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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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Toc

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

Computing molecular distances on a PDB file

Here, we will find atoms closer to three zincs in the 1TUP model. We will consider several distances to these zincs. We will take this opportunity to discuss the performance of algorithms.

Getting ready

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

How to do it...

Take a look at the following steps:

  1. Let’s load our model, as follows:
    from Bio import PDB
    repository = PDB.PDBList()
    parser = PDB.PDBParser()
    repository.retrieve_pdb_file('1TUP', pdir='.', file_format='pdb')
    p53_1tup = parser.get_structure('P 53', 'pdb1tup.ent')
  2. We will now get our zincs, against which we will perform comparisons later:
    zns = []for atom in p53_1tup.get_atoms():
    if atom.element == 'ZN':
    zns.append(atom)
    for zn in zns:
        print(zn, zn.coord)

You should see three zinc atoms.

  1. Now, let’s define a function to get the...
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