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Modeling and Simulation in Python teaches readers how to analyze real-world scenarios using the Python programming language, requiring no more than a background in high school math. Modeling and Simulation in Python is a thorough but easy-to-follow introduction to physical modeling—that is, the art of describing and simulating real-world systems. Readers are guided through modeling things like world population growth, infectious disease, bungee jumping, baseball flight trajectories, celestial mechanics, and more while simultaneously developing a strong understanding of fundamental programming concepts like loops, vectors, and functions. Clear and concise, with a focus on learning by doing, the author spares the reader abstract, theoretical complexities and gets right to hands-on examples that show how to produce useful models and simulations.
Python for Bioinformatics provides a clear introduction to the Python programming language and instructs beginners on the development of simple programming exercises. Important Notice: The digital edition of this book is missing some of the images or content found in the physical edition.
* Weitere Angaben Verfasser: Thomas Lindblad is a professor at the Royal Institute of Technology (Physics) in Stockholm. Working and teaching nuclear and environmental physics his main interest is with sensors, signal processing and intelligent data analysis of torrent data from experiments on-line accelerators, in space, etc. Jason Kinser is an associate professor at George Mason University. He has developed a plethora of image processing applications in the medical, military, and industrial fields. He has been responsible for the conversion of PCNN theory into practical applications providing many improvements in both speed and performance
Optoelectronics is a rapidly expanding field of research and development. In years to come, it is destined to play a primary role in the growing information industry. The basic philosophy behind the science and technology of optoelectronics is to create and develop photonic devices in which optical photons (light waves) instead of electronic carriers, are manipulated for the conventional task performed by microelectronics. Thanks to the availability of large bandwidth at optical frequencies, the development of cost-effective low-loss low-dispersion silica fibers for optical transmission, and the possibility of ultra-fast two-dimensional processing, the field of present-day microelectronics i...
The Fourth Edition of Genetics of Populations is the most current, comprehensive, and accessible introduction to the field for advanced undergraduate and graduate students, and researchers in genetics, evolution, conservation, and related fields. In the past several years, interest in the application of population genetics principles to new molecular data has increased greatly, and Dr. Hedrick's new edition exemplifies his commitment to keeping pace with this dynamic area of study. Reorganized to allow students to focus more sharply on key material, the Fourth Edition integrates coverage of theoretical issues with a clear presentation of experimental population genetics and empirical data. Drawing examples from both recent and classic studies, and using a variety of organisms to illustrate the vast developments of population genetics, this text provides students and researchers with the most comprehensive resource in the field.
R is quickly becoming the number one choice for users in the fields of biology, medicine, and bioinformatics as their main means of storing, processing, sharing, and analyzing biomedical data. R for Medicine and Biology is a step-by-step guide through the use of the statistical environment R, as used in a biomedical domain. Ideal for healthcare professionals, scientists, informaticists, and statistical experts, this resource will provide even the novice programmer with the tools necessary to process and analyze their data using the R environment. Introductory chapters guide readers in how to obtain, install, and become familiar with R and provide a clear introduction to the programming langu...
Thoroughly revised and updated, Exploring Bioinformatics: A Project-Based Approach, Second Edition is intended for an introductory course in bioinformatics at the undergraduate level. Through hands-on projects, students are introduced to current biological problems and then explore and develop bioinformatic solutions to these issues. Each chapter presents a key problem, provides basic biological concepts, introduces computational techniques to address the problem, and guides students through the use of existing web-based tools and software solutions. This progression prepares students to tackle the On-Your-Own Project, where they develop their own software solutions. Topics such as antibiotic resistance, genetic disease, and genome sequencing provide context and relevance to capture student interest.
The Fourth Edition of Genetics of Populations is the most current, comprehensive, and accessible introduction to the field for advanced undergraduate and graduate students, and researchers in genetics, evolution, conservation, and related fields. In the past several years, interest in the application of population genetics principles to new molecular data has increased greatly, and Dr. Hedrick's new edition exemplifies his commitment to keeping pace with this dynamic area of study. Reorganized to allow students to focus more sharply on key material, the Fourth Edition integrates coverage of theoretical issues with a clear presentation of experimental population genetics and empirical data. Drawing examples from both recent and classic studies, and using a variety of organisms to illustrate the vast developments of population genetics, this text provides students and researchers with the most comprehensive resource in the field.
For decades, researchers have been developing algorithms to manipulate and analyze images. From this, a common set of image tools now appear in many high-level programming languages. Consequently, the amount of coding required by a user has significantly lessened over the years. While the libraries for image analysis are coalescing to a common toolkit, the language of image analysis has remained stagnant. Often, textual descriptions of an analytical protocol consume far more real estate than does the computer code required to execute the processes. Furthermore, the textual explanations are sometimes vague or incomplete. This book offers a precise mathematical language for the field of image ...