metagenome and Epigenome Data Analysis.- Chapter 19. Metagenome Data Analysis.- Chapter 20. Epigenome Databases and Tools.- Chapter 21. Epigenome Data Analysis.- Appendix A. BASIC PRACTICE USING R FOR DATA ANALYSIS.- Appendix B. APPLICATION PROGRAM FOR GENOME DATA ANALYSIS INSTALL GUIDE.
Part 1. BIOINFORMATICS FOR LIFE AND PERSONAL GENOME INTERPRETATION.- Chapter 1. Bioinformatics For Life.- Chapter 2. Next Generation Sequencing and Personal Genome Data Analysis.- Chapter 3. Personal Genome Data Analysis.- Chapter 4. Personal Genome Interpretation and Disease Risk Prediction.- Part 2. ADVANCED MICROARRAY DATA ANALYSIS.- Chapter 5. Advanced Microarray Data Analysis.- Chapter 6. Gene Expression Data Analysis.- Chapter 7. Gene Ontology and Biological Pathway-based Analysis.- Chapter 8. Gene-set Approaches and Prognostic Subgroup Prediction.- Chapter 9. MicroRNA Data Analysis.- Part 3. NETWORK BIOLOGY, SEQUENCE, PATHWAY AND ONTOLOGY INFORMATICS.- Chapter 10. Network Biology, Sequence, Pathway and Ontology Informatics.- Chapter 11. Motif and Regulatory Sequence Analysis.- Chapter 12. Molecular Pathways and Gene Ontology.- Chapter 13. Biological Network Analysis.- Part 4. SNPS, GWAS AND CNVS, INFORMATICS FOR GENOME VARIANTS.- Chapter 14. SNPs, GWAS, CNVs: Informatics for Human Genome Variations.- Chapter 15. SNP Data Analysis.- Chapter 16. GWAS Data Analysis.- Chapter 17. CNV Data Analysis.- Part 5. METAGENOME AND EPIGENOME, BASIC DATA ANALYSIS.- Chapter 18. Metagenome and Epigenome Data Analysis.- Chapter 19. Metagenome Data Analysis.- Chapter 20. Epigenome Databases and Tools.- Chapter 21. Epigenome Data Analysis.- Appendix A. BASIC PRACTICE USING R FOR DATA ANALYSIS.- Appendix B. APPLICATION PROGRAM FOR GENOME DATA ANALYSIS INSTALL GUIDE.
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