This book is open access under a CC BY 4.0 license This open access book brings together the latest genome base prediction models currently being used by statisticians, breeders and data scientists. It provides an accessible way to understand the theory behind each statistical learning tool, the required pre-processing, the basics of model building, how to train statistical learning methods, the basic R scripts needed to implement each statistical learning tool, and the output of each tool. To do so, for each tool the book provides background theory, some elements of the R statistical software for its implementation, the conceptual underpinnings, and at least two illustrative examples with data from real-world genomic selection experiments. Lastly, worked-out examples help readers check their own comprehension.The book will greatly appeal to readers in plant (and animal) breeding, geneticists and statisticians, as it provides in a very accessible way the necessary theory, the appropriate R code, and illustrative examples for a complete understanding of each statistical learning tool. In addition, it weighs the advantages and disadvantages of each tool.

People have always sought medical care that is tailored to every individual patient. Alongside with the historical development of institutions of care, the vision of personal and 'holistic' care persisted. Patient-centred medicine, interpersonal communication and shared decision making have become central to medical practice and services. This evolving vision of 'personalized medicine' is in the forefront of medicine, creating debates among ethicists, philosophers and sociologists of medicine about the nature of disease and the definition of wellness, the impact on the daily life of patients, as well as its implications on low-income countries. Is increased 'precision' also an improvement on the personal aspects of care or erosion of privacy? Do 'precise' and 'personalized' approach marginalize public health, and can this care be personalized without attention to culture, economy and society? The book provides a multidisciplinary and interdisciplinary discussion of the ethos and ethics of precision/personal medicine, involving scientists who have shaped the field, in dialogue with ethicists, social scientists and philosophers of science. The contributing scholars come from all over the world and from different cultural backgrounds providing reflective perspectives of history of ideas, critical theory and technology assessment, together with the actual work done by pioneers in the field. It explores issues such as global justice, gender, public health, pharmaceutical industry, international law and religion, and explores themes discussed in relation to personalized medicine such as new-born screening and disorders of consciousness. This book will be of interest to academicians in bioethics, history of medicine, social sciences of medicine as well as general educated readers.

Anatomy of Gene Regulation is the first book to present the parts and processes of gene regulation at the three-dimensional level. Vivid structures of nucleic acids and their companion proteins are revealed in full-color, three dimensional form. Beginning with a general introduction to three-dimensional structures, the book looks at the organization of the genome, the structure of DNA, DNA replication and transcription, splicing, protein synthesis, and ultimate protein death. This concise and unique synthesis and its accompanying web site offer insight into gene regulation, and into the development of methods to interfere with regulation at diseased states.

Probablistic models are becoming increasingly important in analyzing the huge amount of data being produced by large-scale DNA-sequencing efforts such as the Human Genome Project. For example, hidden Markov models are used for analyzing biological sequences, linguistic-grammar-based probabilistic models for identifying RNA secondary structure, and probabilistic evolutionary models for inferring phylogenies of sequences from different organisms. This book gives a unified, up-to-date and self-contained account, with a Bayesian slant, of such methods, and more generally to probabilistic methods of sequence analysis. Written by an interdisciplinary team of authors, it is accessible to molecular biologists, computer scientists, and mathematicians with no formal knowledge of the other fields, and at the same time presents the state of the art in this new and important field.

Surveying the last sixty years of research, this book describes the physical properties of DNA in the context of its biological functioning. It is designed to enable both students and researchers of molecular biology, biochemistry and physics to better understand the biophysics of DNA, addressing key questions and facilitating further research. The chapters integrate theoretical and experimental approaches, emphasising throughout the importance of a quantitative knowledge of physical properties in building and analysing models of DNA functioning. For example, the book shows how the relationship between DNA mechanical properties and the sequence specificity of DNA-protein binding can be analyzed quantitatively by using our current knowledge of the physical and structural properties of DNA. Theoretical models and experimental methods in the field are critically considered to enable the reader to engage effectively with the current scientific literature on the physical properties of DNA.

