Fundamentals of Advanced Omics Technologies: From Genes to Metabolites (Volume 63) (Comprehensive Analytical Chemistry, Volume 63)

__Fundamentals of Advanced Omics Technologies: From Genes to Metabolites__ covers the fundamental aspects of the new instrumental and methodological developments in omics technologies, including those related to genomics, transcriptomics, epigenetics, proteomics and metabolomics, as well as other omics approaches such as glycomics, peptidomics and foodomics. The principal applications are presented in the following complementary volume. The chapters discuss in detail omics technologies, DNA microarray analysis, next-generation sequencing technologies, genome-wide analysis of methylation and histone modifications, emerging nanotechniques in proteomics, imaging mass spectrometry in proteomics, recent quantitative proteomics approaches, and advances in high-resolution NMR-based metabolomics, as well as MS-based non-targeted metabolomics and metabolome analysis by CE-MS, global glycomics analyses, foodomics, and high resolution analytical tools for quantitative peptidomics. Key aspects related to chemometrics, bioinformatics, data treatment, data integration and systems biology, deep-sequencing data analysis, statistical approaches for the analysis of microarray data, the integration of transcriptome and metabolome data and computational approaches for visualization and integration of omics data are also covered. * Covers the latest advances in instrumentation, experimental design, sample preparation, and data analysis * Provides thorough explanations and descriptions of specific omics technologies * Describes advanced tools and methodologies for data pretreatment, storage, curation and analysis, as well as data integration Content: Series Page Page ii Copyright Page iv Contributors to Volume 63 Pages xiii-xvi Series Editor's Preface Pages xvii-xviii D. Barceló Preface Pages xix-xx Carolina Simó, Alejandro Cifuentes, Virginia García-Cañas Chapter 1 - DNA Microarrays Technology: Overview and Current Status Pages 1-23 Alex Sánchez-Pla Chapter 2 - Challenges and Future Trends in DNA Microarray Analysis Pages 25-46 Abootaleb Sedighi, Paul C.H. Li Chapter 3 - Next-Generation Sequencing: New Tools to Solve Old Challenges Pages 47-79 I. Gobernado, A. Sanchez-Herranz, A. Jimenez-Escrig Chapter 4 - Omics Tools for the Genome-Wide Analysis of Methylation and Histone Modifications Pages 81-110 Josep C. Jiménez-Chillarón, Rubén Díaz, Marta Ramón-Krauel Chapter 5 - An Overview of Quantitative Proteomic Approaches Pages 111-135 Adam J. McShane, Vahid Farrokhi, Reza Nemati, Song Li, Xudong Yao Chapter 6 - Emerging Nanotechniques in Proteomics Pages 137-157 Noelia Dasilva, Maria Gonzalez-Gonzalez, Paula Diez, Ricardo Jara-Acevedo, Lucia Lourido, J.M. Sayagues, Alberto Orfao, Manuel Fuentes Chapter 7 - Mass Spectrometry Imaging in Proteomics and Metabolomics Pages 159-185 Benjamin Balluff, Ricardo J. Carreira, Liam A. McDonnell Chapter 8 - Advances in NMR-Based Metabolomics Pages 187-211 G.A. Nagana Gowda, Daniel Raftery Chapter 9 - The Role of Mass Spectrometry in Nontargeted Metabolomics Pages 213-233 Helen G. Gika, Ian D. Wilson, Georgios A. Theodoridis Chapter 10 - Direct Mass Spectrometry-Based Approaches in Metabolomics Pages 235-253 Clara Ibáñez, Virginia García-Cañas, Alberto Valdés, Carolina Simó Chapter 11 - Functional Glycomics Analysis: Challenges and Methodologies Pages 255-280 Nathan W. Stebbins, Ram Sasisekharan Chapter 12 - Applications of Glycan Microarrays to Functional Glycomics Pages 281-303 Ying Yu, Xuezheng Song, David F. Smith, Richard D. Cummings Chapter 13 - High-Resolution Analytical Tools for Quantitative Peptidomics Pages 305-324 Sayani Dasgupta, Lloyd D. Fricker Chapter 14 - Analysis of Deep Sequencing Data: Insights and Challenges Pages 325-354 Jacob W. Malcom, John H. Malone Chapter 15 - Gene Expression Analysis and Profiling of Microarrays Data and RNA-Sequencing Data Pages 355-384 Javier De Las Rivas, Sara Aibar, Beatriz Roson Chapter 16 - Bioinformatic Approaches to Increase Proteome Coverage Pages 385-419 Francesco M. Mancuso, Salvatore Cappadona, Eduard Sabidó Chapter 17 - Transcriptome and Metabolome Data Integration—Technical Perquisites for Successful Data Fusion and Visualization Pages 421-442 Michael Witting, Philippe Schmitt-Kopplin Chapter 18 - Computational Approaches for Visualization and Integration of Omics Data Pages 443-454 Vasudha Sehgal, Tyler J. Moss, Prahlad T. Ram Index Pages 455-467

Fundamentals of Advanced Omics Technologies: From Genes to Metabolites covers the fundamental aspects of the new instrumental and methodological developments in omics technologies, including those related to genomics, transcriptomics, epigenetics, proteomics and metabolomics, as well as other omics approaches such as glycomics, peptidomics and foodomics. The principal applications are presented in the following complementary volume.

The chapters discuss in detail omics technologies, DNA microarray analysis, next-generation sequencing technologies, genome-wide analysis of methylation and histone modifications, emerging nanotechniques in proteomics, imaging mass spectrometry in proteomics, recent quantitative proteomics approaches, and advances in high-resolution NMR-based metabolomics, as well as MS-based non-targeted metabolomics and metabolome analysis by CE-MS, global glycomics analyses, foodomics, and high resolution analytical tools for quantitative peptidomics. Key aspects related to chemometrics, bioinformatics, data treatment, data integration and systems biology, deep-sequencing data analysis, statistical approaches for the analysis of microarray data, the integration of transcriptome and metabolome data and computational approaches for visualization and integration of omics data are also covered.

• Covers the latest advances in instrumentation, experimental design, sample preparation, and data analysis
• Provides thorough explanations and descriptions of specific omics technologies
• Describes advanced tools and methodologies for data pretreatment, storage, curation and analysis, as well as data integration