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Author: Charles C. Tseng Publisher: Springer Science & Business Media ISBN: 1461460832 Category : Medical Languages : en Pages : 264
Book Description
Traditionally, genetics laboratory exercises at the university level focus on mono- and dihybrid crosses and phenotypic analysis—exercises under traditional time, materials, and process constraints. Lately, molecular techniques such as gene cloning, polymerase chain reactions (PCR), and bioinformatics are being included in many teaching laboratories—where affordable. Human chromosome analysis, when present at all, has often been restricted to simple identification of chromosomes by number, through the usual “cut-and-paste” method. Although several online karyotyping (chromosome identification) programs have become available, they are not meaningful for studying the dynamics of the chromosome system, nor do they help students understand genetics as a discipline. The software that accompanies this book has been shown to be an ideal tool for learning about genetics, which requires a combination of understanding, conceptualization, and practical experience.
Author: Charles C. Tseng Publisher: Springer Science & Business Media ISBN: 1461460832 Category : Medical Languages : en Pages : 264
Book Description
Traditionally, genetics laboratory exercises at the university level focus on mono- and dihybrid crosses and phenotypic analysis—exercises under traditional time, materials, and process constraints. Lately, molecular techniques such as gene cloning, polymerase chain reactions (PCR), and bioinformatics are being included in many teaching laboratories—where affordable. Human chromosome analysis, when present at all, has often been restricted to simple identification of chromosomes by number, through the usual “cut-and-paste” method. Although several online karyotyping (chromosome identification) programs have become available, they are not meaningful for studying the dynamics of the chromosome system, nor do they help students understand genetics as a discipline. The software that accompanies this book has been shown to be an ideal tool for learning about genetics, which requires a combination of understanding, conceptualization, and practical experience.
Author: Wolfgang Banzhaf Publisher: Springer Science & Business ISBN: 9781558605107 Category : Computers Languages : en Pages : 506
Book Description
To order this title for shipment to Austria, Germany, or Switzerland, please contact dpunkt verlag directly. "[The authors] have performed a remarkable double service with this excellent book on genetic programming. First, they give an up-to-date view of the rapidly growing field of automatic creation of computer programs by means of evolution and, second, they bring together their own innovative and formidable work on evolution of assembly language machine code and linear genomes." --John R. Koza Since the early 1990s, genetic programming (GP)-a discipline whose goal is to enable the automatic generation of computer programs-has emerged as one of the most promising paradigms for fast, productive software development. GP combines biological metaphors gleaned from Darwin's theory of evolution with computer-science approaches drawn from the field of machine learning to create programs that are capable of adapting or recreating themselves for open-ended tasks. This unique introduction to GP provides a detailed overview of the subject and its antecedents, with extensive references to the published and online literature. In addition to explaining the fundamental theory and important algorithms, the text includes practical discussions covering a wealth of potential applications and real-world implementation techniques. Software professionals needing to understand and apply GP concepts will find this book an invaluable practical and theoretical guide.
Author: Melanie Mitchell Publisher: MIT Press ISBN: 9780262631853 Category : Computers Languages : en Pages : 226
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.
Author: David F. Treagust Publisher: Springer Science & Business Media ISBN: 9400741928 Category : Science Languages : en Pages : 394
Book Description
This new publication in the Models and Modeling in Science Education series synthesizes a wealth of international research on using multiple representations in biology education and aims for a coherent framework in using them to improve higher-order learning. Addressing a major gap in the literature, the volume proposes a theoretical model for advancing biology educators’ notions of how multiple external representations (MERs) such as analogies, metaphors and visualizations can best be harnessed for improving teaching and learning in biology at all pedagogical levels. The content tackles the conceptual and linguistic difficulties of learning biology at each level—macro, micro, sub-micro, and symbolic, illustrating how MERs can be used in teaching across these levels and in various combinations, as well as in differing contexts and topic areas. The strategies outlined will help students’ reasoning and problem-solving skills, enhance their ability to construct mental models and internal representations, and, ultimately, will assist in increasing public understanding of biology-related issues, a key goal in today’s world of pressing concerns over societal problems about food, environment, energy, and health. The book concludes by highlighting important aspects of research in biological education in the post-genomic, information age.
