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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

Introducing Bio.PDB

Here, we will introduce Biopython’s PDB module for working with the PDB. We will use three models that represent part of the p53 protein. You can read more about these files and p53 at http://www.rcsb.org/pdb/101/motm.do?momID=31.

Getting ready

You should already be aware of the basic PDB data model of model, chain, residue, and atom objects. A good explanation of Biopython’s Structural Bioinformatics FAQ can be found at http://biopython.org/wiki/The_Biopython_Structural_Bioinformatics_FAQ.

You can find this content in the Chapter08/PDB.py Notebook file.

Of the three models that we will download, the 1TUP model is the one that will be used in the remainder of the recipes. Take some time to study this model, as it will help you later on.

How to do it...

Take a look at the following steps:

  1. First, let’s retrieve our models of interest, as follows:
    from Bio import PDB
    repository = PDB.PDBList()
    repository.retrieve_pdb_file...
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