Intended for students of biology, genetics and zoology, this manual aims to help students learn how to solve problems in genetics by discussing approximately 10 problem-solving concepts for each major topic in genetics. These include: malosis, X-linkage and chromosomal changes. This guide offers an increased number of problems, accompanied by detailed solutions, discussions and explanations. Features include more coverage of gene technology, and detailed solutions in the appendix.
The Problem Solvers are an exceptional series of books that are thorough, unusually well-organized, and structured in such a way that they can be used with any text. No other series of study and solution guides has come close to the Problem Solvers in usefulness, quality, and effectiveness. Educators consider the Problem Solvers the most effective series of study aids on the market. Students regard them as most helpful for their school work and studies. With these books, students do not merely memorize the subject matter, they really get to understand it. Each Problem Solver is over 1,000 pages, yet each saves hours of time in studying and finding solutions to problems. These solutions are worked out in step-by-step detail, thoroughly and clearly. Each book is fully indexed for locating specific problems rapidly. Thorough coverage is given to cell mechanics, chromosomes, Mendelian genetics, sex determination, mutations and alleles, bacterial and viral genetics, biochemistry, immunogenetics, genetic engineering, probability, and statistics.
Most research in the life sciences involves a core set of molecular-based equipment and methods, for which there is no shortage of step-by-step protocols. Nonetheless, there remains an exceedingly high number of inquiries placed to commercial technical support groups, especially regarding problems. Molecular Biology Problem Solver: A Laboratory Guide asks the reader to consider crucial questions, such as: Have you selected the most appropriate research strategy? Have you identified the issues critical to your successful application of a technique? Are you familiar with the limitations of a given technique? When should common procedural rules of thumb not be applied? What strategies could you apply to resolve a problem? A unique question-based format reviews common assumptions and laboratory practices, with the aim of offering a firm understanding of how techniques and procedures work, as well as how to avoid problems. Some major issues explored by the book's expert contributors include: Working safely with biological samples and radioactive materials DNA and RNA purification PCR Protein and nucleid acid hybridization Prokaryotic and eukaryotic expression systems Properly using and maintaining laboratory equipment
For all introductory genetics courses Informed by many years of genetics teaching and research expertise, authors Mark Sanders and John Bowman use an integrated approach that helps contextualise three core challenges of learning genetics: solving problems, understanding evolution, and understanding the connection between traditional genetics models and more modern approaches. The full text downloaded to your computer With eBooks you can: search for key concepts, words and phrases make highlights and notes as you study share your notes with friends eBooks are downloaded to your computer and accessible either offline through the Bookshelf (available as a free download), available online and also via the iPad and Android apps. Upon purchase, you'll gain instant access to this eBook. Time limit The eBooks products do not have an expiry date. You will continue to access your digital ebook products whilst you have your Bookshelf installed.
This handbook covers all dimensions of breast cancer prevention, diagnosis, and treatment for the non-oncologist. A special emphasis is placed on the long term survivor.
The #1 NEW YORK TIMES Bestseller The basis for the PBS Ken Burns Documentary The Gene: An Intimate History Now includes an excerpt from Siddhartha Mukherjee’s new book Song of the Cell! From the Pulitzer Prize–winning author of The Emperor of All Maladies—a fascinating history of the gene and “a magisterial account of how human minds have laboriously, ingeniously picked apart what makes us tick” (Elle). “Sid Mukherjee has the uncanny ability to bring together science, history, and the future in a way that is understandable and riveting, guiding us through both time and the mystery of life itself.” —Ken Burns “Dr. Siddhartha Mukherjee dazzled readers with his Pulitzer Prize-winning The Emperor of All Maladies in 2010. That achievement was evidently just a warm-up for his virtuoso performance in The Gene: An Intimate History, in which he braids science, history, and memoir into an epic with all the range and biblical thunder of Paradise Lost” (The New York Times). In this biography Mukherjee brings to life the quest to understand human heredity and its surprising influence on our lives, personalities, identities, fates, and choices. “Mukherjee expresses abstract intellectual ideas through emotional stories…[and] swaddles his medical rigor with rhapsodic tenderness, surprising vulnerability, and occasional flashes of pure poetry” (The Washington Post). Throughout, the story of Mukherjee’s own family—with its tragic and bewildering history of mental illness—reminds us of the questions that hang over our ability to translate the science of genetics from the laboratory to the real world. In riveting and dramatic prose, he describes the centuries of research and experimentation—from Aristotle and Pythagoras to Mendel and Darwin, from Boveri and Morgan to Crick, Watson and Franklin, all the way through the revolutionary twenty-first century innovators who mapped the human genome. “A fascinating and often sobering history of how humans came to understand the roles of genes in making us who we are—and what our manipulation of those genes might mean for our future” (Milwaukee Journal-Sentinel), The Gene is the revelatory and magisterial history of a scientific idea coming to life, the most crucial science of our time, intimately explained by a master. “The Gene is a book we all should read” (USA TODAY).
This textbook gives an introduction to genetics and genomics at the college level. It contains a chapter on human genetic evolution. Other chapters treat transmission genetics, molecular genetics and evolutionary genetics and provide an understanding of the basic process of gene transmission, mutation, expression and regulation.
Genetic algorithms have been used in science and engineering as adaptive algorithms for solving practical problems and as computational models of natural evolutionary systems. This brief, accessible introduction describes some of the most interesting research in the field and also enables readers to implement and experiment with genetic algorithms on their own. It focuses in depth on a small set of important and interesting topics—particularly in machine learning, scientific modeling, and artificial life—and reviews a broad span of research, including the work of Mitchell and her colleagues. The descriptions of applications and modeling projects stretch beyond the strict boundaries of computer science to include dynamical systems theory, game theory, molecular biology, ecology, evolutionary biology, and population genetics, underscoring the exciting "general purpose" nature of genetic algorithms as search methods that can be employed across disciplines. An Introduction to Genetic Algorithms is accessible to students and researchers in any scientific discipline. It includes many thought and computer exercises that build on and reinforce the reader's understanding of the text. The first chapter introduces genetic algorithms and their terminology and describes two provocative applications in detail. The second and third chapters look at the use of genetic algorithms in machine learning (computer programs, data analysis and prediction, neural networks) and in scientific models (interactions among learning, evolution, and culture; sexual selection; ecosystems; evolutionary activity). Several approaches to the theory of genetic algorithms are discussed in depth in the fourth chapter. The fifth chapter takes up implementation, and the last chapter poses some currently unanswered questions and surveys prospects for the future of evolutionary computation.