Author: Gail L. Shaw Publisher: Springer Science & Business Media ISBN: 1461546990 Category : Medical Languages : en Pages : 209
Book Description
Cancer genetics is a quickly growing field within oncology. The ability to identify individuals at high risk for cancer improves the chance of early prevention and detection of cancer. The results of genetic testing affect quality of life, employment, and ability to be insured. This volume will provide an overview of cancer genetics, inherited cancer susceptibility, and available services and testing, including both the risks and benefits of testing. Some of the topics covered include: genetics of breast and ovarian cancer, testing minors for inherited cancer risk, chemoprevention of heritable cancer risk, genetics of colorectal cancer, insurance issues in genetic testing for cancer, ethical and legal issues in genetic testing for cancer susceptibility, testing for breast cancer risk in the Ashkenazim, estimating individualized risk of breast cancer, genetic counseling for the individual with inherited cancer susceptibility, and components of a genetic cancer risk clinic. While heritable cancers account for between five and ten percent of all cancer cases, molecular alterations attributable to specific inherited cancer susceptibility may give us important clues into the mechanism by which cancer occurs, not only in predisposed individuals, but also for sporadic cases.
Author: Sandra K. Abell Publisher: Routledge ISBN: 1135619654 Category : Education Languages : en Pages : 1346
Book Description
This state-of-the art research Handbook provides a comprehensive, coherent, current synthesis of the empirical and theoretical research concerning teaching and learning in science and lays down a foundation upon which future research can be built. The contributors, all leading experts in their research areas, represent the international and gender diversity that exists in the science education research community. As a whole, the Handbook of Research on Science Education demonstrates that science education is alive and well and illustrates its vitality. It is an essential resource for the entire science education community, including veteran and emerging researchers, university faculty, graduate students, practitioners in the schools, and science education professionals outside of universities. The National Association for Research in Science Teaching (NARST) endorses the Handbook of Research on Science Education as an important and valuable synthesis of the current knowledge in the field of science education by leading individuals in the field. For more information on NARST, please visit: http://www.narst.org/.
Author: Altuna Akalin Publisher: CRC Press ISBN: 1498781861 Category : Mathematics Languages : en Pages : 463
Book Description
Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology and start with R programming, whereas a computer scientist might want to start with genome biology. After reading: You will have the basics of R and be able to dive right into specialized uses of R for computational genomics such as using Bioconductor packages. You will be familiar with statistics, supervised and unsupervised learning techniques that are important in data modeling, and exploratory analysis of high-dimensional data. You will understand genomic intervals and operations on them that are used for tasks such as aligned read counting and genomic feature annotation. You will know the basics of processing and quality checking high-throughput sequencing data. You will be able to do sequence analysis, such as calculating GC content for parts of a genome or finding transcription factor binding sites. You will know about visualization techniques used in genomics, such as heatmaps, meta-gene plots, and genomic track visualization. You will be familiar with analysis of different high-throughput sequencing data sets, such as RNA-seq, ChIP-seq, and BS-seq. You will know basic techniques for integrating and interpreting multi-omics datasets. Altuna Akalin is a group leader and head of the Bioinformatics and Omics Data Science Platform at the Berlin Institute of Medical Systems Biology, Max Delbrück Center, Berlin. He has been developing computational methods for analyzing and integrating large-scale genomics data sets since 2002. He has published an extensive body of work in this area. The framework for this book grew out of the yearly computational genomics courses he has been organizing and teaching since 2015.
Author: Publisher: BRILL ISBN: 9087904223 Category : Education Languages : en Pages : 384
Book Description
This book is a compilation of papers from the inaugural International Science Education Conference held at the National Institute of Education (Singapore). The title, Science Education at the Nexus of Theory and Practice, reflects a pressing yet ongoing concern worldwide to integrate theory and practice in science education and the reader will find something of interest to both science education practitioners and researchers.
Author: Charles C. Tseng
Author: Charles C. Tseng
Author: Wolfgang Banzhaf
Author: Melanie Mitchell
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Author: David F. Treagust
Author: Gail L. Shaw
Author: Sandra K. Abell
Author: Altuna Akalin
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