The concept of epigenetics has been known about since the 1940s, but it is only in the last 10 years that research has shown just how wide ranging its effects are. It is now a very widely-used term, but there is still a lot of confusion surrounding what it actually is and does. Epigenetics is a new textbook that brings together the structure and machinery of epigenetic modification, how epigenetic modification controls cellular functions, and the evidence for the relationship between epigenetics and disease. It is a valuable source of information about all aspects of the subject for undergraduate students, graduate students, and professionals.

Birds catch the public imagination like no other group of animals; in addition, birders are perhaps the largest non-professional naturalist community. Genomics and associated bioinformatics have revolutionised daily life in just a few decades. At the same time, this development has facilitated the application of genomics technology to ecological and evolutionary studies, including biodiversity and conservation at all levels. This book reveals how the exciting toolbox of genomics offers new opportunities in all areas of avian biology. It presents contributions from prominent experts at the intersection of avian biology and genomics, and offers an ideal introduction to the world of genomics for students, biologists and bird enthusiasts alike. The book begins with a historical perspective on how genomic technology was adopted by bird ecology and evolution research groups. This led, as the book explains, to a revised understanding of avian evolution, with exciting consequences for biodiversity research as a whole. Lastly, these impacts are illustrated using seminal examples and the latest discoveries from avian biology laboratories around the world.

This Microbiology Monographs volume covers the current and most recent advances in genomics and genetics, biochemistry, physiology, and molecular biology of C. reinhardtii. Expert international scientists contribute with reviews on the genome, post-genomic techniques, the genetic toolbox development as well as new insights in regulation of photosynthesis and acclimation strategies towards environmental stresses and other structural and genetic aspects, including applicable aspects in biotechnology and biomedicine. Advancement in Chlamydomonas biology allowed new understandings in biotechnological and biomedical related aspects.

The bestselling introduction to bioinformatics and genomics now in its third edition Widely received in its previous editions, Bioinformatics and Functional Genomics offers the most broad-based introduction to this explosive new discipline. Now in a thoroughly updated and expanded third edition, it continues to be the go-to source for students and professionals involved in biomedical research. This book provides up-to-the-minute coverage of the fields of bioinformatics and genomics. Features new to this edition include: * Extensive revisions and a slight reorder of chapters for a more effective organization * A brand new chapter on next-generation sequencing * An expanded companion website, also updated as and when new information becomes available * Greater emphasis on a computational approach, with clear guidance of how software tools work and introductions to the use of command-line tools such as software for next-generation sequence analysis, the R programming language, and NCBI search utilities The book is complemented by lavish illustrations and more than 500 figures and tables - many newly-created for the third edition to enhance clarity and understanding. Each chapter includes learning objectives, a problem set, pitfalls section, boxes explaining key techniques and mathematics/statistics principles, a summary, recommended reading, and a list of freely available software. Readers may visit a related Web page for supplemental information such as PowerPoints and audiovisual files of lectures, and videocasts of how to perform many basic operations: www.wiley.com/go/pevsnerbioinformatics. Bioinformatics and Functional Genomics, Third Edition serves as an excellent single-source textbook for advanced undergraduate and beginning graduate-level courses in the biological sciences and computer sciences. It is also an indispensable resource for biologists in a broad variety of disciplines who use the tools of bioinformatics and genomics to study particular research problems; bioinformaticists and computer scientists who develop computer algorithms and databases; and medical researchers and clinicians who want to understand the genomic basis of viral, bacterial, parasitic, or other diseases.

With humor, depth, and philosophical and historical insight, "DNA" reaches out to a wide range of readers with its graphic portrayal of a complicated science. Suitable for use in and out of the classroom, this volume covers DNA's many marvels, from its original discovery in 1869 to early-twentieth-century debates on the mechanisms of inheritance and the deeper nature of life's evolution and variety.

Even readers who lack a background in science and philosophy will learn a tremendous amount from this engaging narrative. The book elucidates DNA's relationship to health and the cause and cure of disease. It also covers the creation of new life forms, nanomachines, and perspectives on crime detection, and considers the philosophical sources of classical Darwinian theory and recent, radical changes in the understanding of evolution itself. Already these developments have profoundly affected our notions about living things. Borin Van Loon's humorous illustrations recount the contributions of Gregor Mendel, Frederick Griffith, James Watson, and Francis Crick, among other biologists, scientists, and researchers, and vividly depict the modern controversies surrounding the Human Genome Project and cloning.

