Translational Bioinformatics – serie

"Applied Computational Genomics" focuses on an in-depth review of statistical development and application in the area of human genomics including candidate gene mapping, linkage analysis, population-based, genome-wide association, exon sequencing and whole genome sequencing analysis. The authors are extremely experienced in the area of statistical genomics and will give a detailed introduction of the evolution in the field and critical evaluations of the advantages and disadvantages of the statistical models proposed. They will also share their views on a future shift toward translational biology. The book will be of value to human geneticists, medical doctors, health educators, policy makers, and graduate students majoring in biology, biostatistics, and bioinformatics. Dr. Yin Yao Shugart is investigator in the Intramural Research Program at the National Institute of Mental Health, Bethesda, Maryland USA. ​

“Bioinformatics of Human Proteomics” discusses the development of methods, techniques and applications in the field of protein bioinformatics, an important direction in bioinformatics. It collects contributions from expert researchers in order to provide a practical guide to this complex field of study. The book covers the protein interaction network, drug discovery and development, the relationship between translational medicine and bioinformatics, and advances in proteomic methods, while also demonstrating important bioinformatics tools and methods available today for protein analysis, interpretation and predication. It is intended for experts or senior researchers in the fields of clinical research-related biostatistics, bioinformatics, computational biology, medicine, statistics, system biology, molecular diagnostics, biomarkers, or drug discovery and development. Dr.Xiangdong Wang works as a distinguished professor of Respiratory Medicine at Fudan University, Shanghai, China. He serves as Director of Biomedical Research Center, Fudan University Zhongshan Hospital and adjunct professor of Clinical Bioinformatics at Lund University, Sweden. His main research is focused on the role of clinical bioinformatics in the development of disease-specific biomarkers and dynamic network biomarkers, the molecular mechanism of organ dysfunction and potential therapies.

The book introduces the bioinformatics tools, databases and strategies for the translational research, focuses on the biomarker discovery based on integrative data analysis and systems biological network reconstruction. With the coming of personal genomics era, the biomedical data will be accumulated fast and then it will become reality for the personalized and accurate diagnosis, prognosis and treatment of complex diseases. The book covers both state of the art of bioinformatics methodologies and the examples for the identification of simple or network biomarkers. In addition, bioinformatics software tools and scripts are provided to the practical application in the study of complex diseases. The present state, the future challenges and perspectives were discussed. The book is written for biologists, biomedical informatics scientists and clinicians, etc. Dr. Bairong Shen is Professor and Director of Center for Systems Biology, Soochow University; he is also Director of Taicang Center for Translational Bioinformatics.

The book introduces the bioinformatics resources and tools available for the study of allergenicity. Allergy symptoms affect more than 25% of the population in industrialized countries. At the same time, biotechnology is a rapidly developing field, which often involves the introduction of potentially allergenic novel proteins into drugs or foods. It is essential to avoid transferring a gene that encodes a major allergenic protein (from any source) into a drug/food crop that did not previously contain that protein. Accurately distinguishing candidate genes from allergens before transferring them into a drug or food would aid preventive efforts to curb the rising incidence of allergies. Several public databases have been created in response to increasing allergen data. The resources provided by these databases have paved the way for the creation of specialized bioinformatics tools that allow allergenicity to be predicted. The book is a useful resource for biologists and biomedical informatics scientists, as well as clinicians. Dr. Ailin Tao is the chief of Guangdong Province Key Laboratory of Allergy & Clinical Immunology, Principal Investigator of the State Key Laboratory of Respiratory Disease, the Second Affiliated Hospital of Guangzhou Medical University; Dr. Prof. Eyal Raz is a Professor of Medicine at University of California, San Diego, La Jolla, California, USA. They collaborate very well on allergy research and this book editing.

