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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

Parsing mmCIF files using Biopython

The mmCIF file format is probably the future. Biopython doesn’t have full functionality to work with it yet, but we will take a look at what currently exists.

Getting ready

As Bio.PDB is not able to automatically download mmCIF files, you need to get your protein file and rename it to 1tup.cif. This can be found at https://github.com/PacktPublishing/Bioinformatics-with-Python-Cookbook-third-Edition/blob/master/Datasets.py under 1TUP.cif.

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

How to do it...

Take a look at the following steps:

  1. Let’s parse the file. We just use the MMCIF parser instead of the PDB parser:
    from Bio import PDB
    parser = PDB.MMCIFParser()
    p53_1tup = parser.get_structure('P53', '1tup.cif')
  2. Let’s inspect the following chains:
    def describe_model(name, pdb):
        print()
        for model in p53_1tup:
      ...
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