This book constitutes the proceedings of the 15th International Workshop Comparative Genomics, RECOMB-CG 2017, held in Barcelona, Spain, in October 2017. The 16 full papers presented were carefully reviewed and selected from 32 submissions. The papers report original research in all areas of Comparative Genomics.

Darwin's The Origin of Species is one of the most influential books ever written. It is essential reading for anyone interested in biology, evolution, the natural world, or the history of scientific thought. However, the book can be difficult to follow. The sentences and paragraphs are lengthy, and Darwin often references people and ideas unfamiliar to contemporary readers. The Readable Darwin translates the sixth and final edition of Darwin's The Origin of Species (1872) into clear, engaging prose. Whereas the first edition of The Readable Darwin includes the first eight chapters of Darwin's book, this new edition presents all fifteen chapters of The Origin of Species and features over 100 illustrations. The Readable Darwin begins by discussing artificial selection, demonstrating that selection for new traits can indeed be made to occur, even within our lifetimes. It then presents evidence for natural selection derived from developmental traits and the geological record. Throughout, Pechenik painstakingly revises Darwin's prose. He breaks up long paragraphs, shortens and reorganizes sentences, and replaces weak verbs with strong ones. Footnotes clarify concepts, define terms, and identify the many historical figures Darwin mentions. The Origin of Species is a foundational work of scholarship in the biological sciences. It documents the remarkable diversity of life on earth and is a wonderful example of honest and logical scientific thinking. The Readable Darwin brings this groundbreaking book to life for readers of all backgrounds while remaining true to the original text.

The onset of cancer presents one of the most fundamental problems in modern biology. In "Dynamics of Cancer," Steven Frank produces the first comprehensive analysis of how particular genetic and environmental causes influence the age of onset.

The book provides a unique conceptual and historical framework for understanding the causes of cancer and other diseases that increase with age. Using a novel quantitative framework of reliability and multistage breakdown, Frank unifies molecular, demographic, and evolutionary levels of analysis. He interprets a wide variety of observations on the age of cancer onset, the genetic and environmental causes of disease, and the organization of tissues with regard to stem cell biology and somatic mutation. Frank uses new quantitative methods to tackle some of the classic problems in cancer biology and aging: how the rate of increase in the incidence of lung cancer declines after individuals quit smoking, the distinction between the dosage of a chemical carcinogen and the time of exposure, and the role of inherited genetic variation in familial patterns of cancer.

This is the only book that presents a full analysis of the age of cancer onset. It is a superb teaching tool and a rich source of ideas for new and experienced researchers. For cancer biologists, population geneticists, evolutionary biologists, and demographers interested in aging, this book provides new insight into disease progression, the inheritance of predisposition to disease, and the evolutionary processes that have shaped organismal design.

This book explores the double coding property of DNA, which is manifested in the digital and analog information types as two interdependent codes. This double coding principle can be applied to all living systems, from the level of the individual cell to entire social systems, seen as systems of communication. Further topics discussed include the ubiquitous problem of logical typing, which reflects our inherent incapacity to simultaneously perceive discontinuity and continuity, the problem of time, and the peculiarities of autopoietic living systems. It is shown that the scientific "truths" that appear to be coherent constructions connecting the scientifically verified observations by the rules of logic are in fact always relative and never absolute.

Wide coverage of traditional unsupervised and supervised methods and newer contemporary approaches that help researchers handle the rapid growth of classification methods in DNA microarray studies

Proliferating classification methods in DNA microarray studies have resulted in a body of information scattered throughout literature, conference proceedings, and elsewhere. This book unites many of these classification methods in a single volume. In addition to traditional statistical methods, it covers newer machine-learning approaches such as fuzzy methods, artificial neural networks, evolutionary-based genetic algorithms, support vector machines, swarm intelligence involving particle swarm optimization, and more.

"Classification Analysis of DNA Microarrays "provides highly detailed pseudo-code and rich, graphical programming features, plus ready-to-run source code. Along with primary methods that include traditional and contemporary classification, it offers supplementary tools and data preparation routines for standardization and fuzzification; dimensional reduction via crisp and fuzzy c-means, PCA, and non-linear manifold learning; and computational linguistics via text analytics and n-gram analysis, recursive feature extraction during ANN, kernel-based methods, ensemble classifier fusion.

