Analysis of GenesA and Genomes is a clear introduction to the theoretical and practical basis of genetic engineering, gene cloning and molecular biology. All aspects of genetic engineering in the post-genomic era are covered, beginning with the basics of DNA structure and DNA metabolism. Using an example-driven approach, the fundamentals of creating mutations in DNA, cloning in bacteria, yeast, plants and animals are all clearly presented. Newer technologies such as DNA macro and macroarrays, proteomics and bioinformatics are introduced in later chapters helping students to analyse and understand the vast amounts of data that are now available through genome sequence and function projects. Aimed at students with a basic knowledge of the molecular side of biology, this will be invaluable to those looking to better understand the complexities and capabilities of these important new technologies. A modern post-genome era introduction to key techniques used in genetic engineering. An example driven past-to-present approach to allow the experiments of today to be placed in an historical context Beautifully illustrated in full colour throughout. Associated website including updates, additional content and illustrations

With its unique integration of genetics and molecular biology, this text probes fascinating questions that explore how our understanding of key genetic phenomena can be used to understand biological systems. Opening with a brief overview of key genetic principles, model organisms, and epigenetics, the book goes on to explore the use of gene mutations, the analysis of gene expression and activity, a discussion of the genetic structure of natural populations, and more.

There is growing enthusiasm in the scientific community about the prospect of mapping and sequencing the human genome, a monumental project that will have far-reaching consequences for medicine, biology, technology, and other fields. But how will such an effort be organized and funded? How will we develop the new technologies that are needed? What new legal, social, and ethical questions will be raised? Mapping and Sequencing the Human Genome is a blueprint for this proposed project. The authors offer a highly readable explanation of the technical aspects of genetic mapping and sequencing, and they recommend specific interim and long-range research goals, organizational strategies, and funding levels. They also outline some of the legal and social questions that might arise and urge their early consideration by policymakers.

Sequence - Evolution - Function is an introduction to the computational approaches that play a critical role in the emerging new branch of biology known as functional genomics. The book provides the reader with an understanding of the principles and approaches of functional genomics and of the potential and limitations of computational and experimental approaches to genome analysis. Sequence - Evolution - Function should help bridge the "digital divide" between biologists and computer scientists, allowing biologists to better grasp the peculiarities of the emerging field of Genome Biology and to learn how to benefit from the enormous amount of sequence data available in the public databases. The book is non-technical with respect to the computer methods for genome analysis and discusses these methods from the user's viewpoint, without addressing mathematical and algorithmic details. Prior practical familiarity with the basic methods for sequence analysis is a major advantage, but a reader without such experience will be able to use the book as an introduction to these methods. This book is perfect for introductory level courses in computational methods for comparative and functional genomics.

Rapid advances in our understanding of genetics have required that new books contain topics such as the concept and theory of gene cloning, transgenics, genomics, and various other coverage of traditional and contemporary subjects. Although there is an abundance of textbooks that cover introductory genetics and advanced courses in genetics, there is a noticeable gap at the intermediate (second year) level. In the past gene structure, function and expression were taught at final year /postgraduate level, but the rapid advances in our understanding of genetics has encouraged courses to change considerably. Over recent years these topics have filtered down the curriculum and are currently taught as core topics at second year, with a corresponding change in textbook requirements. Where once second year students were restricted to learning about the concept and theory of gene cloning, now they routinely clone genes for themselves as part of their practical assignments. Genes to Genomics will fill the gap, cover much of the same ground as previous titles, but go further on contemporary topics like transgenics, sequence comparison and analysis of variation. * A concise, up to date textbook that provides a balanced coverage of traditional and contemporary topics taught within intermediate courses in molecular genetics * Jeremy Dale has a proven track record as the successful author of Molecular Genetics of Bacteria * Genes to Genomics will include a series of feature box-outs that will examine some of the topical issues related to the scientific concepts and examples explored within the text * A range of questions and exercises including worked examples and web-based practicals * An accompanying web site will allow the authors to keep their audience up to date in the areas that are prone to date most rapidly between successive editions of the textbook. It will also include the illustrations and images from the textbook, in addition to worked examples, answers to questions within the book, and links to related websites of key interest.

This book presents the foundations of key problems in computational molecular biology and bioinformatics. It focuses on computational and statistical principles applied to genomes, and introduces the mathematics and statistics that are crucial for understanding these applications. The book features a free download of the R software statistics package and the text provides great crossover material that is interesting and accessible to students in biology, mathematics, statistics and computer science. More than 100 illustrations and diagrams reinforce concepts and present key results from the primary literature. Exercises are given at the end of chapters.

Plant Genes, Genomes and Genetics provides a comprehensive treatment of all aspects of plant gene expression. Unique in explaining the subject from a plant perspective, it highlights the importance of key processes, many first discovered in plants, that impact how plants develop and interact with the environment. This text covers topics ranging from plant genome structure and the key control points in how genes are expressed, to the mechanisms by which proteins are generated and how their activities are controlled and altered by posttranslational modifications. Written by a highly respected team of specialists in plant biology with extensive experience in teaching at undergraduate and graduate level, this textbook will be invaluable for students and instructors alike. Plant Genes, Genomes and Genetics also includes: specific examples that highlight when and how plants operate differently from other organisms special sections that provide in-depth discussions of particular issues end-of-chapter problems to help students recapitulate the main concepts rich, full-colour illustrations and diagrams clearly showing important processes in plant gene expression a companion website with PowerPoint slides, downloadable figures, and answers to the questions posed in the book Aimed at upper level undergraduates and graduate students in plant biology, this text is equally suited for advanced agronomy and crop science students inclined to understand molecular aspects of organismal phenomena. It is also an invaluable starting point for professionals entering the field of plant biology.

This book provides state-of-the-art information on gene essentiality screenings in a wide variety of organisms, i.e. screening for protein-coding genes and other genomic elements that are required by an organism to survive under specific conditions. With a focus on the two techniques that have revolutionized the field, the collection begins with chapters employing CRISPR/Cas9-based approaches followed by Tn-seq-based approaches, but later chapters also delve into other techniques for exploring essential genes, such as bioinformatics methods. Written for the highly successful Methods in Molecular Biology series, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Comprehensive and authoritative, Essential Genes and Genomes: Methods and Protocols is an ideal guide for researchers attempting to strip genetics down to its fundamentals.

Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology and start with R programming, whereas a computer scientist might want to start with genome biology. After reading: You will have the basics of R and be able to dive right into specialized uses of R for computational genomics such as using Bioconductor packages. You will be familiar with statistics, supervised and unsupervised learning techniques that are important in data modeling, and exploratory analysis of high-dimensional data. You will understand genomic intervals and operations on them that are used for tasks such as aligned read counting and genomic feature annotation. You will know the basics of processing and quality checking high-throughput sequencing data. You will be able to do sequence analysis, such as calculating GC content for parts of a genome or finding transcription factor binding sites. You will know about visualization techniques used in genomics, such as heatmaps, meta-gene plots, and genomic track visualization. You will be familiar with analysis of different high-throughput sequencing data sets, such as RNA-seq, ChIP-seq, and BS-seq. You will know basic techniques for integrating and interpreting multi-omics datasets. Altuna Akalin is a group leader and head of the Bioinformatics and Omics Data Science Platform at the Berlin Institute of Medical Systems Biology, Max Delbrück Center, Berlin. He has been developing computational methods for analyzing and integrating large-scale genomics data sets since 2002. He has published an extensive body of work in this area. The framework for this book grew out of the yearly computational genomics courses he has been organizing and teaching since 2015.