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Computing Skills for Biologists: A Toolbox, Allesina Stefano, Wilmes Madlen


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Автор: Allesina Stefano, Wilmes Madlen
Название:  Computing Skills for Biologists: A Toolbox
ISBN: 9780691167299
Издательство: Wiley
Классификация:




ISBN-10: 069116729X
Обложка/Формат: Hardcover
Страницы: 344
Вес: 1.22 кг.
Дата издания: 15.01.2019
Язык: English
Размер: 212 x 263 x 27
Ссылка на Издательство: Link
Рейтинг:
Поставляется из: Англии
Описание:

A concise introduction to key computing skills for biologists

While biological data continues to grow exponentially in size and quality, many of todays biologists are not trained adequately in the computing skills necessary for leveraging this information deluge. In Computing Skills for Biologists, Stefano Allesina and Madlen Wilmes present a valuable toolbox for the effective analysis of biological data.

Based on the authors experiences teaching scientific computing at the University of Chicago, this textbook emphasizes the automation of repetitive tasks and the construction of pipelines for data organization, analysis, visualization, and publication. Stressing practice rather than theory, the books examples and exercises are drawn from actual biological data and solve cogent problems spanning the entire breadth of biological disciplines, including ecology, genetics, microbiology, and molecular biology. Beginners will benefit from the many examples explained step-by-step, while more seasoned researchers will learn how to combine tools to make biological data analysis robust and reproducible. The book uses free software and code that can be run on any platform.

Computing Skills for Biologists is ideal for scientists wanting to improve their technical skills and instructors looking to teach the main computing tools essential for biology research in the twenty-first century.

  • Excellent resource for acquiring comprehensive computing skills
  • Both novice and experienced scientists will increase efficiency by building automated and reproducible pipelines for biological data analysis
  • Code examples based on published data spanning the breadth of biological disciplines
  • Detailed solutions provided for exercises in each chapter
  • Extensive companion website





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