Bioinformatics is an active research field that uses a range of simple-to-advanced computations to extract valuable information from biological data, and this book will show you how to manage these tasks using Python.

This updated edition of the Bioinformatics with Python Cookbook begins with a quick overview of the various tools and libraries in the Python ecosystem that will help you convert, analyze, and visualize biological datasets. As you advance through the chapters, you'll cover key techniques for next-generation sequencing, single-cell analysis, genomics, metagenomics, population genetics, phylogenetics, and proteomics with the help of real-world examples. You'll learn how to work with important pipeline systems, such as Galaxy servers and Snakemake, and understand the various modules in Python for functional and asynchronous programming. This book will also help you explore topics such as SNP discovery using statistical approaches under high-performance computing frameworks, including Dask and Spark, and the application of machine learning algorithms to bioinformatics.

By the end of this bioinformatics Python book, you'll be equipped with the knowledge to implement the latest programming techniques and frameworks, empowering you to deal with bioinformatics data on every kind of scale.

Zobacz także:

• Windows Media Center. Domowe centrum rozrywki 66,67 zÅ‚, (8,00 zÅ‚ -88%)
• Ruby on Rails. Ćwiczenia 18,75 zÅ‚, (3,00 zÅ‚ -84%)
• Przywództwo w Å›wiecie VUCA. Jak być skutecznym liderem w niepewnym Å›rodowisku 58,64 zÅ‚, (12,90 zÅ‚ -78%)
• Scrum. O zwinnym zarzÄ…dzaniu projektami. Wydanie II rozszerzone 58,64 zÅ‚, (12,90 zÅ‚ -78%)
• Od hierarchii do turkusu, czyli jak zarzÄ…dzać w XXI wieku 58,64 zÅ‚, (12,90 zÅ‚ -78%)

Spis treści

Bioinformatics with Python Cookbook. Use modern Python libraries and applications to solve real-world computational biology problems - Third Edition eBook -- spis treści

• 1. Python and the Surrounding Software Ecology
• 2. Using Data Processing Libraries: numpy, pandas, arrow, and zarr
• 3. Next Generation Sequencing
• 4. Advanced NGS Data Processing
• 5. Working with Genomes
• 6. Population Genetics
• 7. Phylogenetics
• 8. Using the Protein Data Bank
• 9. Bioinformatics Pipelines
• 10. Machine Learning for Bioinformatics
• 11. Parallel Processing with Dask
• 12. Functional and Asynchronous Programming