This powerful new resource: Provides information on the use of classification analysis for DNA microarrays used for large-scale high-throughput transcriptional studiesServes as a historical repository of general use supervised classification methods as well as newer contemporary methodsBrings the reader quickly up to speed on the various classification methods by implementing the programming pseudo-code and source code provided in the bookDescribes implementation methods that help shorten discovery times

"Classification Analysis of DNA Microarrays" is useful for professionals and graduate students in computer science, bioinformatics, biostatistics, systems biology, and many related fields.

Epigenetics is the most exciting field in biology today, developing our understanding of how and why we inherit certain traits, develop diseases and age, and evolve as a species. This non-fiction comic book introduces us to genetics, cell biology and the fascinating science of epigenetics, which is rapidly filling in the gaps in our knowledge, allowing us to make huge advances in medicine. We'll look at what identical twins can teach us about the epigenetic effects of our environment and experiences, why certain genes are 'switched on' or off at various stages of embryonic development, and how scientists have reversed the specialization of cells to clone frogs from a single gut cell. In Introducing Epigenetics, Cath Ennis and Oliver Pugh pull apart the double helix, examining how the epigenetic building blocks and messengers that interpret and edit our genes help to make us, well, us.

Through this book, researchers and students will learn to use R for analysis of large-scale genomic data and how to create routines to automate analytical steps. The philosophy behind the book is to start with real world raw datasets and perform all the analytical steps needed to reach final results. Though theory plays an important role, this is a practical book for graduate and undergraduate courses in bioinformatics and genomic analysis or for use in lab sessions. How to handle and manage high-throughput genomic data, create automated workflows and speed up analyses in R is also taught. A wide range of R packages useful for working with genomic data are illustrated with practical examples. The key topics covered are association studies, genomic prediction, estimation of population genetic parameters and diversity, gene expression analysis, functional annotation of results using publically available databases and how to work efficiently in R with large genomic datasets. Important principles are demonstrated and illustrated through engaging examples which invite the reader to work with the provided datasets. Some methods that are discussed in this volume include: signatures of selection, population parameters (LD, FST, FIS, etc); use of a genomic relationship matrix for population diversity studies; use of SNP data for parentage testing; snpBLUP and gBLUP for genomic prediction. Step-by-step, all the R code required for a genome-wide association study is shown: starting from raw SNP data, how to build databases to handle and manage the data, quality control and filtering measures, association testing and evaluation of results, through to identification and functional annotation of candidate genes. Similarly, gene expression analyses are shown using microarray and RNAseq data. At a time when genomic data is decidedly big, the skills from this book are critical. In recent years R has become the de facto< tool for analysis of gene expression data, in addition to its prominent role in analysis of genomic data. Benefits to using R include the integrated development environment for analysis, flexibility and control of the analytic workflow. Included topics are core components of advanced undergraduate and graduate classes in bioinformatics, genomics and statistical genetics. This book is also designed to be used by students in computer science and statistics who want to learn the practical aspects of genomic analysis without delving into algorithmic details. The datasets used throughout the book may be downloaded from the publisher's website.

The living world runs on genomic software - what Dawn Field and Neil Davies call the 'biocode' - the sum of all DNA on Earth. In Biocode, they tell the story of a new age of scientific discovery: the growing global effort to read and map the biocode, and what that might mean for the future. The structure of DNA was identified in 1953, and the whole human genome was mapped by 2003. Since then the new field of genomics has mushroomed and is now operating on an industrial scale. Genomes can now be sequenced rapidly and increasingly cheaply. The genomes of large numbers of organisms from mammals to microbes, have been mapped. Getting your genome sequenced is becoming affordable for many. You too can check paternity, find out where your ancestors came from, or whether you are at risk of some diseases. Some check out the pedigree of their pets, while others turn genomes into art. A stray hair is enough to crudely reconstruct the face of the owner. From reading to constructing: the first steps to creating artificial life have already been taken. Some may find the rapidity of developments, and the potential for misuse, alarming. But they also open up unprecedented possibilities. The ability to read DNA has changed how we view ourselves and understand our place in nature. From the largest oceans, to the insides of our guts, we are able to explore the biosphere as never before, from the genome up. Sequencing technology has made the invisible world of microbes visible, and biodiversity genomics is revealing whole new worlds within us and without. The findings are transformational: we are all ecosystems now. Already the first efforts at 'barcoding' entire ecological communities and creating 'genomic observatories' have begun. The future, the authors argue, will involve biocoding the entire planet.

