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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.
Helping undergraduates in the analysis of genetic problems, this work emphasizes solutions, not just answers. The strategy is to provide the student with the essential steps and the reasoning involved in conducting the analysis, and throughout the book, an attempt is made to present a balanced account of genetics. Topics, therefore, center about Mendelian, cytogenetic, molecular, quantitative, and population genetics, with a few more specialized areas. Whenever possible, the student is provided with the appropriate basic statistics necessary to make some the analyses. The book also builds on itself; that is, analytical methods learned in early parts of the book are subsequently revisited and used for later analyses. A deliberate attempt is made to make complex concepts simple, and sometimes to point out that apparently simple concepts are sometimes less so on further investigation. Any student taking a genetics course will find this an invaluable aid to achieving a good understanding of genetic principles and practice.
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
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.
The Manual combines a complete set of solutions for the text with the CD, Interactive Genetics.
Genetic programming (GP) is a method for getting a computer to solve a problem by telling it what needs to be done instead of how to do it. Koza, Bennett, Andre, and Keane present genetically evolved solutions to dozens of problems of design, control, classification, system identification, and computational molecular biology. Among the solutions are 14 results competitive with human-produced results, including 10 rediscoveries of previously patented inventions.
This set of exercises has been created expressly for students and teachers of conservation biology and wildlife management who want to have an impact beyond the classroom. The book presents a set of 32 exercises that are primarily new and greatly revised versions from the book's successful first edition. These exercises span a wide range of conservation issues: genetic analysis, population biology and management, taxonomy, ecosystem management, land use planning, the public policy process and more. All exercises discuss how to take what has been learned and apply it to practical, real-world issues. Accompanied by a detailed instructor’s manual and a student website with software and support materials, the book is ideal for use in the field, lab, or classroom. Also available: Fundamentals of Conservation Biology, 3rd edition (2007) by Malcolm L Hunter Jr and James Gibbs, ISBN 9781405135450 Saving the Earth as a Career: Advice on Becoming a Conservation Professional (2007) by Malcolm L Hunter Jr, David B Lindenmayer and Aram JK Calhoun, ISBN 9781405167611
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.