Introduction to Genetics: A Molecular Approach


Book Description

Introduction to Genetics: A Molecular Approach is a new textbook for first and second year undergraduates. It first presents molecular structures and mechanisms before introducing the more challenging concepts and terminology associated with transmission genetics.




Principles of Biology


Book Description

The Principles of Biology sequence (BI 211, 212 and 213) introduces biology as a scientific discipline for students planning to major in biology and other science disciplines. Laboratories and classroom activities introduce techniques used to study biological processes and provide opportunities for students to develop their ability to conduct research.




An Introduction to Genetics for Language Scientists


Book Description

During the last few decades we have discovered enormous amounts about our genomes, their evolution and, importantly for linguists and language scientists, the genetic foundations of language and speech. Accessible and readable, this introduction is designed specifically for students and researchers working in language and linguistics. It carefully focuses on the most relevant concepts, methods and findings in the genetics of language and speech, and covers a wide range of topics such as heritability, the molecular mechanisms through which genes influence our language, and the evolutionary forces affecting them. Filling a large gap in the literature, this essential guide explores relevant examples including hearing loss, stuttering, dyslexia, brain growth and development, as well as the normal range of variation. It also contains a helpful glossary of terms, and a wide range of references so the reader can pursue topics of interest in more depth.




Introduction to Genetics


Book Description

Introduction to Genetics: Science of Heredity presents a linear programmed text about hereditary and genetics. This book discusses a variety of topics related to heredity and genetics, including chromosomes, genes, Mendelism, mitosis, and meiosis. Organized into six chapters, this book begins with an overview of some of the experiments that first provide an understanding of heredity and laid the foundation of the science of genetics. This text then provides detailed information about the cell and explains how the essential parts of it reproduce and divide. Other chapters consider how the chromosome theory can explain not only the facts of Mendelism, but also the many complications that arise in genetics. This book discusses as well the problems that can happen during the process of mitosis and meiosis. The final chapter deals with the practical problems that confront the plant breeder. This book is a valuable resource for teachers and students of biology.




Introduction to Conservation Genetics


Book Description

This impressive author team brings the wealth of advances in conservation genetics into the new edition of this introductory text, including new chapters on population genomics and genetic issues in introduced and invasive species. They continue the strong learning features for students - main points in the margin, chapter summaries, vital support with the mathematics, and further reading - and now guide the reader to software and databases. Many new references reflect the expansion of this field. With examples from mammals, birds ...




Genes


Book Description

Explores the discovery, nature, and role of genes in evolution and development.




An Introduction to Human Molecular Genetics


Book Description

An Introduction to Human Molecular Genetics Second Edition Jack J. Pasternak The Second Edition of this internationally acclaimed text expandsits coverage of the molecular genetics of inherited human diseaseswith the latest research findings and discoveries. Using a unique,systems-based approach, the text offers readers a thoroughexplanation of the gene discovery process and how defective genesare linked to inherited disease states in major organ and tissuesystems. All the latest developments in functional genomics,proteomics, and microarray technology have been thoroughlyincorporated into the text. The first part of the text introduces readers to the fundamentalsof cytogenetics and Mendelian genetics. Next, techniques andstrategies for gene manipulation, mapping, and isolation areexamined. Readers will particularly appreciate the text'sexceptionally thorough and clear explanation of genetic mapping.The final part features unique coverage of the molecular geneticsof distinct biological systems, covering muscle, neurological, eye,cancer, and mitochondrial disorders. Throughout the text, helpfulfigures and diagrams illustrate and clarify complex material. Readers familiar with the first edition will recognize the text'ssame lucid and engaging style, and will find a wealth of new andexpanded material that brings them fully up to date with a currentunderstanding of the field, including: * New chapters on complex genetic disorders, genomic imprinting,and human population genetics * Expanded and fully revised section on clinical genetics, coveringdiagnostic testing, molecular screening, and varioustreatments This text is targeted at upper-level undergraduate students,graduate students, and medical students. It is also an excellentreference for researchers and physicians who need a clinicallyrelevant reference for the molecular genetics of inherited humandiseases.




An Introduction to Statistical Genetic Data Analysis


Book Description

A comprehensive introduction to modern applied statistical genetic data analysis, accessible to those without a background in molecular biology or genetics. Human genetic research is now relevant beyond biology, epidemiology, and the medical sciences, with applications in such fields as psychology, psychiatry, statistics, demography, sociology, and economics. With advances in computing power, the availability of data, and new techniques, it is now possible to integrate large-scale molecular genetic information into research across a broad range of topics. This book offers the first comprehensive introduction to modern applied statistical genetic data analysis that covers theory, data preparation, and analysis of molecular genetic data, with hands-on computer exercises. It is accessible to students and researchers in any empirically oriented medical, biological, or social science discipline; a background in molecular biology or genetics is not required. The book first provides foundations for statistical genetic data analysis, including a survey of fundamental concepts, primers on statistics and human evolution, and an introduction to polygenic scores. It then covers the practicalities of working with genetic data, discussing such topics as analytical challenges and data management. Finally, the book presents applications and advanced topics, including polygenic score and gene-environment interaction applications, Mendelian Randomization and instrumental variables, and ethical issues. The software and data used in the book are freely available and can be found on the book's website.




An Introduction to Genetic Algorithms


Book Description

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.




Introduction to Theoretical Population Genetics


Book Description

This book covers those areas of theoretical population genetics that can be investigated rigorously by elementary mathematical methods. I have tried to formulate the various models fairly generally and to state the biological as sumptions quite explicitly. I hope the choice and treatment of topics will en able the reader to understand and evaluate detailed analyses of many specific models and applications in the literature. Models in population genetics are highly idealized, often even over idealized, and their connection with observation is frequently remote. Further more, it is not practicable to measure the parameters and variables in these models with high accuracy. These regrettable circumstances amply justify the use of appropriate, lucid, and rigorous approximations in the analysis of our models, and such approximations are often illuminating even when exact solu tions are available. However, our empirical and theoretical limitations justify neither opaque, incomplete formulations nor unconvincing, inadequate analy ses, for these may produce uninterpretable, misleading, or erroneous results. Intuition is a principal source of ideas for the construction and investigation of models, but it can replace neither clear formulation nor careful analysis. Fisher (1930; 1958, pp. x, 23-24, 38) not only espoused similar ideas, but he recognized also that our concepts of intuition and rigor must evolve in time. The book is neither a review of the literature nor a compendium of results. The material is almost entirely self-contained. The first eight chapters are a thoroughly revised and greatly extended version of my published lecture notes (Nagylaki, 1977a).