Statistical genomics is a rapidly developing field, with more and more people involved in this area. However, a lack of synthetic reference books and textbooks in statistical genomics has become a major hurdle on the development of the field. Although many books have been published recently in bioinformatics, most of them emphasize DNA sequence analysis under a deterministic approach. Principles of Statistical Genomics synthesizes the state-of-the-art statistical methodologies (stochastic approaches) applied to genome study. It facilitates understanding of the statistical models and methods behind the major bioinformatics software packages, which will help researchers choose the optimal algorithm to analyze their data and better interpret the results of their analyses. Understanding existing statistical models and algorithms assists researchers to develop improved statistical methods to extract maximum information from their data. Resourceful and easy to use, Principles of Statistical Genomics is a comprehensive reference for researchers and graduate students studying statistical genomics.

This book provides a broad introduction to all major aspects of quantum dot properties including fluorescence, electrochemical, photochemical and electroluminescence. Such properties have been produced for applications in biosensing, cell tracking, in vivo animal imaging and so on. It focuses on their special applications in DNA biosensing and provides readers with detailed information on the preparation and functionalization of quantum dots and the fabrication of DNA biosensors, using examples to show how these properties can be used in DNA biosensor design and the advantages of quantum dots in DNA biosensing. Further new emerging quantum dots such as metal nanoclusters and graphene dots and their applications in DNA biosensing have also been included.

Sequencing is often associated with the Human Genome Project and celebrated achievements concerning the DNA molecule. However, the history of this practice comprises not only academic biology, but also the world of computer-assisted information management. The book uncovers this history, qualifying the hype and expectations around genomics.

Using genome sequencing, one can predict possible interactions among proteins. There are very few titles that focus on protein-protein interaction predictions in bacteria. The authors will describe these methods and further highlight its use to predict various biological pathways and complexity of the cellular response to various environmental conditions. Topics include analysis of complex genome-scale protein-protein interaction networks, effects of reference genome selection on prediction accuracy, and genome sequence templates to predict protein function.

"Genome Transcriptome and Proteome Analysis" is a concise introduction to the subject, successfully bringing together these three key areas of research. Starting with a revision of molecular genetics the book offers clear explanations of the tools and techniques widely used in genome, transcriptome and proteome analysis. Subsequent chapters offer a broad overview of linkage maps, physical maps and genome sequencing, with a final discussion on the identification of genes responsible for disease. An invaluable introduction to the basic concepts of the subject, this text offers the student an excellent overview of current research methods and applications and is a good starting point for those new to the area. It gives a clear, concise introduction to the subject of modern genomic analysis. It provides a technology-oriented approach including the latest developments in the field. It is invaluable to those students taking courses in Bioinformatics, Human Genetics, Biochemistry and Molecular Biology.

Quantitative trait locus (QTL) mapping is used to discover the genetic and molecular architecture underlying complex quantitative traits. It has important applications in agricultural, evolutionary, and biomedical research. R/qtl is an extensible, interactive environment for QTL mapping in experimental crosses. It is implemented as a package for the widely used open source statistical software R and contains a diverse array of QTL mapping methods, diagnostic tools for ensuring high-quality data, and facilities for the fit and exploration of multiple-QTL models, including QTL x QTL and QTL x environment interactions. This book is a comprehensive guide to the practice of QTL mapping and the use of R/qtl, including study design, data import and simulation, data diagnostics, interval mapping and generalizations, two-dimensional genome scans, and the consideration of complex multiple-QTL models. Two moderately challenging case studies illustrate QTL analysis in its entirety.

The book alternates between QTL mapping theory and examples illustrating the use of R/qtl. Novice readers will find detailed explanations of the important statistical concepts and, through the extensive software illustrations, will be able to apply these concepts in their own research. Experienced readers will find details on the underlying algorithms and the implementation of extensions to R/qtl. There are 150 figures, including 90 in full color.