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  • 1
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    Singapore : Springer
    Call number: QH324:49
    Keywords: Bioinformatics ; Medicine ; Statistics ; Biomedicine general ; Statistics for Life Sciences, Medicine, Health Sciences
    Description / Table of Contents: 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
    Abstract: 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. This 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
    Pages: xvi, 367 p. : ill.
    ISBN: 9789811319419
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  • 2
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    Singapore : Springer
    Keywords: Bioinformatics ; Medicine ; Statistics ; Bioinformatics ; Biomedicine general ; Statistics for Life Sciences, Medicine, Health Sciences ; Springer eBooks
    Description / Table of Contents: 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
    Abstract: 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. This 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
    Pages: XVI, 367 p. 645 illus., 236 illus. in color. : online resource.
    ISBN: 9789811319426
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  • 3
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    Singapur : Springer
    Pages: xvi, 367 p.
    ISBN: 9789811319419
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  • 4
    ISSN: 1546-1696
    Source: Nature Archives 1869 - 2009
    Topics: Biology , Process Engineering, Biotechnology, Nutrition Technology
    Notes: [Auszug] Over the last decade, gene expression microarrays have had a profound impact on biomedical research. The diversity of platforms and analytical methods available to researchers have made the comparison of data from multiple platforms challenging. In this study, we describe a framework for ...
    Type of Medium: Electronic Resource
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  • 5
    ISSN: 1540-8191
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Medicine
    Notes: Abstract  We report a successful stent implantation for a coarctation lesion of the lower thoracic aorta in a 44-year-old male. This patient had suffered from claudication of both legs for 30 years. An aortogram revealed a coarctation of the distal thoracic aorta at T11 level with 60 mmHg peak systolic pressure gradient of across the lesion. A balloon angioplasty followed by an 18 mm × 40 mm sized stent implantation was performed successfully. The peak systolic gradient across the coarctation decreased from 60 to 15 mmHg. The patient's symptom was relieved immediately after stenting. No significant or adverse events were observed during 7 months clinical follow-up. Follow-up aortogram after 7 months revealed no restenosis with an improved pressure gradient. Adults with congenital coarctation of the descending thoracic aorta can be successfully treated by stent implantation.
    Type of Medium: Electronic Resource
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  • 6
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