This volume focuses on modern computational and statistical tools for translational gene expression and regulation research to improve prognosis, diagnostics, prediction of severity, and therapies for human diseases. It introduces some of state of the art technologies as well as computational and statistical tools for translational bioinformatics in the areas of gene transcription and regulation, including the tools for next generation sequencing analyses, alternative spicing, the modeling of signaling pathways, network analyses in predicting disease genes, as well as protein and gene expression data integration in complex human diseases etc. The book is particularly useful for researchers and students in the field of molecular biology, clinical biology and bioinformatics, as well as physicians etc.  Dr. Jiaqian Wu is assistant professor in the Vivian L. Smith Department of Neurosurgery and Center for Stem Cell and Regenerative Medicine, University of Texas Health Science Centre, Houston, TX, USA.​

This bookelucidates how genetic, biological and medical information can be applied tothe development of personalized healthcare, medication and therapies. Focusingon aspects of the development of evidence-based approaches in bioinformaticsand computational medicine, including data integration, methodologies, toolsand models for clinical and translational medicine, it offers an essentialintroduction to clinical bioinformatics for clinical researchers andphysicians, medical students and teachers, and scientists working with human disease-based omics and bioinformatics. Dr. XiangdongWang is a distinguished Professor of Medicine. He is Director of ShanghaiInstitute of Clinical Bioinformatics, Director of Fudan University Center forClinical Bioinformatics, Deputy Director of Shanghai Respiratory ResearchInstitute, Director of Biomedical Research Center, Fudan University ZhongshanHospital, Shanghai, China; Dr. Christian Baumgartner is a Professor of HealthCare and Biomedical Engineering at Institute of Health Care Engineering withEuropean Notified Body of Medical Devices, Graz University of Technology, Graz,Austria; Dr. Denis Shields is a Professor of ClinicalBioinformatics at Conway Institute, Belfield, Dublin, Ireland; Dr. Hong-Wen Dengis a Professor at Department of Biostatistics and Bioinformatics, Tulane UniversitySchool of Public Health and Tropical Medicine, USA; Dr. Jacques SBeckmann is a Professor and Director of Section of Clinical Bioinformatics,Swiss Institute of Bioinformatics, Switzerland.

"Applied Computational Genomics" focuses on an in-depth review of statistical development and application in the area of human genomics including candidate gene mapping, linkage analysis, population-based, genome-wide association, exon sequencing and whole genome sequencing analysis. The authors are extremely experienced in the area of statistical genomics and will give a detailed introduction of the evolution in the field and critical evaluations of the advantages and disadvantages of the statistical models proposed. They will also share their views on a future shift toward translational biology. The book will be of value to human geneticists, medical doctors, health educators, policy makers, and graduate students majoring in biology, biostatistics, and bioinformatics. Dr. Yin Yao Shugart is investigator in the Intramural Research Program at the National Institute of Mental Health, Bethesda, Maryland USA. ​

“Bioinformatics of Human Proteomics” discusses the development of methods, techniques and applications in the field of protein bioinformatics, an important direction in bioinformatics. It collects contributions from expert researchers in order to provide a practical guide to this complex field of study. The book covers the protein interaction network, drug discovery and development, the relationship between translational medicine and bioinformatics, and advances in proteomic methods, while also demonstrating important bioinformatics tools and methods available today for protein analysis, interpretation and predication. It is intended for experts or senior researchers in the fields of clinical research-related biostatistics, bioinformatics, computational biology, medicine, statistics, system biology, molecular diagnostics, biomarkers, or drug discovery and development. Dr.Xiangdong Wang works as a distinguished professor of Respiratory Medicine at Fudan University, Shanghai, China. He serves as Director of Biomedical Research Center, Fudan University Zhongshan Hospital and adjunct professor of Clinical Bioinformatics at Lund University, Sweden. His main research is focused on the role of clinical bioinformatics in the development of disease-specific biomarkers and dynamic network biomarkers, the molecular mechanism of organ dysfunction and potential therapies.

