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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 Jun 2015
Publisher
ISBN-13 9781782175117
Length 306 pages
Edition 1st Edition
Languages
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Toc

Table of Contents (11) 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. Other Topics in Bioinformatics 9. Python for Big Genomics Datasets Index

Introducing Bio.PDB


Here, we will introduce Biopython's PDB module to deal 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 06_Prot/PDB.ipynb notebook.

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 __future__ import print_function
    from Bio import PDB
    repository = PDB.PDBList()
    repository.retrieve_pdb_file('1TUP', pdir='.')
    repository.retrieve_pdb_file('1OLG...
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