The Analysis of Biological Data by Michael C. Whitlock and Dolph Schluter offers new method to educating introductory statistics to biology students. Authors use a number of strategies to achieve this distinctive audience.
Bioinformatics, area dedicated to the interpretation and analysis of biological information using computational strategies, has developed tremendously in recent years due to the explosive growth of organic information generated by the scientific community. Comfortable computing is a consortium of methodologies that work synergistically and gives, in one type, versatile information processing capabilities for handling real-life ambiguous situations.
Several research articles coping with the application of soft computing instruments to bioinformatics have been revealed in the current past; nonetheless, they're scattered in different journals, convention proceedings and technical reviews, thus causing inconvenience to readers, students and researchers.
This book, distinctive in its nature, is geared toward offering a treatise in a unified framework, with each theoretical and experimental outcome by describing the basic rules of soppy computing and demonstrating the various methods in which they can be used for analyzing organic data in an environment friendly manner.
Fascinating research articles from eminent scientists around the globe are introduced collectively in a systematic approach such that the reader will be capable of understand the issues and challenges in this area, the present methods of tackling them, current trends, and future directions. This book is the primary of its variety to deliver together two vital analysis areas, gentle computing and bioinformatics, with a purpose to reveal how the tools and strategies in the former can be utilized for effectively fixing a number of problems within the latter.
All through, authors educate statistics in the context of interesting organic and medical examples; they emphasize intuitive understanding slightly than an over-reliance on formulas; they give attention to the information slightly than the mathematical foundations of statistics; and so they introduce - on a conceptual stage - fashionable subjects akin to probability, regression, randomization, meta-analysis and the bootstrap. Instructors and college students constantly reward the book's clear and fascinating writing, robust visualization techniques, and the wide variety of fascinating and related biological examples.
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