The book is intended to be a resource for students as well as scientists in education and for the general public to learn about proteomics and genomics. Chromosomes form the basis for our genetic heritage and are the code for protein synthesis. The Human Genome Map came out in 2002, and the Proteome Sequence Map is under currently being created by a global consortia initiative. Proteome and genome building blocks already form the basis of scientific research areas as well as large parts of the pharmaceutical and biomedical industry. The book initiative will provide the background to and our current understanding of these gene and protein areas, as well as describe how cutting-edge science is using these resources to develop new medicines and new diagnostics for patient care and treatment. The book will be useful for undergraduate students as well as university students and researchers who need a good understanding of genomics and proteomics within the clinical field. The book will also be targeted at a broad public as well as readers not specialized within this field.Dr. Marko-Varga is the head of the Head of Div. Clinical Protein Science & Imaging at the Biomedical Center, Dept. of Measurement Technology and Industrial Electrical Engineering, Lund University, and Professor at the 1st Department of Surgery, Tokyo Medical University, Tokyo, Japan.

The volume focuses on the genomics, proteomics, metabolomics, and bioinformatics of a single cell, especially lymphocytes and on understanding the molecular mechanisms of systems immunology. Based on the author’s personal experience, it provides revealing insights into the potential applications, significance, workflow, comparison, future perspectives and challenges of single-cell sequencing for identifying and developing disease-specific biomarkers in order to understand the biological function, activation and dysfunction of single cells and lymphocytes and to explore their functional roles and responses to therapies. It also provides detailed information on individual subgroups of lymphocytes, including cell characters, function, surface markers, receptor function, intracellular signals and pathways, production of inflammatory mediators, nuclear receptors and factors, omics, sequencing, disease-specific biomarkers, bioinformatics, networks and dynamic networks, their role in disease and future prospects. Dr. Xiangdong Wang is a Professor of Medicine, Director of Shanghai Institute of Clinical Bioinformatics, Director of Fudan University Center for Clinical Bioinformatics, Director of the Biomedical Research Center of Zhongshan Hospital, Deputy Director of Shanghai Respiratory Research Institute, Shanghai, China.

This book introduces the reader to modern computational and statistical tools for translational epigenomics research. Over the last decade, epigenomics has emerged as a key area of molecular biology, epidemiology and genome medicine. Epigenomics not only offers us a deeper understanding of fundamental cellular biology, but also provides us with the basis for an improved understanding and management of complex diseases. From novel biomarkers for risk prediction, early detection, diagnosis and prognosis of common diseases, to novel therapeutic strategies, epigenomics is set to play a key role in the personalized medicine of the future. In this book we introduce the reader to some of the most important computational and statistical methods for analyzing epigenomic data, with a special focus on DNA methylation. Topics include normalization, correction for cellular heterogeneity, batch effects, clustering, supervised analysis and integrative methods for systems epigenomics. This book will be of interest to students and researchers in bioinformatics, biostatistics, biologists and clinicians alike.Dr. Andrew E. Teschendorff is Head of the Computational Systems Genomics Lab at the CAS-MPG Partner Institute for Computational Biology, Shanghai, China, as well as an Honorary Research Fellow at the UCL Cancer Institute, University College London, UK.

This book introduces the reader to modern computational and statistical tools for translational epigenomics research. Over the last decade, epigenomics has emerged as a key area of molecular biology, epidemiology and genome medicine. Epigenomics not only offers us a deeper understanding of fundamental cellular biology, but also provides us with the basis for an improved understanding and management of complex diseases. From novel biomarkers for risk prediction, early detection, diagnosis and prognosis of common diseases, to novel therapeutic strategies, epigenomics is set to play a key role in the personalized medicine of the future. In this book we introduce the reader to some of the most important computational and statistical methods for analyzing epigenomic data, with a special focus on DNA methylation. Topics include normalization, correction for cellular heterogeneity, batch effects, clustering, supervised analysis and integrative methods for systems epigenomics. This book will be of interest to students and researchers in bioinformatics, biostatistics, biologists and clinicians alike.Dr. Andrew E. Teschendorff is Head of the Computational Systems Genomics Lab at the CAS-MPG Partner Institute for Computational Biology, Shanghai, China, as well as an Honorary Research Fellow at the UCL Cancer Institute, University College London, UK.

