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.

The principle objective of this book is to help undergraduate students in the analysis of genetic problems. Many students have a great deal of difficulty doing genetic analysis, and the book will be useful regardless of which genetics text is being used. Most texts provide some kinds of problems and answers: few, if any, however, show the students how to actually solve the problem. Often the student has no idea how the answer was derived. 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. 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 of 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 book an invaluable aid to achieving a good understanding of genetic principles and practice.

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.

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.

An invaluable student-tested study aid, this primer, first published in 2007, provides guided instruction for the analysis and interpretation of genetic principles and practice in problem solving. Each section is introduced with a summary of useful hints for problem solving and an overview of the topic with key terms. A series of problems, generally progressing from simple to more complex, then allows students to test their understanding of the material. Each question and answer is accompanied by detailed explanation. This third edition includes additional problems in basic areas that often challenge students, extended coverage in molecular biology and development, an expanded glossary of terms, and updated historical landmarks. Students at all levels, from beginning biologists and premedical students to graduates seeking a review of basic genetics, will find this book a valuable aid. It will complement the formal presentation in any genetics textbook or stand alone as a self-paced review manual.

Key Benefit: A supplement for any genetics book, this guide gives readers thorough instruction and practice for solving genetics problems. Using callout comments, the author walks readerse through the process of breaking down word problems by dissecting each sentence. At each significant point in the statement of a problem, readers learn to evaluate the given data, think about how it fits into the larger picture, and analyze relationships that lead to a potential solution. Currently, How to Solve Genetics Problems can be packaged with Pearson genetics books for a special value package price. Key Topics: Chromosome Mechanics - Mitosis and Meiosis, Transmission genetics, Linkage and Mapping, Molecular biology: DNA, Molecular biology: Proteins, Transcription, Translation, and Mutation, Genetic regulation: Prokaryotes, Population genetics and Evolution Market: Intended for those interested in learning the basics of genetics

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.

Hyde's"Introduction to Genetics" teaches the principles of genetics with an innovative approach that emphasizes the basic concepts involved in solving problems as well as teaching students how to manipulate genetic data. While most genetics textbooks provide some examples and several problems for the student to work, the texts primarily stress facts and historical information. It is often left to the student to make the connection from what is in the text to elucidating the approaches to solve problems. Dr. David Hyde presents these skills to the students throughout the narrative in a stepped-out fashion, making an explicit tie between the facts and their application. This text maintains the rigor that faculty require in a genetics book, while incorporating a student-friendly presentation style that helps the reader comprehend the material.

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.

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.