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Genome Data Analysis

Ju Han Kim (Autor)

Buch | Softcover

367 Seiten

2019 | 1st ed. 2019
Springer Verlag, Singapore
978-981-13-1941-9 (ISBN)

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This textbook describes recent advances in genomics and bioinformatics and provides numerous examples of genome data analysis that illustrate its relevance to real world problems and will improve the reader’s bioinformatics skills. Basic data preprocessing with normalization and filtering, primary pattern analysis, and machine learning algorithms using R and Python are demonstrated for gene-expression microarrays, genotyping microarrays, next-generation sequencing data, epigenomic data, and biological network and semantic analyses. In addition, detailed attention is devoted to integrative genomic data analysis, including multivariate data projection, gene-metabolic pathway mapping, automated biomolecular annotation, text mining of factual and literature databases, and integrated management of biomolecular databases.

The textbook is primarily intended for life scientists, medical scientists, statisticians, data processing researchers, engineers, and other beginners in bioinformatics who are experiencing difficulty in approaching the field. However, it will also serve as a simple guideline for experts unfamiliar with the new, developing subfield of genomic analysis within bioinformatics.

Professor. Ju Han Kim, Division of Biomedical Informatics, Seoul National University College of Medicine, Seoul , South Korea.

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.

Erscheinungsdatum	30.01.2019
Reihe/Serie	Learning Materials in Biosciences
Zusatzinfo	236 Illustrations, color; 409 Illustrations, black and white; XVI, 367 p. 645 illus., 236 illus. in color.
Verlagsort	Singapore
Sprache	englisch
Original-Titel	Genome Data Analysis
Maße	168 x 240 mm
Themenwelt	Informatik ► Weitere Themen ► Bioinformatik
	Mathematik / Informatik ► Mathematik
	Medizin / Pharmazie
	Naturwissenschaften ► Biologie ► Genetik / Molekularbiologie
ISBN-10	981-13-1941-3 / 9811319413
ISBN-13	978-981-13-1941-9 / 9789811319419
Zustand	Neuware