The book introduces the bioinformatics resources and tools available for the study of allergenicity. Allergy symptoms affect more than 25% of the population in industrialized countries. At the same time, biotechnology is a rapidly developing field, which often involves the introduction of potentially allergenic novel proteins into drugs or foods. It is essential to avoid transferring a gene that encodes a major allergenic protein (from any source) into a drug/food crop that did not previously contain that protein. Accurately distinguishing candidate genes from allergens before transferring them into a drug or food would aid preventive efforts to curb the rising incidence of allergies. Several public databases have been created in response to increasing allergen data. The resources provided by these databases have paved the way for the creation of specialized bioinformatics tools that allow allergenicity to be predicted. The book is a useful resource for biologists and biomedical informatics scientists, as well as clinicians. Dr. Ailin Tao is the chief of Guangdong Province Key Laboratory of Allergy & Clinical Immunology, Principal Investigator of the State Key Laboratory of Respiratory Disease, the Second Affiliated Hospital of Guangzhou Medical University; Dr. Prof. Eyal Raz is a Professor of Medicine at University of California, San Diego, La Jolla, California, USA. They collaborate very well on allergy research and this book editing.

This volume focuses on modern computational and statistical tools for translational gene expression and regulation research to improve prognosis, diagnostics, prediction of severity, and therapies for human diseases. It introduces some of state of the art technologies as well as computational and statistical tools for translational bioinformatics in the areas of gene transcription and regulation, including the tools for next generation sequencing analyses, alternative spicing, the modeling of signaling pathways, network analyses in predicting disease genes, as well as protein and gene expression data integration in complex human diseases etc. The book is particularly useful for researchers and students in the field of molecular biology, clinical biology and bioinformatics, as well as physicians etc.  Dr. Jiaqian Wu is assistant professor in the Vivian L. Smith Department of Neurosurgery and Center for Stem Cell and Regenerative Medicine, University of Texas Health Science Centre, Houston, TX, USA.​

The book is intended to be a resource for students as well as scientists in education and for the general public to learn about proteomics and genomics. Chromosomes form the basis for our genetic heritage and are the code for protein synthesis. The Human Genome Map came out in 2002, and the Proteome Sequence Map is under currently being created by a global consortia initiative. Proteome and genome building blocks already form the basis of scientific research areas as well as large parts of the pharmaceutical and biomedical industry. The book initiative will provide the background to and our current understanding of these gene and protein areas, as well as describe how cutting-edge science is using these resources to develop new medicines and new diagnostics for patient care and treatment. The book will be useful for undergraduate students as well as university students and researchers who need a good understanding of genomics and proteomics within the clinical field. The book will also be targeted at a broad public as well as readers not specialized within this field.Dr. Marko-Varga is the head of the Head of Div. Clinical Protein Science & Imaging at the Biomedical Center, Dept. of Measurement Technology and Industrial Electrical Engineering, Lund University, and Professor at the 1st Department of Surgery, Tokyo Medical University, Tokyo, Japan.

This bookelucidates how genetic, biological and medical information can be applied tothe development of personalized healthcare, medication and therapies. Focusingon aspects of the development of evidence-based approaches in bioinformaticsand computational medicine, including data integration, methodologies, toolsand models for clinical and translational medicine, it offers an essentialintroduction to clinical bioinformatics for clinical researchers andphysicians, medical students and teachers, and scientists working with human disease-based omics and bioinformatics. Dr. XiangdongWang is a distinguished Professor of Medicine. He is Director of ShanghaiInstitute of Clinical Bioinformatics, Director of Fudan University Center forClinical Bioinformatics, Deputy Director of Shanghai Respiratory ResearchInstitute, Director of Biomedical Research Center, Fudan University ZhongshanHospital, Shanghai, China; Dr. Christian Baumgartner is a Professor of HealthCare and Biomedical Engineering at Institute of Health Care Engineering withEuropean Notified Body of Medical Devices, Graz University of Technology, Graz,Austria; Dr. Denis Shields is a Professor of ClinicalBioinformatics at Conway Institute, Belfield, Dublin, Ireland; Dr. Hong-Wen Dengis a Professor at Department of Biostatistics and Bioinformatics, Tulane UniversitySchool of Public Health and Tropical Medicine, USA; Dr. Jacques SBeckmann is a Professor and Director of Section of Clinical Bioinformatics,Swiss Institute of Bioinformatics, Switzerland.

