Shili Lin, PhD is a Professor in the Department of Statistics and a faculty member in the Translational Data Analytics Institute at the Ohio State University. Her research interests are in statistical methodologies for high-dimensional and big data, with a focus on their applications in biomedical research, statistical genetics and genomics, and integration of multiple omics data.Denise Scholtens, PhD is Professor and Chief of the Division of Biostatistics in the Department of Preventive Medicine at Northwestern University Feinberg School of Medicine. She is interested in the design and conduct of large-scale multi-center prospective health research studies, and in the integration of high-dimensional omics data analyses into these settings.Sujay Datta, PhD is an Associate Professor and the Graduate Program Coordinator in the Department of Statistics at the University of Akron. His research interests include statistical analyses of high-dimensional and high-throughput data, graphical and network-based models, statistical models and methods for cancer data, as well as sequential/multistage sampling designs.

"In conclusion, “Bioinformatics Methods: FromOmics to Next Generation Sequencing” is an essential reference for researchers, students, and professionals in the broad field of biomedicine who are interested in the biostatistics and bioinformatics aspects of omics. Its comprehensive coverage, clear explanations, practical applications, and incorporation of the latest advancements make it an invaluable resource. By empowering readers with the knowledge and tools to navigate the complexities of biological data, this book paves the way for groundbreaking discoveries and advancements in the realm of life sciences."Yu-Chiao Chiu, Cancer Therapeutics Program, University of Pittsburgh Medical Center Hillman Cancer Center, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA, Biometrics.

• 1 The Biology of a Living Organism 2 Protein-Protein Interactions 3 Protein-Protein Interaction Network Analyses 4 Detection of Imprinting and Maternal Effects 5 Modelling and Analysis of Next-Generation Sequencing Data 6 Sequencing-Based DNA Methylation Data 7 Modelling and Analysis of Spatial Chromatin Interactions 8 Digital Improvement of Single Cell Hi-C Data 9 Metabolomics Data Pre-processing 10 Metabolomics Data Analysis 11 Appendix

Shili Lin, PhD is a Professor in the Department of Statistics and a faculty member in the Translational Data Analytics Institute at the Ohio State University. Her research interests are in statistical methodologies for high-dimensional and big data, with a focus on their applications in biomedical research, statistical genetics and genomics, and integration of multiple omics data.Denise Scholtens, PhD is Professor and Chief of the Division of Biostatistics in the Department of Preventive Medicine at Northwestern University Feinberg School of Medicine. She is interested in the design and conduct of large-scale multi-center prospective health research studies, and in the integration of high-dimensional omics data analyses into these settings.Sujay Datta, PhD is an Associate Professor and the Graduate Program Coordinator in the Department of Statistics at the University of Akron. His research interests include statistical analyses of high-dimensional and high-throughput data, graphical and network-based models, statistical models and methods for cancer data, as well as sequential/multistage sampling designs.

"In conclusion, “Bioinformatics Methods: FromOmics to Next Generation Sequencing” is an essential reference for researchers, students, and professionals in the broad field of biomedicine who are interested in the biostatistics and bioinformatics aspects of omics. Its comprehensive coverage, clear explanations, practical applications, and incorporation of the latest advancements make it an invaluable resource. By empowering readers with the knowledge and tools to navigate the complexities of biological data, this book paves the way for groundbreaking discoveries and advancements in the realm of life sciences."Yu-Chiao Chiu, Cancer Therapeutics Program, University of Pittsburgh Medical Center Hillman Cancer Center, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA, Biometrics.

• 1 The Biology of a Living Organism 2 Protein-Protein Interactions 3 Protein-Protein Interaction Network Analyses 4 Detection of Imprinting and Maternal Effects 5 Modelling and Analysis of Next-Generation Sequencing Data 6 Sequencing-Based DNA Methylation Data 7 Modelling and Analysis of Spatial Chromatin Interactions 8 Digital Improvement of Single Cell Hi-C Data 9 Metabolomics Data Pre-processing 10 Metabolomics Data Analysis 11 Appendix

Shili Lin, PhD is a Professor in the Department of Statistics and a faculty member in the Translational Data Analytics Institute at the Ohio State University. Her research interests are in statistical methodologies for high-dimensional and big data, with a focus on their applications in biomedical research, statistical genetics and genomics, and integration of multiple omics data.Denise Scholtens, PhD is Professor and Chief of the Division of Biostatistics in the Department of Preventive Medicine at Northwestern University Feinberg School of Medicine. She is interested in the design and conduct of large-scale multi-center prospective health research studies, and in the integration of high-dimensional omics data analyses into these settings.Sujay Datta, PhD is an Associate Professor and the Graduate Program Coordinator in the Department of Statistics at the University of Akron. His research interests include statistical analyses of high-dimensional and high-throughput data, graphical and network-based models, statistical models and methods for cancer data, as well as sequential/multistage sampling designs.

"In conclusion, “Bioinformatics Methods: FromOmics to Next Generation Sequencing” is an essential reference for researchers, students, and professionals in the broad field of biomedicine who are interested in the biostatistics and bioinformatics aspects of omics. Its comprehensive coverage, clear explanations, practical applications, and incorporation of the latest advancements make it an invaluable resource. By empowering readers with the knowledge and tools to navigate the complexities of biological data, this book paves the way for groundbreaking discoveries and advancements in the realm of life sciences."Yu-Chiao Chiu, Cancer Therapeutics Program, University of Pittsburgh Medical Center Hillman Cancer Center, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA, Biometrics.

• 1 The Biology of a Living Organism 2 Protein-Protein Interactions 3 Protein-Protein Interaction Network Analyses 4 Detection of Imprinting and Maternal Effects 5 Modelling and Analysis of Next-Generation Sequencing Data 6 Sequencing-Based DNA Methylation Data 7 Modelling and Analysis of Spatial Chromatin Interactions 8 Digital Improvement of Single Cell Hi-C Data 9 Metabolomics Data Pre-processing 10 Metabolomics Data Analysis 11 Appendix