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professionals and students how to exploit the best parts of Python to solve problems in biology while creating documented, tested, reproducible software;
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Through many examples and exercises, this book helps simplify bioinformatics programming using Python. It's an ideal guide for biologists;
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used in the field. Python for Bioinformatics provides a clear introduction to the Python programming language and instructs beginners on the;
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Discover modern, next-generation sequencing libraries from Python ecosystem to analyze large amounts of biological data Key Features;
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extensive experience, Python for Bioinformatics, Second Edition helps biologists get to grips with the basics of software development. Requiring no;
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extensive experience, Python for Bioinformatics, Second Edition helps biologists get to grips with the basics of software development. Requiring no;
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developers who want to learn how to leverage Regular Expressions in Python. Basic knowledge of Python is required for a better understanding.;
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level. The text encourages mathematical analysis by providing a firm foundation for computations. It analyzes numerous Python scripts for the;
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Bioinformatics Algorithms: Design and Implementation in Python provides a comprehensive book on many of the most important;
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a foundation for both newcomers to computer programming and those interested in learning more about computational biology. The chapters;
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a foundation for both newcomers to computer programming and those interested in learning more about computational biology. The chapters;
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using Python, including what you can use it for.;
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Arbuckle. This dynamic, concise book is full of real-world solutions for Python 3.6 problems, and advanced-level concepts such as reactive;
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efficiently and effectively, including pyATS, Nornir, and Ansible 2.8 Use Python and Ansible for DevOps, network device automation, DevOps, and;
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Advanced Python for Biologists is a programming course for workers in biology and bioinformatics who want to develop their programming;
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to build core trading and risk management systems. Updated for Python 3, the second edition of this hands-on book helps you get started with;
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Python and need to write more sophisticated, flexible code that integrates seamlessly with the rest of Python. This book assumes a computer;
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for biology students without previous experience in programming. By interspersing theory chapters with numerous small and large programming;
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filtering, primary pattern analysis, and machine learning algorithms using R and Python are demonstrated for gene-expression microarrays, genotyping;
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Theano, and use a cluster of computers for large-scale computations using technologies such as Dask and PySpark. With the knowledge of how Python;
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