The book describes the core resources in informatics necessary to support biomedical research programs and how these can best be integrated with hospital systems to receive clinical information that is necessary to conduct translational research. The focus is on the authors’ recent practical experiences in establishing an informatics infrastructure in a large research-intensive children’s hospital.  This book is intended for translational researchers and informaticians in pediatrics, but can also serve as a guide to all institutions facing the challenges of developing and strengthening informatics support for biomedical research. The first section of the book discusses important technical challenges underlying computer-based pediatric research, while subsequent sections discuss informatics applications that support biobanking and a broad range of research programs. Pediatric Biomedical Informatics provides practical insights into the design, implementation, and utilization of informatics infrastructures to optimize care and research to benefit children.

This volume in the series, Translational Bioinformatics, provides an up-to-date overview of genomic approaches to asthma. By applying unbiased “-omics” combined with disease-focused and hypothesis-driven approaches, it enhances readers’ understanding of the asthma endotype. Furthermore, it elucidates how progress in -omics research, such as “genomic,” “transcriptomic,” “protomic,” and “metabolomic,” is applied in asthma, and reports on the related series of important breakthroughs in asthma development, classification, prevention and drug sensitivity. Also covering systems biology knowledge and methodologies, computational models and biostatistical methods to analyze big data, this book provides a valuable resource for scientists and researchers in the field of asthma and respiratory diseases.

The book describes the core resources in informatics necessary to support biomedical research programs and how these can best be integrated with hospital systems to receive clinical information that is necessary to conduct translational research. The focus is on the authors’ recent practical experiences in establishing an informatics infrastructure in a large research-intensive children’s hospital.  This book is intended for translational researchers and informaticians in pediatrics, but can also serve as a guide to all institutions facing the challenges of developing and strengthening informatics support for biomedical research. The first section of the book discusses important technical challenges underlying computer-based pediatric research, while subsequent sections discuss informatics applications that support biobanking and a broad range of research programs. Pediatric Biomedical Informatics provides practical insights into the design, implementation, and utilization of informatics infrastructures to optimize care and research to benefit children.

This volume covers the emerging area of science, Clinical Lipidomics, which is the application of lipidology to the understanding of physiological and pathophysiological changes of lipidomes, with a special focus on lipidomic profiles in human diseases.Lipidomics is widely used to map lipid molecular species in a biological system. Clinical lipidomic analysis has demonstrated the comprehensive characterization of molecular lipids in various severities, durations, and therapies as a critical tool in identification and validation of disease-specific biomarkers. This volume on Clinical Lipidomics will add to the literature and help advance the knowledge of the pathogenesis, diagnosis, prevention and treatment of diseases.

The volume provides a review of statistical development and application in the area of human genomics, including candidate gene mapping, linkage analysis, population-based genome-wide association, exon sequencing, and whole genome sequencing analysis. The authors are extremely experienced in the field of statistical genomics and will give a detailed introduction to the evolution of the field, as well as critical comments on the advantages and disadvantages of the proposed statistical models. The future directions of translational biology will also be described.

This book elucidates how advances in genomics research are being applied in connection with heart diseases. It describes the development of genome-scale technologies and their applications to all areas of cardiac investigations, such as genomics, functional genomics, epigenomics, etc., and how they relate to a series of important breakthroughs in various heart diseases. Applying unbiased genomics, combined with a disease-focused and hypothesis-driven approach, represents a promising way to advance our understanding of cardiac diseases. The book offers an important reference work on introducing genomics in heart disease for all scientists and graduate students whose work involves genomics and cardiology, as well as for clinical physicians.

This volume in the series, Translational Bioinformatics, provides an up-to-date overview of genomic approaches to asthma. By applying unbiased “-omics” combined with disease-focused and hypothesis-driven approaches, it enhances readers’ understanding of the asthma endotype. Furthermore, it elucidates how progress in -omics research, such as “genomic,” “transcriptomic,” “protomic,” and “metabolomic,” is applied in asthma, and reports on the related series of important breakthroughs in asthma development, classification, prevention and drug sensitivity. Also covering systems biology knowledge and methodologies, computational models and biostatistical methods to analyze big data, this book provides a valuable resource for scientists and researchers in the field of asthma and respiratory diseases.

