This book is written by leading researchers in the fields about the intersection of genetics and metabolomics which can lead to more comprehensive studies of inborn variation of metabolism.

Animal biotechnology is an integral component of agriculture. Supported with over 50 figures and more than 30 tables, this textbook is a must have for undergraduates and postgraduates of various agriculture and animal husbandry academia, teachers, professionals, and researchers in basic as well as applied animal sciences including biotechnology, nutrition, physiology and reproduction. The book covers various topics, including economically important livestock breeds, paradigm shifts in livestock production, biotechnology in animal nutrition and in livestock-assisted reproduction, and genomics and genetic engineering tools in livestock production and management.

The Handbook of Metabolic Phenotyping is the definitive work on the rapidly developing subject of metabolic phenotyping. It explores in detail the wide array of analytical chemistry and statistical modeling techniques used in the field, coupled with surveys of the various application areas in human development, nutrition, disease, therapy, and epidemiology to create a comprehensive exploration of the area of study. It covers recent studies that integrate the various -omics data sets to derive a systems biology view. It also addresses current issues on standardization, assay and statistics validation, and data storage and sharing. Written by experts with many years of practice in the field who pioneered many of the approaches widely used today, The Handbook of Metabolic Phenotyping is a valuable resource for postgrads and research scientists studying and furthering the field of metabolomics. - Contains theoretical and practical explanations of all the main analytical chemistry techniques used in metabolic phenotyping - Explores, in detail, the many diverse statistical approaches used in the field - Offers practical tips for successfully conducting metabolic phenotyping studies - Features reviews of all of the various fields of activity relating to human studies

The past three decades have witnessed an explosion of what is now referred to as high-dimensional `omics' data. Bioinformatics Methods: From Omics to Next Generation Sequencing describes the statistical methods and analytic frameworks that are best equipped to interpret these complex data and how they apply to health-related research. Covering the technologies that generate data, subtleties of various data types, and statistical underpinnings of methods, this book identifies a suite of potential analytic tools, and highlights commonalities among statistical methods that have been developed. An ideal reference for biostatisticians and data analysts that work in collaboration with scientists and clinical investigators looking to ensure rigorous application of available methodologies. Key Features: Survey of a variety of omics data types and their unique features Summary of statistical underpinnings for widely used omics data analysis methods Description of software resources for performing omics data analyses

With the appearance of methods for the sequencing of genomes and less expensive next generation sequencing methods, we face rapid advancements of the -omics technologies and plant biology studies: reverse and forward genetics, functional genomics, transcriptomics, proteomics, metabolomics, the movement at distance of effectors and structural biology. From plant genomics to plant biotechnology reviews the recent advancements in the post-genomic era, discussing how different varieties respond to abiotic and biotic stresses, understanding the epigenetic control and epigenetic memory, the roles of non-coding RNAs, applicative uses of RNA silencing and RNA interference in plant physiology and in experimental transgenics and plants modified to specific aims. In the forthcoming years these advancements will support the production of plant varieties better suited to resist biotic and abiotic stresses, for food and non-food applications.This book covers these issues, showing how such technologies are influencing the plant field in sectors such as the selection of plant varieties and plant breeding, selection of optimum agronomic traits, stress-resistant varieties, improvement of plant fitness, improving crop yield, and non-food applications in the knowledge based bio-economy. - Discusses a broad range of applications: the examples originate from a variety of sectors (including in field studies, breeding, RNA regulation, pharmaceuticals and biotech) and a variety of scientific areas (such as bioinformatics, -omics sciences, epigenetics, and the agro-industry) - Provides a unique perspective on work normally performed 'behind closed doors'. As such, it presents an opportunity for those within the field to learn from each other, and for those on the 'outside' to see how different groups have approached key problems - Highlights the criteria used to compare and assess different approaches to solving problems. Shows the thinking process, practical limitations and any other considerations, aiding in the understanding of a deeper approach

Written for drug developers rather than computer scientists, this monograph adopts a systematic approach to mining scientifi c data sources, covering all key steps in rational drug discovery, from compound screening to lead compound selection and personalized medicine. Clearly divided into four sections, the first part discusses the different data sources available, both commercial and non-commercial, while the next section looks at the role and value of data mining in drug discovery. The third part compares the most common applications and strategies for polypharmacology, where data mining can substantially enhance the research effort. The final section of the book is devoted to systems biology approaches for compound testing. Throughout the book, industrial and academic drug discovery strategies are addressed, with contributors coming from both areas, enabling an informed decision on when and which data mining tools to use for one's own drug discovery project.

Many aspects of modern life have become personalized, yet healthcare practices have been lagging behind in this trend. It is now becoming more common to use big data analysis to improve current healthcare and medicinal systems, and offer better health services to all citizens. Applying Big Data Analytics in Bioinformatics and Medicine is a comprehensive reference source that overviews the current state of medical treatments and systems and offers emerging solutions for a more personalized approach to the healthcare field. Featuring coverage on relevant topics that include smart data, proteomics, medical data storage, and drug design, this publication is an ideal resource for medical professionals, healthcare practitioners, academicians, and researchers interested in the latest trends and techniques in personalized medicine.

Advances in Clinical Chemistry, Volume 94, the latest installment in this internationally acclaimed series, contains chapters authored by world-renowned clinical laboratory scientists, physicians and research scientists. The serial discusses the latest technologies relating to the field of clinical chemistry, with specific chapters in this new release covering Hypertensive disorders of pregnancy: Strategy to develop clinical peptide biomarkers for more accurate evaluation of the pathophysiological status of this syndrome, Clotting factors - Clinical biochemistry and their roles as plasma enzymes, Myokines: The endocrine coupling of skeletal muscle and bone, Epigenetic reprogramming and potential application of epigenetic-modifying drugs in acquired chemotherapeutic resistance, and more. - Provides the most up-to-date technologies in clinical chemistry and clinical laboratory science - Authored by world renowned clinical laboratory scientists, physicians and research scientists - Presents the international benchmark for novel analytical approaches in the clinical laboratory

Data Analysis for Omic Sciences: Methods and Applications, Volume 82, shows how these types of challenging datasets can be analyzed. Examples of applications in real environmental, clinical and food analysis cases help readers disseminate these approaches. Chapters of note include an Introduction to Data Analysis Relevance in the Omics Era, Omics Experimental Design and Data Acquisition, Microarrays Data, Analysis of High-Throughput RNA Sequencing Data, Analysis of High-Throughput DNA Bisulfite Sequencing Data, Data Quality Assessment in Untargeted LC-MS Metabolomic, Data Normalization and Scaling, Metabolomics Data Preprocessing, and more. - Presents the best reference book for omics data analysis - Provides a review of the latest trends in transcriptomics and metabolomics data analysis tools - Includes examples of applications in research fields, such as environmental, biomedical and food analysis

Comprehensive Biotechnology, Third Edition, Six Volume Set unifies, in a single source, a huge amount of information in this growing field. The book covers scientific fundamentals, along with engineering considerations and applications in industry, agriculture, medicine, the environment and socio-economics, including the related government regulatory overviews. This new edition builds on the solid basis provided by previous editions, incorporating all recent advances in the field since the second edition was published in 2011. Offers researchers a one-stop shop for information on the subject of biotechnology Provides in-depth treatment of relevant topics from recognized authorities, including the contributions of a Nobel laureate Presents the perspective of researchers in different fields, such as biochemistry, agriculture, engineering, biomedicine and environmental science