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.

The author presents a basic introduction to the world of genetic engineering. Copyright © Libri GmbH. All rights reserved.

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.

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 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.

This introductory text covers all aspects of genetics but adopts a "molecular approach", with the gene dealt with first as a chemical structure and then as a Menedelian entity.