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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

Introducing Bio.PDB


Here, we will introduce Biopython's PDB module for working with the Protein Data Bank. 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 be aware of the basic PDB data model of model/chain/residue/atom objects. A good explanation on 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 Chapter07/PDB.ipynb Notebook file.

Of the three models that we will download, the 1TUP model will be used in the remaining 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('1TUP', pdir='.', file_format='pdb')
repository.retrieve_pdb_file('1OLG', pdir...
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