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Bioinformatics with Python Cookbook

You're reading from   Bioinformatics with Python Cookbook Use modern Python libraries and applications to solve real-world computational biology problems

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Product type Paperback
Published in Sep 2022
Publisher Packt
ISBN-13 9781803236421
Length 360 pages
Edition 3rd Edition
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Author (1):
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Tiago Antao Tiago Antao
Author Profile Icon Tiago Antao
Tiago Antao
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Table of Contents (15) Chapters Close

Preface 1. Chapter 1: Python and the Surrounding Software Ecology 2. Chapter 2: Getting to Know NumPy, pandas, Arrow, and Matplotlib FREE CHAPTER 3. Chapter 3: Next-Generation Sequencing 4. Chapter 4: Advanced NGS Data Processing 5. Chapter 5: Working with Genomes 6. Chapter 6: Population Genetics 7. Chapter 7: Phylogenetics 8. Chapter 8: Using the Protein Data Bank 9. Chapter 9: Bioinformatics Pipelines 10. Chapter 10: Machine Learning for Bioinformatics 11. Chapter 11: Parallel Processing with Dask and Zarr 12. Chapter 12: Functional Programming for Bioinformatics 13. Index 14. Other Books You May Enjoy

Using the Protein Data Bank

Proteomics is the study of proteins, including their function and structure. One of the main objectives of this field is to characterize the three-dimensional structure of proteins. One of the most widely known computational resources in the proteomics field is the Protein Data Bank (PDB), a repository with the structural data of large biomolecules. Of course, many databases focus on protein primary structure instead; these are somewhat similar to the genomic databases that we saw in Chapter 2, Getting to Know NumPy, pandas, Arrow, and Matplotlib.

In this chapter, we will mostly focus on processing data from the PDB. We will look at how to parse PDB files, perform some geometric computations, and visualize molecules. We will use the old PDB file format because, conceptually, it allows you to perform most necessary operations within a stable environment. Having said that, the newer mmCIF slated to replace the PDB format will also be presented in the Parsing...

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