This volume covers the emerging area of science, Clinical Lipidomics, which is the application of lipidology to the understanding of physiological and pathophysiological changes of lipidomes, with a special focus on lipidomic profiles in human diseases.Lipidomics is widely used to map lipid molecular species in a biological system. Clinical lipidomic analysis has demonstrated the comprehensive characterization of molecular lipids in various severities, durations, and therapies as a critical tool in identification and validation of disease-specific biomarkers. This volume on Clinical Lipidomics will add to the literature and help advance the knowledge of the pathogenesis, diagnosis, prevention and treatment of diseases.

The volume provides a review of statistical development and application in the area of human genomics, including candidate gene mapping, linkage analysis, population-based genome-wide association, exon sequencing, and whole genome sequencing analysis. The authors are extremely experienced in the field of statistical genomics and will give a detailed introduction to the evolution of the field, as well as critical comments on the advantages and disadvantages of the proposed statistical models. The future directions of translational biology will also be described.

This book elucidates how advances in genomics research are being applied in connection with heart diseases. It describes the development of genome-scale technologies and their applications to all areas of cardiac investigations, such as genomics, functional genomics, epigenomics, etc., and how they relate to a series of important breakthroughs in various heart diseases. Applying unbiased genomics, combined with a disease-focused and hypothesis-driven approach, represents a promising way to advance our understanding of cardiac diseases. The book offers an important reference work on introducing genomics in heart disease for all scientists and graduate students whose work involves genomics and cardiology, as well as for clinical physicians.

The Book mainly focuses on various aspects of regionalized management of medicine, related with updates of new biotechnology, application of therapeutic strategy, and understanding of disease-associated molecular mechanisms. The book also discusses how medical informatics, systems analysis, database sharing, and artificial intelligent can be applied for improving the quality of hospital managements, disease therapies, regional collaborations, and medical services.This book serves as a professional reference book to clinicians and experts who are interested in medical informatics and artificial intelligence for diseases therapies and therapeutic strategy, better systems analysis and database sharing, and more efficient regional collaborations and medical services.

The Book mainly focuses on various aspects of regionalized management of medicine, related with updates of new biotechnology, application of therapeutic strategy, and understanding of disease-associated molecular mechanisms. The book also discusses how medical informatics, systems analysis, database sharing, and artificial intelligent can be applied for improving the quality of hospital managements, disease therapies, regional collaborations, and medical services.This book serves as a professional reference book to clinicians and experts who are interested in medical informatics and artificial intelligence for diseases therapies and therapeutic strategy, better systems analysis and database sharing, and more efficient regional collaborations and medical services.

This book focuses on the multi-omics big-data integration, the data-mining techniques and the cutting-edge omics researches in principles and applications for a deep understanding of Traditional Chinese Medicine (TCM) and diseases from the following aspects: (1) Basics about multi-omics data and analytical methods for TCM and diseases. (2) The needs of omics studies in TCM researches, and the basic background of omics research in TCM and disease. (3) Better understanding of the multi-omics big-data integration techniques. (4) Better understanding of the multi-omics big-data mining techniques, as well as with different applications, for most insights from these omics data for TCM and disease researches. (5) TCM preparation quality control for checking both prescribed and unexpected ingredients including biological and chemical ingredients. (6) TCM preparation source tracking.  (7) TCM preparation network pharmacology analysis. (8) TCM analysis data resources, web services, andvisualizations. (9) TCM geoherbalism examination and authentic TCM identification. Traditional Chinese Medicine has been in existence for several thousands of years, and only in recent tens of years have we realized that the researches on TCM could be profoundly boosted by the omics technologies. Devised as a book on TCM and disease researches in the omics age, this book has put the focus on data integration and data mining methods for multi-omics researches, which will be explained in detail and with supportive examples the “What”, “Why” and “How” of omics on TCM related researches. It is an attempt to bridge the gap between TCM related multi-omics big data, and the data-mining techniques, for best practice of contemporary bioinformatics and in-depth insights on the TCM related questions.