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Bioinformatics with Python Cookbook

You're reading from   Bioinformatics with Python Cookbook Learn how to use modern Python bioinformatics libraries and applications to do cutting-edge research in computational biology

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Product type Paperback
Published in Nov 2018
Publisher Packt
ISBN-13 9781789344691
Length 360 pages
Edition 2nd Edition
Languages
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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 (12) Chapters Close

Preface 1. Python and the Surrounding Software Ecology 2. Next-Generation Sequencing FREE CHAPTER 3. Working with Genomes 4. Population Genetics 5. Population Genetics Simulation 6. Phylogenetics 7. Using the Protein Data Bank 8. Bioinformatics Pipelines 9. Python for Big Genomics Datasets 10. Other Topics in Bioinformatics 11. Advanced NGS Processing

Extracting more information from a PDB file


Here, we will continue our exploration of the record structure produced by Bio.PDB from PDB files.

Getting ready

For general information about the PDB models that we are using, refer to the previous recipe.

You can find this content in the Chapter07/Stats.ipynb Notebook file.

How to do it...

Take a look at the following steps:

  1. First, let's retrieve 1TUP, as follows:
from Bio import PDB
repository = PDB.PDBList()
parser = PDB.PDBParser()
repository.retrieve_pdb_file('1TUP', pdir='.', file_format='pdb') #XXX
p53_1tup = parser.get_structure('P 53', 'pdb1tup.ent')
  1. Then, extract some atom-related statistics:
from collections import defaultdict

atom_cnt = defaultdict(int)
atom_chain = defaultdict(int)
atom_res_types = defaultdict(int)
for atom in p53_1tup.get_atoms():
    my_residue = atom.parent
    my_chain = my_residue.parent
    atom_chain[my_chain.id] += 1
    if my_residue.resname != 'HOH':
        atom_cnt[atom.element] += 1
    atom_res_types[my_residue...
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